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.

Radiomics-enhanced early regression index for predicting treatment response in rectal cancer: a multi-institutional 0.35 T MRI-guided radiotherapy study.

PURPOSE: The accurate prediction of treatment response in locally advanced rectal cancer (LARC) patients undergoing MRI-guided radiotherapy (MRIgRT) is essential for optimising treatment strategies. This multi-institutional study aimed to investigate the potential of radiomics in enhancing the predictive power of a known radiobiological parameter (Early Regression Index, ERITCP) to evaluate treatment response in LARC patients treated with MRIgRT. METHODS: Patients from three international sites were included and divided into training and validation sets. 0.35 T T2*/T1-weighted MR images were acquired during simulation and at each treatment fraction. The biologically effective dose (BED) conversion was used to account for different radiotherapy schemes: gross tumour volume was delineated on the MR images corresponding to specific BED levels and radiomic features were then extracted. Multiple logistic regression models were calculated, combining ERITCP with other radiomic features. The predictive performance of the different models was evaluated on both training and validation sets by calculating the receiver operating characteristic (ROC) curves. RESULTS: A total of 91 patients was enrolled: 58 were used as training, 33 as validation. Overall, pCR was observed in 25 cases. The model showing the highest performance was obtained combining ERITCP at BED = 26 Gy with a radiomic feature (10th percentile of grey level histogram, 10GLH) calculated at BED = 40 Gy. The area under ROC curve (AUC) of this combined model was 0.98 for training set and 0.92 for validation set, significantly higher (p = 0.04) than the AUC value obtained using ERITCP alone (0.94 in training and 0.89 in validation set). CONCLUSION: The integration of the radiomic analysis with ERITCP improves the pCR prediction in LARC patients, offering more precise predictive models to further personalise 0.35 T MRIgRT treatments of LARC patients.

Magnetic resonance guided SBRT reirradiation in locally recurrent prostate cancer: a multicentric retrospective analysis.

AIMS: Reirradiation of prostate cancer (PC) local recurrences represents an emerging challenge for current radiotherapy. In this context, stereotactic body radiation therapy (SBRT) allows the delivery of high doses, with curative intent. Magnetic Resonance guided Radiation Therapy (MRgRT) has shown promising results in terms of safety, feasibility and efficacy of delivering SBRT thanks to the enhanced soft tissue contrast and the online adaptive workflow. This multicentric retrospective analysis evaluates the feasibility and efficacy of PC reirradiation, using a 0.35 T hybrid MR delivery unit. METHODS: Patients affected by local recurrences of PC and treated in five institutions between 2019 and 2022 were retrospectively collected. All patients had undergone previous Radiation Therapy (RT) in definitive or adjuvant setting. Re-treatment MRgSBRT was delivered with a total dose ranging from 25 to 40 Gy in 5 fractions. Toxicity according to CTCAE v 5.0 and treatment response were assessed at the end of the treatment and at follow-up. RESULTS: Eighteen patients were included in this analysis. All patients had previously undergone external beam radiation therapy (EBRT) up to a total dose of 59.36 to 80 Gy. Median cumulative biologically effective dose (BED) of SBRT re-treatment was 213,3 Gy (103,1-560), considering an α/ß of 1.5. Complete response was achieved in 4 patients (22.2%). No grade ≥ 2 acute genitourinary (GU) toxicity events were recorded, while gastrointestinal (GI) acute toxicity events occurred in 4 patients (22.2%). CONCLUSION: The low rates of acute toxicity of this experience encourages considering MRgSBRT a feasibile therapeutic approach for the treatment of clinically relapsed PC. Accurate gating of target volumes, the online adaptive planning workflow and the high definition of MRI treatment images allow delivering high doses to the PTV while efficiently sparing organs at risk (OARs).

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.

Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images.

