US20210106237A1 - Method and system for image processing of intravascular hemodynamics - Google Patents
Method and system for image processing of intravascular hemodynamics Download PDFInfo
- Publication number
- US20210106237A1 US20210106237A1 US17/128,718 US202017128718A US2021106237A1 US 20210106237 A1 US20210106237 A1 US 20210106237A1 US 202017128718 A US202017128718 A US 202017128718A US 2021106237 A1 US2021106237 A1 US 2021106237A1
- Authority
- US
- United States
- Prior art keywords
- blood flow
- image
- blood
- data
- quantitative
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 82
- 238000012545 processing Methods 0.000 title claims abstract description 18
- 230000000004 hemodynamic effect Effects 0.000 title claims abstract description 14
- 230000017531 blood circulation Effects 0.000 claims abstract description 176
- 210000004204 blood vessel Anatomy 0.000 claims abstract description 102
- 239000002872 contrast media Substances 0.000 claims abstract description 52
- 210000004369 blood Anatomy 0.000 claims abstract description 39
- 239000008280 blood Substances 0.000 claims abstract description 39
- 238000010191 image analysis Methods 0.000 claims abstract description 32
- 230000008859 change Effects 0.000 claims abstract description 24
- 238000004458 analytical method Methods 0.000 claims description 68
- 238000003384 imaging method Methods 0.000 claims description 31
- 238000006243 chemical reaction Methods 0.000 claims description 28
- 238000001356 surgical procedure Methods 0.000 claims description 16
- BDBMLMBYCXNVMC-UHFFFAOYSA-O 4-[(2e)-2-[(2e,4e,6z)-7-[1,1-dimethyl-3-(4-sulfobutyl)benzo[e]indol-3-ium-2-yl]hepta-2,4,6-trienylidene]-1,1-dimethylbenzo[e]indol-3-yl]butane-1-sulfonic acid Chemical group OS(=O)(=O)CCCCN1C2=CC=C3C=CC=CC3=C2C(C)(C)C1=CC=CC=CC=CC1=[N+](CCCCS(O)(=O)=O)C2=CC=C(C=CC=C3)C3=C2C1(C)C BDBMLMBYCXNVMC-UHFFFAOYSA-O 0.000 claims description 14
- 229960004657 indocyanine green Drugs 0.000 claims description 14
- 238000011002 quantification Methods 0.000 claims description 14
- 238000003331 infrared imaging Methods 0.000 claims description 12
- 230000035945 sensitivity Effects 0.000 claims description 4
- GNBHRKFJIUUOQI-UHFFFAOYSA-N fluorescein Chemical group O1C(=O)C2=CC=CC=C2C21C1=CC=C(O)C=C1OC1=CC(O)=CC=C21 GNBHRKFJIUUOQI-UHFFFAOYSA-N 0.000 claims description 3
- 238000007499 fusion processing Methods 0.000 description 52
- 230000010412 perfusion Effects 0.000 description 31
- 238000002591 computed tomography Methods 0.000 description 19
- 238000012360 testing method Methods 0.000 description 18
- 238000005259 measurement Methods 0.000 description 16
- 230000004927 fusion Effects 0.000 description 15
- 238000010586 diagram Methods 0.000 description 14
- 238000002583 angiography Methods 0.000 description 13
- 239000003086 colorant Substances 0.000 description 13
- 238000002595 magnetic resonance imaging Methods 0.000 description 13
- 238000004364 calculation method Methods 0.000 description 12
- 238000011156 evaluation Methods 0.000 description 11
- 239000000126 substance Substances 0.000 description 9
- 230000008569 process Effects 0.000 description 8
- 239000000700 radioactive tracer Substances 0.000 description 8
- 238000007631 vascular surgery Methods 0.000 description 8
- MHMNJMPURVTYEJ-UHFFFAOYSA-N fluorescein-5-isothiocyanate Chemical compound O1C(=O)C2=CC(N=C=S)=CC=C2C21C1=CC=C(O)C=C1OC1=CC(O)=CC=C21 MHMNJMPURVTYEJ-UHFFFAOYSA-N 0.000 description 7
- 238000012937 correction Methods 0.000 description 6
- 230000002792 vascular Effects 0.000 description 6
- 230000000694 effects Effects 0.000 description 5
- 239000000523 sample Substances 0.000 description 5
- 230000001225 therapeutic effect Effects 0.000 description 5
- 239000007789 gas Substances 0.000 description 4
- 238000002600 positron emission tomography Methods 0.000 description 4
- 238000002603 single-photon emission computed tomography Methods 0.000 description 4
- 101000686491 Platymeris rhadamanthus Venom redulysin 1 Proteins 0.000 description 3
- 101000686495 Platymeris rhadamanthus Venom redulysin 2 Proteins 0.000 description 3
- 238000003745 diagnosis Methods 0.000 description 3
- 238000010253 intravenous injection Methods 0.000 description 3
- 230000003902 lesion Effects 0.000 description 3
- 238000002360 preparation method Methods 0.000 description 3
- 238000004445 quantitative analysis Methods 0.000 description 3
- WPPDXAHGCGPUPK-UHFFFAOYSA-N red 2 Chemical compound C1=CC=CC=C1C(C1=CC=CC=C11)=C(C=2C=3C4=CC=C5C6=CC=C7C8=C(C=9C=CC=CC=9)C9=CC=CC=C9C(C=9C=CC=CC=9)=C8C8=CC=C(C6=C87)C(C=35)=CC=2)C4=C1C1=CC=CC=C1 WPPDXAHGCGPUPK-UHFFFAOYSA-N 0.000 description 3
- 208000024891 symptom Diseases 0.000 description 3
- 206010002329 Aneurysm Diseases 0.000 description 2
- 201000008450 Intracranial aneurysm Diseases 0.000 description 2
- 210000001367 artery Anatomy 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 210000004556 brain Anatomy 0.000 description 2
- 210000005013 brain tissue Anatomy 0.000 description 2
- 210000001715 carotid artery Anatomy 0.000 description 2
- 239000012895 dilution Substances 0.000 description 2
- 238000010790 dilution Methods 0.000 description 2
- 201000010099 disease Diseases 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000002347 injection Methods 0.000 description 2
- 239000007924 injection Substances 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 238000000691 measurement method Methods 0.000 description 2
- 230000007170 pathology Effects 0.000 description 2
- 238000012109 statistical procedure Methods 0.000 description 2
- 230000002966 stenotic effect Effects 0.000 description 2
- 238000002604 ultrasonography Methods 0.000 description 2
- 208000019553 vascular disease Diseases 0.000 description 2
- 210000003462 vein Anatomy 0.000 description 2
- 206010010904 Convulsion Diseases 0.000 description 1
- 208000032843 Hemorrhage Diseases 0.000 description 1
- 206010020751 Hypersensitivity Diseases 0.000 description 1
- 208000009433 Moyamoya Disease Diseases 0.000 description 1
- 238000012879 PET imaging Methods 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- 230000000172 allergic effect Effects 0.000 description 1
- 230000007815 allergy Effects 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 208000010668 atopic eczema Diseases 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000008499 blood brain barrier function Effects 0.000 description 1
- 210000001218 blood-brain barrier Anatomy 0.000 description 1
- 230000003925 brain function Effects 0.000 description 1
- 230000003727 cerebral blood flow Effects 0.000 description 1
- 230000002490 cerebral effect Effects 0.000 description 1
- 208000026106 cerebrovascular disease Diseases 0.000 description 1
- 239000013043 chemical agent Substances 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 230000003749 cleanliness Effects 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 239000004020 conductor Substances 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000036461 convulsion Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 210000001513 elbow Anatomy 0.000 description 1
- 230000037149 energy metabolism Effects 0.000 description 1
- 238000000799 fluorescence microscopy Methods 0.000 description 1
- 238000002594 fluoroscopy Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 210000004013 groin Anatomy 0.000 description 1
- 230000023597 hemostasis Effects 0.000 description 1
- 239000012216 imaging agent Substances 0.000 description 1
- 239000007943 implant Substances 0.000 description 1
- 238000001990 intravenous administration Methods 0.000 description 1
- 208000028867 ischemia Diseases 0.000 description 1
- 210000004185 liver Anatomy 0.000 description 1
- 230000003908 liver function Effects 0.000 description 1
- 239000000696 magnetic material Substances 0.000 description 1
- 238000000386 microscopy Methods 0.000 description 1
- 238000002406 microsurgery Methods 0.000 description 1
- 230000003533 narcotic effect Effects 0.000 description 1
- 238000009206 nuclear medicine Methods 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 230000000399 orthopedic effect Effects 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 239000000049 pigment Substances 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 230000002285 radioactive effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 230000004936 stimulating effect Effects 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 210000005166 vasculature Anatomy 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 210000000707 wrist Anatomy 0.000 description 1
- 229910052724 xenon Inorganic materials 0.000 description 1
- FHNFHKCVQCLJFQ-UHFFFAOYSA-N xenon atom Chemical compound [Xe] FHNFHKCVQCLJFQ-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/026—Measuring blood flow
- A61B5/0261—Measuring blood flow using optical means, e.g. infrared light
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0033—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room
- A61B5/0035—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room adapted for acquisition of images from more than one imaging mode, e.g. combining MRI and optical tomography
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
- A61B5/0071—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence by measuring fluorescence emission
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/02028—Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/026—Measuring blood flow
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/026—Measuring blood flow
- A61B5/0263—Measuring blood flow using NMR
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/026—Measuring blood flow
- A61B5/0275—Measuring blood flow using tracers, e.g. dye dilution
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4887—Locating particular structures in or on the body
- A61B5/489—Blood vessels
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7271—Specific aspects of physiological measurement analysis
- A61B5/7278—Artificial waveform generation or derivation, e.g. synthesising signals from measured signals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00315—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body for treatment of particular body parts
- A61B2018/00345—Vascular system
- A61B2018/00404—Blood vessels other than those in or around the heart
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2505/00—Evaluating, monitoring or diagnosing in the context of a particular type of medical care
- A61B2505/05—Surgical care
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2576/00—Medical imaging apparatus involving image processing or analysis
- A61B2576/02—Medical imaging apparatus involving image processing or analysis specially adapted for a particular organ or body part
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/026—Measuring blood flow
- A61B5/0265—Measuring blood flow using electromagnetic means, e.g. electromagnetic flowmeter
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M5/00—Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
- A61M5/007—Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests for contrast media
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R33/00—Arrangements or instruments for measuring magnetic variables
- G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
- G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
- G01R33/48—NMR imaging systems
- G01R33/54—Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
- G01R33/56—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
- G01R33/563—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution of moving material, e.g. flow contrast angiography
- G01R33/56366—Perfusion imaging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10048—Infrared image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
- G06T2207/30104—Vascular flow; Blood flow; Perfusion
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
- G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
Definitions
- CT perfusion involves exposure to X-rays and requires special care when determining quantitative properties in pathologies involving abnormalities in the blood brain barrier, but allows measurements to be taken simply using a standard CT device and analysis software.
