EP2845139A2 - Systèmes et méthodes pour effectuer une analyse de corrélation sur un résultat clinique et des caractéristiques d'un tissu biologique - Google Patents

Systèmes et méthodes pour effectuer une analyse de corrélation sur un résultat clinique et des caractéristiques d'un tissu biologique

Info

Publication number
EP2845139A2
EP2845139A2 EP13721622.2A EP13721622A EP2845139A2 EP 2845139 A2 EP2845139 A2 EP 2845139A2 EP 13721622 A EP13721622 A EP 13721622A EP 2845139 A2 EP2845139 A2 EP 2845139A2
Authority
EP
European Patent Office
Prior art keywords
biological
user interface
view
image
biological tissue
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.)
Withdrawn
Application number
EP13721622.2A
Other languages
German (de)
English (en)
Inventor
Vidya Pundalik KAMATH
Colin Craig MCCULLOCH
Megan ROTHNEY
Alberto Santamaria-Pang
Brion Daryl SARACHAN
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Leica Microsystems CMS GmbH
Original Assignee
General Electric Co
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
Priority claimed from US13/459,958 external-priority patent/US20130286038A1/en
Priority claimed from US13/460,081 external-priority patent/US9036888B2/en
Priority claimed from US13/460,100 external-priority patent/US20150032671A9/en
Priority claimed from US13/459,999 external-priority patent/US8737709B2/en
Priority claimed from US13/460,018 external-priority patent/US20130286043A1/en
Application filed by General Electric Co filed Critical General Electric Co
Publication of EP2845139A2 publication Critical patent/EP2845139A2/fr
Withdrawn legal-status Critical Current

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
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/98—Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
    • G06V10/993—Evaluation of the quality of the acquired pattern
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/69—Microscopic objects, e.g. biological cells or cellular parts
    • 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
    • G16B45/00—ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
    • 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
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B21/00—Microscopes
    • G02B21/36—Microscopes arranged for photographic purposes or projection purposes or digital imaging or video purposes including associated control and data processing arrangements
    • G02B21/365—Control or image processing arrangements for digital or video microscopes
    • G02B21/367—Control or image processing arrangements for digital or video microscopes providing an output produced by processing a plurality of individual source images, e.g. image tiling, montage, composite images, depth sectioning, image comparison