BACKGROUND AND PURPOSE: Early Regression Index (ERITCP) is an image-based parameter based on tumor control probability modelling, that reported interesting results in predicting pathological complete response (pCR) after pre-operative chemoradiotherapy (CRT) in rectal cancer. This study aims to evaluate this parameter for Locally Advanced Cervical Cancer (LACC), considering not only T2-weighted but also diffusion-weighted (DW) Magnetic Resonance (MR) images, comparing it with other image-based parameters such as tumor volumes and apparent coefficient diffusion (ADC). MATERIALS AND METHODS: A total of 88 patients affected by LACC (FIGO IB2-IVA) and treated with CRT were enrolled. An MRI protocol consisting in two acquisitions (T2-w and DWI) in two times (before treatment and at mid-therapy) was applied. Gross Tumor Volume (GTV) was delineated and ERITCP was calculated for both imaging modalities. Surgery was performed for each patient after nCRT: pCR was considered in case of absence of any residual tumor cells. The predictive performance of ERITCP, GTV volumes (calculated on T2-w and DW MR images) and ADC parameters were evaluated in terms of area (AUC) under the Receiver Operating Characteristic (ROC) curve considering pCR and two-years survival parameters as clinical outcomes. RESULTS: ERITCP and GTV volumes calculated on DW MR images (ERIDWI and Vmid_DWI) significantly predict pCR (AUC = 0.77 and 0.75 respectively) with results superior to those observed considering T2-w MR images or ADC parameters. Significance was also reported in the prediction of 2-years local control and disease free-survival. CONCLUSION: This study identified ERITCP and Vmid as good predictor of pCR in case of LACC, especially if calculated considering DWI. Using these indicators, it is possible to early identify not responders and modifying the treatment, accordingly.

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.

Radiation therapy for prostate cancer: What's the best in 2021.

Radiotherapy is highly involved in the management of prostate cancer. Its features and potential applications experienced a radical evolution over last decades, as they are associated to the continuous evolution of available technology and current oncological innovations. Some application of radiotherapy like brachytherapy have been recently enriched by innovative features and multidisciplinary dedications. In this report we aim to put some questions regarding the following issues regarding multiple aspects of modern application of radiation oncology: the current application of radiation oncology; the modern role of stereotactic body radiotherapy (SBRT) for both the management of primary lesions and for lymph-nodal recurrence; the management of the oligometastatic presentations; the role of brachytherapy; the aid played by the application of the organ at risk spacer (spacer OAR), fiducial markers, electromagnetic tracking systems and on-line Magnetic Resonance guided radiotherapy (MRgRT), and the role of the new opportunity represented by radiomic analysis.

Fractal-Based Radiomic Approach to Tailor the Chemotherapy Treatment in Rectal Cancer: A Generating Hypothesis Study.

INTRODUCTION: The aim of this study was to create a radiomic model able to calculate the probability of 5-year disease-free survival (5yDFS) when oxaliplatin (OXA) is or not administered in patients with locally advanced rectal cancer (LARC) and treated with neoadjuvant chemoradiotherapy (nCRT), allowing physicians to choose the best chemotherapy (CT) regimen. METHODS: LARC patients with cT3-4 cN0 or cT1-4 cN1-2 were treated according to an nCRT protocol that included concomitant CT schedules with or without OXA and radiotherapy dose of 55 Gy in 25 fractions. Radiomic analysis was performed on the T2-weighted (T2-w) MR images acquired during the initial tumor staging. Statistical analysis was performed separately for the cohort of patients treated with and without OXA. The ability of every single radiomic feature in predicting 5yDFS as a univariate analysis was assessed using the Wilcoxon-Mann-Whitney (WMW) test or t-test. Two logistic models (one for each cohort) were calculated, and their performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC). RESULTS: A total of 176 image features belonging to four families (morphological, statistical, textural, and fractal) were calculated for each patient. At the univariate analysis, the only feature showing significance in predicting 5yDFS was the maximum fractal dimension of the subpopulation identified considering 30% and 50% as threshold levels (maxFD30-50). Once the models were developed using this feature, an AUC of 0.67 (0.57-0.77) and 0.75 (0.56-0.95) was obtained for patients treated with and without OXA, respectively. A maxFD30-50 >1.6 was correlated to a higher 5yDFS probability in patients treated with OXA. CONCLUSION: This study suggests that radiomic analysis of MR T2-w images can be used to define the optimal concomitant CT regimen for stage III LARC cancer patients. In particular, by providing an indication of the gross tumor volume (GTV) spatial heterogeneity at initial staging, maxFD30-50 seems to be able to predict the probability of 5yDFS. New studies including a larger cohort of patients and external validation sets are recommended to verify the results of this hypothesis-generating study.

