Differential atlas for cancer assessment

US10254358B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10254358-B2
Application numberUS-201715810363-A
CountryUS
Kind codeB2
Filing dateNov 13, 2017
Priority dateJan 5, 2015
Publication dateApr 9, 2019
Grant dateApr 9, 2019

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Abstract

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Methods and apparatus associated with producing a quantification of differences associated with biochemical recurrence (BcR) in a region of tissue demonstrating prostate cancer (PCa) are described. One example apparatus includes a set of logics, and a data store that stores a set of magnetic resonance (MR) images acquired from a population of subjects. The set of logics includes an image acquisition logic that acquires a diagnostic image of a region of tissue in a patient demonstrating PCa, a morphology logic that extracts a shape feature, a volume feature, or an intensity feature from the diagnostic image or from a member of the set of MR images, a differential atlas construction logic that constructs a statistical shape differential atlas from the set of MR images, and a quantification logic that produces a quantification of differences based on the shape feature, the volume feature, or the intensity feature, and the differential atlas.

First claim

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What is claimed is: 1. A non-transitory computer-readable storage device storing computer executable instructions that when executed by a computer control the computer to perform a method for predicting biochemical recurrence (BcR) in a region of tissue demonstrating prostate cancer (PCa) pathology, the method comprising: accessing a set of magnetic resonance (MR) images acquired from a population of subjects; acquiring a diagnostic image of a region of tissue in a patient demonstrating PCa pathology; extracting a shape feature, a volume feature, or an intensity feature from the diagnostic image or the set of MR images; constructing a statistical shape differential atlas from the set of MR images; computing a quantification of differences associated with the shape feature, the volume feature, or the intensity feature, and the differential atlas; generating a BcR probability score for the patient based, at least in part, on the quantification of differences; controlling a computer aided diagnosis (CADx) system to generate a classification of the region of tissue in the image based, at least in part, on the BcR probability score or the quantification of differences; and controlling the CADx system to display the classification, the quantification of differences, or the BcR probability score. 2. The non-transitory computer-readable storage device of claim 1 , where the set of MR images is acquired from a population of patients, where the population includes a set of subpopulations, where a member of the set of MR images includes a prostate capsule shape attribute, a prostate capsule volume attribute, a central gland (CG) shape attribute, or a CG volume attribute. 3. The non-transitory computer-readable storage device of claim 1 , where a member of the set of MR images or the diagnostic image is a 1.5 Tesla (T) T2 weighted (T2w) MR image or a 3T T2w MR image. 4. The non-transitory computer-readable storage device of claim 3 , where acquiring the diagnostic image includes acquiring a T2w MR image of a patient demonstrating PCa pathology using a surface coil approach or an endorectal coil approach. 5. The non-transitory computer-readable storage device of claim 1 , where a first member of the set of MR images is acquired using a first set of MR acquisition parameters having a first set of values, and a second member of the set of MR images is acquired using a second, different set of MR acquisition parameters having a second, different set of values, where the first set of MR acquisition parameters and the second set of MR acquisition parameters includes pixel dimensions, resolution, or slice spacing. 6. The non-transitory computer-readable storage device of claim 1 , where extracting the shape feature, the volume feature, or the intensity feature includes generating an outline of the prostate or an outline of the central gland (CG) of a member of the set of MR images or the diagnostic image by automatically detecting and annotating the prostate or the CG represented in a member of the set of MR images or the diagnostic image, where the CG includes a prostate transitional zone and a prostate central zone. 7. The non-transitory computer-readable storage device of claim 2 , where constructing the statistical shape differential atlas comprises: stratifying the set of MR images into a subset of MR images associated with a subpopulation of subjects, where a subject belongs to a PCa positive (PCa+) subpopulation, a PCa negative (PCa−) subpopulation, or a normal population, where a member of the set of MR images includes a shape feature or a volume feature, where the shape feature is associated with a prostate capsule or a CG represented in the member of the set of MR images, where the volume feature is associated with the prostate capsule or the CG represented in the member of the set of MR images; registering a member of