WO2009156897A1 - Système médical pour récupération d’informations médicales - Google Patents

Système médical pour récupération d’informations médicales Download PDF

Info

Publication number
WO2009156897A1
WO2009156897A1 PCT/IB2009/052555 IB2009052555W WO2009156897A1 WO 2009156897 A1 WO2009156897 A1 WO 2009156897A1 IB 2009052555 W IB2009052555 W IB 2009052555W WO 2009156897 A1 WO2009156897 A1 WO 2009156897A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
medical
type
database
image
Prior art date
Application number
PCT/IB2009/052555
Other languages
English (en)
Inventor
Yasser H. Alsafadi
Original Assignee
Koninklijke Philips Electronics N.V.
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Koninklijke Philips Electronics N.V. filed Critical Koninklijke Philips Electronics N.V.
Publication of WO2009156897A1 publication Critical patent/WO2009156897A1/fr

Links

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G16B25/10—Gene or protein expression profiling; Expression-ratio estimation or normalisation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G16B50/10—Ontologies; Annotations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression

Definitions

  • the invention relates to a medical system and in particular to a medical system for retrieval of medical information related to a search request.
  • microarrays have developed into a powerful tool for analyzing molecular samples by generation of gene expression profiles. Due to the unsurpassed sensitivity and reproducibility of microarrays, the analysis results provide valuable insight into various biological processes. Due to the success of microarrays, they are used for example used for reclassification of diseases based on gene expressions of biological material related to such diseases.
  • medical picture archiving and communication systems are used managing and organizing medical images.
  • Such systems comprise imaging equipment for acquiring the images, workstations for viewing images, databases for storing images and a computer network for interconnecting the system components.
  • Enormous amounts of information are stored in both medical picture archiving systems and analysis results from microarrays such as gene expressions. Due to the enormous amounts of information, it would be desirable to be able to utilize any synergetic effects by combining information from different systems, e.g. medical picture archiving systems and analysis information from microarrays. Accordingly, it is a problem to fully utilize the information provided by different medical systems.
  • US2006/0034508 discloses a medical assistance system with information fusion of inputted genetic and imaging information where the output is determined as a function of a trained classification system.
  • a graphical model e.g., Bayesian network, factor graphs, or hidden Markov models
  • a boosting base model e.g., Booster-Buple-Buple-Buple-Buple-Buple-Buple-Buplea neural network, combinations thereof or other now known or later developed algorithm or training may be used. Determination of the output is performed as a function of a knowledge base stored in a database.
  • the database indicates a relationship between the genetics information and the ultrasound or other imaging information.
  • the classifier is configured or trained for distinguishing between the desired groups of states or to identify options and associated probabilities.
  • US2006/0034508 uses a classifier for processing the inputted genetic and imaging information.
  • the use of a classifier such as a neural network may be a power full method for providing information from the inputted data.
  • the use of such classifiers may also suffer from uncertainties of the predicted output.
  • the invention preferably seeks to mitigate, alleviate or eliminate one or more of the above mentioned disadvantages singly or in any combination.
  • This objective and several other objectives are obtained in a first aspect of the invention by providing a medical apparatus for retrieving second type medical information being related to first type medical information, the apparatus comprising
  • a processor for comparing the received medical information with stored knowledge information for retrieving additional information associated with the received information
  • a processor for comparing the retrieved additional information with stored subject information for retrieving the second type medical information which has a relation to the received first type information, and - an output for providing the retrieved second type information.
  • the invention is particularly, but not exclusively, advantageous for obtaining a medical apparatus for retrieving second type medical information in response to a search request of first type medical information.
  • this embodiment provides a different approach for utilizing medical information from different medical systems, such as medical image databases and analysis results from microarrays.
  • the retrieval of related medical information is performed by inputting first type information that is generalized by annotating, obtaining annotations, or associating additional generalized or standardized information to the first type information.
  • first type information that is generalized by annotating, obtaining annotations, or associating additional generalized or standardized information to the first type information.
  • second type medical information that is related to the first type medical information.
  • This procedure for retrieving second type information may be improved by performing an intermediate search in database comprising knowledge information for generalizing the inputted first type information.
  • the stored knowledge information comprises molecular annotation information and image annotation information.
