Cardiac stereotactic radiation therapy for refractory ventricular arrhythmias in patients with left ventricular assist devices.

Left ventricular assist device (LVAD) implantation is an established treatment for patients with advanced heart failure refractory to medical therapy. However, the incidence of ventricular arrhythmias (VAs) is high in this population, both in the acute and delayed phases after implantation. About one-third of patients implanted with an LVAD will experience sustained VAs, predisposing these patients to worse outcomes and complicating patient management. The combination of pre-existing myocardial substrate and complex electrical remodeling after LVAD implantation account for the high incidence of VAs observed in this population. LVAD patients presenting VAs refractory to antiarrhythmic therapy and catheter ablation procedures are not rare. In such patients, treatment options are extremely limited. Stereotactic body radiation therapy (SBRT) is a technique that delivers precise and high doses of radiation to highly defined targets, reducing exposure to adjacent normal tissue. Cardiac SBRT has recently emerged as a promising alternative with a growing number of case series reporting the effectiveness of the technique in reducing the VA burden in patients with arrhythmias refractory to conventional therapies. The safety profile of cardiac SBRT also appears favorable, even though the current clinical experience remains limited. The use of cardiac SBRT for the treatment of refractory VAs in patients implanted with an LVAD are even more scarce. This review summarizes the clinical experience of cardiac SBRT in LVAD patients and describes technical considerations related to the implementation of the SBRT procedure in the presence of an LVAD.

Online adaptive radiotherapy and dose delivery accuracy: A retrospective analysis.

PURPOSE: With online adaptive radiotherapy (ART), patient-specific quality assurance (PSQA) testing cannot be performed prior to delivery of the adapted treatment plan. Consequently, the dose delivery accuracy of adapted plans (i.e., the ability of the system to interpret and deliver the treatment as planned) are not initially verified. We investigated the variation in dose delivery accuracy of ART on the MRIdian 0.35 T MR-linac (Viewray Inc., Oakwood, USA) between initial plans and their respective adapted plans, by analyzing PSQA results. METHODS: We considered the two main digestive localizations treated with ART (liver and pancreas). A total of 124 PSQA results acquired with the ArcCHECK (Sun Nuclear Corporation, Melbourne, USA) multidetector system were analyzed. PSQA result variations between the initial plans and their respective adapted plans were statistically investigated and compared with the variation in MU number. RESULTS: For the liver, limited deterioration in PSQA results was observed, and was within the limits of clinical tolerance (Initial = 98.2%, Adapted = 98.2%, p = 0.4503). For pancreas plans, only a few significant deteriorations extending beyond the limits of clinical tolerance were observed and were due to specific, complex anatomical configurations (Initial = 97.3%, Adapted = 96.5%, p = 0.0721). In parallel, we observed an influence of the increase in MU number on the PSQA results. CONCLUSION: We show that the dose delivery accuracy of adapted plans, in terms of PSQA results, is preserved in ART processes on the 0.35 T MR-linac. Respecting good practices, and minimizing the increase in MU number can help to preserve the accuracy of delivery of adapted plans as compared to their respective initial plans.

Evaluation of QA software system analysis for the static picket fence test.

Intensity modulation treatments are widely used in radiotherapy because of many known advantages. In this context, the picket fence test (PF) is a relevant test to check the Multileaf Collimator (MLC) performances. So this work compares and evaluates three analysis platforms for the PF used routinely by three different institutions. This study covers two linear accelerators (Linac) with two MLC types, a Millenium 120 MLC and Millenium 120 High Definition MLC respectively on a Varian Truebeam and Truebeam STx. Both linacs include an As 1200 portal imager (EPID). From a reference PF plan, MLC errors have been introduced to modify the slits in position or width (shifts from 0.1 to 0.5 mm on one or both banks). Then errors have been defined on the EPID to investigate detection system deviations (signal sensitivity and position variations). Finally, 110 DICOM-RT images have been generated and analyzed by each software system. All software systems have shown good performances to quantify the position errors, even though the leaf pair identifications can be wrong in some cases regarding the analysis method considered. The slit width measurement (not calculated by all software systems) has shown good sensitivity, but some quantification difficulties have been highlighted regardless of the analysis method used. Linked to the expected accuracy of the PF test, the imager variations have demonstrated considerable influence in the results. Differences in the results and the analysis methods have been pointed out for each software system. The results can be helpful to optimize the settings of each analysis software system depending on expectations and treatment modalities of each institution.

Novel platform for subcutaneous tumor irradiation in mice.

Preclinical development of cancer treatments including radiotherapy (RT) is now crucial to optimize all the treatment aspects for a better efficacy and to help clinicians to build new clinical trials based on robust results. More and more teams use preclinical irradiators to deliver radiotherapy in a comparable way to clinical treatments (image-based RT, arc therapy, stereotactic body RT…). In daily conditions, users usually need to develop easy to use techniques (for applicator technicians for example), allowing to treat many mice per day with a high level of reproducibility. Besides, the best compromise between a satisfying dose coverage to the tumor and nearby organs at risk sparing has to be ensured. We describe here new a home-made immobilization device to irradiate grafted tumors, as well as the different steps to develop the treatment planning and generate an easy procedure to routinely irradiate subcutaneous tumor model.

Salvage Involved-Field and Extended-Field Radiation Therapy in Positron Emission Tomography-Positive Nodal Recurrent Prostate Cancer: Outcomes and Patterns of Failure.

Purpose: The optimal salvage pelvic treatment for nodal recurrences in prostate cancer is not yet clearly defined. We aimed to compare outcomes of salvage involved-field radiation therapy (s-IFRT) and salvage extended-field radiation therapy (s-EFRT) for positron emission tomography/computed tomography-positive nodal-recurrent prostate cancer and to analyze patterns of progressions after salvage nodal radiation therapy. Methods and Materials: Patients with 18F-fluorocholine or 68Ga prostate-specific membrane antigen ligand positron emission tomography/computed tomography-positive nodal-recurrent prostate cancer and treated with s-IFRT or s-EFRT were retrospectively selected. Time to biochemical failure, time to palliative androgen deprivation therapy (ADT), and distant metastasis-free survival were analyzed. Results: Between 2009 and 2019, 86 patients were treated with salvage nodal radiation therapy: 38 with s-IFRT and 48 with s-EFRT. After a median follow-up of 41.9 months (5.4-122.1 months), 47 patients presented a further relapse: 31 after s-IFRT and 16 after s-EFRT, with only 1 in-field relapse. The median time to palliative ADT was 24.8 months (95% confidence interval [CI], 13.3-93.5 months) in the s-IFRT group and not yet reached (95% CI, 40.3 months to not yet reached) in the s-EFRT group (P = .010). The 3-year biochemical failure-free rate was 70.2% (95% CI, 51.5%-82.9%) with s-IFRT and 73.9% (95% CI, 55.4%-85.7%) with s-EFRT (P = .657). The 3-year distant metastasis-free survival was 74.1% (95% CI, 56.0%-85.7%) with s-IFRT and 82.0% (95% CI, 63.0%-91.8%) with s-EFRT (P = .338). Conclusions: s-EFRT and s-IFRT for positron emission tomography-positive nodal-recurrent prostate cancer provide excellent local control. Time to palliative ADT was longer following s-EFRT than following s-IFRT.

Deep learning application for abdominal organs segmentation on 0.35 T MR-Linac images.

Introduction: Linear accelerator (linac) incorporating a magnetic resonance (MR) imaging device providing enhanced soft tissue contrast is particularly suited for abdominal radiation therapy. In particular, accurate segmentation for abdominal tumors and organs at risk (OARs) required for the treatment planning is becoming possible. Currently, this segmentation is performed manually by radiation oncologists. This process is very time consuming and subject to inter and intra operator variabilities. In this work, deep learning based automatic segmentation solutions were investigated for abdominal OARs on 0.35 T MR-images. Methods: One hundred and twenty one sets of abdominal MR images and their corresponding ground truth segmentations were collected and used for this work. The OARs of interest included the liver, the kidneys, the spinal cord, the stomach and the duodenum. Several UNet based models have been trained in 2D (the Classical UNet, the ResAttention UNet, the EfficientNet UNet, and the nnUNet). The best model was then trained with a 3D strategy in order to investigate possible improvements. Geometrical metrics such as Dice Similarity Coefficient (DSC), Intersection over Union (IoU), Hausdorff Distance (HD) and analysis of the calculated volumes (thanks to Bland-Altman plot) were performed to evaluate the results. Results: The nnUNet trained in 3D mode achieved the best performance, with DSC scores for the liver, the kidneys, the spinal cord, the stomach, and the duodenum of 0.96 ± 0.01, 0.91 ± 0.02, 0.91 ± 0.01, 0.83 ± 0.10, and 0.69 ± 0.15, respectively. The matching IoU scores were 0.92 ± 0.01, 0.84 ± 0.04, 0.84 ± 0.02, 0.54 ± 0.16 and 0.72 ± 0.13. The corresponding HD scores were 13.0 ± 6.0 mm, 16.0 ± 6.6 mm, 3.3 ± 0.7 mm, 35.0 ± 33.0 mm, and 42.0 ± 24.0 mm. The analysis of the calculated volumes followed the same behavior. Discussion: Although the segmentation results for the duodenum were not optimal, these findings imply a potential clinical application of the 3D nnUNet model for the segmentation of abdominal OARs for images from 0.35 T MR-Linac.

Computed tomography synthesis from magnetic resonance imaging using cycle Generative Adversarial Networks with multicenter learning.

