Distinguishing hyperprogression from other response patterns to PD1/PD-L1 inhibitors in non-small cell lung cancer with pre-therapy radiomic features
US10839513B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 11, 2019 |
| Grant date | Nov 17, 2020 |
| Priority date | — |
| Expiry date | May 16, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30096
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments access a pre-immunotherapy image of tissue demonstrating NSCLC including a tumor and a peritumoral region; extract a first set of radiomic features from the image; provide the first set of radiomic features to a first machine learning classifier; receive a first probability from the first classifier that the tissue is hyperprogressor (HP) or non-responder (R); if the first probability that the tissue is within a threshold: generate a first classification of the ROT as HP or non-R based on the first probability; if the first probability is not within the threshold: extract a second set of radiomic features from the peritumoral region and provide the second set to a second machine learning classifier; receive a second probability from the second classifier that the tissue is HP or R; generate a second classification of the tissue as HP or R based on the second probability; and display the classification.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.