  • inputted first type information may be generalized by associated molecular annotation information and image annotation information.
  • the stored subject information comprises molecular subject information and image subject information.
  • molecular information and image information from subjects may be retrieved in response to inputted first type information.
  • the medical apparatus is capable of both determining second type information from inputted first type medical information and first type information from inputted second type information.
  • second type information may be retrieved from inputted first type information and first type information may be retrieved from inputted second type information.
  • retrieved second type medical information comprising molecular subject information may be retrieved from inputted first type medical information comprising image information.
  • retrieved second type medical information comprising image subject information may be retrieved from inputted first type medical information comprising molecular information
  • An embodiment of the medical apparatus accordingly comprises an input for receiving a search constraint for constraining the retrieval of second type information from the stored subject information. It may be an advantage to constrain the retrieval of second type information by inputting a search constraint saying e.g. that only MR-scanning images should be retrieved.
  • a second aspect of the invention relates to a medical database system comprising a medical apparatus according to the first aspect and a database for storing knowledge information and/or subject information.
  • the medical database system may additionally comprise other devices such as data generating devices, e.g. a reporting workstation where a clinician reports on the images.
  • the database or the plurality of databases comprised by the medical database system may be used for storing acquired images, reports and molecular signatures as well as collections of ontology databases and knowledge databases that describe the domains of the application.
  • the medical database system may also comprise a request and visualization workstation allowing a user to input search requests to the medical apparatus.
  • the devices of the medical database system may be interconnected by one or more data network, including the Internet for connecting to remote devices.
  • a third aspect of the invention relates to a method for retrieving second type medical information being related to first type medical information, comprising - providing the first type medical information to an input of a medical apparatus,
  • a fourth aspect relates to a computer program enabling a computer to perform the method according to the third aspect.
  • the invention relates to a medical system for retrieving medical images or reports which are related to molecular information or, oppositely for retrieving molecular information, e.g. gene expression profiles which are related to medical images.
  • a medical system where a user can input a search request, such as a request for retrieving e.g. medical images of a cancer tumor where all images are related to an inputted molecular signature, e.g. a gene expression profile. That is, all retrieved medical images somehow originate from persons having the same or corresponding molecular signature or from cancer cells having the same or similar molecular signature.
  • the first, second, third and fourth aspect of the present invention may each be combined with any of the other aspects.
  • Fig. 1 shows a medical apparatus for retrieval of medical information related to inputted medical information
  • Fig. 2 schematically illustrates retrieval of second type information from first type information by use two types of medical database information
  • Fig. 3 shows an example of organizing subject databases
  • Fig. 4 illustrates a practical application of the medical apparatus
  • Fig. 5 illustrates method steps according to the invention.
  • Fig. 1 shows a medical database system 190 comprising a medical apparatus 100 and one or more databases 191,192.
  • the database 191 may store medical knowledge information
  • the database 192 may store medical subject information.
  • the knowledge information and subject information may also be stored on a single database or the information may be distributed on more than two databases.
  • a database is a computer program which is either a general database for storing and organizing various types of data or a specialized computer program for storing and organising specific data types, e.g. molecular signatures.
  • the medical knowledge information stored in the knowledge database 191 comprises information such as knowledge and ontology information on various medical aspects, e.g. molecular imaging data standards, medical reporting standards, etc. More concrete examples of knowledge databases 191 are provided below.
  • the subject information stored in the subject database 192 comprises imaging information, report information and molecular profile information from patients, other persons, animals, plants bacteria and viruses. More concrete examples of subject databases 192 are provided below. In this context the term subject covers humans, animals, plants and microbiology organisms.
  • the medical apparatus 100 comprises an input 101 for receiving a first type of medical information, e.g. molecular information or image information.
  • the medical apparatus 100 further comprises a processor 102 for comparing the received medical first type information with medical knowledge information stored on one of the databases 191,192.
