CN113706557A - Method for judging depth of lung nodule in three-dimensional space by symmetrical four regions of lung parenchyma - Google Patents
Method for judging depth of lung nodule in three-dimensional space by symmetrical four regions of lung parenchyma Download PDFInfo
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Abstract
The invention discloses a method for judging depth of a lung nodule in a three-dimensional space by four symmetrical partitions of lung parenchyma, which comprises the following steps: s1: acquiring image data; s2: performing picture processing on the image data in the S1, and symmetrically four-partitioning the lung lobes of the whole lung; s3: finding out a bronchus of the region to which the target pulmonary nodule belongs in the symmetrical four-partition of the whole lung lobe of S2, and taking the center of the cross section of the bronchus of the region to which the target pulmonary nodule belongs as an O point; s4: the center point of the target pulmonary nodule is a point A, and the point O and the point A are connected to form a line segment OA; s5: on the line segment OA, an extension line is made outwards from the point A until the line segment OA intersects with the pleura at the point B to form a line segment OB; s6: measuring data of line segment OA and line segment OB; s7: according to the formula (OB-OA)/OB, calculating the percentage value of the three-dimensional space depth of the target lung nodule in the lung parenchyma of the affiliated subarea; s8: and (6) judging. The advantages are that: the method of the invention provides a data quantification concept for the depth position of a lesion-lung nodule in a three-dimensional space in the lung parenchyma under the condition of avoiding the influence of mediastinum factors as much as possible.
Description
Technical Field
The invention relates to a method for judging the position of a pulmonary nodule, in particular to a method for judging the depth of the pulmonary nodule in a three-dimensional space by symmetrical four regions of lung parenchyma.
Background
With the popularization of early screening of lung cancer, the disease spectrum of lung cancer changes silently, and the detection rate of early lung cancer with the syndrome of wearing glass nodules is continuously increased. Corresponding surgical treatment methods are also rapidly developed, and precise minimally invasive surgical treatment of early non-small cell lung cancer (NSCLC) is internationally recognized, wherein lung section resection is gradually popularized and applied.
The surgical planning strategy of taking 'focus as center and lung sublevel as surgical unit' is gradually becoming the core concept of sub-lobe resection, and an important factor to be referred to when making an individualized surgical plan is the nodule depth position.
The National Comprehensive Cancer Network (NCCN) guidelines indicate that one of the current indications for sub-lobe resection surgery includes peripheral nodules, and conventional X-ray diagnosis divides the lung image into three fields, namely, upper, middle and lower fields, and three bands, namely, inner, middle and outer bands, however, with the gradual maturation and wide application of three-dimensional reconstruction techniques, clinicians find this approach inappropriate when attempting to define the depth position of nodules in three-dimensional images using the conventional methods described above. Researchers have suggested defining lesions located in the quaternary bronchi area as peripheral lesions, however, this is a concept established by the pathological anatomy of surgically excised specimens, cannot be applied to the physiologically dilated lung for lesion localization, and none of the above methods have quantitative data on depth location. Although the method for measuring the depth ratio by taking the lung lobe opening section as the center can provide quantitative data of the depth position of the lung nodule in the three-dimensional space, the method can be influenced by mediastinal factors, cannot truly reflect the three-dimensional space depth position of the lung nodule in the lung parenchyma, and cannot provide accurate depth position information for preoperative planning of sub-lobe resection operations such as 'taking a focus as the center and taking a lung subsection as an operation unit'.
