Radiomics analysis of ultrasound images to discriminate between benign and malignant adnexal masses with solid ultrasound morphology.

OBJECTIVE: Our primary aim was to identify radiomic ultrasound features that can distinguish benign from malignant adnexal masses with solid ultrasound morphology, and primary invasive from metastatic solid ovarian masses, and to develop ultrasound-based machine learning models that include radiomics features to discriminate between benign and malignant solid adnexal masses. Our secondary aim was to compare the diagnostic performance of our radiomics models with that of the ADNEX model and subjective assessment by an experienced ultrasound examiner. METHODS: This is a retrospective observational single center study. Patients with a histological diagnosis of an adnexal tumor with solid morphology at preoperative ultrasound examination performed between 2014 and 2021 were included. The patient cohort was split into training and validation sets with a ratio of 70:30 and with the same proportion of benign and malignant (borderline, primary invasive and metastatic) tumors in the two subsets. The extracted radiomic features belonged to two different families: intensity-based statistical features and textural features. Models to predict malignancy were built based on a random forest classifier, fine-tuned using 5-fold cross-validation over the training set, and tested on the held-out validation set. The variables used in model building were patient's age, and those radiomic features that were statistically significantly different between benign and malignant adnexal masses (Wilcoxon-Mann-Whitney Test with Benjamini-Hochberg correction for multiple comparisons) and assessed as not redundant based on the Pearson correlation coefficient. We describe discriminative ability as area under the receiver operating characteristics curve (AUC) and classification performance as sensitivity and specificity. RESULTS: 326 patients were identified and 775 preoperative ultrasound images were analyzed. 68 radiomic features were extracted, 52 differed statistically significantly between benign and malignant tumors in the training set, and 18 features were selected for inclusion in model building. The same 52 radiomic features differed statistically significantly between benign, primary invasive malignant and metastatic tumors. However, the values of the features manifested overlap between primary malignant and metastatic tumors and did not differ statistically significantly between them. In the validation set, 25/98 tumors (25.5%) were benign, 73/98 (74.5%) were malignant (6 borderline, 57 primary invasive, 10 metastases). In the validation set, a model including only radiomics features had an AUC of 0.80, and 78% sensitivity and 76% specificity at its optimal risk of malignancy cutoff (68% based on Youden's index). The corresponding results for a model including age and radiomics features were 0.79, 86% and 56% (cutoff 60% based on Youden's method), while those of the ADNEX model were 0.88, 99% and 64% (at 20% malignancy cutoff). Subjective assessment had sensitivity 99% and specificity 72%. CONCLUSIONS: Even though our radiomics models had discriminative ability inferior to that of the ADNEX model, our results are promising enough to justify continued development of radiomics analysis of ultrasound images of adnexal masses. This article is protected by copyright. All rights reserved.

Radiomics for clinical decision support in radiation oncology.

Radiomics is a promising tool for the development of quantitative biomarkers to support clinical decision-making. It has been shown to improve the prediction of response to treatment and outcome in different settings, particularly in the field of radiation oncology by optimising the dose delivery solutions and reducing the rate of radiation-induced side effects, leading to a fully personalised approach. Despite the promising results offered by radiomics at each of these stages, standardised methodologies, reproducibility and interpretability of results are still lacking, limiting the potential clinical impact of these tools. In this review, we briefly describe the principles of radiomics and the most relevant applications of radiomics at each stage of cancer management in the framework of radiation oncology. Furthermore, the integration of radiomics into clinical decision support systems is analysed, defining the challenges and offering possible solutions for translating radiomics into a clinically applicable tool.

A cost-effectiveness analysis of an integrated clinical-radiogenomic screening program for the identification of BRCA 1/2 carriers (e-PROBE study).