  • the purpose of comparing the received information with stored medical knowledge information is to retrieve additional knowledge information 110 associated with the received information, in order to for example generalise the received information, to add various descriptors to the received information or for classifying the received information into one or more medical classes.
  • the same processor 102 or some other processor comprised by the medical apparatus 100 is further adapted for comparing the retrieved additional knowledge information 110 with stored subject information 120 for retrieving a second type of medical information.
  • the stored subject information 120 comprises searchable information which has a data format allowing the retrieved additional knowledge information 110 to be compared with the stored subject information 120.
  • the second type of medical information comprises any information retrieved from the subject database 192, such as patient images, patient reports, molecular images, other representations of molecular data, and data of a patient and patient measurements.
  • Second type information related to the inputted molecular information may be molecular information from other subjects, e.g. human patients, which is related to the inputted molecular information via the generalisation of the inputted molecular information and the selected comparable patient data.
  • second type information related to the inputted molecular information may be medical image information from other patients which is related to the inputted molecular information via the generalization of the inputted molecular information and the selected comparable patient data.
  • the user may input molecular information in order to retrieve related medical images, for example images of cancer tumors, reports on cancer tissue biopsies, pathological images and reports, histological images and reports, and radiological reports.
  • Second type information related to the inputted medical image information may be medical image information from other patients which is related to the inputted image information via the generalisation of the inputted image information and the selected comparable patient data.
  • second type information related to the inputted image information may be molecular information from other patients which is related to the inputted image information via the generalization of the inputted molecular information and the selected comparable patient data.
  • the clinician may input image information in order to retrieve related molecular information, for example genetic profiles images of microarrays, images of mass spectrum analysis, methylation sequences, haplotype maps, single nucleotide polymorphisms (SNPs) maps, etc.
  • the retrieved second type information may be provided via the output 103 e.g. for displaying on a monitor or for further data or image processing.
  • a clinician may wish to find genetic profiles from humans which somehow are related to an MR-scanning image inputted to the medical apparatus 100 as first type information.
  • it is not possible to simply compare the images with records of genetic profiles since the images only contain pixel information that is not comparable with the records of genetic profiles.
  • the inputted image can be attributed with e.g. a particular shape-attribute.
  • the genetic profiles stored in the subject database 192 are also associated with e.g. MR-scanning images which are also attributed with shape-attributes, it is possible to retrieve those genetic profiles having shape- attributes which are comparable with the shape-attributes of the inputted image.
  • Fig. 2 schematically illustrates an embodiment of the invention where first type information 211, e.g. molecular information, is used as an object of information for searching for additional associated information in a knowledge information database 221, illustrated by connection 231.
  • the knowledge information database 221 returns a record of additional associated information 212, illustrated by connection 232.
  • the record of additional information 212 comprises one or more additional information objects 1), 2)... 9), where each of them comprises additional information associated with the inputted information 211.
  • the record of additional information 212 may as an example generalize the inputted information 211 into classes of information in the form of information objects 1), 2)... 9) or as another example, the information objects 1), 2)... 9) may contain associated information attributable to the inputted information 211.
  • the retrieved additional information 212 is not of very much use for the clinician and, therefore, another search is made by using one or more of the objects 1), 2)... 9) for searching for objects contained in the subject information database 222.
  • the retrieved additional information 212 could comprise a group of genes comprising the inputted gene expression profile, annotations that signify molecular function or locations, pathway information, the molecular relationship to a disease or generally to some phenotype.
  • annotations that may be retrieved in response to inputted gene expressions are biological processes such as proteolysis, apoptosis, anti-apoptosis, negative regulation of apoptosis which are related to specific genes and metadata associated with the gene, its expression, or its profile.
  • the additional information 212 can be used for searching for images in the subject information database 222, for retrieving image information 213 which in addition to the images contains the additional information 212 being searched for.
