A convolutional attention model for predicting response to chemo-immunotherapy from ultrasound elastography in mouse tumor models.

ABSTRACT:

Background

In the era of personalized cancer treatment, understanding the intrinsic heterogeneity of tumors is crucial. Despite some patients responding favorably to a particular treatment, others may not benefit, leading to the varied efficacy observed in standard therapies. This study focuses on the prediction of tumor response to chemo-immunotherapy, exploring the potential of tumor mechanics and medical imaging as predictive biomarkers. We have extensively studied "desmoplastic" tumors, characterized by a dense and very stiff stroma, which presents a substantial challenge for treatment. The increased stiffness of such tumors can be restored through pharmacological intervention with mechanotherapeutics.

Methods

We developed a deep learning methodology based on shear wave

SUBMITTER: Voutouri C 

PROVIDER: S-EPMC11487255 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature