Clinical implementation and initial experience with a 1.5 Tesla MR-linac for MR-guided radiotherapy for gynecologic cancer: An R-IDEAL stage 1/2a first in humans/feasibility study of new technology implementation

Purpose: Magnetic resonance imaging-guided linear accelerator systems (MR-linacs) can facilitate the daily adaptation of radiotherapy plans. Here, we report our early clinical experience using an MR-linac for adaptive radiotherapy of gynecologic malignancies. Methods and Materials: Treatments were planned with an Elekta Monaco v5.4.01 and delivered by a 1.5 Tesla Elekta Unity MR-linac. The system offers a choice of daily adaptation based on either position (ATP) or shape (ATS) of the tumor and surrounding normal structures. The ATS approach has the option of manually editing the contours of tumors and surrounding normal structures before the plan is adapted. Here we documented the duration of each treatment fraction; set-up variability (assessed by isocenter shifts in each plan) between fractions; and, for quality assurance, calculated the percentage of plans meeting the ;γ-criterion of 3%/3-mm distance to agreement. Deformable accumulated dose calculations were used to compare ATP plans with reference dose plans. Results: Of the 10 patients treated with 90 fractions on the MR-linac, most received boost doses to recurrence in nodes or isolated tumors. Each treatment fraction lasted a median 32 minutes; fractions were shorter with ATP than with ATS (30 min vs 42 min, P<0.0001). The γ-criterion for all fraction plans exceeded >90% (median 99.9%, range 92.4%-100%), i.e., all plans passed quality assurance testing. The average extent of isocenter shift was <0.5 cm in each axis. The accumulated dose to the gross tumor volume was within 10% of the reference plan for all ATP cases. Accumulated doses for lesions in the pelvic periphery were within 1% of the reference plan as opposed to -5.8% to -9.6% for central tumors. Conclusions: The MR-linac is a reliable and clinically feasible tool for treating patients with gynecologic cancer.

Introducing matrix sparsity with kernel truncation into dose calculations for fluence optimization.

Deep learning algorithms for radiation therapy treatment planning automation require large patient datasets and complex architectures that often take hundreds of hours to train. Some of these algorithms require constant dose updating (such as with reinforcement learning) and may take days. When these algorithms rely on commerical treatment planning systems to perform dose calculations, the data pipeline becomes the bottleneck of the entire algorithm’s efficiency. Further, uniformly accurate distributions are not always needed for the training and approximations can be introduced to speed up the process without affecting the outcome. These approximations not only speed up the calculation process, but allow for custom algorithms to be written specifically for the purposes of use in AI/ML applications where the dose and fluence must be calculated a multitude of times for a multitude of different situations. Here we present and investigate the effect of introducing matrix sparsity through kernel truncation on the dose calculation for the purposes of fluence optimzation within these AI/ML algorithms. The basis for this algorithm relies on voxel discrimination in which numerous voxels are pruned from the computationally expensive part of the calculation. This results in a significant reduction in computation time and storage. Comparing our dose calculation against calculations in both a water phantom and patient anatomy in Eclipse without heterogenity corrections produced gamma index passing rates around 99% for individual and composite beams with uniform fluence and around 98% for beams with a modulated fluence. The resulting sparsity introduces a reduction in computational time and space proportional to the square of the sparsity tolerance with a potential decrease in cost greater than 10 times that of a dense calculation allowing not only for faster caluclations but for calculations that a dense algorithm could not perform on the same system.