  • a record of image information 213 is retrieved where the record 213 comprises objects Al), Bl), A2) each containing one or more of the additional information objects 1), 2)... 9). Therefore, the retrieved image objects Al), Bl), A2) contains image information or report information which is related to the inputted gene expression profile 211 via the generalizing search in the knowledge information database 221.
  • the data-object of the first type medical information 211 and data-objects of the knowledge information 110 comprise data-attributes having the same data format, such as MPEG7 formats. Since both data-objects comprise searchable data- attributes of the same format, the knowledge information objects 110 can be searched by inputted first type medical information 211.
  • the data-objects of subject information 120 comprise data-attributes, e.g. standardized gene annotations, of the same data format as other data-attributes of the knowledge information objects 110. Accordingly, molecular signatures 120 having standardized gene annotation attributes, can be searched by an inputted image, since the image has been associated with additional knowledge information 110 having standardise gene attributes.
  • the method for establishing a relationship between first type medical information and second type medical information may be extended with more databases 221, 222 and more searches.
  • the retrieved additional information objects 1), 2)... 9) may be used for retrieving more additional information al), bl) etc. which can be attributed to the inputted first type information 211.
  • the last retrieved additional information al), bl) or a combination of the first retrieved information 1), 2)... 9) and last retrieved al), bl) may be used for retrieving image information objects 213.
  • the search may be constrained by additionally inputting a search constraint 252 via input 251 (see Fig. 1 and 2).
  • the search constraint 252 may for example contain instructions saying that only images of a particular type, e.g. MR scanning images, should be outputted via output 103.
  • the search constraint 252 may be used as a constraint on the search in the patient or subject data database 222, it may be used to sort the retrieved image objects Al), Bl), A2), or it may be used in other suitable ways.
  • the constraint 252 may relate to combinations of clinical data, categorical data and microarray data.
  • Clinical data comprises age, weight or sex of the patient, the size or the grade of a tumor, information about lymph nodes, or results from a histological analysis.
  • Categorical data comprises classification of a tumor regarding its malignancy such as the patients' survival time after the analysis or the success of a chemotherapy treatment.
  • Microarray data comprises gene expression data that tell us what genes are expressed in a particular cell type of an organism, at a particular time, under particular conditions .
  • the first type information 211 is a medical image, for example a MR- scanning image or a report
  • this image can be used as an object of information for searching for additional associated information 212 in the medical knowledge information database 221.
  • the additional information 212 retrieved in response to the image may be a color, a shape, texture or MPEG7 like features associated with the inputted image.
  • the objects of additional information 1), 2)... 9), is used for retrieving molecular information objects Al), Bl), A2) from the subject information database 222, which molecular information object contains the molecular information and the additional image attributes 212 being searched for.
  • the retrieved information objects Al), Bl), A2) contain molecular information, e.g. gene expression profiles which is related to the inputted medical image 211 via the generalizing search in the knowledge information database 221.
  • Molecular information which may be inputted via input 101 as a search request, or outputted via output 103 as a search result from a search request comprises gene expression profiles obtained from microarrays, results from protein arrays, methylation sequences, SNP maps, haplotype maps, or proteomic data such as mass spectrometry data.
  • Image information which may be inputted via input 101 as a search request, or outputted via output 103 as a search result from a search request comprises, medical images, for example cardiac images or tumor images, obtained using MR, CT, ultrasound or other imaging techniques or modalities.
  • Image information should be understood broadly and may also comprise clinical reports on patient's diseases or treatments, reports on analysis results of biopsies.
  • the medical knowledge database 191 may be a single database or the medical database 191 may be constituted by a plurality of databases in the form of knowledge databases and ontologies, for example:
  • a medical imaging domain ontology database which describes the concepts and types of data used in the imaging reports.
  • An image features ontology database which contains visual descriptors of the image such as color, shape, and texture.
  • An example is the MPEG-7 multimedia content description standard.
  • a molecular signature ontology database which contains types of data associated with a molecular signature. Accordingly, this database provides the possibility of annotating human and computer readable data to gene expression data from microarrays;
  • a biological ontology database which provides consistent descriptors for elements of the molecular signature, for example descriptors and classifications for gene products according to cellular location, molecular function, or biological process.
  • the Gene Ontology provides descriptors and classifications for gene products according to cellular location, molecular function, or biological process;
  • a biological annotation knowledge database which contains annotations for elements of the molecular signature, for example, gene annotations for a gene expression profile.
