Impact of bias field correction on 0.35 T pelvic MR images: evaluation on generative adversarial network-based OARs' auto-segmentation and visual grading assessment.

Purpose: Magnetic resonance imaging (MRI)-guided radiotherapy enables adaptive treatment plans based on daily anatomical changes and accurate organ visualization. However, the bias field artifact can compromise image quality, affecting diagnostic accuracy and quantitative analyses. This study aims to assess the impact of bias field correction on 0.35 T pelvis MRIs by evaluating clinical anatomy visualization and generative adversarial network (GAN) auto-segmentation performance. Materials and methods: 3D simulation MRIs from 60 prostate cancer patients treated on MR-Linac (0.35 T) were collected and preprocessed with the N4ITK algorithm for bias field correction. A 3D GAN architecture was trained, validated, and tested on 40, 10, and 10 patients, respectively, to auto-segment the organs at risk (OARs) rectum and bladder. The GAN was trained and evaluated either with the original or the bias-corrected MRIs. The Dice similarity coefficient (DSC) and 95th percentile Hausdorff distance (HD95th) were computed for the segmented volumes of each patient. The Wilcoxon signed-rank test assessed the statistical difference of the metrics within OARs, both with and without bias field correction. Five radiation oncologists blindly scored 22 randomly chosen patients in terms of overall image quality and visibility of boundaries (prostate, rectum, bladder, seminal vesicles) of the original and bias-corrected MRIs. Bennett's S score and Fleiss' kappa were used to assess the pairwise interrater agreement and the interrater agreement among all the observers, respectively. Results: In the test set, the GAN trained and evaluated on original and bias-corrected MRIs showed DSC/HD95th of 0.92/5.63 mm and 0.92/5.91 mm for the bladder and 0.84/10.61 mm and 0.83/9.71 mm for the rectum. No statistical differences in the distribution of the evaluation metrics were found neither for the bladder (DSC: p = 0.07; HD95th: p = 0.35) nor for the rectum (DSC: p = 0.32; HD95th: p = 0.63). From the clinical visual grading assessment, the bias-corrected MRI resulted mostly in either no change or an improvement of the image quality and visualization of the organs' boundaries compared with the original MRI. Conclusion: The bias field correction did not improve the anatomy visualization from a clinical point of view and the OARs' auto-segmentation outputs generated by the GAN.

Spine Instability Neoplastic Score (SINS) as a Predictive Tool in Conventional Radiotherapy: A Narrative Review.

AIMS: This narrative review seeks to identify the SINS score application in the radiation oncology field. METHODS: This literature review was performed searching papers on MEDLINE published from January 2010 to August 2022. RESULTS: In terms of vertebral painful lesions and RT symptomatic responses, the SINS score could be an interesting aid in order to choose the right therapeutic approach. Lesions with higher level of instability, and therefore higher SINS score, could did not find any significant benefit from radiation therapy which is more effective on the tumor-related pain component. For SINS as a predictor of adverse event after RT or its changes after RT, we obtained contrasting results. CONCLUSIONS: The reported few experiences showed ambiguous conclusions. Further prospective studies are needed.

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.

CT angiography-based radiomics as a tool for carotid plaque characterization: a pilot study.