Current approach to identify BRCA 1/2 carriers in the general population is ineffective as most of the carriers remain undiagnosed. Radiomics is an emerging tool for large scale quantitative analysis of features from standard diagnostic imaging and has been applied also to identify gene mutational status. The objective of this study was to evaluate the clinical and economic impact of integrating a radiogenomics model with clinical and family history data in identifying BRCA mutation carriers in the general population. This cost-effective analysis compares three different approaches to women selection for BRCA testing: established clinical criteria/family history (model 1); established clinical criteria/family history and the currently available radiogenomic model (49% sensitivity and 87% specificity) based on ultrasound images (model 2); same approach used in model 2 but simulating an improvement of the performances of the radiogenomic model (80% sensitivity and 95% specificity) (model 3). All models were trained with literature data. Direct costs were calculated according to the rates currently used in Italy. The analysis was performed simulating different scenarios on the generation of 18-year-old girls in Italy (274,000 people). The main outcome was to identify the most effective model comparing the number of years of BRCA-cancer healthy life expectancy (HLYs). An incremental cost-effectiveness ratio (ICER) was also derived to determine the cost in order to increase BRCA carriers-healthy life span by 1 year. Compared to model 1, model 2 increases the detection rate of BRCA carriers by 41.8%, reduces the rate of BRCA-related cancers by 23.7%, generating over a 62-year observation period a cost increase by 2.51 €/Year/Person. Moreover, model 3 further increases BRCA carriers detection (+ 68.3%) and decrease in BRCA-related cancers (- 38.4%) is observed compared to model 1. Model 3 increases costs by 0.7 €/Year/Person. After one generation, the estimated ICER in the general population amounts to about 3800€ and 653€ in model 2 and model 3 respectively. Model 2 has a massive effect after only one generation in detecting carriers in the general population with only a small cost increment. The clinical impact is limited mainly due to the current low acceptance rate of risk-reducing surgeries. Further multicentric studies are required before implementing the integrated clinical-radiogenomic model in clinical practice.

Tumor-like presentation of herpetic cervicitis: A case report.

The case of a 20-year-old immunocompetent woman with necrotizing cervicitis of the cervix caused by a primary infection with herpes simplex virus type 2 is presented, along with its respective evolution in images. Cervical cancer was included in the differential diagnoses, but biopsies ruled out malignancy and laboratory tests demonstrated the viral etiology of the cervical inflammation. After initiating specific treatment, the cervical lesions completely healed within 3 weeks. This case highlights the need to consider herpes simplex infection in the differential diagnosis of cervical inflammation and tumor formation. Additionally, it provides images that can aid in diagnosis and allow for the observation of its clinical evolution.

MRI-derived radiomics to guide post-operative management of glioblastoma: Implication for personalized radiation treatment volume delineation.

Background: The glioblastoma's bad prognosis is primarily due to intra-tumor heterogeneity, demonstrated from several studies that collected molecular biology, cytogenetic data and more recently radiomic features for a better prognostic stratification. The GLIFA project (GLIoblastoma Feature Analysis) is a multicentric project planned to investigate the role of radiomic analysis in GB management, to verify if radiomic features in the tissue around the resection cavity may guide the radiation target volume delineation. Materials and methods: We retrospectively analyze from three centers radiomic features extracted from 90 patients with total or near total resection, who completed the standard adjuvant treatment and for whom we had post-operative images available for features extraction. The Manual segmentation was performed on post gadolinium T1w MRI sequence by 2 radiation oncologists and reviewed by a neuroradiologist, both with at least 10 years of experience. The Regions of interest (ROI) considered for the analysis were: the surgical cavity ± post-surgical residual mass (CTV_cavity); the CTV a margin of 1.5 cm added to CTV_cavity and the volume resulting from subtracting the CTV_cavity from the CTV was defined as CTV_Ring. Radiomic analysis and modeling were conducted in RStudio. Z-score normalization was applied to each radiomic feature. A radiomic model was generated using features extracted from the Ring to perform a binary classification and predict the PFS at 6 months. A 3-fold cross-validation repeated five times was implemented for internal validation of the model. Results: Two-hundred and seventy ROIs were contoured. The proposed radiomic model was given by the best fitting logistic regression model, and included the following 3 features: F_cm_merged.contrast, F_cm_merged.info.corr.2, F_rlm_merged.rlnu. A good agreement between model predicted probabilities and observed outcome probabilities was obtained (p-value of 0.49 by Hosmer and Lemeshow statistical test). The ROC curve of the model reported an AUC of 0.78 (95% CI: 0.68-0.88). Conclusion: This is the first hypothesis-generating study which applies a radiomic analysis focusing on healthy tissue ring around the surgical cavity on post-operative MRI. This study provides a preliminary model for a decision support tool for a customization of the radiation target volume in GB patients in order to achieve a margin reduction strategy.

Project for interventional Oncology LArge-database in liveR Hepatocellular carcinoma - Preliminary CT-based radiomic analysis (POLAR Liver 1.1).