Disclosure of Invention
In view of the above disadvantages, the present invention provides a method for determining depth of lung nodule in three-dimensional space by symmetric four-partition of lung parenchyma, comprising the following steps:
s1: acquiring image data;
s2: performing picture processing on the image data in the S1, symmetrically dividing the lung lobes of the whole lung into four regions, namely an upper region, a middle region, a back region and a lower region; wherein, the upper right lung region is the whole upper right lobe of the right lung and comprises a right upper lung tip section, a rear section and a front section; the middle area of the right lung, i.e. the entire right lobe of the right lung, includes the lateral and medial sections; the right lung back area is a right lung inferior lobe back section; the right inferior pulmonary region is a right inferior pulmonary lobe basal section and comprises a right inferior pulmonary inner basal section, a front basal section, an outer basal section and a back basal section;
the left lung upper region is an inherent section of the left lung upper lobe and comprises a rear section and a front section of the left lung upper lobe tip; the middle area of the left lung is a left lung superior lobe tongue section which comprises an upper tongue section and a lower tongue section; the left lung back area is a left lung inferior lobe back section; the left subvalvular region is a left lung basal segment and comprises an anterior basal segment, an outer basal segment and a posterior basal segment;
s3: finding out a bronchus of the region to which the target pulmonary nodule belongs in the symmetrical four-partition of the whole lung lobe of S2, and taking the center of the cross section of the bronchus of the region to which the target pulmonary nodule belongs as an O point;
s4: the center point of the target pulmonary nodule is a point A, and the point O and the point A are connected to form a line segment OA;
s5: on the line segment OA, an extension line is made outwards from the point A until the line segment OA intersects with the pleura at the point B to form a line segment OB;
s6: measuring data of line segment OA and line segment OB;
s7: according to the formula (OB-OA)/OB, calculating the three-dimensional space depth percentage value of the target lung nodule in the lung parenchyma of the affiliated subarea;
s8: judging that the percentage value is between 0 and 33.33 percent and is an outer band, the percentage value is between 33.33 and 66.66 percent and is a middle band, and the percentage value is more than 66.66 percent and is an inner band.
The invention firstly proposes a concept of data quantification in the determination of the three-dimensional spatial depth position of a lesion-lung nodule within the lung parenchyma.
Preferably, in S1, the CT scan and CT image data are stored in DICOM format.
Preferably, in S3, the point O is a center of a cross section at the beginning of the upper right lobe bronchus, a center of a cross section at the beginning of the middle right lobe bronchus in the right lung, a center of a cross section at the beginning of the lower right lobe bronchus in the right lung, a center of a cross section at the base section of the lower right lobe bronchus in the right lung, a center of a cross section at the native left upper lobe bronchus in the left lung, a center of a cross section at the bronchial section of the left lung lingual lobe bronchus in the left lung, a center of a cross section at the starting of the lower left lobe bronchus in the left lung, or a center of a cross section at the base section of the lower left lung bronchus in the left lung.
The preferred technical scheme of the invention is that the specific method of S2 is as follows:
s21: opening the CT image data downloaded in advance in the RadiAnt DICOM Viewer software;
s22: after the image loading is finished, clicking a Multiplanar reconfiguration function key → 3D MPR image of the RadiAnt DICOM Viewer software to switch to a two-dimensional three-section mode, and then clicking an Adjust window → CT ranges to Adjust the image from a mediastinal window to a lung window; at this time, the upper left corner in the two-dimensional three-section image is a sagittal plane, the lower left corner is a cross section, and the right side is a coronal plane;
s23: double-click the enlarged cross-section image, scroll a mouse to browse the cross-section image data, find a target pulmonary nodule and roughly judge the center of the pulmonary nodule;
s24: finding a target pulmonary nodule on the cross section, placing the center of a vector coordinate axis to the center of the target pulmonary nodule, and then reducing the cross section image by double-clicking a mouse to recover to a two-dimensional three-section mode;
s25: adjusting and observing images of a sagittal plane and a coronal plane simultaneously, and determining that the center of a vector coordinate axis is positioned at the center of a target pulmonary nodule;
s26: and rotating the horizontal line clockwise or anticlockwise in the cross-sectional image, observing the coronal image, finding the bronchus of the target lung nodule in the symmetrical four-subarea of the whole lung lobe, and taking the center of the cross section of the bronchus starting part of the area of the target lung nodule as an O point.
Preferably, after the point O is determined, an extension line is outwards extended from the point A to a pleural point B on a line segment OA connecting the point O with a center point A of a target pulmonary nodule, data measurement is carried out, and a percentage value is calculated.