Predicting Radiotherapy Impact on Late Bladder Toxicity in Prostate Cancer Patients: An Observational Study.

BACKGROUND AND PURPOSE: The aim of our study was to elaborate a suitable model on bladder late toxicity in prostate cancer (PC) patients treated by radiotherapy with volumetric technique. MATERIALS AND METHODS: PC patients treated between September 2010 and April 2017 were included in the analysis. An observational study was performed collecting late toxicity data of any grade, according to RTOG and CTCAE 4.03 scales, cumulative dose volumes histograms were exported for each patient. Vdose, the value of dose to a specific volume of organ at risk (OAR), impact was analyzed through the Mann-Whitney rank-sum test. Logistic regression was used as the final model. The model performance was estimated by taking 1000 samples with replacement from the original dataset and calculating the AUC average. In addition, the calibration plot (Hosmer-Lemeshow goodness-of-fit test) was used to evaluate the performance of internal validation. RStudio Software version 3.3.1 and an in house developed software package "Moddicom" were used. RESULTS: Data from 175 patients were collected. The median follow-up was 39 months (min-max 3.00-113.00). We performed Mann-Whitney rank-sum test with continuity correction in the subset of patients with late bladder toxicity grade ≥ 2: a statistically significant p-value with a Vdose of 51.43 Gy by applying a logistic regression model (coefficient 4.3, p value 0.025) for the prediction of the development of late G ≥ 2 GU toxicity was observed. The performance for the model's internal validation was evaluated, with an AUC equal to 0.626. Accuracy was estimated through the elaboration of a calibration plot. CONCLUSIONS: Our preliminary results could help to optimize treatment planning procedures and customize treatments.

MRI-guided stereotactic radiation therapy for hepatocellular carcinoma: a feasible and safe innovative treatment approach.

PURPOSE: Hepatocellular carcinoma (HCC) in early stages benefits from local ablative treatments such as radiofrequency ablation (RFA) or transarterial chemoembolization (TACE). In this context, radiotherapy (RT) has shown promising results but has not been thoroughly evaluated. Magnetic resonance-guided RT (MRgRT) may represent a paradigm shifting improvement in stereotactic body radiotherapy (SBRT) for liver tumors. METHODS: We retrospectively evaluated HCC patients treated on a hybrid low-tesla MRgRT unit. A total biologically effective dose (BED) > 100 Gy was delivered in 5 consecutive fractions, respecting the appropriate organs-at-risk constraints. Hybrid MR scans were used for treatment planning and cine MR was used for delivery gating. Patients were followed up for toxicity and treatment-response assessment. RESULTS: Ten patients were enrolled, with a total of 12 lesions. All the lesions were irradiated with no interruptions. Six patients had already performed previous local therapies. Median follow-up after SBRT was 6.5 months (1-25). Two cases of acute toxicity were reported (G ≤ 2 according to CTCAE v4.0). At the time of the analysis, 90% of the population presented local control. Child-Pugh before and after treatment remained unchanged in all but one patient. CONCLUSION: MRgRT is a feasible and safe option showing favorable toxicity profile for HCC treatment.

Delta Radiomics Analysis for Local Control Prediction in Pancreatic Cancer Patients Treated Using Magnetic Resonance Guided Radiotherapy.

The aim of this study is to investigate the role of Delta Radiomics analysis in the prediction of one-year local control (1yLC) in patients affected by locally advanced pancreatic cancer (LAPC) and treated using Magnetic Resonance guided Radiotherapy (MRgRT). A total of 35 patients from two institutions were enrolled: A 0.35 Tesla T2*/T1 MR image was acquired for each case during simulation and on each treatment fraction. Physical dose was converted in biologically effective dose (BED) to compensate for different radiotherapy schemes. Delta Radiomics analysis was performed considering the gross tumour volume (GTV) delineated on MR images acquired at BED of 20, 40, and 60 Gy. The performance of the delta features in predicting 1yLC was investigated in terms of Wilcoxon Mann-Whitney test and area under receiver operating characteristic (ROC) curve (AUC). The most significant feature in predicting 1yLC was the variation of cluster shade calculated at BED = 40 Gy, with a p-value of 0.005 and an AUC of 0.78 (0.61-0.94). Delta Radiomics analysis on low-field MR images might play a promising role in 1yLC prediction for LAPC patients: further studies including an external validation dataset and a larger cohort of patients are recommended to confirm the validity of this preliminary experience.

