{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Voutouri C"],"funding":["European Research Council","EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)"],"pagination":["203"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11487255"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["4(1)"],"pubmed_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 "],"journal":["Communications medicine"],"pubmed_title":["A convolutional attention model for predicting response to chemo-immunotherapy from ultrasound elastography in mouse tumor models."],"pmcid":["PMC11487255"],"funding_grant_id":["956201","101069207"],"pubmed_authors":["Englezos D","Strouthos I","Voutouri C","Stylianopoulos T","Zamboglou C","Papanastasiou G"],"additional_accession":[]},"is_claimable":false,"name":"A convolutional attention model for predicting response to chemo-immunotherapy from ultrasound elastography in mouse tumor models.","description":"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 ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Oct","modification":"2026-06-01T09:14:52.637Z","creation":"2025-04-04T09:58:23.201Z"},"accession":"S-EPMC11487255","cross_references":{"pubmed":["39420199"],"doi":["10.1038/s43856-024-00634-4"]}}