PURPOSES: Radiomics is a quantitative method able to analyze a high-throughput extraction of minable imaging features. Herein, we aim to develop a CT angiography-based radiomics analysis and machine learning model for carotid plaques to discriminate vulnerable from no vulnerable plaques. MATERIALS AND METHODS: Thirty consecutive patients with carotid atherosclerosis were enrolled in this pilot study. At surgery, a binary classification of plaques was adopted ("hard" vs "soft"). Feature extraction was performed using the R software package Moddicom. Pairwise feature interdependencies were evaluated using the Spearman rank correlation coefficient. A univariate analysis was performed to assess the association between each feature and the plaque classification and chose top-ranked features. The feature predictive value was investigated using binary logistic regression. A stepwise backward elimination procedure was performed to minimize the Akaike information criterion (AIC). The final significant features were used to build the models for binary classification of carotid plaques, including logistic regression (LR), support vector machine (SVM), and classification and regression tree analysis (CART). All models were cross-validated using fivefold cross validation. Class-specific accuracy, precision, recall and F-measure evaluation metrics were used to quantify classifier output quality. RESULTS: A total of 230 radiomics features were extracted from each plaque. Pairwise Spearman correlation between features reported a high level of correlations, with more than 80% correlating with at least one other feature at |ρ|> 0.8. After a stepwise backward elimination procedure, the entropy and volume features were found to be the most significantly associated with the two plaque groups (p < 0.001), with AUCs of 0.92 and 0.96, respectively. The best performance was registered by the SVM classifier with the RBF kernel, with accuracy, precision, recall and F-score equal to 86.7, 92.9, 81.3 and 86.7%, respectively. The CART classification tree model for the entropy and volume features model achieved 86.7% well-classified plaques and an AUC of 0.987. CONCLUSION: This pilot study highlighted the potential of CTA-based radiomics and machine learning to discriminate plaque composition. This new approach has the potential to provide a reliable method to improve risk stratification in patients with carotid atherosclerosis.

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.

Personalized automation of treatment planning in head-neck cancer: A step forward for quality in radiation therapy?

PURPOSE: To perform a comprehensive dosimetric and clinical evaluation of the new Pinnacle Personalized automated planning system for complex head-and-neck treatments. METHODS: Fifteen consecutive head-neck patients were enrolled. Radiotherapy was prescribed using VMAT with simultaneous integrated boost strategy. Personalized planning integrates the Feasibility engine able to supply an "a priori" DVH prediction of the achievability of planning goals. Comparison between clinically accepted manually-generated (MP) and automated (AP) plans was performed using dose-volume histograms and a blinded clinical evaluation by two radiation oncologists. Planning time between MP and AP was compared. Dose accuracy was validated using the PTW Octavius-4D phantom together with the 1500 2D-array. RESULTS: For similar targets coverage, AP plans reported less irradiation of healthy tissue, with significant dose reduction for spinal cord, brainstem and parotids. On average, the mean dose to parotids and maximal doses to spinal cord and brainstem were reduced by 13-15% (p < 0.001), 9% (p < 0.001) and 16% (p < 0.001), respectively. The integral dose was reduced by 16% (p < 0.001). The dose conformity for the three PTVs was significantly higher with AP plans (p < 0.001). The two oncologists chose AP plans in more than 80% of cases. Overall planning times were reduced to <30 min for automated optimization. All AP plans passed the 3%/2 mm γ-analysis by more than 95%. CONCLUSION: Complex head-neck plans created using Personalized automated engine provided an overall increase of plan quality, in terms of dose conformity and sparing of normal tissues. The Feasibility module allowed OARs dose sparing well beyond the clinical objectives.

Systematic review of stereotactic body radiotherapy for nodal metastases.

The aim of this analysis was to assess the efficacy of stereotactic body radiotherapy (SBRT) in terms of local control (LC) and progression-free survival (PFS) in patients with lymph node metastases (NMs) from solid tumors. A systematic literature search from the earliest date to July 25th, 2019 was performed following PRISMA guidelines. Papers reporting LC and/or PFS of NMs using SBRT (< 10 fractions) were selected. The clinical outcomes rates were pooled by means of a random or fixed-effect model. Twenty-nine studies were eligible (969 patients: 938 (LC) and 698 (PFS)). LC and PFS results were reported in 28 and 18 papers, respectively. Heterogeneity was observed in terms of patient and treatment characteristics. Pooled 2-year LC reported in 11 studies was 79.3% (95%CI, 72.8%-85.7%) with substantial heterogeneity between studies (Q2 test: p = 0.0083; I2 = 57.9%), while pooled 2-year PFS reported in 8 studies was 35.9% (95%CI, 22.1%-49.7%) with very high heterogeneity between studies (Q2 test: p < 0.0001; I2 = 86.1%). Grade ≥ 3 and Grade 5 toxicity rates were 2.0% and 0.2%, respectively. SBRT of NMs seems to be safe and effective in terms of LC. However, due to the marked heterogeneity of the included series, prospective studies are required.

