A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases.

INTRODUCTION: This study aims to apply a conditional Generative Adversarial Network (cGAN) to generate synthetic Computed Tomography (sCT) from 0.35 Tesla Magnetic Resonance (MR) images of the thorax. METHODS: Sixty patients treated for lung lesions were enrolled and divided into training (32), validation (8), internal (10,TA) and external (10,TB) test set. Image accuracy of generated sCT was evaluated computing the mean absolute (MAE) and mean error (ME) with respect the original CT. Three treatment plans were calculated for each patient considering MRI as reference image: original CT, sCT (pure sCT) and sCT with GTV density override (hybrid sCT) were used as Electron Density (ED) map. Dose accuracy was evaluated comparing treatment plans in terms of gamma analysis and Dose Volume Histogram (DVH) parameters. RESULTS: No significant difference was observed between the test sets for image and dose accuracy parameters. Considering the whole test cohort, a MAE of 54.9 ± 10.5 HU and a ME of 4.4 ± 7.4 HU was obtained. Mean gamma passing rates for 2%/2mm, and 3%/3mm tolerance criteria were 95.5 ± 5.9% and 98.2 ± 4.1% for pure sCT, 96.1 ± 5.1% and 98.5 ± 3.9% for hybrid sCT: the difference between the two approaches was significant (p = 0.01). As regards DVH analysis, differences in target parameters estimation were found to be within 5% using hybrid approach and 20% using pure sCT. CONCLUSION: The DL algorithm here presented can generate sCT images in the thorax with good image and dose accuracy, especially when the hybrid approach is used. The algorithm does not suffer from inter-scanner variability, making feasible the implementation of MR-only workflows for palliative treatments.

Clinical Validation of a Deep-Learning Segmentation Software in Head and Neck: An Early Analysis in a Developing Radiation Oncology Center.

BACKGROUND: Organs at risk (OARs) delineation is a crucial step of radiotherapy (RT) treatment planning workflow. Time-consuming and inter-observer variability are main issues in manual OAR delineation, mainly in the head and neck (H & N) district. Deep-learning based auto-segmentation is a promising strategy to improve OARs contouring in radiotherapy departments. A comparison of deep-learning-generated auto-contours (AC) with manual contours (MC) was performed by three expert radiation oncologists from a single center. METHODS: Planning computed tomography (CT) scans of patients undergoing RT treatments for H&N cancers were considered. CT scans were processed by Limbus Contour auto-segmentation software, a commercial deep-learning auto-segmentation based software to generate AC. H&N protocol was used to perform AC, with the structure set consisting of bilateral brachial plexus, brain, brainstem, bilateral cochlea, pharyngeal constrictors, eye globes, bilateral lens, mandible, optic chiasm, bilateral optic nerves, oral cavity, bilateral parotids, spinal cord, bilateral submandibular glands, lips and thyroid. Manual revision of OARs was performed according to international consensus guidelines. The AC and MC were compared using the Dice similarity coefficient (DSC) and 95% Hausdorff distance transform (DT). RESULTS: A total of 274 contours obtained by processing CT scans were included in the analysis. The highest values of DSC were obtained for the brain (DSC 1.00), left and right eye globes and the mandible (DSC 0.98). The structures with greater MC editing were optic chiasm, optic nerves and cochleae. CONCLUSIONS: In this preliminary analysis, deep-learning auto-segmentation seems to provide acceptable H&N OAR delineations. For less accurate organs, AC could be considered a starting point for review and manual adjustment. Our results suggest that AC could become a useful time-saving tool to optimize workload and resources in RT departments.

Dosimetric Impact of Inter-Fraction Variability in the Treatment of Breast Cancer: Towards New Criteria to Evaluate the Appropriateness of Online Adaptive Radiotherapy.

Purpose: As a discipline in its infancy, online adaptive RT (ART) needs new ontologies and ad hoc criteria to evaluate the appropriateness of its use in clinical practice. In this experience, we propose a predictive model able to quantify the dosimetric impact due to daily inter-fraction variability in a standard RT breast treatment, to identify in advance the treatment fractions where patients might benefit from an online ART approach. Methods: The study was focused on right breast cancer patients treated using standard adjuvant RT on an artificial intelligence (AI)-based linear accelerator. Patients were treated with daily CBCT images and without online adaptation, prescribing 40.05 Gy in 15 fractions, with four IMRT tangential beams. ESTRO guidelines were followed for the delineation on planning CT (pCT) of organs at risk and targets. For each patient, all the CBCT images were rigidly aligned to pCT: CTV and PTV were manually re-contoured and the original treatment plan was recalculated. Various radiological parameters were measured on CBCT images, to quantify inter-fraction variability present in each RT fraction after the couch shifts compensation. The variation of these parameters was correlated with the variation of V95% of PTV (ΔV95%) using the Wilcoxon Mann-Whitney test. Fractions where ΔV95% > 2% were considered as adverse events. A logistic regression model was calculated considering the most significant parameter, and its performance was quantified with a receiver operating characteristic (ROC) curve. Results: A total of 75 fractions on 5 patients were analyzed. The body variation between daily CBCT and pCT along the beam axis with the highest MU was identified as the best predictor (p = 0.002). The predictive model showed an area under ROC curve of 0.86 (95% CI, 0.82-0.99) with a sensitivity of 85.7% and a specificity of 83.8% at the best threshold, which was equal to 3 mm. Conclusion: A novel strategy to identify treatment fractions that may benefit online ART was proposed. After image alignment, the measure of body difference between daily CBCT and pCT can be considered as an indirect estimator of V95% PTV variation: a difference larger than 3 mm will result in a V95% decrease larger than 2%. A larger number of observations is needed to confirm the results of this hypothesis-generating study.

Five-Fraction Stereotactic Radiotherapy for Brain Metastases: A Single-Institution Experience on Different Dose Schedules.

INTRODUCTION: The most common intracranial neoplasm diagnosed in adults are brain metastases (BrM). The benefit in terms of clinical control and toxicity for stereotactic radiotherapy (SRT) has been investigated for patients with low load of BrM. AIM: The aim of this single-institution experience was to investigate the best dose schedule for five-fraction SRT (FFSRT). METHODS: A retrospective analysis of patients treated for BrM with different dose schedules of FFSRT was performed. Local control (LC) and clinical outcomes were evaluated with magnetic resonance imaging at 3, 6, and 9 months. Toxicity data were also collected. RESULTS: A total of 41 patients treated from November 2016 to September 2020 were enrolled in the analysis. Non-small cell lung cancer (51.2%) and breast cancer (24.3%) represented the most frequent primitive tumors. Treatment was performed on 5 consecutive days with prescribed dose ranging from 30 to 40 Gy, prescribed to the 95% isodose line that covered at least 98% of the gross tumor volume. Statistically significant differences (p = 0.025) with higher LC rates for dose schedules >6 Gy for fractions. Toxicity rates were not found to be higher than G1. CONCLUSION: The results of this retrospective analysis suggest that FFSRT for BrM seems to be safe and feasible. Our results also underline that a total dose lower than 30 Gy in 5 fractions should not be used due to the expected minor LC.

New fractionations in breast cancer: a dosimetric study of 3D-CRT versus VMAT.