Preferably, in S26, the method for checking the O point includes the following steps:
s261, adjusting the image of the sagittal plane, observing the deformation of the bronchus of the sagittal plane, finding out the center of the section of the bronchus at the starting part of the region of the target pulmonary nodule from the sagittal plane as a point O, and checking whether the point O determined by the coronal plane is consistent with the point O determined by the sagittal plane;
when the section of the bronchus starting position of the region of the target pulmonary nodule is symmetrically divided by a vertical line on the sagittal plane image, a point O on the coronal plane image is on the vertical line of the coronal plane image; the determined point O on the coronal plane image is consistent with the determined point O on the sagittal plane, namely the sagittal plane position of the determined point O on the coronal plane image is correct;
otherwise, they are not consistent; adjusting the point O on the coronal image until the point O is on a vertical line in the coronal image;
s262: adjusting the cross section image, observing the shape of the bronchus of the cross section, finding out the center of the cross section at the starting position of the bronchus of the region of the target pulmonary nodule from the cross section as a point O, and checking whether the point O determined by the coronal plane is consistent with the point O determined by the cross section;
when the horizontal line on the cross-sectional image symmetrically divides the section of the bronchus starting position of the region to which the target pulmonary nodule belongs, the point O on the coronal plane image is on the horizontal line in the coronal plane image; the determined point O on the coronal plane image is consistent with the determined point O of the cross section, i.e. the cross section position of the determined point O on the coronal plane image is correct;
otherwise, they are not consistent; the adjustment of point O is performed on the coronal image until point O is located on a horizontal line within the coronal image.
The preferred technical scheme of the invention is that the specific method of S2 is as follows:
s2-1: importing the CT image data downloaded in advance into the deep insight software image processor;
s2-2: after the data import is finished, loading the sequence data to the image processor;
s2-3: clicking the lung function in the image processor of the deep insight software to enter a three-dimensional reconstruction image making mode;
s2-4: adjusting the longitudinal partition window image into a lung window by presetting a window width window level, and primarily browsing the image data to find a target lung nodule;
s2-5: sequentially extracting a bronchus, a pulmonary vessel and a target pulmonary nodule;
s2-6: and clicking a distance calibration function in the DeepInsight software, and then finding out the center of the cross section of the bronchus starting position of the region to which the target pulmonary nodule belongs as an O point according to the shape of the bronchus of the region to which the target pulmonary nodule belongs in the cross-sectional image.
Preferably, after the O point is determined, a distance calibration function in deep insight software marks and determines to generate corresponding OB and OB-OA values, and a percentage value is calculated.
In the preferred embodiment of the present invention, the method for checking the O point comprises: modifying the window width and window position of the deep insight software in the three-dimensional reconstruction image mode to enable the three-dimensional reconstruction image to show a bronchus mode, and judging whether the marked point O is accurate or not by the bronchus generated by rotation; if the error exists, the adjusting point O needs to be carried out again in the cross section; if accurate, OB and OB-OA values automatically generated by DeepInsight software are read and percentage values are calculated.
Compared with the prior art, the invention has the following beneficial effects:
the invention firstly provides a concept of data quantification for determining the three-dimensional space position of a lesion-pulmonary nodule in lung parenchyma.
In the method, the two lungs of the invention are respectively divided into an upper region, a middle region, a back region and a lower region, the center of the section of the bronchus starting position in the region to which the focus belongs is used as a measurement starting point, and the influence of mediastinal internal organs (such as aorta, pulmonary artery, pulmonary vein and pericardium) is eliminated, so that the measured depth ratio can be ensured to be the depth of a lung nodule in the real lung parenchyma, and the method is more in line with the lung parenchyma concept proposed in the NCCN subphylum lobe resection guide, and therefore, the method has strong guiding significance in the preoperative planning of the subphylum lobe resection operation.
In the method, the judgment result in the two-dimensional three-section image has high consistency with the judgment result in the three-dimensional reconstruction image, and the method is feasible and reasonable for judging the three-dimensional space position of the lung nodule.
Drawings
Fig. 1 is a flowchart of a method for determining depth in three-dimensional space of a lung nodule in symmetric quadrants of lung parenchyma according to the present invention.
FIG. 2 is a graph showing the influence of the pulmonary artery on the OB value in the two-dimensional three-slice image according to the embodiment.
FIG. 3 is a graph showing the influence of the OA value of the depth ratio in the two-dimensional three-slice image on the pulmonary artery according to the embodiment.
Fig. 4 is a graph showing the influence of pulmonary arteries on the depth ratio OA and OB in the three-dimensional reconstructed image according to the embodiment.
Fig. 5 is a diagram of a two-dimensional three-section image with the vector coordinate axis positioned to the center of the lung nodule to determine a point a.
Fig. 6 is a diagram of the center O of the cross section of the bronchus at the beginning of the region where the target pulmonary nodule is found in the coronal plane by adjusting the cross-sectional image in the two-dimensional three-section image.
FIG. 7 is a two-dimensional three-section image showing the accuracy of the point O identified in the sagittal plane versus the coronal plane.