  • gene annotations for a gene expression profile are biological processes proteolysis, apoptosis, anti-apoptosis and negative regulation of apoptosis.
  • the medical patient database 192 may be a single database or the medical database 192 may be constituted by a plurality of databases, for example:
  • a patient database which contains information about the subject of the imaging study, such as a patient's age, gender, ethnic group, medical alerts and smoking status.
  • the database may include DICOM's Patient information object definition;
  • a study and image database which contains the images and metadata that describe the organization of a series of images in a study.
  • the study may be the requested procedural description of the study of a patient, a requested contrast agent of a patient study, imaging modalities in the study, and a patient study description.
  • the images of a study may be pixel data characteristics, image orientation, image slice thickness, and an image slice location.
  • a report database which contains image reports that describe observations, findings, and conclusions from patient examinations.
  • a measurement database which contains measurements made based on images, e.g. MR scanning images of a tumor. The measurements can be made by an observer, e.g. a clinician, generating the report, or by an image-processing program analyzing the image.
  • This database includes images of molecular signatures, e.g. gene expression profiles, the signature description, and the signature data.
  • images of molecular signatures e.g. gene expression profiles, the signature description, and the signature data.
  • a molecular signature based on gene expression arrays it will contain the images of gene expression arrays, description of the genes on the array, and numerical representation of expression levels.
  • any of the entries of the subject databases 192 contains attributes which may match to annotations, definitions and other generalized terms retrieved from the medical knowledge databases 191.
  • a molecular signature e.g. a gene expression profile obtained by analyzing a tissue sample of a patient with a microarray may be inputted as an input 211.
  • the molecular signature is used as a search object in the biological annotation knowledge database 221,191 which may return the annotation "apoptosis" 212.
  • the retrieved annotation "apoptosis" 212 is subsequently used as a search object in the report database 222,192 which returns reports 213 containing "apoptosis" as searchable attributes.
  • the retrieved annotation "apoptosis" may be used as a search object in the measurement database 222,292 which returns measurement data or images 213 which also contains "apoptosis” as searchable attributes.
  • additional annotations, other than "apoptosis” may be retrieved from the knowledge databases.
  • an input data type 262 may be inputted to the medical apparatus 100 via input 261, which input data type 262 informs the processor 102 what kind of medical information 211 is inputted and, therefore, informs the processor to search only selected databases of the plurality of knowledge databases 191.
  • the input data type 262 may be inputted manually by a clinician, e.g. by ticking off a data type box in a graphic user interface. For example, by indicating via input 261 that a molecular signature 211 is inputted, the processor 102 is instructed to search only in the biological annotation knowledge database.
  • Fig. 3 shows how subject databases 192 may be organized via interrelations.
  • object 301 may represent a patient which has none, one or a plurality associated "molecular-signature-image-and-data” database objects 302.
  • a "molecular-signature-image- and-data” database object 302 may have none, one or a plurality of associated annotations 303.
  • the patent object 301 may have none, one or a plurality associated "study- and-image” database objects 304.
  • a "study-and-image” database object 304 may have one or more associated report database objects 305 and one or more associated image database objects 306.
  • measurement objects 307 are associated to other objects as shown in Fig. 3.
  • the search object may match corresponding search attributes of entries in e.g. the measurement database 192.
  • the search objects of the measurement database 192,307 may be used to retrieve associated objects of e.g. the report and molecular-signature databases 305, 302.
  • subject databases 192 may be organized differently than the example given in Fig. 3.
  • Fig. 4 illustrates an application of the medical apparatus 100 for optimizing the treatment of a patient.
  • a treatment is applied to the patient.
  • the effect of the treatment is examined by performing for example a genetic test or a MR-scanning of a tumor.
  • the result from the examination is inputted to the medical apparatus 100 via input 101. If a genetic test was performed, the genetic result, e.g. the numerical representation of expression levels in a gene expression microarray test, is inputted to the medical apparatus in order to retrieve e.g. reports and images from the patient database 192 which are characterized by similar genetic results. If an MR-scanning was performed, the MR- image itself of image-analysis results may be inputted to the medical apparatus 100 in order to retrieve molecular signatures which are characterised by similar MR- images or similar image-analysis results.