OBJECTIVE: The objective of this study is to find a contrast-enhanced CT-radiomic signature to predict clinical incomplete response in patients affected by hepatocellular carcinoma who underwent locoregional treatments. PATIENTS AND METHODS: 190 patients affected by hepatocellular carcinoma treated using focal therapies (radiofrequency or microwave ablation) from September 2018 to October 2020 were retrospectively enrolled. Treatment response was evaluated on a per-target-nodule basis on the 6-months follow-up contrast-enhanced CT or MR imaging using the mRECIST criteria. Radiomics analysis was performed using an in-house developed open-source R library. Wilcoxon-Mann-Whitney test was applied for univariate analysis; features with a p-value lower than 0.05 were selected. Pearson correlation was applied to discard highly correlated features (cut-off=0.9). The remaining features were included in a logistic regression model and receiver operating characteristic curves; sensitivity, specificity, positive and negative predictive value were also computed. The model was validated performing 2000 bootstrap resampling. RESULTS: 56 treated lesions from 42 patients were selected. Treatment responses were: complete response for 26 lesions (46.4%), 18 partial responses (32.1%), 10 stable diseases (17.9%), 2 progression diseases (3.6%). Area-Under-Curve value was 0.667 (95% CI: 0.527-0.806); accuracy, sensitivity, specificity, positive and negative predictive values were respectively 0.66, 0.85, 0.50, 0.59 and 0.79. CONCLUSIONS: This contrast-enhanced CT-based model can be helpful to early identify poor responder's hepatocellular carcinoma patients and personalize treatments.

Developing and validating ultrasound-based radiomics models for predicting high-risk endometrial cancer.

OBJECTIVES: The primary aim of this study was to develop and validate radiomics models, applied to ultrasound images, capable of differentiating from other cancers high-risk endometrial cancer, as defined jointly by the European Society for Medical Oncology, European Society of Gynaecological Oncology and European Society for Radiotherapy & Oncology (ESMO-ESGO-ESTRO) in 2016. The secondary aim was to develop and validate radiomics models for differentiating low-risk endometrial cancer from other endometrial cancers. METHODS: This was a multicenter, retrospective, observational study. From two participating centers, we identified consecutive patients with histologically confirmed diagnosis of endometrial cancer who had undergone preoperative ultrasound examination by an experienced examiner between 2016 and 2019. Patients recruited in Center 1 (Rome) were included as the training set and patients enrolled in Center 2 (Milan) formed the external validation set. Radiomics analysis (extraction of a high number of quantitative features from medical images) was applied to the ultrasound images. Clinical (including preoperative biopsy), ultrasound and radiomics features that were statistically significantly different in the high-risk group vs the other groups and in the low-risk group vs the other groups on univariate analysis in the training set were considered for multivariate analysis and for developing ultrasound-based machine-learning risk-prediction models. For discriminating between the high-risk group and the other groups, a random forest model from the radiomics features (radiomics model), a binary logistic regression model from clinical and ultrasound features (clinical-ultrasound model) and another binary logistic regression model from clinical, ultrasound and previously selected radiomics features (mixed model) were created. Similar models were created for discriminating between the low-risk group and the other groups. The models developed in the training set were tested in the validation set. The performance of the models in discriminating between the high-risk group and the other groups, and between the low-risk group and the other risk groups for both validation and training sets was compared. RESULTS: The training set comprised 396 patients and the validation set 102 patients. In the validation set, for predicting high-risk endometrial cancer, the radiomics model had an area under the receiver-operating-characteristics curve (AUC) of 0.80, sensitivity of 58.7% and specificity of 85.7% (using the optimal risk cut-off of 0.41); the clinical-ultrasound model had an AUC of 0.90, sensitivity of 80.4% and specificity of 83.9% (using the optimal cut-off of 0.32); and the mixed model had an AUC of 0.88, sensitivity of 67.3% and specificity of 91.0% (using the optimal cut-off of 0.42). For the prediction of low-risk endometrial cancer, the radiomics model had an AUC of 0.71, sensitivity of 65.0% and specificity of 64.5% (using the optimal cut-off of 0.38); the clinical-ultrasound model had an AUC of 0.85, sensitivity of 70.0% and specificity of 80.6% (using the optimal cut-off of 0.46); and the mixed model had an AUC of 0.85, sensitivity of 87.5% and specificity of 72.5% (using the optimal cut-off of 0.36). CONCLUSIONS: Radiomics seems to have some ability to discriminate between low-risk endometrial cancer and other endometrial cancers and better ability to discriminate between high-risk endometrial cancer and other endometrial cancers. However, the addition of radiomics features to the clinical-ultrasound models did not result in any notable increase in performance. Other efficacy studies and further effectiveness studies are needed to validate the performance of the models. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

When your MR linac is down: Can an automated pipeline bail you out of trouble?