Background and Purpose: Addressing the need for accurate dose calculation in MRI-only radiotherapy, the generation of synthetic Computed Tomography (sCT) from MRI has emerged. Deep learning (DL) techniques, have shown promising results in achieving high sCT accuracies. However, existing sCT synthesis methods are often center-specific, posing a challenge to their generalizability. To overcome this limitation, recent studies have proposed approaches, such as multicenter training . Material and methods: The purpose of this work was to propose a multicenter sCT synthesis by DL, using a 2D cycle-GAN on 128 prostate cancer patients, from four different centers. Four cases were compared: monocenter cases, monocenter training and test on another center, multicenter trainings and a test on a center not included in the training and multicenter trainings with an included center in the test. Trainings were performed using 20 patients. sCT accuracy evaluation was performed using Mean Absolute Error, Mean Error and Peak-Signal-to-Noise-Ratio. Dose accuracy was assessed with gamma index and Dose Volume Histogram comparison. Results: Qualitative, quantitative and dose results show that the accuracy of sCTs for monocenter trainings and multicenter trainings using a seen center in the test did not differ significantly. However, when the test involved an unseen center, the sCT quality was inferior. Conclusions: The aim of this work was to propose generalizable multicenter training for MR-to-CT synthesis. It was shown that only a few data from one center included in the training cohort allows sCT accuracy equivalent to a monocenter study.

A deep learning model to generate synthetic CT for prostate MR-only radiotherapy dose planning: a multicenter study.

Introduction: For radiotherapy based solely on magnetic resonance imaging (MRI), generating synthetic computed tomography scans (sCT) from MRI is essential for dose calculation. The use of deep learning (DL) methods to generate sCT from MRI has shown encouraging results if the MRI images used for training the deep learning network and the MRI images for sCT generation come from the same MRI device. The objective of this study was to create and evaluate a generic DL model capable of generating sCTs from various MRI devices for prostate radiotherapy. Materials and methods: In total, 90 patients from three centers (30 CT-MR prostate pairs/center) underwent treatment using volumetric modulated arc therapy for prostate cancer (PCa) (60 Gy in 20 fractions). T2 MRI images were acquired in addition to computed tomography (CT) images for treatment planning. The DL model was a 2D supervised conditional generative adversarial network (Pix2Pix). Patient images underwent preprocessing steps, including nonrigid registration. Seven different supervised models were trained, incorporating patients from one, two, or three centers. Each model was trained on 24 CT-MR prostate pairs. A generic model was trained using patients from all three centers. To compare sCT and CT, the mean absolute error in Hounsfield units was calculated for the entire pelvis, prostate, bladder, rectum, and bones. For dose analysis, mean dose differences of D 99% for CTV, V 95% for PTV, Dmax for rectum and bladder, and 3D gamma analysis (local, 1%/1 mm) were calculated from CT and sCT. Furthermore, Wilcoxon tests were performed to compare the image and dose results obtained with the generic model to those with the other trained models. Results: Considering the image results for the entire pelvis, when the data used for the test comes from the same center as the data used for training, the results were not significantly different from the generic model. Absolute dose differences were less than 1 Gy for the CTV D 99% for every trained model and center. The gamma analysis results showed nonsignificant differences between the generic and monocentric models. Conclusion: The accuracy of sCT, in terms of image and dose, is equivalent to whether MRI images are generated using the generic model or the monocentric model. The generic model, using only eight MRI-CT pairs per center, offers robust sCT generation, facilitating PCa MRI-only radiotherapy for routine clinical use.

Characterisation of a split gradient coil design induced systemic imaging artefact on 0.35 T MR-linac systems.

Objective. The aim of this work was to highlight and characterize a systemic 'star-like' artefact inherent to the low field 0.35 T MRIdian MR-linac system, a magnetic resonance guided radiotherapy device. This artefact is induced by the original split gradients coils design. This design causes a surjection of the intensity gradient inZ(or head-feet) direction. This artefact appears on every sequence with phase encoding in the head-feet direction.Approach. Basic gradient echo sequence and clinical mandatory bSSFP sequence were used. Three setups using manufacturer provided QA phantoms were designed: two including the linearity control grid used for the characterisation and a third including two homogeneity control spheres dedicated to the artefact management in a more clinical like situation. The presence of the artefact was checked in four different MRidian sites. The tested parameters based on the literature were: phase encoding orientation, slab selectivity, excitation bandwidth (BWRF), acceleration factor (R) and phase/slab oversampling (PO/SO).Main results. The position of this artefact is constant and reproducible over the tested MRIdian sites. The typical singularity saturated dot or star is visible even with the 3D slab-selection enabled. A management is proposed by decreasing the BWRF, theRin head-feet direction and increasing the PO/SO. The oversampling can be optimized using a formula to anticipate the location of artefact in the field of view.Significance. The star-like artefact has been well characterised. A manageable solution comes at the cost of acquisition time. Observed in clinical cases, the artefact may degrade the images used for the RT planning and repositioning during the treatment unless corrected.