Fig. 8 is a diagram showing the accuracy of the point O determined in the coronal plane of the cross sectional plane of the two-dimensional three-section image.
FIG. 9 is a graph of OB values measured in a two-dimensional three-slice image.
FIG. 10 is a graph of measured OA values in a two-dimensional three-section image.
Fig. 11 is a diagram of the determination of the center point a of the target lung nodule in the cross-sectional image of the three-dimensional reconstruction software.
Fig. 12 is a central point O diagram of a cross section of the bronchial tube at the beginning of the region to which the target pulmonary nodule belongs, determined from the cross-sectional image of the three-dimensional reconstruction software.
Fig. 13 is a diagram showing whether the observation point O is accurate after the reconstructed image is rotated to a proper position in the three-dimensional reconstruction software.
Fig. 14 is a graph showing specific values of OA and OB read by the three-dimensional reconstruction software.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to fig. 1 to 14 and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
A method for judging the depth of a lung nodule in a three-dimensional space by four symmetric partitions of lung parenchyma is characterized by comprising the following steps:
s1: acquiring image data;
s2: performing picture processing on the image data in the S1, symmetrically dividing the lung lobes of the whole lung into four regions, namely an upper region, a middle region, a back region and a lower region; wherein, the upper right lung region is the whole upper right lobe of the right lung and comprises a right upper lung tip section, a rear section and a front section; the middle area of the right lung, i.e. the entire right lobe of the right lung, includes the lateral and medial sections; the right lung back area is a right lung inferior lobe back section; the right inferior pulmonary region is a right inferior pulmonary lobe basal section and comprises a right inferior pulmonary inner basal section, a front basal section, an outer basal section and a back basal section;
the left lung upper region is an inherent section of the left lung upper lobe and comprises a rear section and a front section of the left lung upper lobe tip; the middle area of the left lung is a left lung superior lobe tongue section which comprises an upper tongue section and a lower tongue section; the left lung back area is a left lung inferior lobe back section; the left subvalvular region is a left lung basal segment and comprises an anterior basal segment, an outer basal segment and a posterior basal segment;
s3: finding out a bronchus of the region to which the target pulmonary nodule belongs in the symmetrical four-partition of the whole lung lobe of S2, and taking the center of the cross section of the bronchus of the region to which the target pulmonary nodule belongs as an O point;
s4: the center point of the target pulmonary nodule is a point A, and the point O and the point A are connected to form a line segment OA;
s5: on the line segment OA, an extension line is made outwards from the point A until the line segment OA intersects with the pleura at the point B to form a line segment OB;
s6: measuring data of line segment OA and line segment OB;
s7: according to the formula (OB-OA)/OB, calculating the percentage value of the three-dimensional space depth of the target lung in the lung parenchyma of the affiliated subarea;
s8: judging that the percentage value is between 0 and 33.33 percent and is an outer band, the percentage value is between 33.33 and 66.66 percent and is a middle band, and the percentage value is more than 66.66 percent and is an inner band.
In the method, the method for acquiring the image data by CT scanning comprises the following steps:
the CT examination used a third generation dual source CT (Somatom form, siemens, germany), dual barrel high pressure syringe, iopromide 370 (bayer healthcare limited). The patient is in the supine position, the two hands are placed on the top of the head, and a 22G venous indwelling needle is placed in the median brachial vein or the forearm vein. A time-density curve was obtained using a double-barrel high-pressure syringe (medreri Medrad) using the bolus method, and the scanning start time was set. A non-ionic contrast medium (Youyuwei, Xianling Bayer, Germany) was injected at a rate of 5ml/s, and the amount of the contrast medium injected was set according to parameters such as height and weight, and then 20 ml of physiological saline was added at the same rate. The scan range includes the thoracic access plane to the diaphragm plane. Scanning parameters are as follows: the tube voltage is 120 kV, the effective tube current is about 100-150 mA, the thickness of the collimator is 0.6mm, the thickness of the reconstruction layer is 1mm, the layer spacing is 0.8mm, and the reconstructed convolution kernel (kernel) is a soft tissue algorithm (B30). During the scanning process, the patient holds breath to scan along with the breathing instruction. When using an iodine contrast agent, care should be taken to prevent adverse reactions.
The image data obtained by CT scanning is stored in DICOM format for further use.