INTRODUCTION: Adjuvant radiation therapy (RT) following primary surgery in women affected by early breast cancer (EBC) plays a central role in reducing local recurrences and overall mortality. The FAST-FORWARD trial recently demonstrated that 1-week hypofractionated adjuvant RT is not inferior to the standard schedule in terms of local relapse, cosmetic outcomes and toxicity. The aim of this in silico study was to evaluate the dosimetric aspects of a 1-week RT course, administered through volumetric modulated arc therapy (VMAT), compared with traditional three-dimensional conformal radiation therapy (3D-CRT) with tangential fields. METHODS: Patients affected by left-side EBC undergoing adjuvant RT were selected. ESTRO guidelines for the clinical target volume (CTV) delineation and FAST-FORWARD protocol for CTV to planning target volume (PTV) margin definition were followed. Total prescribed dose was 26 Gy in five fractions. The homogeneity index (HI) and the global conformity index (GCI) were taken into account for planning and dose distribution optimisation purposes. Both 3D-CRT tangential fields and VMAT plans were generated for each patient. RESULTS: The analysis included 21 patients. PTV coverage comparison between 3D-CRT and VMAT plans showed significant increases for GCI (P < 0.05) in VMAT technique; no statistically significant differences were observed regarding HI. For organs at risks (OAR), statistically significant increases were observed in terms of skin V103% (P < 0.002) and ipsilateral lung V30% (P < 0.05) with 3D-CRT and of heart V5% (P < 0.05) with VMAT technique. CONCLUSIONS: This in silico study showed that both 3D-CRT and VMAT are dosimetrically feasible techniques in the framework of 1-week hypofractionated treatments for left EBC.

Radiofrequency Thermoablation and Hypofractionated Radiotherapy Combined Treatment for Bone Metastases: A Retrospective Study.

INTRODUCTION: Bone metastases (BMs) are the common cause of cancer-related pain, as approximately 45% of cancer patients suffer from bone pain (BP). Radiotherapy (RT) is well established as BP treatment strategy; also, other approaches have been shown to be effective in this setting. Radiofrequency thermoablation (RFA) in a combined strategy with RT appears to be feasible and effective in the treatment of metastatic BP ensuring a better quality of life. Aim of this retrospective study was to describe a case series of patients with painful osteolytic lesions at risk of fracture treated with the RFA-RT combined approach, analyzing local control and pain control as outcomes. METHODS: Data of all patients with BM treated with combined approach in our center from April 2016 to June 2020 were retrospectively analyzed. Patients underwent RFA followed by cementoplasty on the same day and RT in a second phase. RT dose ranged between 30 and 37.5 Gy in 5/10 fractions. BP was evaluated according to the numeric rating scale (NRS), at the beginning of treatment and at 1, 2, 3, 6, 9, and 12 months from the end of combined treatment. RESULTS: A total of 27 patients were treated from April 2016 to June 2020 with RFA-RT combined approach. The large majority of patients underwent stereotactic body radiotherapy (SBRT) (23/27). All patients experienced an NRS value decrease >2 at 1 month and between the first and second months. NRS mean value reached 0 at 3, 6, 9, and 12 months' evaluations. DISCUSSION/CONCLUSION: The results of this retrospective analysis of patients treated with RFA-RT combined approach for BP support its safety and efficacy in terms of pain reduction. SBRT role in this combined approach has to be investigated in randomized trials.

Hypofractionated Radiotherapy in Head and Neck Cancer Elderly Patients: A Feasibility and Safety Systematic Review for the Clinician.

OBJECTIVE: Radiotherapy (RT) in the head and neck (H&N) site are undoubtedly the most challenging treatments for patients. Older and frail patients are not always able to tolerate it, and there are still no clear guidelines on the type of treatments to be preferred for them. The recommendations for Risk-Adapted H&N Cancer Radiation Therapy during the coronavirus disease 2019 (COVID-19) pandemic provided by the ASTRO-ESTRO consensus statement achieved a strong agreement about hypofractionated RT (HFRT). A systematic literature review was conducted in order to evaluate the feasibility and safety of HFRT for older patients affected by H&N malignancies. MATERIALS AND METHODS: A systematic database search was performed on PubMed and Embase according to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Original studies, case series, and case reports describing the use of HFRT (with at least 2.2 Gy fractions) in patients with mean age ≥65 years were included. The analysis was based on the type of study, number of patients, mean age, tumor site, histology, performance status (PS), RT details, concomitant chemotherapy (CT), and described clinical outcomes. All the reported doses have been calculated in equivalent dose in 2 Gy fractions (EQD2) and biologically effective dose (BED) using α/ß = 10 Gy or α/ß = 12 Gy. RESULTS: We selected 17 papers that met the inclusion criteria and divided them in 4 categories: 6 articles analyze HFRT performed twice daily in repeated cycles, 3 once a day in repeated cycles, 4 in alternative days, and the last 4 in consecutive days. CONCLUSION: HFRT seems to be a good treatment with an acceptable prolonged disease control. In older patients fit for radical treatments, a 55 Gy in 20 fractions regimen can be proposed as a valid alternative to the standard fractionated RT, but there are a multitude of hypofractionated regimens, ranging from single fraction, quad shot, and 1-, 2-, 3-, 4-, and 5-week schedules that all may be appropriate. The correct regimen for a patient depends on many factors, and it represents the result of a more specific and complex decision.

