Patent ID: 7769547

Claim:
A method for quantitatively measuring a prognosis for a tumor recurrence, comprising the steps of: (a) imaging nuclei from a plurality of tissue samples from known recurrent and non-recurrent tumor cases to produce corresponding optical-density data for each case; (b) performing a first discriminant analysis of said optical-density data associated with said cases in order to identify a first set of cases suitable for classification as either recurrent or non-recurrent with a first predetermined degree of certainty based on a first discriminant chromatin feature, thereby also identifying a second set of cases from said known recurrent and non-recurrent tumor cases in step (a) that are not suitable for classification within said first predetermined degree of certainty based on said first discriminant chromatin feature; (c) performing a second discriminant analysis of optical-density data associated with said second set of cases in order to identify a subset of cases suitable for classification as either recurrent or non-recurrent with a second predetermined degree of certainty based on a second discriminant chromatin feature; (d) segregating subpopulations of nuclei from said subset of cases using a non-supervised learning algorithm applied to said second discriminant chromatin feature; (e) analyzing said subpopulations of nuclei to produce a statistically significant indicator of said tumor recurrence based on said second discriminant chromatin feature; (f) imaging a test tissue sample from a patient to produce test optical-density data corresponding thereto; (g) obtaining a value of said statistically significant indicator from said test optical-density data corresponding to the test tissue sample; and (h) providing a prognosis for a tumor recurrence in said patient based on said value of the statistically significant indicator.