Definitions

  • exemplary embodiments may access data corresponding to multiple biological tissue samples corresponding to a patient cohort including the first patient and one or more other patients with breast cancer. Exemplary embodiments may retrieve data for the cohort corresponding to one or more features
  • the computer processor is also programmed to, in response to user input selecting a first biomarker and a first field of view corresponding to a biological tissue at the field of view selection component, render, on the graphical user interface, a first image of the selected first field of view corresponding to the biological tissue, the first image representing expression levels of the selected first biomarker and including representations of one or more biological units in the biological tissue.
  • a file structure browser 306 may be displayed to allow the user to view a file structure in which data files are organized.
  • the file structure browser 306 may allow the user to select one or more topmost level directories that include all of the image and/or text data corresponding to a study.
  • a default data source may be automatically selected if the user fails to make a selection.
  • the user interface may render in an overlaid manner the first image of the selected field-of-view of biological tissue in which expression levels of the first biomarker are automatically represented as one or more intensities of the first color, and a second image of the selected field-of-view corresponding to the biological tissue in which the expression levels of the second biomarker are automatically represented as one or more intensities of the second color.
  • Exemplary embodiments may display expression of one or more DNA sequences and one or more protein biomarkers in an overlaid manner in the same display panel.
  • the expression and non-expression of DNA sequences on a cell-by-cell basis may be determined based on fluorescence in situ hybridization (FISH).
  • FISH is a technique used to detect and localize the presence or absence of specific DNA sequences on chromosomes.
  • FISH is used in a similar manner as used for multiplexing to detect the hybridization of DNA probes at the cellular level.
  • the probes may look like tiny bright dots on a dark background, with each dot representing a probe on one copy of the gene. The brighter a spot, the more likely it is that the dot represents overlapping copies of the gene.
  • the morphological representation 1910 may facilitate identifying one or more biomarkers that are effective for isolating a target morphologically-related population of particles.
  • the user interface may receive, at the field-of-view selection component, user input selecting a field-of-view of biological tissue.
  • the user interface may also receive user input selection one or more biomarkers whose expression levels are to be displayed in the selected field-of-view of the biological tissue.
  • the user interface may receive, at the clinical outcome selection component, user input selecting a clinical outcome, for example, positive diagnosis of a disease or tissue condition, negative diagnosis of a disease or tissue condition, a disease prognosis, a prediction of drug response, stratification into a clinically-relevant group, and the like.
  • a clinical outcome for example, positive diagnosis of a disease or tissue condition, negative diagnosis of a disease or tissue condition, a disease prognosis, a prediction of drug response, stratification into a clinically-relevant group, and the like.
  • the selection of the aspects of the field-of- view may be automatically expanded using a supervised learning method or algorithm encoded on one or more non-transitory computer-readable media and implemented as computer- executable instructions.
  • the supervised leaming method may expand the selection of the aspects of the field-of-view by including one or more additional aspects in the same data cohort having one or more similar features. For example, if the user selects one or more biological units, exemplary embodiments may expand the selection with one or more additional biological units in the cohort having one or more similar features as in the user-selected biological units.
  • the quality review selection component 2504 may include a "Next Marker" tool 2514 to allow a user to replace the first image displayed in the display panel 502 with a different image of the same field-of-view of biological tissue obtained by treating the biological tissue with a different biomarker than the biomarker used to obtain the first image.
  • the user interface may render a second, different image of the selected field-of-view of biological tissue, while continuing to render the representation of the result of the selected morphological analysis such that the second image is overlaid by the representation of the result of the morphological analysis.
  • the second image may replace the first image on the user interface.
  • the second image result may be overlaid on the first image on the user interface.
  • Figure 30 is a flowchart illustrating an exemplary computer-implemented method performed in exemplary embodiments to allow a user to perform quality review of results of an image analysis method.
  • the class may manage one or more file streams used to read files and/or images in the database, memory allocated to store temporary data and/or variables during the data access operations, and the like.
  • Exemplary inputs to the class may include, but are not limited to, a class derived from the PathData interface class, information on specific images to be read, and the like.
  • the "PathlmageData" class may query the data structures generated by the "PathData” class to selectively retrieve the data specified in the input.
  • the attributes may include, but are not limited to, a unique identifier for the cell, a sample identifier identifying a sample, test, slide, and/or spot in which the cell was identified, a tissue identifier identifying a tissue that the cell is part of, and the like.
  • the attributes may also include, but are not limited to, one or more types corresponding to the cell (e.g., a structural type like red blood cell, a morphological type like oversized, a diagnostic type like diseased, and the like), a size of the cell, the boundaries of the cell (e.g., the boundaries of the cell on an image of biological tissue), a location of the cell (e.g., a location of the cell on an image of biological tissue), and the like.
  • the attributes may also include, but are not limited to, one or more expression levels associated with the cell (e.g., expression levels of one or more biomarkers, expression of one or more DNA sequences), and the like.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Quality & Reliability (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Biotechnology (AREA)
  • Biophysics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Biomedical Technology (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Genetics & Genomics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Data Mining & Analysis (AREA)
  • Radiology & Medical Imaging (AREA)
  • Epidemiology (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
  • Medical Treatment And Welfare Office Work (AREA)
  • User Interface Of Digital Computer (AREA)
  • Apparatus Associated With Microorganisms And Enzymes (AREA)
  • Processing Or Creating Images (AREA)
  • Image Processing (AREA)

Abstract

Les modes de réalisation de l'invention comprennent des méthodes, des systèmes et des dispositifs permettant de déterminer une corrélation positive ou négative entre un résultat clinique et une ou plusieurs fonctions de tissu biologique. Une interface utilisateur donnée à titre d'exemple permet à un utilisateur de sélectionner un résultat clinique et un ou plusieurs aspects d'un champ observé affiché de tissu biologique. Les modes de réalisation donnés à titre d'exemple permettent d'effectuer automatiquement une analyse de corrélation entre le résultat clinique sélectionné et une ou plusieurs caractéristiques fonctionnelles des aspects sélectionnés par l'utilisateur du champ observé de tissu biologique. Ces modes de réalisation permettent, par exemple, d'effectuer automatiquement une analyse de corrélation entre le résultat clinique sélectionné et une ou plusieurs caractéristiques fonctionnelles d'une ou de plusieurs unités biologiques du tissu biologique.
EP13721622.2A 2012-04-30 2013-04-26 Systèmes et méthodes pour effectuer une analyse de corrélation sur un résultat clinique et des caractéristiques d'un tissu biologique Withdrawn EP2845139A2 (fr)

