Attention-based Vision Transformer Enables Early Detection of Radiotherapy-Induced Toxicity in Magnetic Resonance Images of a Preclinical Model
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Le résumé fourni par la source
IntroductionEarly identification of patients at risk for toxicity induced by radiotherapy (RT) is essential for developing personalized treatments and mitigation plans. Preclinical models with relevant endpoints are critical for systematic evaluation of normal tissue responses. This study aims to determine whether attention-based vision transformers can classify MR images of irradiated and control mice, potentially aiding early identification of individuals at risk of developing toxicity.MethodC57BL/6J mice (n = 14) were subjected to 66 Gy of fractionated RT targeting the oral cavity, swallowing muscles, and salivary glands. A control group (n = 15) received no irradiation but was otherwise treated identically. T2-weighted MR images were obtained 3-5 days post-irradiation. Late toxicity in terms of saliva production in individual mice was assessed at day 105 after treatment. A pre-trained vision transformer model (ViT Base 16) was employed to classify the images into control and irradiated groups.ResultsThe ViT Base 16 model classified the MR images with an accuracy of 69%, with identical overall performance for control and irradiated animals. The ViT's model predictions showed a significant correlation with late toxicity (r = 0.65, p < 0.01). One of the attention maps from the ViT model highlighted the irradiated regions of the animals.ConclusionsAttention-based vision transformers using MRI have the potential to predict individuals at risk of developing early toxicity. This approach may enhance personalized treatment and follow-up strategies in head and neck cancer radiotherapy.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Attention-based Vision Transformer Enables Early Detection of Radiotherapy-Induced Toxicity in Magnetic Resonance Images of a Preclinical Model
- Date Crossref
- 04/04/2025
- Éditeur
- SAGE Publications
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Oslo University Hospital Department of Radiation Biology pays non établi dans la noticeÉtablissement de santé
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Norwegian Cancer Society pays non établi dans la noticeOrganisation à but non lucratif
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Norwegian University of Life Sciences pays non établi dans la noticeUniversité ou école supérieure
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University of Oslo Department of Physics pays non établi dans la noticeUniversité ou école supérieure
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Faculty of Science and Technology pays non établi dans la noticeUniversité ou école supérieure
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Faculty of Dentistry Institute for Oral Biology pays non établi dans la noticeUniversité ou école supérieure
Department of Radiation Biology — Oslo University Hospital, Norwegian Cancer Society et Norwegian University of Life Sciences, avec 3 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.