the set of MR images using template-based anatomically constrained registration based on the outline of the prostate capsule represented in the member of the set of MR images, the outline of the CG in the member of the set of MR images, or a T2w MR intensity of the member of the set of MR images; computing a spatial median for the set of MR images based, at least in part, on the shape feature or the volume feature; iteratively updating a template based, at least in part, on the spatial median; and characterizing a statistical difference between a shape feature associated with a first subpopulation and shape feature associated with a second subpopulation, or between a volume feature associated with the first subpopulation and a volume feature associated with the second subpopulation. 8. The non-transitory computer-readable storage device of claim 1 , where computing the quantification of differences comprises: generating a registered diagnostic image by registering the diagnostic image to the statistical shape differential atlas. 9. The non-transitory computer-readable storage device of claim 8 , the method further comprising controlling the CADx system to display the registered diagnostic image. 10. An apparatus employed in a computer assisted diagnosis (CADx) device, the apparatus comprising: one or more processors configured to: access a set of magnetic resonance (MR) images acquired from a population of patients, where the population includes a set of subpopulations, where a member of the set of MR images includes a prostate capsule shape attribute, a prostate capsule volume attribute, a central gland (CG) shape attribute, or a CG volume attribute, and where the set of subpopulations includes a PCa positive (PCa+) subpopulation, a PCa negative (PCa−) subpopulation, or a normal subpopulation; construct a statistical shape atlas from the set of MR images; access an MR image of a region of prostate tissue in a patient demonstrating cancerous pathology, where the MR image of the region of prostate tissue has a prostate capsule shape attribute, a prostate capsule volume attribute, a CG shape attribute, or a CG volume attribute; produce a quantification of differences between the MR image of the region of prostate and the statistical shape atlas; compute a BcR probability score based, at least in part, on the quantification of differences; generate a classification of the region of tissue in the image based, at least in part, on the BcR probability score or the quantification of differences; and display the classification, the BcR probability score, or the quantification of differences. 11. The apparatus of claim 10 , where producing the quantification of differences comprises comparing the prostate capsule shape attribute of the MR image of the region of prostate tissue demonstrating cancerous pathology, the prostate capsule volume attribute of the MR image of the region of prostate tissue demonstrating cancerous pathology, the CG shape attribute of the MR image of the region of prostate tissue demonstrating cancerous pathology, or the CG volume attribute of the MR image of the region of prostate tissue demonstrating cancerous pathology, with the statistical shape atlas. 12. The apparatus of claim 10 , where the subpopulations are acquired across a plurality of institutions. 13. The apparatus of claim 10 , the one or more processors further configured to automatically annotate the prostate capsule or the CG in a member of the set of MR images or in the MR image of the region of prostate tissue demonstrating cancerous pathology. 14. The apparatus of claim 10 , where the CG includes a prostate central zone and a prostate transitional zone. 15. The apparatus of claim 10 , where a member of the set

Assignees

Inventors

Classifications

  • implantable coils or coils being geometrically adaptable to the sample, e.g. flexible coils or coils comprising mutually movable parts · CPC title

  • G06V10/772Primary

    Determining representative reference patterns, e.g. averaging or distorting patterns; Generating dictionaries · CPC title

  • Determining representative reference patterns, e.g. by averaging or distorting; Generating dictionaries · CPC title

  • Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection · CPC title

  • Editing of three-dimensional [3D] images, e.g. changing shapes or colours, aligning objects or positioning parts · CPC title

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What does patent US10254358B2 cover?
Methods and apparatus associated with producing a quantification of differences associated with biochemical recurrence (BcR) in a region of tissue demonstrating prostate cancer (PCa) are described. One example apparatus includes a set of logics, and a data store that stores a set of magnetic resonance (MR) images acquired from a population of subjects. The set of logics includes an image acquis…
Who is the assignee on this patent?
Univ Case Western Reserve
What technology area does this patent fall under?
Primary CPC classification G01R33/34084. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Apr 09 2019 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 5 related publications on this page (citations in our corpus or others sharing the same primary CPC).