PURPOSE: The unique treatment delivery technique provided by magnetic resonance guided radiotherapy (MRgRT) can represent a significant drawback when system fail occurs. This retrospective study proposes and evaluates a pipeline to completely automate the workflow necessary to shift a MRgRT treatment to a traditional radiotherapy linac. MATERIAL AND METHODS: Patients undergoing treatment during the last MRgRT system failure were retrospectively included in this study. The core of the proposed pipeline was based on a tool able to mimic the original MR linac dose distribution. The so obtained dose distribution (AUTO) has been compared with the distribution obtained in the conventional radiotherapy linac (MAN). Plan comparison has been performed in terms of time required to obtain the final dose distribution, DVH parameters, dosimetric indices and visual analogue scales scoring by radiation oncologists. RESULTS: AUTO plans generation has been obtained within 10 min for all the considered cases. All AUTO plans were found to be within clinical tolerance, showing a mean target coverage variation of 1.7% with a maximum value of 4.3% and a minimum of 0.6% when compared with MAN plans. The highest OARs mean variation has been found for rectum V60 (6.7%). Dosimetric indices showed no relevant differences, with smaller gradient measure in favour of AUTO plans. Visual analogue scales scoring has confirmed comparable plan quality for AUTO plans. CONCLUSION: The proposed workflow allows a fast and accurate generation of automatic treatment plans. AUTO plans can be considered equivalent to MAN ones, with limited clinical impact in the worst-case scenario.

On dose cube pixel spacing pre-processing for features extraction stability in dosiomic studies.

PURPOSE: Dosiomics allows to parameterize regions of interest (ROIs) and to produce quantitative dose features encoding the spatial and statistical distribution of radiotherapy dose. The stability of dosiomics features extraction on dose cube pixel spacing variation has been investigated in this study. MATERIAL AND METHODS: Based on 17 clinical delivered dose distributions (Pn), dataset has been generated considering all the possible combinations of four dose grid resolutions and two calculation algorithms. Each dose voxel cube has been post-processed considering 4 different dose cube pixel spacing values: 1x1x1, 2x2x2, 3x3x3 mm3 and the one equal to the planning CT. Dosiomics features extraction has been performed from four different ROIs. The stability of each extracted dosiomic feature has been analyzed in terms of coefficient of variation (CV) intraclass correlation coefficient (ICC). RESULTS: The highest CV mean values were observed for PTV ROI and for the grey level size zone matrix features family. On the other hand, the lowest CV mean values have been found for RING ROI for the grey level co-occurrence matrix features family. P3 showed the highest percentage of CV >1 (1.14%) followed by P15 (0.41%), P1 (0.29%) and P13 (0.19%). ICC analysis leads to identify features with an ICC >0.95 that could be considered stable to use in dosiomic studies when different dose cube pixel spacing are considered, especially the features in common among the seventeen plans. CONCLUSION: Considering the observed variability, dosiomic studies should always provide a report not only on grid resolution and algorithm dose calculation, but also on dose cube pixel spacing.

Radiofrequency thermoablation (RFA) and radiotherapy (RT) combined treatment for bone metastases: a systematic review.

OBJECTIVE: Approximately 50% of cancer patients develop bone metastases in their natural disease history. The management of metastatic bone disease requires a multidisciplinary approach. Both radiofrequency ablation (RFA) and radiation therapy (RT) were safe and effective in the management of painful metastases, even if they rely on totally different action mechanisms. A synergistic combination of RT and RFA seems to result in a better pain control. A systematic review was performed to describe the feasibility and effectiveness of the association between RFA and RT in the treatment of metastatic bone pain in oligo-metastatic patients, evaluating its role in alleviating bone pain, reducing the risk of fractures, and consequently ensuring a better quality of life. MATERIALS AND METHODS: A systematic database search was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This systematic review included studies that reported populations meeting the following inclusion criteria: (I) confirmed bone metastases in adult patients; (II) active bone metastases pain; (III) patients treated with combined RFA-RT; (IV) Original studies. RESULTS: Three papers that evaluated the combined treatment with doses ranging from moderately hypofractionated three-dimensional conformal RT (3D-CRT) and stereotactic body radiation therapy (SBRT) schedules were selected. CONCLUSIONS: The RFA-RT combined strategy appears to be promising in terms of efficiency and safety with adequate pain control and quality of life improvement. Positive effects on time to local failure and overall survival increase were also observed. Further prospective studies are needed to better delineate RFA-RT treatment benefits.

VMAT-like plans for magnetic resonance guided radiotherapy: Addressing unmet needs.

