Improving treatment precision in head and neck BNCT: delineation of oral and pharyngeal mucosa based on an MRI Atlas for standardized applications
Hirose, K.; Kato, R.; Sato, M.; Ichise, K.; Tanaka, M.; Fujioka, I.; Kawaguchi, H.; Hatayama, Y.; Aoki, M.; Takai, Y.
Show abstract
Background and purposeBoron neutron capture therapy (BNCT) has been routinely practiced for treatment of head and neck cancer in Japan. However, differences in contouring the oral and pharyngeal mucosa can lead to discrepancies in treatment. This study aimed to introduce a standardized approach using an MRI-based atlas, aiming to minimize inter-observer error and improve dose precision. Materials and MethodsAn MRI atlas of the head and neck mucosa was developed using water/fat-separated images from a healthy man. Using CT images from three patients, seven radiation oncologists performed contouring of the head and neck mucosa twice over a 3-week period. Contouring was first performed using CT alone, then later using fused T2-weighted images with the mucosal atlas for guidance. Contouring errors were assessed and their impacts on tumor dose were evaluated. ResultsThe introduction of the MRI-based mucosal atlas significantly reduced inter-observer variation in mucosal volume (the coefficient of variation, abbreviated with COV, decreased from 0.61 with CT alone to 0.21 with the MRI atlas; p=0.003). Moreover, the atlas resulted in improved contour homology among observers and reduced variations in tumor dose. For all cases, COVs for maximum, mean, and minimum tumor doses were all below 5%. ConclusionUtilizing an MRI-based mucosal atlas in BNCT contouring can significantly reduce inter-observer variation, improve contour homology, and decrease variations in tumor dose. These findings suggest strong potential for standardizing and enhancing the quality of BNCT for head and neck cancer.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Comprehensive Quantitative Evaluation of Inter-observer Delineation Performance of MR-guided Delineation of Oropharyngeal Gross Tumor Volumes and High-risk Clinical Target Therapy: An R-IDEAL Stage 0 Prospective Study 98%
- Normal Tissue Complication Probability (NTCP) prediction model for osteoradionecrosis of the mandible in head and neck cancer patients following radiotherapy: Large-scale observational cohort 97%
- Clinical Impact of Contouring Variability for Prostate Cancer Tumor Boost 97%
Similar papers in this journal
- Morphological changes after cranial fractionated photon radiotherapy: localized loss of white matter and grey matter volume with increasing dose 96%
- Detection of Alteration in Carotid Artery Volumetry Using Standard-of-care Computed Tomography Surveillance Scans Following Unilateral Radiation Therapy for Early-stage Tonsillar Squamous Cell Carcinoma Survivors: A Cross-Sectional Internally-Matched Carotid Isodose Analysis 96%
- Personalized volume-deescalated elective nodal irradiation in oropharyngeal squamous cell carcinoma (DeEscO): a study protocol 94%
Similar papers in this journal
- Evaluation of indirect damage and damage saturation effects in dose-response curves of hypofractionated radiotherapy of early-stage NSCLC and brain metastases 97%
- First demonstration of the FLASH effect with ultrahigh dose-rate high-energy X-rays 96%
- Dosimetric and biologic intercomparison between electron and proton FLASH beams 96%
Similar papers in this journal
- Leveraging intelligent optimization for automated, cardiac-sparing accelerated partial breast treatment planning 98%
- Avasopasem Manganese acts as both a Radioprotector and a Radiomitigator of Radiation-Induced Acute or Late Effects. 94%
- Segmentation stability of human head and neck medical images for radiotherapy applications under de-identification conditions: benchmarking for data sharing and artificial intelligence use-cases 90%
Similar papers in this journal
- Effectiveness of FLASH vs conventional dose rate radiotherapy in a model of orthotopic, murine breast cancer 97%
- Standardising Breast Radiotherapy Structure Naming Conventions: A Machine Learning Approach 96%
- Quality of life and patient-reported outcomes following proton therapy for oropharyngeal carcinoma: a systematic review 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.