SYSTEMS AND METHODS OF TREATING, DIAGNOSING AND PREDICTING THE OCCURRENCE OF A MEDICAL CONDITION

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...

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Bibliographic Details
Main Authors VENGRENYUK, YEVGEN, FERNANDEZ, GERARDO, CARDON-CARDO, CARLOS, COSTA, JOSE, TABESH, ALI, FOGARASI, STEPHEN, DONOVAN, MICHAEL, KHAN, FAISAL, MESA-TEJADA, RICARDO
Format Patent
LanguageEnglish
French
Published 28.01.2010
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary: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.
Bibliography:Application Number: CA20092731747