In the method, the point O in S3 is that the right upper lung region is the center of the cross section at the starting position of the right upper lung lobe bronchus, the right middle lung region is the center of the cross section at the starting position of the right middle lung lobe bronchus, the right back lung region is the center of the cross section at the starting position of the right lower lung lobe bronchus, the right lower lung region is the center of the cross section at the base position of the right lower lung lobe bronchus, the left upper lung region is the center of the cross section at the starting position of the left upper lung lobe bronchus at the left upper lung lobe bronchus, the left middle lung region is the center of the cross section at the bronchial position of the left upper lung lobe bronchus at the left tongue lobe bronchus, and the left back lung region is the center of the cross section at the starting position of the left lower lung lobe bronchus at the left lung lobe bronchus or the left lower lung region is the center of the cross section at the base position of the left lower lung bronchus.
Example 1:
and in the two-dimensional three-section image, the depth of the target pulmonary nodule is judged by using the method.
The method is used for judging the depth of the target lung nodule in the two-dimensional three-section image by utilizing the RadiAnt DICOM Viewer software known by the ordinary skilled person in the technical field.
Examples of such applications are
Patient's women, age 56 years old, chest CT suggestion left lung superior lobe is proper to be had one and is ground glass lung nodule, and the depth ratio judgement result that uses the center of the initial cross-section of lung lobe bronchus as point O is: 1) two-dimensional trisection OB =103, OA =71.1, depth ratio = (OB-OA)/OB = 30.97%; 2) the three-dimensional reconstruction OB =103, OA =71, depth ratio = (OB-OA)/OB = 31.07%, belonging to an extinct lung nodule in three-dimensional space. However, when the center of the cross section at the beginning of the bronchus of the lung lobe is taken as the point O, the measured depth ratio result is influenced by mediastinal factors, and in this embodiment, the position of the pulmonary artery in the space is also included in the depth ratio calculation, as shown in fig. 2, 3 and 4, so that the depth of the pulmonary nodule in the true lung parenchyma cannot be effectively determined.
The image data obtained by CT scanning is stored in DICOM format for further use.
S21: opening the CT image data downloaded in advance in the RadiAnt DICOM Viewer software;
s22: after the image loading is finished, clicking a Multiplanar reconfiguration function key → 3D MPR image of the RadiAnt DICOM Viewer software to switch to a two-dimensional three-section mode;
then click on Adjust window → CT lungs to Adjust the image from mediastinal window to lung window; at this time, the upper left corner in the two-dimensional three-section image is a sagittal plane, the lower left corner is a cross section, and the right side is a coronal plane;
s23: double-click the enlarged cross-section image, scroll a mouse to browse the cross-section image data, find a target pulmonary nodule and roughly judge the center of the pulmonary nodule;
s24: finding a target pulmonary nodule on the cross section, placing the center of a vector coordinate axis to the center of the target pulmonary nodule, and then reducing the cross section image by double-clicking a mouse to recover to a two-dimensional three-section mode;
s25: adjusting and observing the images of the cross section, the sagittal plane and the coronal plane simultaneously, and determining that the center of the coordinate axis of the vector is positioned at the center of the target pulmonary nodule, as shown in FIG. 5;
s26: the horizontal line is rotated clockwise or counterclockwise in the cross-sectional image, and the coronal image is observed to find the bronchus of the target lung nodule in the symmetrical four-segment of the lung lobes, and the center of the cross section of the bronchus starting position of the region of the target lung nodule is taken as the point O, as shown in fig. 6.
In this embodiment, the method for checking the O point determined in S26 includes the following steps:
s261, adjusting the image of the sagittal plane, observing the deformation of the bronchus of the sagittal plane, finding out the center of the section of the bronchus at the starting part of the region of the target pulmonary nodule from the sagittal plane as a point O, and checking whether the point O determined by the coronal plane is consistent with the point O determined by the sagittal plane or not, as shown in FIG. 7;
when the section of the bronchus starting position of the region of the target pulmonary nodule is symmetrically divided by a vertical line on the sagittal plane image, a point O on the coronal plane image is on the vertical line of the coronal plane image; the determined point O on the coronal plane image is consistent with the determined point O on the sagittal plane image, and the sagittal plane position of the determined point O on the coronal plane image is correct;
otherwise, they are not consistent; adjusting the point O on the coronal image until the point O is on a vertical line in the coronal image;
s262: adjusting the cross-section image, observing the shape of the bronchus of the cross-section, finding out the center of the cross-section at the starting position of the bronchus of the region to which the target pulmonary nodule belongs from the cross-section as a point O, and checking whether the point O determined by the coronal plane is consistent with the point O determined by the cross-section or not, as shown in FIG. 8;
when the horizontal line on the cross-sectional image symmetrically divides the section of the bronchus starting position of the region to which the target pulmonary nodule belongs, the point O on the coronal plane image is on the horizontal line in the coronal plane image; if the determined point O on the coronal plane image is consistent with the determined point O on the transverse plane, the transverse plane position of the determined point O on the coronal plane image is correct;
otherwise, they are not consistent; the adjustment of point O is performed on the coronal image until point O is located on a horizontal line within the coronal image.