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
US13/459,958 US20130286038A1 (en) 2012-04-30 2012-04-30 Systems and methods for selection and display of multiplexed images of biological tissue
US13/460,081 US9036888B2 (en) 2012-04-30 2012-04-30 Systems and methods for performing quality review scoring of biomarkers and image analysis methods for biological tissue
US13/460,100 US20150032671A9 (en) 2010-07-23 2012-04-30 Systems and methods for selecting and analyzing particles in a biological tissue
US13/459,999 US8737709B2 (en) 2012-04-30 2012-04-30 Systems and methods for performing correlation analysis on clinical outcome and characteristics of biological tissue
US13/460,018 US20130286043A1 (en) 2012-04-30 2012-04-30 Systems and methods for analyzing biomarker co-localization in a biological tissue
PCT/EP2013/058790 WO2013164281A2 (fr) 2012-04-30 2013-04-26 Systèmes et méthodes pour effectuer une analyse de corrélation sur un résultat clinique et des caractéristiques d'un tissu biologique

Publications (1)

Publication Number Publication Date
EP2845139A2 true EP2845139A2 (fr) 2015-03-11

Family

ID=48190980

Family Applications (3)

Application Number Title Priority Date Filing Date
EP13719105.2A Withdrawn EP2845138A1 (fr) 2012-04-30 2013-04-26 Systèmes et méthodes d'analyse de colocalisation de biomarqueurs dans un tissu biologique
EP13719104.5A Active EP2845137B1 (fr) 2012-04-30 2013-04-26 Systèmes et méthodes pour noter un examen de la qualité de biomarqueurs, et méthodes d'analyse d'image de tissu biologique
EP13721622.2A Withdrawn EP2845139A2 (fr) 2012-04-30 2013-04-26 Systèmes et méthodes pour effectuer une analyse de corrélation sur un résultat clinique et des caractéristiques d'un tissu biologique

Family Applications Before (2)

Application Number Title Priority Date Filing Date
EP13719105.2A Withdrawn EP2845138A1 (fr) 2012-04-30 2013-04-26 Systèmes et méthodes d'analyse de colocalisation de biomarqueurs dans un tissu biologique
EP13719104.5A Active EP2845137B1 (fr) 2012-04-30 2013-04-26 Systèmes et méthodes pour noter un examen de la qualité de biomarqueurs, et méthodes d'analyse d'image de tissu biologique

Country Status (4)

Country Link
EP (3) EP2845138A1 (fr)
JP (2) JP6317732B2 (fr)
AU (1) AU2013255961B2 (fr)
WO (5) WO2013164280A1 (fr)

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JP7026625B2 (ja) * 2015-11-04 2022-02-28 メタボロン，インコーポレイテッド サンプルの質の自動評価
CN111479934A (zh) * 2017-10-18 2020-07-31 韦恩生物科技股份公司 用于诊断和治疗监测的生物学指标的鉴定和用途
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Also Published As

Publication number Publication date
JP6187989B2 (ja) 2017-08-30
JP2015527622A (ja) 2015-09-17
AU2013255961A1 (en) 2014-10-23
WO2013164277A2 (fr) 2013-11-07
WO2013164277A3 (fr) 2013-12-27
WO2013164279A1 (fr) 2013-11-07
EP2845137B1 (fr) 2021-01-20
WO2013164281A2 (fr) 2013-11-07
JP6317732B2 (ja) 2018-04-25
WO2013164278A1 (fr) 2013-11-07
JP2015526771A (ja) 2015-09-10
WO2013164281A3 (fr) 2013-12-27
EP2845138A1 (fr) 2015-03-11
WO2013164280A1 (fr) 2013-11-07
AU2013255961B2 (en) 2017-12-07
EP2845137A1 (fr) 2015-03-11

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