- MRI perfusion has the drawbacks of being inapplicable to patients who have undergone surgery to implant magnetic materials into the body, and involving difficulties in obtaining quantitative data due to linearity not being ensured between the contrast agent concentration and the signal strength.
- neither CT perfusion nor MRI perfusion can be used on patients having allergies to the contrast agent, since the tracer cannot be intravenously injected.
- FIG. 1 A flow diagram of a method according to a first embodiment.
- Peak peak amplitude image
- the image output of video images is analyzed by the following procedure.
- an ROI is prepared at the same blood vessel position as the specific blood vessel position that was measured with the electromagnetic blood flow meter ( FIG. 4 ).
- an ROI statistical procedure is performed on the rBF image.
- the mean relative blood flow calculated by the ROI statistical procedure is defined as rBF (ROI).
- the conversion coefficient Kbf between eBF (ROI) and rBF (ROI) is calculated.
- BV Kbf*rBV: quantification conversion formula between rBV and BV established for entire image
- the quantitative MTT is a calculated quantity that can be defined by using the same concepts for both tissue analysis and capillary analysis.
- the area under the curve is defined as r ⁇ .
- the following relationship is established between the relative r ⁇ , the quantitative MTT and the rMFV (Mean Flow Velocity).
- the “working distance” refers to the distance from the tip of the objective lens of the microscope camera to the object being imaged, on which the focal point is trained.
- the “angle” refers to the angle at which the microscope camera is viewing the object being imaged.
- the amount of the fluorescent contrast agent administered refers to the amount of chemical injected when injecting the fluorescent contrast agent (ICG; FITC) from a vein in the arm.
- the fluorescent contrast agent is diluted to make it easier to inject. This means that the state of dilution is made the same and that the same amount of injected chemical is injected after dilution.
- the specific conditions for matching the operating conditions can be determined by each organization, for example, by the hospital.
- Embodiments of the present invention have been explained above. A part of the method of the first embodiment may be replaced with the fourth embodiment. Additionally, a part of the method of the first embodiment may be replaced by the second embodiment or the third embodiment. In other words, the above-described embodiments may be combined.
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Physics & Mathematics (AREA)
- Animal Behavior & Ethology (AREA)
- Pathology (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Physiology (AREA)
- Cardiology (AREA)
- Hematology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Psychiatry (AREA)
- Signal Processing (AREA)
- Quality & Reliability (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Vascular Medicine (AREA)
- Apparatus For Radiation Diagnosis (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
Abstract
Description
- The present invention relates to a method and system for image processing of intravascular hemodynamics.
- With cerebrovascular diseases such as cerebral aneurysms and moyamoya disease, various tests are performed in order to determine therapeutic results or diagnoses of the diseases. For example, CT (Computed Tomography) tests and MRI (Magnetic Resonance Imaging) tests use tomograms or images reconstructed therefrom, and in angiography, blood vessels are visualized by injecting a contrast agent from a catheter, and consecutively taken images are used to observe the state of the brain parenchyma, the passage of blood vessels, and the flow of blood.
- When performing diagnoses for surgical operations on blood vessels, the forms of the organs and blood vessels are observed as images, not only in order to observe ischemia sites and ranges, and to judge the elapsed time from onset, but also to image and numericize the state of blood flow in the blood vessels so as to allow for quantitative and qualitative judgments of the effects of therapeutic results and diagnosis of diseases.
- Perfusion imaging is an imaging method wherein, with respect to the blood flow (perfusion) in the capillaries of tissues or the functional vasculature associated therewith, some kind of mark (tracer) is made in the blood flow on the arterial side, and the manner in which the tracer rides the blood flow in passing through the tissues is observed. The method allows for quantitative or semi-quantitative imaging of capillary-level tissue blood flow, and the images taken by such a method are known as perfusion images. Perfusion imaging is a tissue (capillary) analysis method.
- Additionally, as parameters for judging the flow of blood, arrival time (AT), time to peak (TTP), blood flow (BF), blood volume (BV) and mean transit time (MTT) are used. For example, when quantitatively evaluating blood flow using a diagnostic image, a time density curve (TDC) indicating the density change over time of an image due to a tracer substance is calculated, and this is analyzed to calculate the aforementioned evaluation value. Furthermore, qualitative images of BF, BV and MTT are prepared on the basis of these evaluation values and TDC analysis, and these qualitative images are used for clinical evaluation.
- Tests that allow the state of blood flow to be imaged or numericized include the following.
- Imaging methods using CT devices are known as CT perfusion, imaging methods using MRI devices are known as MRI perfusion. Perfusion images using CT and MRI are obtained by rapid intravenous injection, as a tracer, of a contrast agent for taking enhanced images of the blood vessels, consecutive imaging of tomograms of the same section, calculation of the TDC representing the concentration change over time at each pixel in the resulting tomograms, and analysis thereof. CT perfusion and MRI perfusion are both tissue (capillary) analysis methods.
- CT perfusion involves exposure to X-rays and requires special care when determining quantitative properties in pathologies involving abnormalities in the blood brain barrier, but allows measurements to be taken simply using a standard CT device and analysis software. On the other hand, MRI perfusion has the drawbacks of being inapplicable to patients who have undergone surgery to implant magnetic materials into the body, and involving difficulties in obtaining quantitative data due to linearity not being ensured between the contrast agent concentration and the signal strength. Additionally, neither CT perfusion nor MRI perfusion can be used on patients having allergies to the contrast agent, since the tracer cannot be intravenously injected.
- Methods using non-radioactive Xe (xenon) gas as the tracer make use of the fact that, when Xe gas is inhaled and tomograms are taken by a CT device over time, the Xe spreads to the brain tissue, and the tissue concentration in the CT image (CT value) lightly rises. This increase in the CT value over time is used to calculate the TDC and form an image of the state of blood flow.
- Xe gas has stimulatory and narcotic effects and is therefore difficult to use, requires a closed-circuit apparatus for supplying the gas, and also requires care due to X-ray exposure.
- Methods using chemicals containing radioisotope elements (hereinafter referred to as RI chemicals) as the tracer, wherein a RI chemical is injected into a peripheral artery or inhaled, and the bodily distribution of the RI chemical over time is measured from outside the body using a SPECT (Single Photon Emission Computed Tomography) device or a PET (Positron Emission Tomography) device to calculate the TDC, and thereby form images of the state of blood flow.
- Tests using PET provide the best quantitative performance among currently usable perfusion imaging methods, and they have the advantage of enabling the oxygen intake and energy metabolism to be simultaneously measured. However, since SPECT and PET imaging both involve handling RI chemicals, they require nuclear medical equipment and involve frequent exposure due to testing.
