Predicting breast cancer responsiveness to hormone treatment using quantitative textural analysis
AssigneeImaging Endpoints II LLC
InventorRonald L. Korn
Life of this patent
Estimating the term…
Abstract
Biomarker signatures for predicting breast cancer tumor aggressiveness. The signatures are derived from QTA-based parameters from a first population of low risk scores and a second population of high risk scores. The signatures may be expressed in the form log (RS)=Mx+B for linear modeling, or for logistic modeling the signatures may be expressed as either p=ex/[1+ex] where x=Ay+B, or in the form log it(p)=C(PR)+Ay+B, where y is a QTA based parameter.
Claims21
A method of predicting responsiveness of breast tumors to hormone therapy, the method comprising:
- performing a quantitative textual analysis (QTA) based on a breast scan for a patient;
- determining using the QTA based on the breast scan for the patient, a particular value for a QTA-based parameter;
- estimating an Oncotype DX Assay Recurrence Score (RS) value for the patient using a biomarker signature for use in identifying subsequent breast tumors having a high risk Oncotype DX Assay RS, and the particular value for the QTA based parameter,
- wherein the biomarker signature was derived through linear modeling of a first population of prior images having low risk RS scores and a second population of prior images having high risk RS scores, the biomarker signature expressed in the form
- log(RS)=Mx+B, where:
- M is a coefficient;
- x is the QTA-based parameter;
- and
- B is a constant;
- and
- predicting responsiveness to hormone therapy for the patient based on the estimated RS value.
A method of predicting responsiveness of breast tumors to hormone therapy, the method comprising:
- performing a quantitative textual analysis (QTA) based on a breast scan for a patient;
- determining using the QTA based on the breast scan for the patient, a particular value for a QTA-based parameter;
- estimating a recurrence score (RS) value for the patient using a biomarker signature for use in identifying breast tumors having a probability p of exhibiting a high risk RS value, the signature derived from high risk and low risk legacy tumor data using logistic modeling and expressed in the form
- p=ex/[1+ex] where x=Ay+B, and:
- A is a coefficient;
- Y is a QTA based parameter;
- and
- B is a constant;
- and
- predicting responsiveness to hormone therapy for the patient based on the estimated RS value.
A method of predicting responsiveness of breast tumors to hormone therapy, the method comprising:
- performing a quantitative textual analysis (QTA) based on a breast scan for a patient;
- determining using the QTA based on the breast scan for the patient, a particular value for a QTA-based parameter;
- estimating a recurrence score (RS) value for the patient using a biomarker signature for use in identifying breast tumors having a probability log it(p) of exhibiting a high risk RS value, the signature derived from high risk and low risk legacy tumor data using logistic modeling and expressed in the faun
- log it(p)=C(PR)+Ay+B where:
- PR−=0 and PR+=1;
- C is a first coefficient;
- A is a second coefficient;
- y is a QTA-based parameter;
- and
- B is a constant;
- and
- predicting responsiveness to hormone therapy for the patient based on the estimated RS value.
Dependencies are inferred from the claim text.