US Patent:
20100177950, Jul 15, 2010
Inventors:
Michael Donovan - Cambridge MA, US
Faisal Khan - Fishkill NY, US
Gerardo Fernandez - Yorktown Heights NY, US
Ali Tabesh - New York NY, US
Ricardo Mesa-Tejada - Pleasantville NY, US
Carlos Cordon-Cardo - New York NY, US
Jose Costa - Guilford CT, US
Stephen Fogarasi - Pawling NY, US
Yevgen Vengrenyuk - Mamaroneck NY, US
Assignee:
Aureon Laboratories, Inc. - Yonkers NY
International Classification:
G06K 9/00
G06F 19/00
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.