In this embodiment, after the point O is determined, the connection point O and the center point a of the target lung nodule and the line segment OA are extended outward from the point a to the pleural point B to form a line segment OB, and the numerical values of the line segment OA and the line segment OB are measured by using the functions of measures and tools in the radiaant DICOM Viewer software, as shown in fig. 9 and 10; according to the formula depth ratio = (OB-OA)/OB, a depth ratio value is calculated. 0 to 33.33% of the inner band is an outer band, 33.33 to 66.66% of the inner band is a middle band, and > 66.66% of the outer band is an inner band.
In this example, OB =98, OA =64, depth ratio = 34.69%; judging that the lung nodule is located at the rear section of the upper lobe tip of the left lung and belongs to the upper left region, and judging the depth of the lung nodule in the three-dimensional space by the symmetrical four-region lung parenchyma judging method judges that the lung nodule is a lung nodule with lung.
Example 2:
in the three-dimensional reconstruction image, the depth of the target pulmonary nodule is judged by the method:
the depth of the target pulmonary nodule is judged by the method in the two-dimensional three-section image by utilizing deep insight software (DEMO version) known by a person skilled in the art:
for example, as in example 1, a target lung nodule.
The image data obtained by CT scanning is stored in DICOM format for further use.
S2-1: importing the CT image data downloaded in advance into the deep insight software image processor;
s2-2: after the data import is finished, loading the sequence data to the image processor;
s2-3: clicking the lung function in the image processor of the deep insight software to enter a three-dimensional reconstruction image making mode;
s2-4: presetting window width window positions (1200-600), adjusting the mediastinum window image into a lung window, and primarily browsing the image data to find a target lung nodule;
s2-5: sequentially extracting bronchi, pulmonary blood vessels and target pulmonary nodules, as shown in fig. 11;
s2-6: clicking a distance calibration function in the deep sight software, and then finding out the center of the cross section of the bronchial starting position of the region to which the target pulmonary nodule belongs as an O point according to the bronchial shape of the region to which the target pulmonary nodule belongs in the cross-sectional image, as shown in fig. 12.
In this embodiment, the method for checking the O point includes: modifying the window width and window position of the deep insight software in the three-dimensional reconstruction image mode to enable the three-dimensional reconstruction image to show a bronchus mode, and judging whether the marked point O is accurate or not by the bronchus generated by rotation, as shown in fig. 13, if the marked point O is wrong, adjusting the point O again in the cross section; if accurate, the OB and OB-OA values automatically generated by the DeepInsight software are read, as shown in FIG. 14, and the percentage values are calculated.
In this embodiment, after the O point is determined, a distance calibration function in the DeepInsight software performs marking and determining to generate corresponding OB and OB-OA values, and calculates a percentage value. According to the formula depth ratio = (OB-OA)/OB, a depth ratio value is calculated. 0 to 33.33% of the inner band is an outer band, 33.33 to 66.66% of the inner band is a middle band, and > 66.66% of the outer band is an inner band.
In this example, OB =98, OA =64, depth ratio = 34.69%; judging that the lung nodule is located at the rear section of the upper lobe tip of the left lung and belongs to the upper left region, and judging the depth of the lung nodule in the three-dimensional space by the symmetrical four-region lung parenchyma judging method judges that the lung nodule is a lung nodule with lung.
Based on the embodiment 1 and the embodiment 2, the depth of the target lung nodule can be determined in the two-dimensional three-section image and the three-dimensional reconstruction image by the method, and it can be found that the ratio of the measured depth in the two modes to the measured depth has high consistency, and the depth determination results of the two modes on the target lung nodule are completely the same. Compared with a depth ratio measuring method taking the center of the section at the beginning of the bronchus of the lung lobe as a point O, the method for determining the depth of the lung nodule in the three-dimensional space by the symmetrical four-partition of the lung parenchyma sets the point O as the center of the section at the beginning of the bronchus of the target lung nodule attribution region.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the protection scope of the present invention.
