Quantitative analysis of MRI-guided radiotherapy treatment process time for tumor real-time gating efficiency.

PURPOSE: Magnetic Resonance-guided radiotherapy (MRgRT) systems allow continuous monitoring of therapy volumes during treatment delivery and personalized respiratory gating approaches. Treatment length may therefore be significantly affected by patient's compliance and breathing control. We quantitatively analyzed treatment process time efficiency (TE ) using data obtained from real-world patient treatment logs to optimize MRgRT delivery settings. METHODS: Data corresponding to the first 100 patients treated with a low T hybrid MRI-Linac system, both in free breathing (FB) and in breath hold inspiration (BHI) were collected. TE has been computed as the percentage difference of the actual single fraction's total treatment time and the predicted treatment process time, as computed by the TPS during plan optimization. Differences between the scheduled and actual treatment room occupancy time were also evaluated. Finally, possible correlations with planning, delivery and clinical parameters with TE were also investigated. RESULTS: Nine hundred and nineteen treatment fractions were evaluated. TE difference between BHI and FB patients' groups was statistically significant and the mean TE were 42.4%, and -0.5% respectively. No correlation was found with TE for BHI and FB groups. Planning, delivering and clinical parameters classified BHI and FB groups, but no correlation with TE was found. CONCLUSION: The use of BHI gating technique can increase the treatment process time significantly. BHI technique could be not always an adequate delivery technique to optimize the treatment process time. Further gating techniques should be considered to improve the use of MRgRT.

Uterus motion analysis for radiotherapy planning optimization. The innovative contribution of on-board hybrid MR imaging.

Introduction: Organ motion (OM) and volumetric changes pose challenges in radiotherapy (RT) for locally advanced cervical cancer (LACC). Magnetic Resonance-guided Radiotherapy (MRgRT) combines improved MRI contrast with adaptive RT plans for daily anatomical changes. Our goal was to analyze cervico-uterine structure (CUS) changes during RT to develop strategies for managing OM. Materials and methods: LACC patients received chemoradiation by MRIdian system with a simultaneous integrated boost (SIB) protocol. Prescription doses of 55-50.6 Gy at PTV1 and 45-39.6 Gy at PTV2 were given in 22 and 25 fractions. Daily MRI scans were co-registered with planning scans and CUS changes were assessed.Six PTVs were created by adding 0.5, 0.7, 1, 1.3, 1.5, and 2 cm margins to the CUS, based on the simulation MRI. Adequate margins were determined to include 95 % of the CUSs throughout the entire treatment in 95 % of patients. Results: Analysis of 15 LACC patients and 372 MR scans showed a 31 % median CUS volume decrease. Asymmetric margins of 2 cm cranially, 0.5 cm caudally, 1.5 cm posteriorly, 2 cm anteriorly, and 1.5 cm on both sides were optimal for PTV, adapting to CUS variations. Post-14th fraction, smaller margins of 0.7 cm cranially, 0.5 cm caudally, 1.3 cm posteriorly, 1.3 cm anteriorly, and 1.3 cm on both sides sufficed. Conclusion: CUS mobility varies during RT, suggesting reduced PTV margins after the third week. MRgRT with adaptive strategies optimizes dose delivery, emphasizing the importance of streamlined IGRT with reduced PTV margins using a tailored MRgRT workflow with hybrid MRI-guided systems.

Mesorectal motion evaluation in rectal cancer MR-guided radiotherapy: an exploratory study to quantify treatment margins.

BACKGROUND: Mesorectal motion (MM) is a source of uncertainty during neoadjuvant chemoradiotherapy (nCRT) delivery for locally advanced rectal cancer (LARC). Previously published experiences using cone-beam computed tomography imaging have already described significant movement. Aim of this analysis is to assess inter-fraction MM using the higher tissue contrast provided by hybrid magnetic resonance imaging (MRI) in LARC patients (pts) treated with MRI guided radiation therapy (MRgRT). METHODS: The total mesorectum, its superior (Msup), middle (Mmid) and lower (Mlow) regions were contoured on the positioning MRIs acquired on simulation day and on each treatment day. Six PTVs were obtained adding 0.5, 0.7, 1, 1.3, 1.5 and 2 cm margin to the whole mesorectum, starting from the simulation MRI. Margins including 95% of the mesorectal structures during whole treatment in 95% of patients (pts) were considered adequate. RESULTS: A total number of 312 fractions of 12 consecutive pts was retrospectively analyzed. The different mesorectum regions show specific motion variability. In particular, Msup shows larger variability in left, right and anterior directions, while the Mlow in caudal and posterior ones. The anterior margin is significantly larger in the Msup than in the other regions. CONCLUSION: Different mesorectal regions move differently throughout the radiotherapy treatment, with the largest MM in the Msup anterior direction. Asymmetrical margins are recommended.