- These are methods wherein a catheter is guided to the target blood vessel from the groin, elbow or wrist, a contrast agent is injected into the blood vessel and subjected to X-ray fluoroscopy in order to observe the passage of the blood vessel and constricted sites, and these techniques can be used simultaneously with treatment. The imaging is performed by digital subtraction angiography (DSA), and they allow high-contrast observation of only blood vessels injected with contrast agent. By setting an ROI in a blood vessel to be evaluated in a taken DSA image and analyzing the TDC of a blood vessel (contrast agent) present in the set ROI, the state of blood flow can be imaged.
- While angiography allows the effects after intravenous surgery to be easily judged, there is exposure to X-rays, and furthermore, patients who are allergic to the contrast agent cannot be tested. Additionally, since a catheter is directly inserted into the blood vessel, the testing room and testing equipment must have a level of cleanliness on the order of that in an operating room. Additionally, after the operation, several hours of absolute rest are required for hemostasis, so the test basically requires hospitalization.
- The diagnoses of vascular diseases are performed not only to image the state of blood flow, but also to quantitatively and qualitatively numericize the state of blood flow and the blood flow rate. This information can be obtained by a method of calculation by analyzing a chronological concentration change graph of the aforementioned images, or by a method using Doppler ultrasound making use of ultrasonic waves, or a blood flow measuring device using an electromagnetic blood flow meter.
- By using color Doppler imaging in an ultrasonic analyzer, the hemodynamics in the living body can be colored in real-time, enabling the state of blood flow to be superimposed on a B-mode image which is a two-dimensional tomogram. Color Doppler imaging is a technology that makes use of changes in the frequency of reflected acoustic waves due to the Doppler effect on ultrasonic waves, so as to judge whether or not a target object (blood) is approaching or receding from the probe, and to thereby form images.
- Since ultrasonic probe chips are large, they cannot evaluate small blood vessels, and blood flow measurements are also impossible if the probe size differs from the blood vessel diameter, but they allow simple testing without restrictions on location, allow observation from multiple directions, and enable observations to be made in real-time.
- These methods are based on Fleming's Law wherein an electromotive force is generated when a conductor is moved in a magnetic field. Blood flow is regarded as electric current, and the generation of an electromotive force in the direction perpendicular to both blood flow and the magnetic field is used to measure the instantaneous blood flow, the mean blood flow and the single stroke volume.
- Methods using electromagnetic blood flow meters can be used in blood flow measurements during surgery, and can provide real-time measurement results. However, electromagnetic blood flow meters require the probe to be directly mounted on a blood vessel, so measurements cannot be taken without exposing the blood vessel of interest.
- Furthermore, evaluations of blood flow can also be made by observing the flow of blood itself.
- These methods evaluate blood flow by taking video, using the near-infrared light from a surgical microscope, of fluorescent light in the near-infrared region that is excited from a fluorescent vascular contrast agent that has been intravenously administered as a tracer.
- While they are capable of revealing the state of fluorescent vascular contrast agent in blood vessels (presence or absence of blood flow), they are not capable of analyzing small signal changes such as the state of blood flow and blood flow rate. While the imaging requires video imaging of the blood vessel of interest in the near-infrared light from a surgical microscope device, the state of blood flow during the operation can be confirmed in real-time.
- As mentioned above, the evaluation of blood flow in vascular diseases involves various types of tests and measurement methods, but at the site of clinical operations, the optimal testing and measurement methods are considered and used in accordance with the patient pathology, application and diagnostic timing. For example, when evaluating the state of blood flow after aneurysm clipping, the blood flow is evaluated in real-time during the operation. In this case, tests requiring dedicated equipment that is not provided in the operating room, such as CT, MRI and angiography, cannot be used, and blood flow evaluations making use of electromagnetic blood flow meters or intraoperative fluorescence angiography are chosen.
- Furthermore, the possibility of using a testing or measuring method also depends on the type of information that can be obtained by the device used. For example, while electromagnetic blood flow meters can be used to measure instantaneous blood flow, mean blood flow and single stroke volume, the outputted data are numerical data (graphs), and while intraoperative fluorescence angiography allows visual estimation of AT and TTP images, the preparation of BV, BF, MTT data and blood flow evaluation images including such information is impossible. For this reason, an operator must evaluate an operation by appropriately choosing devices capable of obtaining information necessary to make the evaluations after an operation, based also on the data measurable thereby. In other words, for example, when wishing to obtain BV, BF or MTT values and blood flow evaluation images, CT perfusion images must be taken several days after surgery when the patient's condition has stabilized, and the taken images must further be analyzed. In other words, it is difficult to obtain BV, BF and MTT values, and blood flow evaluation images, in real-time during an operation.
- For example,
Patent Document 1 discloses a method of evaluating the patency of a blood vessel that has been subjected to a bypass graft operation, using a fluorescence imaging agent that emits radiation at specific wavelengths. - Patent Document 1: JP 2011-147797 A
- However, with the conventional art, it was very difficult to estimate the desired information such as BV (Blood Volume), BF (Blood Flow) and MTT (Mean Transit Time) from intraoperative fluorescence angiography.
- The present invention offers an analysis technique relating to video data of a fluorescent contrast agent taken by a microscope during an operation, and has the purpose of offering a method and system that applies perfusion analysis methods capable of estimating information such as BV, BF and MTT to fluorescent contrast agent analysis, enabling information such as BV, BF and MTT as well as vascular wall thickness to be estimated even by fluorescent contrast agent analysis.
- The method for image processing of intravascular hemodynamics according to the present invention is characterized by shooting video using infrared light, wherein the object of shooting is a portion of a blood vessel injected with a standard amount of a fluorescent contrast agent; performing image analysis of a shape of a chronological change curve of intensity values of image outputs from the video shooting; and calculating relative data for blood volume and blood flow based on results of the image analysis.
- According to one embodiment of the present invention, quantitative data for the blood volume or blood flow are calculated instead of the relative data.
- According to one embodiment of the present invention, blood volume is measured using an electromagnetic blood flow meter, wherein the object of measurement is the portion of the blood vessel; and quantitative data for blood volume or blood flow are calculated based on results of these measurements and the relative data.
- According to one embodiment of the present invention, an analysis image is generated from the quantitative data for the blood volume or blood flow. Additionally, an analysis video is generated instead of the analysis image.
- According to one embodiment of the present invention, the fluorescent contrast agent is indocyanin green or fluorescein.
- According to one embodiment of the present invention, video of the portion of the blood vessel is shot using natural light, and the output images of the video shot using natural light are fused with the output images of video shot using infrared light.
- The system for image processing of intravascular hemodynamics according to the present invention is characterized by comprising an infrared imaging device for shooting video images, using natural light, of a portion of a blood vessel injected with a standard amount of a fluorescent contrast agent; and an image analysis device for performing image analysis of a shape of a chronological change curve of intensity values of image outputs shot by the imaging device, and calculating relative data for blood volume or blood flow based on results of the image analysis.
- According to one embodiment of the present invention, the image analysis device comprises an image analysis device that calculates quantitative data instead of relative data.
- According to one embodiment of the present invention, the system further comprises an analysis image generating device for generating analysis images from the quantitative data for blood volume or blood flow.
- According to one embodiment of the present invention, the system further comprises a natural light imaging device for shooting video images of the portion of the blood vessels using natural light; and an image fusion device for fusing the output images of the natural light imaging device and analysis images generated by the analysis image generating device.
- The method and system for image processing of intravascular hemodynamics according to the present invention is capable of estimating information such as BV, BF, MTT, and vascular wall thickness.
-
FIG. 1 A flow diagram of a method according to a first embodiment. -
FIG. 2 A diagram showing an example of a system configuration. -
FIG. 3 A diagram explaining the definitions of output parameter images in the image analysis of the first embodiment. -
FIG. 4 A diagram explaining the ROI preparation position. -
FIG. 5 A diagram explaining the definitions of output parameter images in the image analysis of the first embodiment. -
FIG. 6 A diagram explaining the definitions of output parameter images in the image analysis of the second embodiment. -
FIG. 7 A flow diagram explaining the calculation method of BF. -
FIG. 8 A diagram explaining the relationship between BF and blood vessel cross-sectional area. -
FIG. 9 A diagram explaining the calculation method of BF in the second embodiment. -
FIG. 10 A diagram explaining the calculation method of BF in the third embodiment. -
FIG. 11 A diagram showing the change in analysis images before and after bypass surgery. -
FIG. 12 A flow diagram of a method including an image fusion process. -
FIG. 13 A diagram showing the procedure for an image fusion process. - Herebelow, embodiments of the method and system for image processing of intravascular hemodynamics according to the present invention will be explained. As the present embodiment, an example of a method of diagnosis by calculating BV and BF quantitative images in an operating room during cerebrovascular bypass surgery will be explained.
