Magnetic Resonance Image-Guided Radiotherapy (MRIgRT): A 4.5-Year Clinical Experience.

AIMS: Magnetic resonance image-guided radiotherapy (MRIgRT) has been clinically implemented since 2014. This technology offers improved soft-tissue visualisation, daily imaging, and intra-fraction real-time imaging without added radiation exposure, and the opportunity for adaptive radiotherapy (ART) to adjust for anatomical changes. Here we share the longest single-institution experience with MRIgRT, focusing on trends and changes in use over the past 4.5 years. MATERIALS AND METHODS: We analysed clinical information, including patient demographics, treatment dates, disease sites, dose/fractionation, and clinical trial enrolment for all patients treated at our institution using MRIgRT on a commercially available, integrated 0.35 T MRI, tri-cobalt-60 device from 2014 to 2018. For each patient, factors including disease site, clinical rationale for MRIgRT use, use of ART, and proportion of fractions adapted were summated and compared between individual years of use (2014-2018) to identify shifts in institutional practice patterns. RESULTS: Six hundred and forty-two patients were treated with 666 unique treatment courses using MRIgRT at our institution between 2014 and 2018. Breast cancer was the most common disease, with use of cine MRI gating being a particularly important indication, followed by abdominal sites, where the need for cine gating and use of ART drove MRIgRT use. One hundred and ninety patients were treated using ART in 1550 fractions, 67.6% (1050) of which were adapted. ART was primarily used in cancers of the abdomen. Over time, breast and gastrointestinal cancers became increasingly dominant for MRIgRT use, hypofractionated treatment courses became more popular, and gastrointestinal cancers became the principal focus of ART. DISCUSSION: MRIgRT is widely applicable within the field of radiation oncology and new clinical uses continue to emerge. At our institution to date, applications such as ART for gastrointestinal cancers and accelerated partial breast irradiation (APBI) for breast cancer have become dominant indications, although this is likely to continue to evolve.

A framework for automated contour quality assurance in radiation therapy including adaptive techniques.

Contouring of targets and normal tissues is one of the largest sources of variability in radiation therapy treatment plans. Contours thus require a time intensive and error-prone quality assurance (QA) evaluation, limitations which also impair the facilitation of adaptive radiotherapy (ART). Here, an automated system for contour QA is developed using historical data (the 'knowledge base'). A pilot study was performed with a knowledge base derived from 9 contours each from 29 head-and-neck treatment plans. Size, shape, relative position, and other clinically-relevant metrics and heuristically derived rules are determined. Metrics are extracted from input patient data and compared against rules determined from the knowledge base; a computer-learning component allows metrics to evolve with more input data, including patient specific data for ART. Nine additional plans containing 42 unique contouring errors were analyzed. 40/42 errors were detected as were 9 false positives. The results of this study imply knowledge-based contour QA could potentially enhance the safety and effectiveness of RT treatment plans as well as increase the efficiency of the treatment planning process, reducing labor and the cost of therapy for patients.