Evaluation of a generalized knowledge-based planning performance for VMAT irradiation of breast and locoregional lymph nodes-Internal mammary and/or supraclavicular regions.

PURPOSE: To evaluate the performance of eleven Knowledge-Based (KB) models for planning optimization (RapidPlantm (RP), Varian) of Volumetric Modulated Arc Therapy (VMAT) applied to whole breast comprehensive of nodal stations, internal mammary and/or supraclavicular regions. METHODS AND MATERIALS: Six RP models have been generated and trained based on 120 VMAT plans data set with different criteria. Two extra-structures were delineated: a PTV for the optimization and a ring structure. Five more models, twins of the previous models, have been created without the need of these structures. RESULTS: All models were successfully validated on an independent cohort of 40 patients, 30 from the same institute that provided the training patients and 10 from an additional institute, with the resulting plans being of equal or better quality compared with the clinical plans. The internal validation shows that the models reduce the heart maximum dose of about 2 Gy, the mean dose of about 1 Gy and the V20Gy of 1.5 Gy on average. Model R and L together with model B without optimization structures ensured the best outcomes in the 20% of the values compared to other models. The external validation observed an average improvement of at least 16% for the V5Gy of lungs in RP plans. The mean heart dose and for the V20Gy for lung IPSI were almost halved. The models reduce the maximum dose for the spinal canal of more than 2 Gy on average. CONCLUSIONS: All KB models allow a homogeneous plan quality and some dosimetric gains, as we saw in both internal and external validation. Sub-KB models, developed by splitting right and left breast cases or including only whole breast with locoregional lymph nodes, have shown good performances, comparable but slightly worse than the general model. Finally, models generated without the optimization structures, performed better than the original ones.

Characterization of an inorganic scintillator for small-field dosimetry in MR-guided radiotherapy.

INTRODUCTION: Aim of this study is to dosimetrically characterize a new inorganic scintillator designed for magnetic resonance-guided radiotherapy (MRgRT) in the presence of 0.35 tesla magnetic field (B). METHODS: The detector was characterized in terms of signal to noise ratio (SNR), reproducibility, dose linearity, angular response, and dependence by energy, field size, and B orientation using a 6 MV magnetic resonance (MR)-Linac and a water tank. Field size dependence was investigated by measuring the output factor (OF) at 1.5 cm. The results were compared with those measured using other detectors (ion chamber and synthetic diamond) and those calculated using a Monte Carlo (MC) algorithm. Energy dependence was investigated by acquiring a percentage depth dose (PDD) curve at two field sizes (3.32 × 3.32 and 9.96 × 9.96 cm2 ) and repeating the OF measurements at 5 and 10 cm depths. RESULTS: The mean SNR was 116.3 ± 0.6. Detector repeatability was within 1%, angular dependence was <2% and its response variation based on the orientation with respect to the B lines was <1%. The detector has a temporal resolution of 10 Hz and it showed a linear response (R2  = 1) in the dose range investigated. All the OF values measured at 1.5 cm depth using the scintillator are in accordance within 1% with those measured with other detectors and are calculated using the MC algorithm. PDD values are in accordance with MC algorithm only for 3.32 × 3.32 cm2 field. Numerical models can be applied to compensate for energy dependence in case of larger fields. CONCLUSION: The inorganic scintillator in the present form can represent a valuable detector for small-field dosimetry and periodic quality controls at MR-Linacs such as dose stability, OFs, and dose linearity. In particular, the detector can be effectively used for small-field dosimetry at 1.5 cm depth and for PDD measurements if the field dimension of 3.32 × 3.32 cm2 is not exceeded.