- It should be evident that the present invention is not limited to the following embodiments.
- In the following embodiments, the terminology and abbreviations (analysis output image names) correspond as indicated below.
- AT: Arrival Time [sec]
- TTP: Time To Peak [sec]
- MTT: Mean Transit Time [sec]
- MFV: Mean Flow Velocity [cm/sec]
- BV: Blood Volume [ml]
- BF: Blood Flow [ml/min]
- rMFV: relative Mean Flow Velocity
- rBV: relative Blood Volume
- rBF: relative Blood Flow
- eBF: electromagnetic blood flow meter-measured Blood Flow [ml/min]
- Peak: peak amplitude image
- Kbf: quantification conversion coefficient
- S: vascular cross-sectional area (inner) [mm*mm]
- Fusion: image fusion
- ROI: Region of Interest
- ICG: Indocyanin green
- FITC: Fluorescein isothiocyanate
- In the present embodiment, image output refers to output by images, video, or images extracted from frames of video.
- First, the configuration of the system for image processing of intravascular hemodynamics according to the first embodiment will be explained. The system according to the present embodiment, as shown in
FIG. 1 , comprises aninfrared imaging device 100 for taking video of blood vessels using infrared light, avideo conversion device 102 for converting the video signals outputted from theinfrared imaging device 100 and preparing a video file, animage analysis device 104 for analyzing the video file converted by thevideo conversion device 102 and calculating relative data for blood volume or blood flow based on the image analysis results, and an analysisimage generating device 106 for generating an analysis image from quantitative data for the blood volume or blood flow obtained by theimage analysis device 104. - These devices can, for example, be provided within a single personal computer. Alternatively, they may be separate devices. Alternatively, some or all of the functions could be installed in a personal computer, or in measuring equipment, a display device or an analysis device in the form of software.
-
FIG. 2 shows an example of the configuration of a system according to the present embodiment.FIG. 2 describes an example of the configuration of the invention according to the present embodiment in microsurgery (surgery performed using a microscope). - The procedure for carrying out the method according to the present embodiment is as described below.
- Indocyanin green is administered as a fluorescent contrast agent. The administration is performed transvenously or transarterially. Ex.) 25 mg of indocyanin green is diluted to 10 ml and administered 2 ml at a time.
- As the fluorescent contrast agent, indocyanin green (ICG) or fluorescein isothiocyanate (FITC) may be used. ICG polymerizes with a-lipoproteins in blood to emit monochromatic fluorescent light in response to infrared light. This phenomenon is used in the field of ophthalmology for application to fundus fluorescent angiography. FITC is a fluorescent pigment that emits green light when exposed to ultraviolet rays.
- Aside from the above-described fluorescent contrast agents, other chemical agents may be appropriately used as long as they emit light of specific wavelengths when illuminated by light of specific wavelengths.
- An electromagnetic blood flow meter is used to measure the quantitative blood flow value at a single specific blood vessel position. The actual measurement operations using an electromagnetic blood flow meter are performed by sandwiching a blood vessel structure including a bypass graft in between electromagnetic blood flow meter probes.
- Video is taken with the
infrared imaging device 100. As theinfrared imaging device 100, a common surgical microscope capable of infrared imaging may be used. - Analog (composite) video signals taken with the
infrared imaging device 100 are analog-digital converted using a video capture device in thevideo conversion device 102. The digital video signals are loaded as video files into a local disk using a personal computer. The video files may be common video files such as MPEG or MOV. - In the
image analysis device 104, the image output of video images is analyzed by the following procedure. - In this case, the quantitative MTT data and relative rBV and rBF data are calculated by carrying out a first moment calculation procedure of perfusion analysis using a fluorescent angiography chemical during surgery, while simultaneously measuring the quantitative BF value using an electromagnetic blood flow meter on a single specific blood vessel which is visible in the surgical field of vision before vascular surgery.
- First, a single point (single pixel) in a blood vessel in an image is monitored over the passage of time. As a result, information on the change in the intensity value at that single point (single pixel) in the blood vessel can be obtained. In this case, the information on the change in intensity value can be obtained for just a single pixel, or the information may be the mean value for the intensity values of a plurality of pixels.
- By analyzing the chronological intensity value change curve, the state of passage of a clump of the ICG agent through the blood vessel can be quantitatively examined. The quantitative analysis shown in
FIG. 3 is performed for all pixels in the video image. AT, TTP and MTT, for which the analysis results are calculated in units of time (X axis), are determined as quantitative image data. rBV and rBF for which the analysis results are calculated from the integral of the intensity value (Y axis) are determined as relative image data. - While observing video data of the fluorescent contrast agent as a guide image, an ROI is prepared at the same blood vessel position as the specific blood vessel position that was measured with the electromagnetic blood flow meter (
FIG. 4 ). Next, an ROI statistical procedure is performed on the rBF image. The mean relative blood flow calculated by the ROI statistical procedure is defined as rBF (ROI). The conversion coefficient Kbf between eBF (ROI) and rBF (ROI) is calculated. -
eBF(ROI)=Kbf*rBF(ROI) - Here, ROI refers to a Region of Interest. ROI preparation is a process of preparing a region of interest by surrounding the region of interest in an image being observed with a two-dimensional closed curve. ROI statistics refer to image processing to calculate the mean image value per unit pixel inside an ROI shape.
- The quantification conversion formula that is established for a specific blood vessel position (ROI):
-
eBF(ROI)=Kbf*rBF(ROI) - is assumed to be a quantification conversion formula that applies to all positions in the image space.
- In other words, as shown in the following formula, conversion to the quantitative BF is possible by multiplication with the entire relative rBF image calculated by the first moment calculation procedure in perfusion analysis.
-
BF=Kbf*rBF - Due to the relationships established by first moment calculation in perfusion analysis:
-
rBF=rBF/MTT,BF=BV/MTT - and the quantification conversion formula for converting relative rBF images to quantitative BF images:
-
BF=Kbf*rBF - the following quantification conversion formula for converting relative rBV images to quantitative BV images is established.
-
BF=Kbf*rBV - The above-described parameters are related as shown below.
-
rBF=rBV/MTT: relative relationship -
BF=BV/MTT: quantitative relationship -
eBF(ROI)=Kbf*rBF(ROI): quantification conversion formula established at specific blood vessel position (ROI) -
BF=Kbf*rBF: quantification conversion formula between rBF and BF established for entire image -
BV=Kbf*rBV: quantification conversion formula between rBV and BV established for entire image - An output parameter image for image analysis can be extracted from the shape of the chronological intensity value change curve obtained from the information on the change in intensity value at one point in the blood vessel as shown in
FIG. 5 , and the relationship between the parameters is a relationship as shown inFIG. 5 . - Examples of analysis images before and after bypass surgery are shown in
FIG. 11 . This example shows that, after bypass surgery, the AT became shorter (the blood flow became faster), and the dark area in the center of the image became larger. - Quantitative intraoperative fluorescence angiography depends on the timing of the intravenous injection of the fluorescent contrast agent, and it is difficult to obtain stable results. By determining the integral value from the chronological intensity value change curve and determining the centroid of the area, stable BF, BV and MTT values that do not depend on the timing of the injection can be determined. Additionally, by referring to the graft blood flow due to the electromagnetic blood flow meter, a more precise BF can be calculated in consideration of the dosage of the graft blood vessel diameter and the amount of the fluorescent contrast agent administered. In accordance with need, tests can be repeated at standard timings by injecting a fluorescent contrast agent into the carotid artery.
- As described above, the method according to the present embodiment allows the state of the blood vessels before or after vascular surgery to be diagnosed by measuring quantitative BF values of specific blood vessels using an electromagnetic blood flow meter, and it can provide the information in a particularly visually recognizable form.
- Additionally, with a first moment method in perfusion analysis such as CT perfusion and MRI perfusion used as the analysis method for the tissues (capillaries), the area under the curve is defined as relative rBV, so the relative rBV image can be easily determined for each pixel. Additionally, when defining the AT time as the origin zero [sec], the time of the area centroid is defined as the quantitative MTT. The quantitative MTT can also be easily determined for each pixel.
- In conventional perfusion analysis methods, it is known that the equation rBF=rBV/MTT is established between the relative rBV and the relative rBF. While the quantitative BV and BF images cannot be estimated using only the first moment method of conventional perfusion analysis, according to the method of the present embodiment, the relative rBF image can be easily determined from the relative rBV image and the quantitative MTT image for each pixel by using the equation rBF=rBV/MTT.
- In the method of the second embodiment, the calculation technique for the “quantitative analysis of the video file” differs from that of the first embodiment, but the system configuration and other steps in the method are the same as in the first embodiment.
- Herebelow, the calculation method will be explained for the case wherein the perfusion imaging method (first moment method) for CT perfusion and MRI perfusion, which are tissue (capillary) analysis methods, are used in the blood vessel analysis method using intraoperative fluorescent angiography data (using a microscope camera).
