{"version":"1","article":{"id":"italy-mri-radiomics-glioma-encephalitis-2026","slug":"italy-mri-radiomics-glioma-encephalitis-2026","language":"en","url":"https://haberpaper.com/en/news/italy-mri-radiomics-glioma-encephalitis-2026","api_url":"https://haberpaper.com/api/v1/articles/italy-mri-radiomics-glioma-encephalitis-2026?lang=en","title":"Small Italian study tests MRI model to distinguish glioma from encephalitis","summary":"Rome researchers compared radiomics and machine-learning models using non-contrast MRI from 41 patients. The best FLAIR model reported an AUC of 0.82; the authors call for larger multicentre validation.","category":"business","region":"world","topics":["ai"],"published_at":"2026-10-13T20:11:52+03:00","modified_at":"2026-10-13T20:11:52+03:00","publication_basis":"publication-record","event_period":"2026-10-10","event_period_basis":"event-or-reference-period","sources":[{"name":"Scientific Reports, Radiomics and machine learning analysis to differentiate low grade glioma and encephalitis on non-contrast MRI","url":"https://www.nature.com/articles/s41598-026-74097-z","checkedAt":"2026-10-13","publishedAt":"2026-10-10"}],"translations":[{"language":"tr","url":"https://haberpaper.com/tr/news/italy-mri-radiomics-glioma-encephalitis-2026","api_url":"https://haberpaper.com/api/v1/articles/italy-mri-radiomics-glioma-encephalitis-2026?lang=tr"},{"language":"en","url":"https://haberpaper.com/en/news/italy-mri-radiomics-glioma-encephalitis-2026","api_url":"https://haberpaper.com/api/v1/articles/italy-mri-radiomics-glioma-encephalitis-2026?lang=en"},{"language":"ar","url":"https://haberpaper.com/ar/news/italy-mri-radiomics-glioma-encephalitis-2026","api_url":"https://haberpaper.com/api/v1/articles/italy-mri-radiomics-glioma-encephalitis-2026?lang=ar"},{"language":"fr","url":"https://haberpaper.com/fr/news/italy-mri-radiomics-glioma-encephalitis-2026","api_url":"https://haberpaper.com/api/v1/articles/italy-mri-radiomics-glioma-encephalitis-2026?lang=fr"},{"language":"es","url":"https://haberpaper.com/es/news/italy-mri-radiomics-glioma-encephalitis-2026","api_url":"https://haberpaper.com/api/v1/articles/italy-mri-radiomics-glioma-encephalitis-2026?lang=es"}],"data_types":[],"data":null,"data_compilations":[],"data_downloads":[],"content":{"paragraphs":["A single-centre study published on 10 October in Scientific Reports examined non-contrast 3T MRI scans from 41 patients whose emergency diagnoses raised a difficult distinction between low-grade glioma and encephalitis. Researchers at the University of Rome Tor Vergata and affiliated hospital units trained random-forest classifiers on radiomic features from T2-FLAIR, diffusion and T1 scans. The cohort was split into 31 training cases and 10 for independent validation. FLAIR-based models performed best; the model combining radiomics with clinical data across sequences had an AUC of 0.80.","For that combined-sequence model, the paper reports 100% sensitivity, 80% specificity and 90% accuracy on the validation set. But only 10 patients were in that set, and the confidence intervals were wide: the FLAIR AUC was 0.82 with a 95% interval of 0.54–1.00. The authors describe the work as proof of concept and say larger multicentre studies are needed before clinical use."],"key_points":[],"sections":[]},"text":"Rome researchers compared radiomics and machine-learning models using non-contrast MRI from 41 patients. The best FLAIR model reported an AUC of 0.82; the authors call for larger multicentre validation.\n\nA single-centre study published on 10 October in Scientific Reports examined non-contrast 3T MRI scans from 41 patients whose emergency diagnoses raised a difficult distinction between low-grade glioma and encephalitis. Researchers at the University of Rome Tor Vergata and affiliated hospital units trained random-forest classifiers on radiomic features from T2-FLAIR, diffusion and T1 scans. The cohort was split into 31 training cases and 10 for independent validation. FLAIR-based models performed best; the model combining radiomics with clinical data across sequences had an AUC of 0.80.\n\nFor that combined-sequence model, the paper reports 100% sensitivity, 80% specificity and 90% accuracy on the validation set. But only 10 patients were in that set, and the confidence intervals were wide: the FLAIR AUC was 0.82 with a 95% interval of 0.54–1.00. The authors describe the work as proof of concept and say larger multicentre studies are needed before clinical use.","corrections":[],"editorial_illustration":{"kind":"symbolic-editorial-illustration","documentary":false,"scope":"section","asset_id":"business","url":"https://haberpaper.com/assets/illustrations/business-1536.webp","width":1536,"height":1024,"alt":"Symbolic industrial workshop with machinery, a warehouse and a crane.","language":"en"},"section_illustration":{"kind":"symbolic-editorial-illustration","documentary":false,"scope":"section","asset_id":"business","url":"https://haberpaper.com/assets/illustrations/business-1536.webp","width":1536,"height":1024,"alt":"Symbolic industrial workshop with machinery, a warehouse and a crane.","language":"en"}}}