Development and validation of a length- and habitus-based method of ideal and lean body weight estimation for critically ill adults requiring urgent weight-based medical intervention

Objective: Accurate drug dosing in obese patients requires an estimation of ideal body weight (IBW) or lean body weight (LBW) for dosing hydrophilic medications. Erroneous weight estimates during the management of critically ill adults may contribute to poor outcomes. Existing methods of IBW and LBW estimation or measurement are very difficult to use during emergency care. A new point-of-care model is needed to provide rapid estimates of IBW and LBW for this purpose. Methods A model was derived based on the PAWPER XL-MAC tape, a pediatric weight estimation system, which uses recumbent length and mid-arm circumference to estimate IBW and LBW. The model was used to generate weight estimations in a derivation sample (n=33155) and a validation sample (n=5926) from National Health and Nutrition Examination Survey (NHANES) datasets. The outcome measure was to achieve >95% of IBW and LBW estimations within 20% of recognized reference standards (P20>95%) and >70% of estimations within 10% of these standards (P10>70%). Main Results: The new model achieved a P20 of 100% and a P10 of 99.9% for IBW and a P20 of 98.3% and a P10 of 78.3% for LBW. This accuracy was maintained in both sexes, all ages, all ethnic groups, all lengths and in all habitus-types, except for the morbidly obese female subgroup. Conclusions The modified PAWPER XL-MAC model proved to be an accurate method of IBW and LBW estimation. It could, therefore, have an important role in facilitating emergency drug dose calculations in acutely or critically ill obese adult patients. Conclusions The modified PAWPER XL-MAC model proved to be an accurate method of IBW and LBW estimation. It could, therefore, have an important role in facilitating emergency drug dose calculations in acutely or critically ill obese adult patients.

The Effect of Contrast Agents on Dose Calculations of Volumetric Modulated Arc Radiotherapy Plans for Critical Structures

Radiotherapy dose calculation requires accurate Computed Tomography (CT) imaging while tissue delineation may necessitate the use of contrast agents (CA). Acquiring these two sets is a common practice in radiotherapy. This study aims to evaluate the effect of CA on the dose calculations. Two hundred and twenty-six volumetric modulated arc therapy (VMAT) patients that had planning CT with contrast (CCT) and non-contrast CT (NCCT) of different cancer sites (e.g., brain, head, and neck (H&N), chest, abdomen, and pelvis) were evaluated. Treatment plans were recalculated using CCT, then compared to NCCT. The variation in Hounsfield units (HU) and dose distributions for critical structures and target volumes were analyzed using mean HU, mean and maximum relative dose values, D2%, D98%, and 3D gamma analysis. HU variations were statistically significant for most structures. However, this was not clinically significant as the difference in mean HU values was within 30 HU for soft tissue and 50 HU for lungs. Variation in target volumes’ D2% and D98% were insignificant for all sites except brain and nasopharynx. Dose maximum differences were within 2% for the majority of critical structures and target volumes. 3D gamma analysis results revealed that majority of plans satisfied the 2% and 2 mm criteria. CCT may be acquired for VMAT radiotherapy planning purposes instead of NCCT, since there is no clinically significant difference in dose calculations based on either image set.

Skyshine Dose Estimations for an 18 MeV Photon Beam Using MCNPX Code: A Comparison of Flattened and Flattening Filter-Free Beam

Purpose: The current study aimed to estimate photon skyshine dose rate from a Varian linac equippedwith a Flattening Filter (FF) and its FF-Free (FFF) mode. The skyshine photons from a Linac bunker can influence the radiation dose received by personnel and the public in radiation therapy centers. Materials and Methods: In the current study skyshine dose from the conventional flattened beam and the flattening-free beam were compared. The MCNPX Monte Carlo code was used to model an18 MeV photon beam of Varian linac. The skyshine radiation was calculated for FF and FFF linac photon beams at the control room, parking, sidewalk, and corridor around the linac room. Results: For the conventional beam, the skyshine dose rates of 0.53, 0.42, 0.45, and 0.50 mSv/h were estimated for the control room, corridor, sidewalk, and parking, respectively. While for the FFF beam, dose rates of 0.21, 0.20, 0.20, and 0.23 mSv/h were estimated for the same positions, respectively. The results indicated that the empirical method of NCRP 151 can not distinguish between FF and FFF beams in skyshine dose calculations. Our results found a 50% lower level dose rate from the FFF beam at distant and nearby locations. Conclusion: The findings of current can be helpful in the radiation dose calculations and the radiation protection designation of radiation therapy bunkers.