Validation of an electron Monte Carlo dose calculation algorithm in the presence of heterogeneities using EGSnrc and radiochromic film measurements.

The purpose of this study is to validate Eclipse's electron Monte Carlo algorithm (eMC) in heterogeneous phantoms using radiochromic films and EGSnrc as a reference Monte Carlo algorithm. Four heterogeneous phantoms are used in this study. Radiochromic films are inserted in these phantoms, including in heterogeneous media, and the measured relative dose distributions are compared to eMC calculations. Phantoms A, B, and C contain 1D heterogeneities, built with layers of lung- (phantom A) and bone- (phantoms B and C) equivalent materials sandwiched in Plastic Water. Phantom D is a thorax anthropomorphic phantom with 2D lung heterogeneities. Electron beams of 6, 9, 12 and 18 MeV from a Varian Clinac 2100 are delivered to these phantoms with a 10 × 10 cm2 applicator. Monte Carlo simulations with an independent algorithm (EGSnrc) are also used as a reference tool for two purposes: (1) as a second validation of the eMC dose calculations, and (2) to calculate the stopping power ratio between radiochromic films and bone medium, when dose is measured inside the heterogeneity. Percent depth dose (PDD) film measurements and eMC calculations agree within 2% or 3 mm for phantom A, and within 3% or 3 mm for phantoms B and C for almost all beam energies. One exception is observed with phantom B and the 6 MeV, where measured PDDs and those calculated with eMC differ by up to 4 mm. Gamma analysis of the measured and calculated 2D dose distributions in phantom D agree with criteria of 3%, 3mm for 9, 12, and 18 MeV beams, and criteria of 5%, 3 mm for the 6 MeV beam. Dose calculations in heterogeneous media with eMC agree within 3% or 3 mm with radiochromic film measurements. Six (6) MeV beams are not modeled as accurately as other beam energies. The eMC algorithm is suitable for clinical dose calculations involving lung and bone.

Complexity metrics for IMRT and VMAT plans: a review of current literature and applications.

Modulated radiotherapy with multileaf collimators is widely used to improve target conformity and normal tissue sparing. This introduced an additional degree of complexity, studied by multiple teams through different properties. Three categories of complexity metrics were considered in this review: fluence, deliverability and accuracy metrics. The first part of this review is dedicated to the inventory of these complexity metrics. Different applications of these metrics emerged. Influencing the optimizer by integrating complexity metrics into the cost function has been little explored and requires more investigations. In modern treatment planning system, it remains confined to MUs or treatment time limitation. A large majority of studies calculated metrics only for analysis, without plan modification. The main application was to streamline the patient specific quality assurance workload, investigating the capability of complexity metrics to predict patient specific quality assurance results. Additionally complexity metrics were used to analyze behaviour of TPS optimizer, compare TPS, operators and plan properties, and perform multicentre audit. Their potential was also explored in the context of adaptive radiotherapy and automation planning. The second part of the review gives an overview of these studies based on the complexity metrics.

Inferring postimplant dose distribution of salvage permanent prostate implant (PPI) after primary PPI on CT images.

PURPOSE: To evaluate the dose distribution of additional radioactive seeds implanted during salvage permanent prostate implant (sPPI) after a primary permanent prostate implant (pPPI). METHODS AND MATERIALS: Patients with localized prostate cancer were primarily implanted with iodine-125 seeds and had a dosimetric assessment based on day 30 postimplant CT (CT1). After an average of 6 years, these patients underwent sPPI followed by the same CT-based evaluation of dosimetry (CT2). Radioactive seeds on each CT were detected. The detected primary seeds on CT1 and CT2 were registered and then removed from CT2 referred as a modified CT2 (mCT2). Dosimetry evaluations (D90 and V100) of sPPI were performed with dedicated planning software on CT2 and mCT2. Indeed, prostate volume, D90, and V100 differences between CT2 and either CT1 or mCT2 were calculated, and values were expressed as mean (standard deviation). RESULTS: The mean prostate volume difference between sPPI and pPPI over the 6 patients was 9.85 (7.32) cm3. The average D90 and V100 assessed on CT2 were 486.5 Gy (58.9) and 100.0% (0.0), respectively, whereas it was 161.3 Gy (47.5) and 77.3% (25.2) on mCT2 (p = 0.031 each time). The average D90 the day of sPPI [145.4 Gy (11.2)] was not significantly different from that observed on mCT2 (p = 0.56). CONCLUSION: Postimplant D90 and V100 of sPPI after pPPI can be estimated on CT images after removing the primary seeds.