- In tissue (capillary) analysis using perfusion imaging (first moment method), when the AT time is defined as the origin zero [sec], the time at the area centroid is defined as the quantitative MTT and the area under the curve is defined as the relative rBV. The following relationship is established between the relative rBV, the relative rBF and the quantitative MTT.
-
rBF=rBV/MTT - The electromagnetic blood flow meter correction formula for tissue (capillary) analysis will be considered. The relative rBF can be quantitatively converted to a BF [ml/min] image by measuring the quantitative BF [ml/min] at a specific blood vessel position using an electromagnetic blood flow meter.
-
BF [ml/min]=Kbf*rBF: electromagnetic blood flow meter correction formula - Here, BF [ml/min] refers to the quantitative blood flow that is “flowing per unit tissue”.
- Tissue (capillary) analysis allows the BF [ml/min] and the BV [ml/min] to be directly calculated. The concept of “flowing per unit tissue” can be predicted to be inappropriate for blood vessel analysis. In blood vessel analysis, the BF [ml/min] and BV [ml] flowing in a single blood vessel must be calculated.
- The exact solution when applying tissue (capillary) analysis using perfusion imaging (first moment method) to blood vessel analysis will be studied. In blood vessel analysis, when the AT time is defined as the origin zero [sec], the time at the area centroid is defined as the quantitative MTT. This relationship is no different from that in tissue (capillary) analysis.
- The quantitative MTT is a calculated quantity that can be defined by using the same concepts for both tissue analysis and capillary analysis. The area under the curve is defined as rβ. The following relationship is established between the relative rβ, the quantitative MTT and the rMFV (Mean Flow Velocity).
-
rMFV=rβ/MTT - In this embodiment, the aforementioned rBF in
FIG. 3 corresponds to rβ. - An explanation of the above-described relationship is shown in
FIG. 6 . This relationship was able to be derived from data analysis of phantom tests performed by changing the blood vessel diameter. As a result of the phantom tests, rβ/MTT was not proportional to rBF. The tests came to the conclusion that “rβ/MTT” is proportional to “rBF/S”. - The electromagnetic blood flow meter correction formula for the blood vessel analysis will be contemplated. The relative rMFV can be quantitatively converted to MFV [cm/sec] by measuring the quantitative MFV [cm/sec] at a specific blood vessel position using an electromagnetic blood flow meter.
-
MFV [cm/sec]=Kbf*fMFV: electromagnetic blood flow correction meter - MFV [cm/sec] is the mean blood flow velocity that is “flowing per unit space”. Here, the space in “per unit space” is considered to refer to both blood vessels and tissues (capillaries).
- The blood vessel diameter conversion formula for blood vessel conversion will be considered. The quantitative value to be finally calculated is BF [ml/min], so a method of calculating quantitative BF will be considered. The following blood vessel diameter conversion formula is established between the quantitative MFV and the quantitative BF.
-
BF [ml/min]=S [mm*mm]*MFV [cm/sec]: blood vessel diameter conversion formula - A summary of the BF calculation process is shown in the flow diagram of
FIG. 7 . - Additionally, as shown in
FIG. 8 , S is defined as the inner blood vessel cross-sectional area at a certain blood vessel position. - This blood vessel diameter conversion formula means that the quantitative BF can be calculated if the inner blood vessel cross-sectional area S can be measured at the position of each blood vessel. The fact that the inner blood vessel cross-sectional area S is not a single value is important. The thickness (blood vessel cross sectional area) of a blood vessel differs for each blood vessel. Additionally, when considered strictly, the thickness (blood vessel cross sectional area) of a blood vessel will differ even in a single blood vessel if the position is different. These differences mean that the inner blood vessel cross sectional area S is given exactly by the image.
- When using perfusion imaging (first moment method) blood vessel analysis, the directly obtained physical quantity is the relative rMFV. From this relative rMFV, the quantitative BF can be calculated by using the electromagnetic blood flow meter correction formula (MFV=Kbf*rMFV) and the blood vessel diameter conversion formula (BF=S*MFV) (
FIG. 9 ). - The method of the second embodiment enables a more exact BF value to be calculated.
- With the method of the third embodiment, the formula for calculating BF differs from the second embodiment, but the other steps relating to the system configuration and method are the same as in the first embodiment.
- In order to exactly calculate BF, the inner blood vessel cross sectional area S [mm*mm] must be exactly measured. However, it is difficult to exactly measure the inner blood vessel cross sectional area S [mm*mm].
- In the step of performing electromagnetic blood flow meter correction, the blood flow velocity (blood flow) is measured at a certain single blood vessel position. The blood vessel diameter R [mm] at this single location can be measured. The inner blood vessel cross sectional area S is determined from the measured blood vessel diameter R [mm]. As the first approximation, the inner blood vessel cross sectional area S is approximated as being the same within the same single blood vessel measured by the electromagnetic blood flow meter.
- The inner blood vessel cross sectional area S of other blood vessels not measured by the electromagnetic blood flow meter are also approximated. Due to this approximation, the inner blood vessel cross sectional area: S image, for which exact measurement was difficult, can be treated as a constant.
- Due to the method of the third embodiment, the perfusion image (first moment) blood vessel analysis can be calculated by approximation.
- As a fourth embodiment, a method that allows analysis similar to the first to third embodiments to be performed without performing electromagnetic blood flow meter measurements, by defining the operating conditions, will be explained. The fourth embodiment is the same as the above-described first to third embodiments, other than the fact that the operating conditions are defined without performing electromagnetic blood flow meter measurements.
- It is not easy to perform electromagnetic blood flow meter measurements every time. The measurement operations for electromagnetic blood flow measurements include the risk of damaging the blood vessel structure, and under current conditions, should be avoided as much as possible. The quantitative BV and BF images can be approximately calculated by matching the operating conditions, even without using an electromagnetic blood flow meter. In this case, the operating conditions include the sensitivity of the microscope camera, the magnification of the microscope camera, the working distance of the microscope camera, the angle of the microscope camera, and the amount of the fluorescent contrast agent administered.
- The “working distance” refers to the distance from the tip of the objective lens of the microscope camera to the object being imaged, on which the focal point is trained. The “angle” refers to the angle at which the microscope camera is viewing the object being imaged.
- The amount of the fluorescent contrast agent administered refers to the amount of chemical injected when injecting the fluorescent contrast agent (ICG; FITC) from a vein in the arm. Generally, the fluorescent contrast agent is diluted to make it easier to inject. This means that the state of dilution is made the same and that the same amount of injected chemical is injected after dilution. The specific conditions for matching the operating conditions can be determined by each organization, for example, by the hospital.
- In the method according to the fourth embodiment, the quantitative BV and BF images can be approximately calculated by matching the operating conditions, without using an electromagnetic blood flow meter or technology that allows the quantitative BV and BF images to be calculated by using an electromagnetic blood flow meter. For this reason, there are specific effects such as predictions of the blood flow that can be supplied to tissues by a bypass graft, and the long-term patency of a bypass.
- In cerebral aneurysms and carotid artery stenotic lesions, thickness information can provide information on the risks involved in surgical operations such as the tear susceptibility of arterial aneurysms and release of thrombi from stenotic lesions.
- ICG is capable of viewing to depths of 10 mm due to its fluorescence frequency. Blood vessel walls are about 0.1 to 10 mm thick, and the properties of blood vessel walls are important during surgery. Since the ICG intensity changes depending on the blood vessel wall thickness, the wall thickness can be estimated by holding constant the amount administered, the microscope camera sensitivity, the distance to the object being observed, and the magnification.
- FITC can view down to depths of 5 mm due to its fluorescence frequency. It is capable of observing blood vessel lesions having relatively thin blood vessel walls, and the patency of bypasses.
- The present method has the purpose of determining the blood flow (BF), blood volume (BV) and mean transit time (MTT) not only of brain tissue, but also of blood vessels themselves, as well as the thickness of blood vessel walls from the signal intensity.
- With just the above-mentioned output parameter image data from the results of fluorescent contrast agent analysis, the relationships between the anatomical positions such as arteries/veins and cerebral sulci are unclear. The relationships between the anatomical positions can be understood by performing image superimposition (image fusion) of output parameter image data of fluorescent contrast agent analysis results onto anatomical image (video) data.
- While image fusion is a tissue (capillary) analysis method, it requires a blood vessel analysis method. The results of the above-described image processing of intravascular hemodynamics can be used. The system used for the intravascular hemodynamics image processing method including an image fusion process has the configuration shown in
FIG. 12 . - In image processing of intravascular hemodynamics including an image fusion process, imaging is performed with a natural
light imaging device 108 as well as imaging with aninfrared imaging device 100. In this case, imaging is performed by natural light, and image or video data are recorded. - An image fusion device 110, with the natural
light imaging device 108 that takes video of a portion of a blood vessel by natural light, fuses the output images from the naturallight imaging device 108 and the analysis (video) images generated by the analysis image (video) generatingdevice 106. - In image fusion, the following types of image (video) data (A), (B) and (C) are used.