Advanced head and neck cancer in older adults: Results of a short course accelerated radiotherapy trial.

OBJECTIVES: To assess the feasibility and safety of a repeated SHort course Accelerated RadiatiON therapy (SHARON) regimen in the palliative setting of Head and Neck (H&N) cancer in older adults. MATERIAL AND METHODS: Patients with histological confirmed H&N cancers, age ≥ 80 years, expected survival >3 months, and Eastern Cooperative Oncology Group (ECOG) performance status of ≤3 were enrolled. Patients were treated in cohorts of six patients: a total dose of 20 Gy was delivered in 2 consecutive days with a twice-daily fractionation (5 Gy per fraction) and at least 8-h interval. If no Grade 3 toxicity was registered, a second enrollment started with another cohort of six patients to whom were administered two cycles (total dose of 40 Gy). The primary endpoint was to evaluate the feasibility of the two cycles of treatment. Secondary endpoints were evaluation of symptoms control rate, symptoms-free survival (SFS), and Quality of Life (QoL) scores. RESULTS: Seventeen consecutive patients (median age: 85 years) were treated. Nine patients were treated with one cycle and 8 patients with two cycles. No G3 toxicity was reported in either cohort. With a median follow-up time of 4 months, 3-month SFS in the first and second cohorts was 83.3%, and 87.5%, respectively. The overall palliative response rate was 88%. Among 13 patients reporting pain, 8 (61.5%) showed an improvement or resolution of their pain. CONCLUSION: Repeated short course accelerated radiotherapy in a palliative setting of H&N cancers is safe and well-tolerated in older adults.

Stereobody radiotherapy for nodal recurrences in oligometastatic patients: a pooled analysis from two phase I clinical trials.

Stereotactic body radiotherapy (SBRT) has been shown to achieve high local control rates in limited metastatic burden of disease. Few papers reported on the efficacy of SBRT in nodal oligometastases. The primary aim of the present paper was to analyze the treatment outcome in this setting. Data from DESTROY-1 and SRS-DESTROY-2 phase I clinical trials were reviewed and analyzed. These trials were based on a 5 fractions and a single fraction regimens, respectively. End-points of this analysis were toxicity rates, overall response rate (ORR), and local control (LC). Patients treated between December 2003 and January 2018, with any metastatic site, and primary tumor type and histology were included. One hundred-eighty-one patients (M/F: 93/88; median age: 67, range 37-88) treated with SBRT on 253 nodal lesions were analyzed. Initially, the used technique was 3D-CRT (20.9%), while subsequently treatments were delivered by VMAT (79.1%). The total dose to the PTV ranged between 12 Gy/single fraction to 50 Gy/5 fractions. With a median follow-up of 21 months (2-124), no grade 3 acute or late toxicity was recorded. ORR based on functional imaging was 92.5% with a complete response rate of 76%. Two- and three-year actuarial LC were 81.6% and 76.0%, respectively. Our large pooled analysis confirms the efficacy and safety of SBRT/SRS in patients with nodal metastases and identifies clinical and treatment variables able to predict complete response and local control rate.

Post-Operative Accelerated-Hypofractionated Chemoradiation With Volumetric Modulated Arc Therapy and Simultaneous Integrated Boost in Glioblastoma: A Phase I Study (ISIDE-BT-2).