Claims (9)
1. A method for judging the depth of a lung nodule in a three-dimensional space by four symmetric partitions of lung parenchyma is characterized by comprising the following steps:
s1: acquiring image data;
s2: performing picture processing on the image data in the S1, symmetrically dividing the lung lobes of the whole lung into four regions, namely an upper region, a middle region, a back region and a lower region; wherein, the upper right lung region is the whole upper right lobe of the right lung and comprises a right upper lung tip section, a rear section and a front section; the middle area of the right lung, i.e. the entire right lobe of the right lung, includes the lateral and medial sections; the right lung back area is a right lung inferior lobe back section; the right inferior pulmonary region is a right inferior pulmonary lobe basal section and comprises a right inferior pulmonary inner basal section, a front basal section, an outer basal section and a back basal section;
the left lung upper region is an inherent section of the left lung upper lobe and comprises a rear section and a front section of the left lung upper lobe tip; the middle area of the left lung is a left lung superior lobe tongue section which comprises an upper tongue section and a lower tongue section; the left lung back area is a left lung inferior lobe back section; the left subvalvular region is a left lung basal segment and comprises an anterior basal segment, an outer basal segment and a posterior basal segment;
s3: finding out a bronchus of the region to which the target pulmonary nodule belongs in the symmetrical four-partition of the whole lung lobe of S2, and taking the center of the cross section of the bronchus of the region to which the target pulmonary nodule belongs as an O point;
s4: the center point of the target pulmonary nodule is a point A, and the point O and the point A are connected to form a line segment OA;
s5: on the line segment OA, an extension line is made outwards from the point A until the line segment OA intersects with the pleura at the point B to form a line segment OB;
s6: measuring data of line segment OA and line segment OB;
s7: according to the formula (OB-OA)/OB, calculating the percentage value of the three-dimensional space depth of the target lung nodule in the lung parenchyma of the affiliated subarea;
s8: judging that the percentage value is between 0 and 33.33 percent and is an outer band, the percentage value is between 33.33 and 66.66 percent and is a middle band, and the percentage value is more than 66.66 percent and is an inner band.
2. The method of claim 1, wherein the symmetrical four-segmentation of lung parenchyma determines depth of lung nodule in three-dimensional space, wherein: in S1, the CT scan and CT image data are stored in DICOM format.
3. The method of claim 1, wherein the symmetrical four-segmentation of lung parenchyma determines depth of lung nodule in three-dimensional space, wherein: in S3, point O is a center of a right superior lung area of a right superior lung bronchus starting section, a center of a right middle lung area of a right lower lung area of a bronchus starting section, a center of a right inferior lung area of a right lower lung area of a bronchus emitting base section, a center of a left superior lung area of a left upper lung area of a left superior lung area of a left lingual section bronchus emitting section, a center of a left posterior lung area of a left inferior lung area of a left lower lung area of a left inferior lung area of a left superior lung area of a left posterior section bronchus starting section, and a center of a left inferior lung area of a base section emitting section bronchus.
4. The method for determining the depth of a lung nodule in three-dimensional space according to the symmetrical four-partition of lung parenchyma of claim 2 or 3, wherein: the specific method of S2 is as follows:
s21: opening the CT image data downloaded in advance in the RadiAnt DICOM Viewer software;
s22: after the image loading is finished, clicking a Multiplanar reconfiguration function key → 3D MPR image of the RadiAnt DICOM Viewer software to switch to a two-dimensional three-section mode, and then clicking an Adjust window → CT ranges to Adjust the image from a mediastinal window to a lung window; at this time, the upper left corner in the two-dimensional three-section image is a sagittal plane, the lower left corner is a cross section, and the right side is a coronal plane;
s23: double-click the enlarged cross-section image, scroll a mouse to browse the cross-section image data, find a target pulmonary nodule and roughly judge the center of the pulmonary nodule;
s24: finding a target pulmonary nodule on the cross section, placing the center of a vector coordinate axis to the center of the target pulmonary nodule, and then reducing the cross section image by double-clicking a mouse to recover to a two-dimensional three-section mode;
s25: adjusting and observing images of a sagittal plane and a coronal plane simultaneously, and determining that the center of a vector coordinate axis is positioned at the center of a target pulmonary nodule;
s26: and rotating the horizontal line clockwise or anticlockwise in the cross-sectional image, observing the coronal image, finding the bronchus of the target lung nodule in the symmetrical four-subarea of the whole lung lobe, and taking the center of the cross section of the bronchus starting part of the area of the target lung nodule as an O point.