Computed Tomography to Cone Beam Computed Tomography Deformable Image Registration for Contour Propagation Using Head and Neck, Patient-Based Computational Phantoms: A Multicenter Study.

PURPOSE: To investigate the performance of various algorithms for deformable image registration (DIR) for propagating regions of interest (ROIs) using multiple commercial platforms, from computed tomography to cone beam computed tomography (CBCT) and megavoltage computed tomography. METHODS AND MATERIALS: Fourteen institutions participated in the study using 5 commercial platforms: RayStation (RaySearch Laboratories, Stockholm, Sweden), MIM (Cleveland, OH), VelocityAI and SmartAdapt (Varian Medical Systems, Palo Alto, CA), and ABAS (Elekta AB, Stockholm, Sweden). Algorithms were tested on synthetic images generated with the ImSimQA (Oncology Systems Limited, Shrewsbury, UK) package by applying 2 specific deformation vector fields (DVF) to real head and neck patient datasets. On-board images from 3 systems were used: megavoltage computed tomography from Tomotherapy and 2 kinds of CBCT from a clinical linear accelerator. Image quality of the system was evaluated. The algorithms' accuracy was assessed by comparing the DIR-mapped ROIs returned by each center with those of the reference, using the Dice similarity coefficient and mean distance to conformity metrics. Statistical inference on the validation results was carried out to identify the prognostic factors of DIR performance. RESULTS: Analyzing 840 DIR-mapped ROIs returned by the centers, it was demonstrated that DVF intensity and image quality were significant prognostic factors of DIR performance. The accuracy of the propagated contours was generally high, and acceptable DIR performance can be obtained with lower-dose CBCT image protocols. CONCLUSIONS: The performance of the systems proved to be image quality specific, depending on the DVF type and only partially on the platforms. All systems proved to be robust against image artifacts and noise, except the demon-based software.

Evaluation of a simplified optimizer for MR-guided adaptive RT in case of pancreatic cancer.

PURPOSE: Magnetic resonance-guided adaptive radiotherapy (MRgART) is considered a promising resource for pancreatic cancer, as it allows to online modify the dose distribution according to daily anatomy. This study aims to compare the dosimetric performance of a simplified optimizer implemented on a MR-Linac treatment planning system (TPS) with those obtained using an advanced optimizer implemented on a conventional Linac. METHODS: Twenty patients affected by locally advanced pancreatic cancer (LAPC) were considered. Gross tumor volume (GTV) and surrounding organ at risks (OARs) were contoured on the average 4DCT scan. Planning target volume was generated from GTV by adding an isotropic 3 mm margin and excluding overlap areas with OARs. Treatment plans were generated by using the simple optimizer for the MR-Linac in intensity-modulated radiation therapy (IMRT) and the advanced optimizer for conventional Linac in IMRT and volumetric modulated arc therapy (VMAT) technique. Prescription dose was 40 Gy in five fractions. The dosimetric comparison was performed on target coverage, dosimetric indicators, and low dose diffusion. RESULTS: The simplified optimizer of MR-Linac generated clinically acceptable plans in 80% and optimal plans in 55% of cases. The number of clinically acceptable plans obtained using the advanced optimizer of the conventional Linac with IMRT was the same of MR-Linac, but the percentage of optimal plans was higher (65%). Using the VMAT technique, it is possible to obtain clinically acceptable plan in 95% and optimal plans in 90% of cases. The advanced optimizer combined with VMAT technique ensures higher target dose homogeneity and minor diffusion of low doses, but its actual optimization time is not suitable for MRgART. CONCLUSION: Simplified optimization solutions implemented in the MR-Linac TPS allows to elaborate in most of cases treatment plans dosimetrically comparable with those obtained by using an advanced optimizer. A superior treatment plan quality is possible using the VMAT technique that could represent a breakthrough for the MRgART if the modern advancements will lead to shorter optimization times.