- (A) M-frame natural light video data (color images)
(B) N-frame fluorescent contrast agent video data (gray scale images)
(C) Still image data of analysis results (color scale images) [sometimes including plural data such as BF, BV and MTT] - In this case, the (gray scale images) refer to value-type images (used primarily in MRI and CT for medical images) in which the display colors are assigned by referring to a gray scale color table.
- The (color scale images) refer to value-type images (used primarily in nuclear medicine for medical images) in which the display colors are assigned by referring to color tables of rainbow colors etc.
- The (color images) refer to images in which the colors are fixed as in photographs.
- In this case, N-frame video data refers to images consisting of an animation of N frames in the time axis direction. Still image data refers to a single image like a photograph.
- The fluorescent contrast agent analysis according to the art of the above-described
Embodiment 1 or 2 is a process of deriving (C) from (B). The important points are that (A) is not used in processing of only fluorescent contrast agent analysis, and that (B) and (C) have the same positional relationship because the still image (C) is prepared from video (B). Regarding the image fusion process for (B) and (C), since they are at the same position, their positional relationship is always aligned. - Whether (A) has the same positional relationship as (B) and (C) differs depending on the equipment used. There are devices in which the shooting positions of the natural light video and the infrared light video differ and devices in which the positions are the same. Additionally, the number M of animation frames of the natural light video and the number N of animation frames of the fluorescent contrast agent video generally differ. Additionally, whether the time of shooting of the natural light video and the time of shooting of the fluorescent contrast agent video are the same also differs depending on the microscopy equipment. Whether or not they are shot at the same time is not an essential condition for the image fusion process.
- For the present embodiment, the next three types of image fusion process will be explained.
- (I) Image fusion process I (multiplication type image fusion process): Image fusion process I wherein image fusion still image data (color images) are prepared by image fusion processing of peak still image data (gray scale images) calculated from fluorescent contrast agent video data and output parameter still image data (gray scale images) from (C) image analysis.
- With this process, a (single color image) is prepared by combining a (single gray scale image) and a (single color scale image).
- (II) Image fusion process II (multiplication type image fusion process): Image fusion process II wherein image fusion video data (color image) is prepared by image fusion processing of (B) fluorescent contrast agent video data (gray scale image) and (C) image analysis output parameter still image data (color scale image).
- With this process, (N-frame color images) are prepared by combining (N-frame gray scale images) and a (single color scale image).
- (III) Image fusion process III (natural light video and image fusion process): Image fusion process III wherein image fusion video data (color images) are prepared by image fusion processing of image fusion video data (color images) prepared by image fusion processing and (A) natural light video data (color images) or (A) natural light still image data (color images).
- With this process, an (N-frame color image) is prepared by combining an (N-frame color image) and an (M-frame or single color image).
-
FIG. 13 shows an example of a processing procedure for image superimposition processing (image fusion processing). This processing procedure involves performing image fusion process II and image fusion process III, and preparing an (N-frame color image) from a combination of an (N-frame color image) and an (M-frame or single color image). - Image fusion process I and image fusion process II both involve performing the same multiplication-type image fusion process. The difference between image fusion process I and image fusion process II is that, in (I), there is one (gray scale image), whereas in (II), there are N frames of (gray scale images). The (C) image analysis output parameter still image data (color scale image) is also a single frame.
- In image fusion process I, just one multiplication-type image fusion process is performed. In image fusion process II, the process is performed N times while changing the fluorescent contrast agent video data (gray scale images). As for the resulting images for the image fusion processes, image fusion process I results in a still image, and image fusion process II results in video.
- The details of the multiplication-type image fusion processes that are commonly used in both image fusion process I and image fusion process II will now be explained. The advantage of multiplication-type image fusion processes is that the color of both gray scale images and color images can be reliably reproduced.
- Herebelow, the specific processing procedure for a multiplication-type image fusion process will be explained for a single gray scale image and a single color scale image. First, the fact that addition-type image fusion processes are not optimal will be explained.
- Addition-type image fusion processes use calculations based on the following basic formulas.
-
Color of color scale image1=(Red1,Green1,B1ue1) -
Color of color scale image2=(Red2,Green2,Blue2) -
Color of image after image fusion process=(FusionRed,FusionGreen,FusionBlue) - α: synthesis ratio which is a value represented by a number between 0.0 and 1.0.
-
FusionRed=α*Red2+(1.0−α)*Red1 -
FusionGreen=α*Green2+(1.0−α)*Green1 -
FusionBlue=α*Blue2+(1.0−α)*B1ue1 - Since the addition-type image fusion process formula adds the colors of the two images, it is referred to as an addition-type image fusion processing formula.
- In addition-type image fusion, in the case of a single gray scale image and a single color scale image:
-
The colors of color scale image1=(Red1,Green1,B1ue1) are replaced by -
the colors of a gray scale image=(Gray,Gray,Gray). -
The colors of color scale image2=(Red2,Green2,Blue2) are replaced by -
the colors of a color scale image=(Red,Green,Blue) -
FusionRed=α*Red+(1.0−α)*Gray -
FusionGreen=α*Green+(1.0−α)*Gray -
FusionBlue=α*Blue+(1.0−α)*Gray - It can be seen that the addition-type image fusion processing formula is not capable of reproducing the colors (Red, Green, Blue) of the color scale image.
- In this way, addition-type image fusion processing is a technique that is incapable of reliably reproducing the colors (Red, Green, Blue) in a color scale image. In contrast, the multiplication-type image fusion processing formula multiplies the colors of two images, and is therefore referred to as a multiplication-type image fusion processing formula.
- By using a multiplication-type image fusion processing formula, the colors (Red, Green, Blue) of color scale images can be reliably reproduced. The positions where the gray scale image is black can always be made black in the color scale image after fusion processing. The positions where the gray scale image is white can be made the same as the color (Red, Green, Blue) of the gray scale image of the original image in the color scale image after fusion processing.
- There are cases in which only a single natural light still image of a specific time is used from among M-frame natural light video data. In cases such as when it becomes complicated to use video, the process can be simplified by using just a single natural light still image.
- Embodiments of the present invention have been explained above. A part of the method of the first embodiment may be replaced with the fourth embodiment. Additionally, a part of the method of the first embodiment may be replaced by the second embodiment or the third embodiment. In other words, the above-described embodiments may be combined.
- As explained above, in vascular surgical operations, it is very important to keep abreast of the state of blood flow during the operation. The judgment of therapeutic effects of vascular surgery is important, such as whether cerebral blood flow blockage is complete, or whether adequate blood volume is provided to shunt blood vessels. In the inventions according to the embodiments described above, the BF, BV and MTT which could not conventionally be observed by fluorescent contrast agent analysis can be stably observed, and the inventions further can estimate the blood vessel wall thickness by signal intensity changes, and provide anatomical orientation by natural light and fusion. By fusing fluorescent contrast agent analysis results with images shot in natural light, the anatomical positional relationship can also be easily understood.
- In particular, it becomes possible to predict the long term patency of grafts and to predict the risk of hyperperfusion including evaluations of blood flow from grafts, to observe the state of blood flow changes on the brain surface, and to detect BV and BF changes caused by brain function reactions. Furthermore, there is a possibility that monochromatic video editing can be applied not only to fluorescent contrast agent analysis, but also to similar analysis of gray scale video, such as normal blood vessel imaging. By quantitatively comparing the state before vascular surgery and the state after vascular surgery using quantitative BV, BF and MTT images, therapeutic effects can be judged immediately after vascular surgery.
- In conventional methods, the amount and timing of intravenous injection of the fluorescent contrast agent are important, and since the fluorescent contrast agent is metabolized in the liver, the attenuation history of the intensity of the fluorescent contrast agent will change depending on the liver function. The quantitative BV, BF and MTT images calculated by the invention according to the above-described embodiments are capable of minimizing the effects of differences even if there are differences in the timing of injection of the fluorescent contrast agent. For this reason, the invention provides an analysis method that is effective for judging therapeutic effects.
- Additionally, there may be symptoms due to hyperperfusion of blood flow after bypass surgery. In such cases, predictive diagnoses can be made by observing the BV and BF quantitative images after bypass surgery. Since hyperperfusion carries the risk of hemorrhage and convulsions, it is extremely useful to be able to predict these symptoms during the operation. The predictive diagnosis of such symptoms was difficult given only AT and TTP information which was provided by the conventional art, while the invention according to the above-described embodiments is capable of handling such predictions.
- Additionally, by using fusion images, it is also possible to predict whether hyperperfusion is likely to occur in a certain area.