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.

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.

BIT-ART: Multicentric Comparison of HDR-brachytherapy, Intensity-modulated Radiotherapy and Tomotherapy for Advanced Radiotherapy in Prostate Cancer.

BACKGROUND/AIM: The aim of the study was to evaluate acute and late genitourinary (GU) and gastrointestinal (GI) toxicity in patients with high- or intermediate-risk prostate cancer. PATIENTS AND METHODS: We evaluated data of patients from three Radiation Oncology Departments (Rome, Lübeck and Perugia). Patients treated in Rome underwent exclusive intensity-modulated-radiotherapy (IMRT) or IMRT plus high-dose-rate interventional radiotherapy (HDR-IRT). IMRT plus two fractions HDR-IRT was performed in Lübeck, while in Perugia Helical Tomotherapy was performed. The Common Toxicity Criteria for Adverse Event (Version 4.03) scale was used to describe acute and late toxicity. RESULTS: At a median follow-up of 28 months, all 51 patients were alive and disease-free. Patients treated by HDR-IRT plus VMAT showed only G1-2 genitourinary- gastrointestinal (GU-GI) acute and late toxicity. Univariate analysis showed a lower risk of acute GU toxicity (p=0.048) in IMRT+HDR-IRT. CONCLUSION: Low grade and less acute GU toxicity was observed in patients undergoing HDR-IRT boost.

Tailored postoperative treatment of prostate cancer: final results of a phase I/II trial.

BACKGROUD: The European Organization for Research and Treatment of Cancer (EORTC) trial 22,911 reported 74% 5-year biochemical disease-free survival (bDFS) in patients with prostate carcinoma treated with radical prostatectomy (RP) followed by postoperative radiotherapy (RT). This study aimed to improve these outcomes by using a combined-intensified-modulated-adjuvant treatment, including RT and hormone therapy (HT) after RP. MATERIALS AND METHODS: This phase I/II trial treatment was designed to improve 5-year bDFS from ~ 75 to 90%. Patients were consecutively enrolled using the following inclusion criteria: age < 80 years, histological diagnosis of prostate adenocarcinoma without known metastases, stage pT2-4N0-1, and Eastern Cooperative Oncology Group performance status of 0-2. All patients had at least one of these pathologic features: capsular perforation, positive surgical margins, seminal vesicle invasion, and pelvic lymph nodes involvement. A minimum dose of 64.8 Gy to the tumor bed was delivered in all patients. Depending on tumor characteristics at diagnosis, patients received a higher dose (70.2 Gy; 85.4%) and/or prophylactic pelvic lymph nodes irradiation (57.7%) and/or HT (69.1%). Biochemical relapse was defined as two consecutive rising prostate-specific antigen (PSA) values > 0.2 ng/ml. RESULTS: A total of 123 patients were enrolled in the study and completed the scheduled treatment. Median preoperative and postoperative PSA were: 8.8 and 0.06 ng/mL, respectively. The percentages of patients with pathologically involved nodes and positive resection margins were: 14.6% and 58.5%, respectively. With a median follow-up of 67 months (range: 37-120 months), the actuarial 5-year bDFS, local control, metastasis-free survival, and overall survival (OS) were: 92.9%, 98.7%, 96.1%, and 95.1%, respectively. CONCLUSION: A higher 5-year bDFS (92.9%) was recorded compared to studies based on standard adjuvant RT, even though patients with nodal disease and detectable postoperative PSA were enrolled. Clinical end points, as long-term disease-free survival and OS, will require further assessments. (ClinicalTrials.gov: NCT03169933).

Perioperative HDR brachytherapy for reirradiation in head and neck recurrences: single-institution experience and systematic review.

