{"doi":"10.3389/fonc.2023.1185738","title":"An image-based modeling framework for predicting spatiotemporal brain cancer biology within individual patients","abstract":"Imaging is central to the clinical surveillance of brain tumors yet it provides limited insight into a tumor's underlying biology. Machine learning and other mathematical modeling approaches can leverage paired magnetic resonance images and image-localized tissue samples to predict almost any characteristic of a tumor. Image-based modeling takes advantage of the spatial resolution of routine clinical scans and can be applied to measure biological differences within a tumor, changes over time, as well as the variance between patients. This approach is non-invasive and circumvents the intrinsic challenges of inter- and intratumoral heterogeneity that have historically hindered the complete assessment of tumor biology and treatment responsiveness. It can also reveal tumor characteristics that may guide both surgical and medical decision-making in real-time. Here we describe a general framework for the acquisition of image-localized biopsies and the construction of spatiotemporal radiomics models, as well as case examples of how this approach may be used to address clinically relevant questions.","journal":"Frontiers in Oncology","year":2023,"id":381181,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9539,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":376752,"name":"Lee Curtin","orcid":"0000-0002-4083-3803","position":1,"is_corresponding":false},{"id":414056,"name":"Sara Ranjbar","orcid":"0000-0002-4344-1282","position":2,"is_corresponding":false},{"id":1147173,"name":"Ariana E. Afshari","orcid":null,"position":3,"is_corresponding":false},{"id":247456,"name":"Leland Hu","orcid":"0000-0001-9282-7619","position":4,"is_corresponding":false},{"id":104960,"name":"Joshua B. Rubin","orcid":"0000-0002-7395-1937","position":5,"is_corresponding":false},{"id":262755,"name":"Kristin R. Swanson","orcid":"0000-0002-2464-6119","position":6,"is_corresponding":false},{"id":536865,"name":"Kamila M. Bond","orcid":"0000-0002-7042-4146","position":0,"is_corresponding":true}],"reference_count":75,"raw_metadata":null,"created_at":"2026-07-19T01:17:08.831117Z","pmid":"37849813","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}