- While the method and system according to the present invention can be applied to vascular surgery in the fields of neurosurgery, orthopedic surgery and ophthalmic surgery using microscopes during the operation, there is no particular limitation thereto, and they can be applied to various forms of vascular surgery.
-
- 100 Infrared light imaging device
- 102 Video conversion device
- 104 Image analysis device
- 106 Analysis image (video) generation device
- 108 Natural light imaging device
- 110 Image (video) fusion device
Claims (21)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US17/128,718 US20210106237A1 (en) | 2013-09-20 | 2020-12-21 | Method and system for image processing of intravascular hemodynamics |
Applications Claiming Priority (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2013194898 | 2013-09-20 | ||
JP2013-194898 | 2013-09-20 | ||
PCT/JP2014/074801 WO2015041312A1 (en) | 2013-09-20 | 2014-09-19 | Method and system for image processing of intravascular hemodynamics |
US201615023015A | 2016-06-01 | 2016-06-01 | |
US17/128,718 US20210106237A1 (en) | 2013-09-20 | 2020-12-21 | Method and system for image processing of intravascular hemodynamics |
Related Parent Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/023,015 Continuation US10898088B2 (en) | 2013-09-20 | 2014-09-19 | Method and system for image processing of intravascular hemodynamics |
PCT/JP2014/074801 Continuation WO2015041312A1 (en) | 2013-09-20 | 2014-09-19 | Method and system for image processing of intravascular hemodynamics |
Publications (1)
Publication Number | Publication Date |
---|---|
US20210106237A1 true US20210106237A1 (en) | 2021-04-15 |
Family
ID=52688959
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/023,015 Active 2037-10-21 US10898088B2 (en) | 2013-09-20 | 2014-09-19 | Method and system for image processing of intravascular hemodynamics |
US17/128,718 Pending US20210106237A1 (en) | 2013-09-20 | 2020-12-21 | Method and system for image processing of intravascular hemodynamics |
Family Applications Before (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/023,015 Active 2037-10-21 US10898088B2 (en) | 2013-09-20 | 2014-09-19 | Method and system for image processing of intravascular hemodynamics |
Country Status (5)
Country | Link |
---|---|
US (2) | US10898088B2 (en) |
EP (1) | EP3047796B1 (en) |
JP (1) | JP5953437B2 (en) |
CN (1) | CN105705084B (en) |
WO (1) | WO2015041312A1 (en) |
Families Citing this family (21)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10426361B2 (en) | 2013-06-14 | 2019-10-01 | Novadaq Technologies ULC | Quantification of absolute blood flow in tissue using fluorescence-mediated photoplethysmography |
EP3047796B1 (en) | 2013-09-20 | 2020-11-04 | National University Corporation Asahikawa Medical University | Method and system for image processing of intravascular hemodynamics |
CN108882896B (en) * | 2015-09-23 | 2022-05-27 | 史赛克欧洲运营有限公司 | Methods and systems for assessing healing of tissue |
CN105559810B (en) * | 2015-12-10 | 2017-08-08 | 博动医学影像科技(上海)有限公司 | The computational methods of vascular units time CBF and VPV |
CA3053274A1 (en) * | 2016-02-16 | 2017-08-24 | Novadaq Technologies ULC | Facilitating assessment of blood flow and tissue perfusion using fluorescence-mediated photoplethysmography |
US10586314B2 (en) * | 2016-04-12 | 2020-03-10 | Shenzhen Everbest Machinery Industry Co., Ltd | Image fusion method, apparatus, and infrared thermal imaging device |
AU2017371512A1 (en) | 2016-12-09 | 2019-07-04 | Perfusion Tech IVS | System and method for assessing perfusion in an anatomical structure |
CN110177505B (en) * | 2017-01-11 | 2023-03-14 | 株式会社岛津制作所 | Fluorescence imaging apparatus and fluorescence imaging system |
JP6708143B2 (en) * | 2017-02-07 | 2020-06-10 | 株式会社島津製作所 | Time intensity curve measuring device |
EP3505059A1 (en) * | 2017-12-28 | 2019-07-03 | Leica Instruments (Singapore) Pte. Ltd. | Apparatus and method for measuring blood flow direction using a fluorophore |
EP3793432A4 (en) * | 2018-05-17 | 2022-03-23 | London Health Sciences Centre Research Inc. | Dynamic angiographic imaging |
US11911139B2 (en) | 2018-06-14 | 2024-02-27 | Perfusion Tech Aps | System and method for automatic perfusion measurement |
WO2019238912A1 (en) | 2018-06-14 | 2019-12-19 | Perfusion Tech Aps | System and method for automatic perfusion measurement |
US11253165B2 (en) | 2019-04-24 | 2022-02-22 | Mohammad Nasser | Intravascular MRI probe assembly |
EP4005472B1 (en) * | 2019-07-31 | 2024-05-22 | Suzhou Rainmed Medical Technology Co., Ltd. | Method and apparatus for correcting blood flow velocity on the basis of interval time between angiographic images |
DE102020102681B3 (en) * | 2020-02-03 | 2021-08-05 | Carl Zeiss Meditec Ag | Computer-implemented method, computer program and operating system for determining the blood volume flow through a section of a blood vessel in an operating area |
KR102386872B1 (en) * | 2020-03-10 | 2022-04-13 | 부산대학교 산학협력단 | Method for analyzing Colon Perfusion using real-time images |
CN111429457B (en) * | 2020-06-03 | 2020-09-11 | 中国人民解放军总医院 | Intelligent evaluation method, device, equipment and medium for brightness of local area of image |
CN115697193A (en) * | 2020-11-04 | 2023-02-03 | 株式会社Leimac | Non-contact blood vessel analysis device |
CN113616226B (en) * | 2021-09-14 | 2023-06-23 | 上海联影医疗科技股份有限公司 | Vascular analysis method, system, equipment and storage medium |
WO2023063324A1 (en) * | 2021-10-12 | 2023-04-20 | 国立大学法人東京工業大学 | Blood pump system and blood circulation system |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102008040803A1 (en) * | 2008-07-28 | 2010-02-04 | Carl Zeiss Surgical Gmbh | Method for the quantitative representation of the blood flow |
DE102008040804A1 (en) * | 2008-07-28 | 2010-02-04 | Carl Zeiss Surgical Gmbh | Method for quantitative representation of blood flow in tissue or vein region based on signal of contrast unit injected into blood, involves recording multiple individual images of signal emitted by tissue or vein region |
US20100168554A1 (en) * | 2005-06-30 | 2010-07-01 | Jens Sorensen | Evaluating Cardiac Function With Dynamic Imaging Techniques and Contrast Media |
WO2010136092A1 (en) * | 2009-05-25 | 2010-12-02 | Olympus Winter & Ibe Gmbh | Operation light, imaging system, and use of the operation light |
Family Cites Families (21)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5150292A (en) * | 1989-10-27 | 1992-09-22 | Arch Development Corporation | Method and system for determination of instantaneous and average blood flow rates from digital angiograms |
DE4214402C2 (en) * | 1992-04-30 | 1997-04-24 | Pulsion Verwaltungs Gmbh & Co | Device for determining the filling status of a blood circulation |
EP0794729B1 (en) * | 1994-12-01 | 2001-04-11 | Hoeft, Andreas, Prof. Dr. med. | Device for determining cerebral blood flow and intracerebral blood volume |
JP3799173B2 (en) | 1998-09-10 | 2006-07-19 | キヤノン株式会社 | Fundus blood flow measurement device |
US6844465B2 (en) * | 1998-10-30 | 2005-01-18 | Ajinomoto Co., Inc. | Method for preparing highly stable crystals of aspartame derivative |
US20050182434A1 (en) | 2000-08-11 | 2005-08-18 | National Research Council Of Canada | Method and apparatus for performing intra-operative angiography |
US6915154B1 (en) | 1999-09-24 | 2005-07-05 | National Research Council Of Canada | Method and apparatus for performing intra-operative angiography |
BR0014289A (en) | 1999-09-24 | 2002-07-02 | Ca Nat Research Council | Method and apparatus for performing intraoperative angiography |
DE10120980B4 (en) * | 2001-05-01 | 2009-12-03 | Pulsion Medical Systems Ag | A method, apparatus and computer program for determining blood flow in a tissue or organ region |
US8620410B2 (en) * | 2002-03-12 | 2013-12-31 | Beth Israel Deaconess Medical Center | Multi-channel medical imaging system |
JP3920140B2 (en) * | 2002-05-13 | 2007-05-30 | 株式会社東芝 | MRI apparatus and flow quantification apparatus |
JP2007525250A (en) * | 2003-06-02 | 2007-09-06 | ザ・ジェネラル・ホスピタル・コーポレイション | Tissue blood flow delay-compensated calculation method |
DE102005059520B4 (en) | 2005-12-13 | 2019-06-13 | Iprm Intellectual Property Rights Management Ag | Dilution device and computer program |