BACKGROUND: Glioblastoma Multiforme (GBM) is the most common primary brain cancer and one of the most lethal tumors. Theoretically, modern radiotherapy (RT) techniques allow dose-escalation due to the reduced irradiation of healthy tissues. This study aimed to define the adjuvant maximum tolerated dose (MTD) using volumetric modulated arc RT with simultaneous integrated boost (VMAT-SIB) plus standard dose temozolomide (TMZ) in GBM. METHODS: A Phase I clinical trial was performed in operated GBM patients using VMAT-SIB technique with progressively increased total dose. RT was delivered in 25 fractions (5 weeks) to two planning target volumes (PTVs) defined by adding a 5-mm margin to the clinical target volumes (CTVs). The CTV1 was the tumor bed plus the MRI enhancing residual lesion with 10-mm margin. The CTV2 was the CTV1 plus 20-mm margin. Only PTV1 dose was escalated (planned dose levels: 72.5, 75, 77.5, 80, 82.5, 85 Gy), while PTV2 dose remained unchanged (45 Gy/1.8 Gy). Concurrent and sequential TMZ was prescribed according to the EORTC/NCIC protocol. Dose-limiting toxicities (DLTs) were defined as any G ≥ 3 non-hematological acute toxicity or any G ≥ 4 acute hematological toxicities (RTOG scale) or any G ≥ 2 late toxicities (RTOG-EORTC scale). RESULTS: Thirty-seven patients (M/F: 21/16; median age: 59 years; median follow-up: 12 months) were enrolled and treated as follows: 6 patients (72.5 Gy), 10 patients (75 Gy), 10 patients (77.5 Gy), 9 patients (80 Gy), 2 patients (82.5 Gy), and 0 patients (85 Gy). Eleven patients (29.7%) had G1-2 acute neurological toxicity, while 3 patients (8.1%) showed G ≥ 3 acute neurological toxicities at 77.5 Gy, 80 Gy, and 82.5 Gy levels, respectively. Since two DLTs (G3 neurological: 1 patient and G5 hematological toxicity: 1 patient) were observed at 82.5 Gy level, the trial was closed and the 80 Gy dose-level was defined as the MTD. Two asymptomatic histologically proven radionecrosis were recorded. CONCLUSIONS: According to the results of this Phase I trial, 80 Gy in 25 fractions accelerated hypofractionated RT is the MTD using VMAT-SIB plus standard dose TMZ in resected GBM.

MR-guided radiotherapy in rectal cancer: First clinical experience of an innovative technology.

•This study represents one of the first reports of online MRgRT.•Integrated Low-field MR provides better anatomical visualization than CBCT or MVCT.•Better visualization of the target can help to reduce the margins from CTV to PTV.•MRgRT appears a feasible option in rectal cancer treatment offering potential benefits.•MRgRT represents a promising technology for rectal cancer management.

Adjuvant chemoradiation in pancreatic cancer: impact of radiotherapy dose on survival.

BACKGROUND: To evaluate the impact of radiation dose on overall survival (OS) in patients treated with adjuvant chemoradiation (CRT) for pancreatic ductal adenocarcinoma (PDAC). METHODS: A multicenter retrospective analysis on 514 patients with PDAC (T1-4; N0-1; M0) treated with surgical resection with macroscopically negative margins (R0-1) followed by adjuvant CRT was performed. Patients were stratified into 4 groups based on radiotherapy doses (group 1: < 45 Gy, group 2: ≥ 45 and < 50 Gy, group 3: ≥ 50 and < 55 Gy, group 4: ≥ 55 Gy). Adjuvant chemotherapy was prescribed to 141 patients. Survival functions were plotted using the Kaplan-Meier method and compared through the log-rank test. RESULTS: Median follow-up was 35 months (range: 3-120 months). At univariate analysis, a worse OS was recorded in patients with higher preoperative Ca 19.9 levels (≥ 90 U/ml; p < 0.001), higher tumor grade (G3-4, p = 0.004), R1 resection (p = 0.004), higher pT stage (pT3-4, p = 0.002) and positive nodes (p < 0.001). Furthermore, patients receiving increasing doses of CRT showed a significantly improved OS. In groups 1, 2, 3, and 4, median OS was 13.0 months, 21.0 months, 22.0 months, and 28.0 months, respectively (p = 0.004). The significant impact of higher dose was confirmed by multivariate analysis. CONCLUSIONS: Increasing doses of CRT seems to favorably impact on OS in adjuvant setting. The conflicting results of randomized trials on adjuvant CRT in PDAC could be due to < 45 Gy dose generally used.