5. The method of claim 4, wherein the lung parenchymal symmetric four-partition is used for determining the depth of the lung nodule in the three-dimensional space, and the method comprises the following steps: in S26, after the point O is determined, the connecting point O is extended outwards from the point A to the pleural point B on the line segment OA with the center point A of the target pulmonary nodule, and data measurement is carried out to calculate the percentage value.
6. The method of claim 4, wherein the lung parenchymal symmetric four-partition is used for determining the depth of the lung nodule in the three-dimensional space, and the method comprises the following steps: in S26, the method for checking the point O includes the following steps:
s261, adjusting the image of the sagittal plane, observing the deformation of the bronchus of the sagittal plane, finding the center of the section of the bronchus at the beginning of the region of the target pulmonary nodule from the sagittal plane as a point O, and checking whether the point O determined by the coronal plane is consistent with the point O determined by the sagittal plane;
when the section of the bronchus starting position of the region of the target pulmonary nodule is symmetrically divided by a vertical line on the sagittal plane image, a point O on the coronal plane image is on the vertical line of the coronal plane image; the point O determined by the coronal plane is consistent with the point O determined by the sagittal plane, namely the sagittal plane position of the point O determined on the coronal plane image is correct;
otherwise, they are not consistent; adjusting the point O on the coronal image until the point O is on a vertical line in the coronal image;
s262: adjusting the cross section image, observing the shape of the bronchus of the cross section, finding the center of the cross section of the bronchus starting part of the region of the target pulmonary nodule from the cross section as a point O, and checking whether the point O determined by the coronal plane is consistent with the point O determined by the cross section;
when the horizontal line on the cross-sectional image symmetrically divides the section of the bronchus starting position of the region to which the target pulmonary nodule belongs, the point O on the coronal plane image is on the horizontal line in the coronal plane image; the determined point O of the coronal plane is consistent with the determined point O of the transverse plane, namely the transverse position of the determined point O on the coronal plane image is correct;
otherwise, they are not consistent; the adjustment of point O is performed on the coronal image until point O is located on a horizontal line within the coronal image.
7. The method for determining the depth of a lung nodule in three-dimensional space according to the symmetrical four-partition of lung parenchyma of claim 2 or 3, wherein: the specific method of S2 is as follows:
s2-1: importing the CT image data downloaded in advance into the deep insight software image processor;
s2-2: after the data import is finished, loading the sequence data to the image processor;
s2-3: clicking the lung function in the image processor of the deep insight software to enter a three-dimensional reconstruction image making mode;
s2-4: presetting a window width window level, adjusting the mediastinum window image into a lung window, and primarily browsing the image data to find a target lung nodule;
s2-5: sequentially extracting a bronchus, a pulmonary vessel and a target pulmonary nodule;
s2-6: and clicking a distance calibration function in the DeepInsight software, and then finding the center of the section of the bronchus starting position of the region to which the target pulmonary nodule belongs according to the shape of the bronchus of the region to which the target pulmonary nodule belongs in the cross-section image, wherein the center is an O point.
8. The method of claim 7, wherein the symmetrical quadrants of lung parenchyma determine depth in three-dimensional space of lung nodules, wherein: in S2-6, after the O point is determined, the distance calibration function in the deep insight software marks and determines, corresponding OB and OB-OA values are automatically generated, and percentage values are calculated.
9. The method of claim 7, wherein the symmetrical quadrants of lung parenchyma determine depth in three-dimensional space of lung nodules, wherein: in S2-6, the method for checking the O point comprises the following steps: modifying the window width and window position of the deep insight software in the three-dimensional reconstruction image mode to enable the three-dimensional reconstruction image to show a bronchus mode, and judging whether the marked point O is accurate or not by the bronchus generated by rotation;
if the error exists, the adjusting point O needs to be carried out again in the cross section;
if accurate, OB and OB-OA values automatically generated by DeepInsight software are read and percentage values are calculated.
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