KR100818669B1 (en) * | 2007-03-09 | 2008-04-02 | 한국과학기술원 | Apparatus for measuring the perfusion rate of legs |
JP5290290B2 (en) * | 2007-07-18 | 2013-09-18 | シルク・ロード・メディカル・インコーポレイテッド | Method and system for establishing regurgitation of carotid blood flow |
JP2010017396A (en) | 2008-07-11 | 2010-01-28 | Olympus Corp | Method and device for observing living body |
US20110028850A1 (en) * | 2009-07-28 | 2011-02-03 | Thomas Schuhrke | Process for quantitative display of blood flow |
JP2013003495A (en) * | 2011-06-21 | 2013-01-07 | Mitaka Koki Co Ltd | Microscope system |
EP4147631A1 (en) | 2011-07-09 | 2023-03-15 | Gauss Surgical, Inc. | System for determining and method for estimating extracorporeal blood volume in a portion of a physical sample |
JP5385350B2 (en) | 2011-08-16 | 2014-01-08 | 富士フイルム株式会社 | Image display method and apparatus |
EP3047796B1 (en) | 2013-09-20 | 2020-11-04 | National University Corporation Asahikawa Medical University | Method and system for image processing of intravascular hemodynamics |
-
2014
- 2014-09-19 EP EP14846348.2A patent/EP3047796B1/en active Active
- 2014-09-19 US US15/023,015 patent/US10898088B2/en active Active
- 2014-09-19 WO PCT/JP2014/074801 patent/WO2015041312A1/en active Application Filing
- 2014-09-19 CN CN201480060640.XA patent/CN105705084B/en active Active
- 2014-09-19 JP JP2015537973A patent/JP5953437B2/en active Active
-
2020
- 2020-12-21 US US17/128,718 patent/US20210106237A1/en active Pending
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100168554A1 (en) * | 2005-06-30 | 2010-07-01 | Jens Sorensen | Evaluating Cardiac Function With Dynamic Imaging Techniques and Contrast Media |
DE102008040803A1 (en) * | 2008-07-28 | 2010-02-04 | Carl Zeiss Surgical Gmbh | Method for the quantitative representation of the blood flow |
DE102008040804A1 (en) * | 2008-07-28 | 2010-02-04 | Carl Zeiss Surgical Gmbh | Method for quantitative representation of blood flow in tissue or vein region based on signal of contrast unit injected into blood, involves recording multiple individual images of signal emitted by tissue or vein region |
WO2010136092A1 (en) * | 2009-05-25 | 2010-12-02 | Olympus Winter & Ibe Gmbh | Operation light, imaging system, and use of the operation light |
Non-Patent Citations (6)
Title |
---|
Bassingthwaighte, J. B., Ackerman, F. H., & Wood, E. H. (1966). Applications of the lagged normal density curve as a model for arterial dilution curves. Circulation Research, 18(4), 398-415. (Year: 1966) * |
Canas, R. V., & Liatsis, P. (2012). Interactive retinal blood flow estimation from fluorescein angiograms. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 226(10), 2521-2537. (Year: 2012) * |
Carl Zeiss Meditec AG. (2011). OPMI PENTERO 900. (Year: 2011) * |
Kamp, M. A., Slotty, P., Turowski, B., Etminan, N., Steiger, H. J., Hänggi, D.,& Stummer, W. (2012). Microscope-integrated quantitative analysis of intraoperative indocyanine green fluorescence angiography for blood flow assessment: first experience in 30 patients. Operative Neurosurgery, 70, ons65-74 (Year: 2012) * |
Sanislo, S. R, Blumenkranz, M. S, Verstraeten, T. C. (2006). Fluorescein and Indocyanine Green Angiography in Infectious and Inflammatory Diseases of the Retina and Choroid. In W. Tasman & E. A. Jaeger (Eds.), Duane's Opthamology on CD-ROM (2006 edition). Lippincott Williams & Wilkins. (Year: 2006) * |
Schubert, G. A., Seiz-Rosenhagen, M., Ortler, M., Czabanka, M., Scheufler, K. M., & Thomé, C. (2012). Cortical indocyanine green videography for quantification of acute hypoperfusion after subarachnoid hemorrhage: a feasibility study. Operative Neurosurgery, 71, ons260-ons268. (Year: 2012) * |
Also Published As
Publication number | Publication date |
---|---|
WO2015041312A1 (en) | 2015-03-26 |
US10898088B2 (en) | 2021-01-26 |
JPWO2015041312A1 (en) | 2017-03-02 |
CN105705084B (en) | 2019-07-12 |
CN105705084A (en) | 2016-06-22 |
JP5953437B2 (en) | 2016-07-20 |
EP3047796A1 (en) | 2016-07-27 |
US20160262638A1 (en) | 2016-09-15 |
EP3047796A4 (en) | 2017-05-31 |
EP3047796B1 (en) | 2020-11-04 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20210106237A1 (en) | Method and system for image processing of intravascular hemodynamics | |
Yeon et al. | Delayed-enhancement cardiovascular magnetic resonance coronary artery wall imaging: comparison with multislice computed tomography and quantitative coronary angiography | |
US8050737B2 (en) | Method and medical apparatus for measuring pulmonary artery blood flow | |
US8521260B2 (en) | Characterization of arteriosclerosis by optical imaging | |
JP5166596B2 (en) | Equipment for quantitatively determining blood in blood vessels and operating method thereof | |
Clevert et al. | Improving the follow up after EVAR by using ultrasound image fusion of CEUS and MS-CT | |
Ohno et al. | Oxygen-enhanced MR imaging: correlation with postsurgical lung function in patients with lung cancer | |
JP4446049B2 (en) | Myocardial blood flow quantification device | |
JP2005052648A (en) | Automatic calibration method of perfusion parameter image | |
Temov et al. | Coronary computed tomography angiography investigation of the association between left main coronary artery bifurcation angle and risk factors of coronary artery disease | |
Li et al. | Evaluation of the early enhancement of coronary atherosclerotic plaque by contrast-enhanced MR angiography | |
US20060173279A1 (en) | Method for implementing a medical imaging examination procedure | |
Pereira et al. | Non-invasive imaging techniques and assessment of carotid vasa vasorum neovascularization: Promises and pitfalls | |
Peñate Medina et al. | Imaging Inflammation–From Whole Body Imaging to Cellular Resolution | |
Knollmann et al. | Quantification of atherosclerotic coronary plaque components by submillimeter computed tomography | |
Kamada et al. | Novel techniques of real-time blood flow and functional mapping | |
Al-Qaisi et al. | Imaging of peripheral vascular disease | |
Hansch et al. | Quantitative evaluation of MR perfusion imaging using blood pool contrast agent in subjects without pulmonary diseases and in patients with pulmonary embolism | |
WO2017217340A1 (en) | Free radical consumption speed information acquisition method and nash determination method | |
Marcus et al. | Myocardial perfusion imaging by computed tomography: today and tomorrow | |
Cui et al. | Comparative analysis of 3D time-resolved contrast-enhanced magnetic resonance angiography, color Doppler ultrasound and digital subtraction angiography in symptomatic carotid stenosis | |
Richter et al. | Assessment of renal artery stenosis by phase-contrast magnetic resonance angiography | |
Gao et al. | Green tagging in displaying color Doppler aliasing: a comparison to standard color mapping in renal artery stenosis | |
US7030384B2 (en) | Adaptive opto-emission imaging device and method thereof | |
Wächter | 3D reconstruction of cerebral blood flow and vessel morphology from x-ray rotational angiography |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: NATIONAL UNIVERSITY CORPORATION ASAHIKAWA MEDICAL UNIVERSITY, JAPAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:KAMADA, KYOSUKE;REEL/FRAME:054717/0286 Effective date: 20160415 Owner name: NATIONAL UNIVERSITY CORPORATION ASAHIKAWA MEDICAL UNIVERSITY, JAPAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:INFOCOM CORPORATION;REEL/FRAME:054717/0258 Effective date: 20160412 Owner name: INFOCOM CORPORATION, JAPAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:HAYASHI, HIDEAKI;REEL/FRAME:054717/0213 Effective date: 20160411 |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: APPLICATION DISPATCHED FROM PREEXAM, NOT YET DOCKETED |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: DOCKETED NEW CASE - READY FOR EXAMINATION |
|
AS | Assignment |
Owner name: LEICA MICROSYSTEMS (SCHWEIZ) AG, SWITZERLAND Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:NATIONAL UNIVERSITY CORPORATION ASAHIKAWA MEDICAL UNIVERSITY;REEL/FRAME:060746/0120 Effective date: 20220418 |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: RESPONSE TO NON-FINAL OFFICE ACTION ENTERED AND FORWARDED TO EXAMINER |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: NON FINAL ACTION MAILED |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: FINAL REJECTION MAILED |