Method and system for determining the risk of occurrence of prostate cancer

US9858389B2 · kind B2 · utility

Assignee

• FUNDAçÃO D. ANNA DE SOMMER CHAMPALIMAUD E DR. CARLOS MONTEZ CHAMPALIMAUD · PT

Inventors

• Michael Donovan · Boston, US
• Faisal Khan · Fishkill, US
• Gerardo Fernandez · New York, US
• Ali Tabesh · Tucson, US
• Ricardo Mesa-Tejada · Pleasantville, US
• Carlos Cordon-Cardo · New York, US
• Jose Costa · Ottawa, CA
• Stephen Fogarasi · Everett, US
• Yevgen Vengrenyuk · Mamaroneck, US

Key dates

• Filing date: Jul 27, 2009
• Grant date: Jan 2, 2018
• Expiry date: Oct 15, 2031

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H50/70
• WIPO field: Medical technology
• WIPO sector: Instruments

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.