  • Other applications of the medical apparatus 100 comprise finding eligible patients for clinical trials, e.g. by inputting a particular genetic expression profile to the medical apparatus 100 for finding patients 301 and reports 305 from the subject database 192 being associated with that particular genetic expression profile. Accordingly, reports 305 may be retrieved since the reports 305 themselves contains data attributes that are searchable by the inputted genetic expression 311 or since the annotations 303 associated to the "molecular-signature-image-and-data" database object 302 and the report objects 305 are searchable by the inputted genetic expression 311.
  • Another application of the medical apparatus 100 is for understanding drug effects on phenotypes presented in images, such as tumor size, a molecular signature showing the absence or presence of a gene product, or protein mass spectroscopy images showing appearance or disappearance of certain proteins.
  • a protein mass spectroscopy image may be obtained and inputted to the medical apparatus in order to retrieve e.g. drugs which had shown the same effect on the proteins or for retrieving similar protein mass spectroscopy images.
  • Step 501 comprises providing the first type medical information 211 to the input 101 of the medical apparatus 100.
  • the first type medical information 211 could be a molecular signature, e.g. a gene profile, or medical image information, e.g. a patient study report.
  • the first type medical information may be inputted manually such as via a touchscreen or the medical information may by input by a computer connected with the medical apparatus.
  • Step 502 comprises comparing the first type medical information 211 with stored knowledge information 110 for retrieving additional information 212 associated with the first type medical information.
  • the stored knowledge information 110 may be stored in a knowledge database 191,221 or distributed over a plurality of knowledge databases 191,221.
  • the comparison may be performed by a data processor 102 such as a computer instructed to compare the first type medical information with database entries of the knowledge database 191,221.
  • the retrieved additional information 212 could be annotations that signify molecular function or locations, pathway information, etc.
  • the first type medical information 211 was a medical image, for example an MR-scanning image or a patient study report
  • the retrieved additional information 212 could be a color, a shape, texture or MPEG7 standardized metadata of the image content.
  • Step 503 comprises comparing the retrieved additional information 212 with stored subject information 120 for retrieving the second type medical information 213 which has a relation to the first type medical information 211.
  • the stored subject information 120 may be stored in a subject information database 222, e.g. a patient database, or distributed over a plurality of subject information databases 192,222.
  • the comparison may be performed by a data processor 102 such as a computer instructed to compare the retrieved additional information 212 with database entries of the subject information database 192,222.
  • the data processor 102 used in step 503 may be the same processor 102 or computer used in step 502, or the processor 102 used in step 503 may be different from the processor 102 used in the preceding step 502.
  • the retrieved second type medical information 213 could be a molecular signature, e.g. a gene expression profile. If the first type medical information 211 was a molecular signature, the retrieved second type medical information 213 could be a medical image or report.
  • Step 504 comprises providing the retrieved second type information 213 to an output 103 of the medical apparatus 103, such as a computer display 103, an internet connection 103, a local area network 102 or a handheld computer, e.g. a Personal Digital Assistant.
  • an output 103 of the medical apparatus 103 such as a computer display 103, an internet connection 103, a local area network 102 or a handheld computer, e.g. a Personal Digital Assistant.
  • step 502 may be succeeded by another step 502a for retrieving further annotation data.
  • step 503 may be succeeded by another step 503a for retrieving further data, e.g. image data based on data retrieved from the previous step 503.
  • the medical apparatus 100 may be hardware and/or software implemented. Thus, the medical apparatus 100 may be implemented on an electronic circuit board or a computer device comprising data inputs/interfaces 101, 251 and 261 for receiving first type medical information, data interfaces for communicating the with databases 191, 192 and an output 103 for providing the retrieved medical information.
  • the software implementation of the medical apparatus 100 may be carried out by loading a computer program into a storage medium for later execution by a processor.
  • the storage medium may for example be a read-only-memory (ROM), a hard disc drive, or other suitable storage devices.
  • the medical apparatus 100 may be designed using a combination of hardware, firmware and software implementations.
  • the medical database system 190 comprising the medical apparatus 100, may also be hardware or software implemented.
  • the medical database system 190 may be a computer network.
  • the computer network of the medical database system 190 may comprise data generating devices for example an MR-scanning image acquisition device, a reporting workstation where a clinician reports on the images and a molecular signature acquisition device.
  • the medical database system 190 may also comprise repositories that keep the acquired images, reports and signatures, as well as a collection of ontology databases and knowledge databases that describe the domains of the application.
  • the user of the system may communicate with the medical apparatus 100 via a request and visualization workstation. All devices of the medical database system 190 may be connected with a data network.