Delivery of online adaptive magnetic resonance guided radiotherapy based on isodose boundaries.

Magnetic Resonance-guided Radiotherapy (MRgRT) allows direct monitoring of treated volumes. The aim of this study was to investigate the feasibility of a new gating strategy consisting in using an isodose as boundary. Forty-four patients treated for thoracic and abdominal lesions using MRgRT were enrolled. The accuracy of the new strategy was compared to the conventional one in terms of area improvement available for gating without compromising target coverage. A mean increase of 24% for lung, 15% for liver and 11% for pancreas was observed, demonstrating how the new method can be useful in challenging situations with low dose conformality.

A deep learning approach to generate synthetic CT in low field MR-guided adaptive radiotherapy for abdominal and pelvic cases.

PURPOSE: Artificial intelligence (AI) can play a significant role in Magnetic Resonance guided Radiotherapy (MRgRT), especially to speed up the online adaptive workflow. The aim of this study is to set up a Deep Learning (DL) approach able to generate synthetic computed tomography (sCT) images from low field MR images in pelvis and abdomen. METHODS: A conditional Generative Adversarial Network (cGAN) was used for sCT generation: a total of 120 patients treated on pelvic and abdominal sites were enrolled and divided in training (80) and test sets (40). Intensity modulated radiotherapy (IMRT) treatment plans were calculated on sCT and original CT and then compared in terms of gamma analysis and differences in Dose Volume Histogram (DVH). The two one-sided test for paired samples (TOST-P) was used to evaluate the equivalence among different DVH parameters calculated for target and organs at risks (OAR) on CT and sCT images. RESULTS: Using a CPU architecture, the mean time required by the neural network to generate a synthetic CT was 175 ± 43 seconds (s) for pelvic cases and 110 ± 40 s for abdominal ones. Mean gamma passing rates for the three tolerance criteria analysed (1%/1 mm, 2%/2 mm and 3%/3 mm) were respectively 90.8 ± 4.5%, 98.7 ± 1.1% and 99.8 ± 0.2% for abdominal cases; 89.3 ± 4.8%, 99.0 ± 0.7% and 99.9 ± 0.2% for pelvic ones, while equivalence within 1% was observed among the DVH indicators. CONCLUSION: This study demonstrated that sCT generation using a DL approach is feasible for low field MR images in pelvis and abdomen, allowing a reliable calculation of IMRT plans in MRgRT.

Case Report: First in Human Online Adaptive MR Guided SBRT of Peritoneal Carcinomatosis Nodules: A New Therapeutic Approach for the Oligo-Metastatic Patient.

Peritoneal carcinosis (PC) is characterized by poor prognosis. PC is currently treated as a locoregional disease and the possibility to perform very precise treatments such as stereotactic body radiation therapy (SBRT) has opened up new therapeutic perspectives. More recently, the introduction of Magnetic Resonance-guided Radiation Therapy (MRgRT) allowed online adaptation (OA) of treatment plan to optimize daily dose distribution based on patient's anatomy. The aim of this study is the evaluation of the effectiveness of SBRT OA workflow in an oligometastatic patient affected by PC. We report the clinical case of a patient affected by PC originating from colon cancer, previously treated with chemotherapy and surgery, addressed to OA SBRT treatment on a single chemoresistant PC nodule, delivered with a 0.35 T MR Linac. Treatment was delivered using gating approach in deep inspiration breath hold condition in order to reduce intrafraction variability. Prescription dose was 35 Gy in 5 fractions. The PTV V95% of the original plan was 96.6%, while the predicted values for the following fractions were 11.9, 56.4, 0, 0, and 61%. Similarly, the small bowel V19.5 Gy of the original plan was 4.63 cc, while the predicted values for the following fractions were 3.7, 8.6, 10.7, 1.96, 3.7 cc. Thanks to the OA approach, the re-optimized PTV V95% coverage improved to 96.1, 89.0, 85.5, 94.5, and 94%; while the small bowel V19.5 Gy to 3.36; 3.28; 1.84; 2.62; 2.6 cc respectively. After the end of RT, the patient was addressed to follow-up, and the re-evaluation 18F-FDG PET-CT was performed after 10 months from irradiation showed complete response. No acute or late toxicities were recorded. MRgRT with OA approach in PC patients is technically and clinically feasible with clean toxicity result. Online adaptive SBRT for oligometastases opens up new therapeutic scenarios in the management of this category of patients.