Systems and methods for treating, diagnosing and predicting the occurrence of a medical condition
First Claim
1. Apparatus for evaluating a risk of prostate cancer recurrence in a patient, the apparatus comprising:
- a model predictive of prostate cancer recurrence configured to evaluate a dataset for a patient to thereby evaluate a risk of prostate cancer recurrence in the patient, wherein the model is based on at least the following features;
seminal vesicle involvement;
a measurement of androgen receptor (AR); and
a morphometric measurement of epithelial nuclei derived from a tissue image.
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Accused Products
Abstract
Methods and systems are provided that use clinical information, molecular information and computer-generated morphometric information in a predictive model for predicting the occurrence (e.g., recurrence) of a medical condition, for example, cancer. In an embodiment, a model that predicts prostate cancer recurrence is provided, where the model is based on features including seminal vesicle involvement, surgical margin involvement, lymph node status, androgen receptor (AR) staining index of tumor, a morphometric measurement of epithelial nuclei, and at least one morphometric measurement of stroma. In another embodiment, a model that predicts clinical failure post prostatectomy is provided, wherein the model is based on features including biopsy Gleason score, lymph node involvement, prostatectomy Gleason score, a morphometric measurement of epithelial cytoplasm, a morphometric measurement of epithelial nuclei, a morphometric measurement of stroma, and intensity of androgen receptor (AR) in racemase (AMACR)-positive epithelial cells.
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Citations
33 Claims
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1. Apparatus for evaluating a risk of prostate cancer recurrence in a patient, the apparatus comprising:
a model predictive of prostate cancer recurrence configured to evaluate a dataset for a patient to thereby evaluate a risk of prostate cancer recurrence in the patient, wherein the model is based on at least the following features; seminal vesicle involvement; a measurement of androgen receptor (AR); and a morphometric measurement of epithelial nuclei derived from a tissue image. - View Dependent Claims (2, 3, 14, 15)
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4. A method of evaluating a risk of prostate cancer recurrence in a patient, the method comprising:
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evaluating a dataset for a patient with a model predictive of prostate cancer recurrence, wherein the model is based on at least the following features;
seminal vesicle involvement, a measurement of androgen receptor (AR), and a morphometric measurement of epithelial nuclei derived from a tissue image,thereby evaluating the risk of prostate cancer recurrence in the patient. - View Dependent Claims (5, 6, 16, 17)
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7. A computer-readable medium comprising computer executable instructions recorded thereon for performing the method comprising:
evaluating a dataset for a patient with a model predictive of prostate cancer recurrence to thereby evaluate the risk of prostate cancer recurrence in the patient, wherein the model is based on at least the following features;
seminal vesicle involvement, a measurement of androgen receptor (AR), and a morphometric measurement of epithelial nuclei derived from a tissue image.- View Dependent Claims (18, 19, 20, 21)
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8. An apparatus for evaluating a risk of clinical failure in a patient subsequent to the patient having a radical prostatectomy, the apparatus comprising:
a model predictive of clinical failure configured to evaluate a dataset for a patient to thereby evaluate a risk of clinical failure for the patient, wherein the model is based on at least the following features; lymph node involvement; a morphometric measurement of cytoplasm derived from a tissue image; and a measurement of intensity of androgen receptor (AR) in epithelial cells. - View Dependent Claims (9)
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10. A method of evaluating a risk of clinical failure in a patient subsequent to the patient having a radical prostatectomy, the method comprising:
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evaluating a dataset for a patient with a model predictive of clinical failure post-prostatectomy, wherein the model is based on at least the following features;
lymph node involvement, a morphometric measurement of cytoplasm derived from a tissue image, and a measurement of intensity of androgen receptor (AR) in epithelial cells,thereby evaluating the risk of clinical failure in the patient. - View Dependent Claims (11)
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12. A computer-readable medium comprising computer executable instructions recorded thereon for performing the method comprising:
evaluating a dataset for a patient with a model predictive of clinical failure post-prostatectomy to thereby evaluate the risk of clinical failure in the patient, wherein the model is based on at least the following features;
lymph node involvement, a morphometric measurement of cytoplasm derived from a tissue image, and a measurement of intensity of androgen receptor (AR) in epithelial cells.- View Dependent Claims (13)
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22. A method of evaluating a risk of occurrence of a medical condition in a patient, the method comprising:
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receiving a patient dataset for the patient; and evaluating the patient dataset with a model predictive of the medical condition to produce a value indicative of the risk of occurrence of the medical condition in the patient, wherein the model is based on one or more clinical feature(s), one or more molecular feature(s) generated based on computer analysis of one or more tissue images showing immunofluorescence (IF), and one or more computer-generated morphometric feature(s) generated from one or more tissue image(s). - View Dependent Claims (23, 24, 25)
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26. An apparatus for evaluating the risk of occurrence of a medical condition in a patient, the apparatus comprising:
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a model predictive of the medical condition, wherein the model is based on one or more clinical feature(s), one or more molecular feature(s) generated based on computer analysis of one or more tissue images showing immunofluorescence (IF), and one or more computer-generated morphometric feature(s) generated from one or more tissue image(s), 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 medical condition in the patient. - View Dependent Claims (27, 28, 29)
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30. A computer-readable medium comprising computer executable instructions recorded thereon for performing the method comprising:
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receiving a patient dataset for a patient; and evaluating the patient dataset with a model predictive of a medical condition to produce a value indicative of the risk of occurrence of the medical condition in the patient, wherein the model is based on one or more clinical feature(s), one or more molecular feature(s) generated based on computer analysis of one or more tissue images showing immunofluorescence (IF), and one or more computer-generated morphometric feature(s) generated from one or more tissue image(s). - View Dependent Claims (31, 32, 33)
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Specification