Landscapes

  • Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Biotechnology (AREA)
  • Evolutionary Biology (AREA)
  • Biophysics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Genetics & Genomics (AREA)
  • Bioethics (AREA)
  • Databases & Information Systems (AREA)
  • Molecular Biology (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

La présente invention concerne un système médical pour récupérer des images médicales ou des rapports médicaux qui sont liés à des informations moléculaires ou, inversement, pour récupérer des informations moléculaires, par exemple des profils d’expression génique qui sont liés aux images médicales. On y parvient à l’aide d’un système médical où un utilisateur peut entrer une demande de recherche, telle qu’une demande pour récupérer, par exemple, des images médicales d’une tumeur cancéreuse où toutes les images sont liées à une signature moléculaire entrée, par exemple un profil d’expression génique. A savoir, toutes les images médicales récupérées ont plus ou moins pour origine des personnes ayant une signature moléculaire identique ou correspondante ou des cellules cancéreuses ayant une signature moléculaire identique ou similaire.
PCT/IB2009/052555 2008-06-23 2009-06-16 Système médical pour récupération d’informations médicales WO2009156897A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US7484908P 2008-06-23 2008-06-23
US61/074,849 2008-06-23

Publications (1)

Publication Number Publication Date
WO2009156897A1 true WO2009156897A1 (fr) 2009-12-30

Family

ID=40973123

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IB2009/052555 WO2009156897A1 (fr) 2008-06-23 2009-06-16 Système médical pour récupération d’informations médicales

Country Status (1)

Country Link
WO (1) WO2009156897A1 (fr)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015104512A1 (fr) * 2014-01-10 2015-07-16 Imabiotech Procede de traitement de donnees d'imagerie moleculaire et serveur de donnees correspondant
US9953133B2 (en) 2015-06-03 2018-04-24 General Electric Company Biological data annotation and visualization
US10672505B2 (en) 2015-06-03 2020-06-02 General Electric Company Biological data annotation and visualization

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020106119A1 (en) * 2000-11-30 2002-08-08 Foran David J. Collaborative diagnostic systems
US20060034508A1 (en) * 2004-06-07 2006-02-16 Zhou Xiang S Computer system and method for medical assistance with imaging and genetics information fusion
WO2008054768A2 (fr) * 2006-10-31 2008-05-08 The Board Of Trustees Of The Leland Stanford Junior University Procédés d'élaboration de cartes d'association de données d'imagerie et de données biologiques

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020106119A1 (en) * 2000-11-30 2002-08-08 Foran David J. Collaborative diagnostic systems
US20060034508A1 (en) * 2004-06-07 2006-02-16 Zhou Xiang S Computer system and method for medical assistance with imaging and genetics information fusion
WO2008054768A2 (fr) * 2006-10-31 2008-05-08 The Board Of Trustees Of The Leland Stanford Junior University Procédés d'élaboration de cartes d'association de données d'imagerie et de données biologiques