AIM: The aim of our study was to evaluate the outcomes of patients reirradiated with high-dose-rate (HDR) intensity-modulated brachytherapy (IMBT) for recurrent head and neck cancer and to perform a systematic review of the literature. MATERIALS AND METHODS: Patients treated with prior radiation doses >65 Gy were considered. After resection of macroscopic disease, catheters were fixed to the tumor bed. The total dose was 30 Gy in 12 fractions of 2.5 Gy twice daily for 5 days a week. A systematic literature search was conducted through several electronic databases including Medline/PubMed, Scopus, Embase and the Cochrane library. RESULTS: Seventeen patients were included; median overall survival was 19 months with a median local control interval of 15 months. Median follow-up was 36 months. Seven papers were considered for the review. CONCLUSIONS: IMBT could play an important role in the retreatment of recurrent head and neck cancer.

Reducing heart dose during left breast cancer radiotherapy: comparison among 3 radiation techniques.

PURPOSE: Breast cancer survivors have a high risk of cardiac death as a consequence of heart irradiation during left breast tangential radiotherapy (RT). This study compares the cardiac dose delivered by standard 3D conformal tangential RT (CRT) to that delivered by prospective-gating RT (PGRT) or 5-field intensity-modulated RT (IMRT). METHODS: Patients with early left breast cancer, referred for adjuvant RT to our institution, were enrolled in this study. For each patient, 2 simulation computed tomography scans were acquired: the first during free breathing, and the second on prospective gating during deep inspiration breath-hold. The scans were monitored by the Varian RPM™ respiratory gating system. For each patient, 3 treatment plans were performed: a 3D-CRT and an IMRT plan, each based on the free-breathing scan, and a PGRT plan, based on the deep inspiration breath-hold scan. Dose-volume histograms were compared by means of the Friedman test. RESULTS: The median mean heart dose was 3 Gy (range 0.9-7.3 Gy) in the CRT plans, 1.9 Gy (range 0.5-3.6 Gy) in the PGRT plans, and 4.5 Gy (range 1.1-10.5 Gy) in the IMRT plans (p = 0.001). The mean heart V25 was 1.2% (range 0%-9.7%), 0% (range 0%-2.0%), and 0.2% (range 0%-7.3%) for CRT, PGRT, and IMRT plans, respectively (p<0.001). CONCLUSIONS: Prospective-gating RT to the left breast offered the best protection of heart and lung, as well as a lower irradiation of the contralateral breast, compared to CRT or IMRT.

[Air quality assessment in an urban-industrial area: the Taranto case study]. / La valutazione della qualità dell'aria in una zona urbana-industriale: il caso Taranto.

OBJECT: The chemical-physical characterization of suspended particulate matter and particulate deposition, heavy metals and benzo[a]pyrene, found in the town of Taranto and the nearby industrial area (steelworks, cement production, refinery). DESIGN: Atmospheric deposition Bulks, air of High Volume (HV) samplers equipped with PM10 probe and total suspended particulate matter samplers were used. SETTING: 4 sites of monitoring in different urban areas: two of them close to the cokery, one near the school, and the last one in the town of Statte (Taranto). MAIN OUTCOME MEASURES: Determination of suspended and deposition particulate matter concentration, further determination of heavy metal concentration in the suspended and deposition particulate matter, and determination of BaP concentration. RESULTS: Data evidenced that in the site of Tamburi Cemetery (near the cokery) suspended particulate matter PM10 concentrations vary with the different seasons (warm period: 67 microg/m3, cold period: 39 microg/m3). Lead concentrations are lower than the national limit (0,5 microg/m3); for those heavy metals not yet regulated by law, values are comparable with other industrial areas. Deposition particulate matter concentrations found nearby the steelworks (warm period: 699 mg/m2d, cold period 575 mg/m2d), vary in each different monitoring site. In the town of Statte (Taranto) the concentrations found are: 236 mg/m2d in the warm period, and 154 mg/m2d in the cold period. BaP concentrations for PM10 found in the area of Tamburi near the cookery are the following: 1,9 ng/m3 in the warm period, and 2,6 ng/m3 in the cold period. CONCLUSION: A very compromised situation is found in the area under study as regard air quality, especially the particulate matter in its different fractions and its content of organic and inorganic pollutants.