Systems and methods for treating, diagnosing and predicting the occurrence of a medical condition
First Claim
1. Apparatus for evaluating a risk of progression of prostate cancer in a patient, the apparatus comprising:
- a model predictive of prostate cancer progression configured to evaluate a dataset for a patient to thereby evaluate a risk of prostate cancer progression in the patient, wherein the model is based on one or more features selected from the following group of features;
preoperative PSA;
dominant Gleason Grade;
Gleason Score;
at least one of a measurement of expression of androgen receptor (AR) in epithelial nuclei and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei;
a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei; and
a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area.
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Accused Products
Abstract
Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts risk of prostate cancer progression in a patient, where the model is based on features including one or more (e.g., all) of preoperative PSA, dominant Gleason Grade, Gleason Score, at least one of a measurement of expression of AR in epithelial and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei, and a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area. In some embodiments, the morphometric information is based on image analysis of tissue subject to multiplex immunofluorescence and may include characteristic(s) of a minimum spanning tree (MST) and/or a fractal dimension observed in the images.
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Citations
41 Claims
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1. Apparatus for evaluating a risk of progression of prostate cancer in a patient, the apparatus comprising:
a model predictive of prostate cancer progression configured to evaluate a dataset for a patient to thereby evaluate a risk of prostate cancer progression in the patient, wherein the model is based on one or more features selected from the following group of features; preoperative PSA; dominant Gleason Grade; Gleason Score; at least one of a measurement of expression of androgen receptor (AR) in epithelial nuclei and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei; a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei; and a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A method of evaluating a risk of progression of prostate cancer in a patient, the method comprising:
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evaluating a dataset for a patient with a model predictive of prostate cancer progression, wherein the model is based on one or more features selected from the following group of features;
preoperative PSA;
dominant Gleason Grade;
Gleason Score;
at least one of a measurement of expression of androgen receptor (AR) in epithelial nuclei and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei;
a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei; and
a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area;thereby evaluating the risk of prostate cancer progression in the patient. - View Dependent Claims (14, 15, 16, 17, 18)
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19. A computer readable medium comprising computer executable instructions recorded thereon for performing the method comprising:
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evaluating a dataset for a patient with a model predictive of prostate cancer progression, wherein the model is based on one or more features selected from the following group of features;
preoperative PSA;
dominant Gleason Grade;
Gleason Score;
at least one of a measurement of expression of androgen receptor (AR) in epithelial nuclei and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei;
a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei; and
a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area;thereby evaluating the risk of prostate cancer progression in the patient. - View Dependent Claims (20)
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21. Apparatus for evaluating a risk of occurrence of an outcome with respect to a medical condition in a patient, the apparatus comprising:
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a model predictive of an outcome with respect to the medical condition, wherein the model is based on one or more computer-generated morphometric features generated from one or more images of tissue subject to multiplex immunofluorescence (IF), wherein the model is configured to; receive a patient dataset for the patient; and evaluate the patient dataset according to the model to produce a value indicative of the risk of occurrence of the outcome with respect to the medical condition in the patient. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29)
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30. A method of evaluating a risk of occurrence of an outcome with respect a medical condition in a patient, the method comprising:
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evaluating a dataset for a patient with a model predictive of an outcome with respect to the medical condition, wherein the model is based on one or more computer-generated morphometric feature(s) generated from one or more images of tissue subject to multiplex immunofluorescence (IF); thereby evaluating the risk of occurrence of the outcome with respect to the medical condition in the patient. - View Dependent Claims (31, 32)
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33. A computer readable medium comprising computer executable instructions recorded thereon for performing the method comprising:
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evaluating a dataset for a patient with a model predictive of an outcome with respect to a medical condition, wherein the model is based on one or more computer-generated morphometric features generated from one or more images of tissue subject to multiplex immunofluorescence (IF); thereby evaluating the risk of occurrence of the medical condition in the patient. - View Dependent Claims (34, 35)
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36. Apparatus for identifying objects of interest in images of tissue, the apparatus comprising:
an image analysis tool configured to segment a tissue image into pathological objects comprising glands, wherein starting with lumens in the tissue image identified as seeds, the image analysis tool is configured to perform controlled region growing on the image comprising; initiating growth around the lumen seeds in the tissue image thus encompassing epithelial cells identified in the image through said growth; continuing growth of each gland around each lumen seed so long as the area of each successive growth ring is larger than the area of the preceding growth ring; and discontinuing said growth of said gland when the area of a growth ring is less than the area of the preceding growth ring for said gland.
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37. Apparatus for measuring the expression of one or more biomarkers in images of tissue subject to immunofluorescence (IF), the apparatus comprising:
an image analysis tool configured to; measure within an image of tissue the intensity of a biomarker as expressed within a particular type of pathological object, wherein said measuring comprises determining a plurality of percentiles of the intensity of the biomarker as expressed within the particular type of pathological object; and identify one of said plurality of percentiles as the percentile corresponding to a positive level of said biomarker in said pathological object. - View Dependent Claims (38, 39, 40)
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41. Apparatus for identifying objects of interest in images of tissue, the apparatus comprising:
an image analysis tool configured to; detect the presence of CD34 in an image of tissue subject to immunofluorescence (IF); and based on said detection, detect and segment blood vessels which are in proximity to said CD34.
Specification