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
MARINELLI ROBERT J; MONTGOMERY KELLI; LIU CHIH LONG; SHAH NIGAM H; PRAPONG WIJAN; NITZBERG MICHAEL; ZACHARIAH ZACHARIAH K; SHERLOC: "The Stanford Tissue Microarray Database.", NUCLEIC ACIDS RESEARCH JAN 2008, vol. 36, no. Database issue, January 2008 (2008-01-01), pages D871 - D877, XP002544163, ISSN: 1362-4962 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015104512A1 (fr) * 2014-01-10 2015-07-16 Imabiotech Procede de traitement de donnees d'imagerie moleculaire et serveur de donnees correspondant
FR3016461A1 (fr) * 2014-01-10 2015-07-17 Imabiotech Procede de traitement de donnees d'imagerie moleculaire et serveur de donnees correspondant
CN105940402A (zh) * 2014-01-10 2016-09-14 Ima生物科技公司 用于处理分子成像数据的方法及对应的数据服务器
JP2017509945A (ja) * 2014-01-10 2017-04-06 イマビオテクＩｍａｂｉｏｔｅｃｈ 分子イメージングデータを処理する方法及び対応するデータサーバ
US10013598B2 (en) 2014-01-10 2018-07-03 Imabiotech Method for processing molecular imaging data and corresponding data server
CN105940402B (zh) * 2014-01-10 2019-01-29 Ima生物科技公司 用于处理分子成像数据的方法及对应的数据服务器
US9953133B2 (en) 2015-06-03 2018-04-24 General Electric Company Biological data annotation and visualization
US10672505B2 (en) 2015-06-03 2020-06-02 General Electric Company Biological data annotation and visualization

Similar Documents

Publication Publication Date Title
Van Griethuysen et al. Computational radiomics system to decode the radiographic phenotype
US11379516B2 (en) Similar medical image search
US7756309B2 (en) Method and system for storing, indexing and searching medical images using anatomical structures of interest
US9122955B2 (en) Method and system of classifying medical images
JP2014505950A (ja) 撮像プロトコルの更新及び／又はリコメンダ
US7505867B2 (en) System and method for predicting medical condition
Zheng Computer-aided diagnosis in mammography using content-based image retrieval approaches: current status and future perspectives
US20130282404A1 (en) Integrated access to and interation with multiplicity of clinica data analytic modules
Wong et al. Design and applications of a multimodality image data warehouse framework
JP2022528095A (ja) 医療情報を評価するためのプラットフォームおよびその使用方法
CN107408123A (zh) 用于对临床发现的背景敏感性评价的方法和系统
US20230011031A1 (en) Automatically determining a medical recommendation for a patient based on multiple medical images from multiple different medical imaging modalities
Boone et al. Systematic review: Bias in imaging studies-the effect of manipulating clinical context, recall bias and reporting intensity
US20130159022A1 (en) Clinical state timeline
JP6845071B2 (ja) 自動レイアウト装置および自動レイアウト方法並びに自動レイアウトプログラム
Oliveira et al. A bag-of-tasks approach to speed up the lung nodules retrieval in the bigdata age
WO2009156897A1 (fr) Système médical pour récupération d’informations médicales
US20230062811A1 (en) Systems and methods for processing electronic images in forensic pathology
Tafavvoghi et al. Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review
US20200043167A1 (en) Auto comparison layout based on image similarity
Corvò et al. Visual analytics in digital pathology: Challenges and opportunities
Müller et al. D9. 1: Report on image use behaviour and requirements
Bonizzi et al. Biobanking in the digital pathology era
Li et al. Tbidoc: 3d content-based ct image retrieval system for traumatic brain injury
US11409786B2 (en) Systems and methods for computer-assisted search of image slices for indications of a finding

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 09769707

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 09769707

Country of ref document: EP

Kind code of ref document: A1