PURPOSE: VMAT delivery technique is currently not applicable to Magnetic Resonance-guided radiotherapy (MRgRT) hybrid systems. Aim of this study is to evaluate an innovative VMAT-like (VML) delivery technique. MATERIAL AND METHODS: First, planning and dosimetric evaluation of the MRgRT VML treatment have been performed on 10 different disease sites and the results have been compared with the corresponding IMRT plans. Then, in the second phase, 10 of the most dosimetrically challenging locally advanced pancreas treatment plans have been retrospectively re-planned using the VML approach to explore the potentiality of this new delivery technique. Finally, VML robustness was evaluated and compared with the IMRT plans, considering a lateral positioning error of ± 5 mm. RESULTS: In phase one, all VML plans were within constraint for all OARs. When PTV coverage is considered, in the 50% of the cases VML PTV coverage is equal or higher than in IMRT plan. In the remaining 50%, the highest target under coverage difference in comparison with IMRT plan is -1.71%. The mean and maximum treatment time differences (VML-IMRT) is 0.2 min and 3.1 min respectively. In phase two, the treatment time variation (VML-IMRT), shows a mean, maximum and minimum variations of 1.3, 4.6 and -0.6 min respectively. All VML plans have a better target coverage if compared with IMRT plans, keeping in any case the OARs constraints within tolerance. VML doesn't increase plan robustness. CONCLUSION: VMAT-like treatment approach appeared to be an efficient planning solution and it was decided to clinically implement it in daily practice, especially in the frame of hypo fractionated treatments.

Radiotherapy for benign disorders: current use in clinical practice.

OBJECTIVE: The aim of this paper is to provide an update about the current clinical indications of RT in this poorly explored field outside the traditional oncological setting. MATERIALS AND METHODS: We performed a literature search on the main databases, including PubMed, Scopus and Cochrane from their inception until 31st December 2020. An additional manual check of scientific meeting proceedings and books was conducted in order to identify all the potentially useful sources. Only essays published in English have been considered for the purposes of this analysis. The searched items included: "Radiotherapy or Radiation Therapy" and "Benign disorder or Benign disease". RESULTS: We provided a list of current clinical indications for benign disorders based on the latest international surveys available, including major sites: eye, bone, head and neck, skin, brain, heart and peripheral vascular system. CONCLUSIONS: Radiotherapy for benign diseases is still a feasible therapeutic strategy, which may allow to treat several invalidating conditions, especially after medical therapies have failed thus avoiding potentially invalidating major surgical procedures. A careful evaluation in selecting the indication is essential and all the choices should be thoroughly discussed with the patients.

Dosimetric accuracy of dual isocenter irradiation in low magnetic field resonance guided radiotherapy system for extended abdominal tumours.

PURPOSE: Due to limited field size of Magnetic Resonance Linear Accelerators (MR-Linac), some treatments could require a dual-isocenter planning approach to achieve a complete target coverage and thus exploit the benefits of the online adaptation. This study evaluates the dosimetric accuracy of the dual-isocenter intensity modulated radiation therapy (IMRT) delivery technique for MR-Linac. MATERIAL AND METHODS: Dual-isocenter multi leaf collimator (MLC) and couch accuracy tests have been performed to evaluate the delivery accuracy of the system. A mono-isocenter plan delivered in clinical practice has then been retrospectively re-planned with dual-isocenter technique. The dual-isocenter plan has been re-calculated and delivered on a 3-dimensional (3D) ArcCHECK phantom and 2-dimensional (2D) films to assess its dosimetric accuracy in terms of gamma analysis. Clinical and planning target volume (CTV and PTV respectively) coverage robustness was then investigated after the introduction of ± 2 mm and ± 5 mm positioning errors by shifting the couch. RESULTS: MLC and couch accuracy tests confirmed the system accuracy in delivering a dual-isocenter irradiation. 2D/3D gamma analysis results occurred always to be above 95% if considered a gamma criteria 1%/2 mm and 1%/1 mm respectively for the 2D and 3D analysis. The mean variations for CTV D98% and PTV V95% were 0.2% and 1.1% respectively when positioning error was introduced separately in each direction, while the maximum observed variations were 0.9% (CTV) and 3.7% (PTV). CONCLUSION: The dosimetric accuracy of dual-isocenter irradiation has been verified for MR-Linac, achieving accurate and robust treatment strategy and improving dose conformality also in presence of targets whose extension exceeds the nominal maximum field size.

Mammary Paget's disease and radiotherapy: a systematic literature review.

OBJECTIVE: Paget disease of the breast (PDB) is a rare form of cutaneous breast cancer. Up to date, no randomized studies evaluated the different management strategies. This systematic review investigates the role of radiotherapy and its best technical profile in the treatment of this disease, with great attention to doses and fractionation regimens. MATERIALS AND METHODS: A systematic search was performed on PubMed, Embase and Scopus in order to detect case reports, case series and prospective as well as retrospective clinical studies describing histologically proven PDB and providing information about pertinent radiation treatments. Searching strategy followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. RESULTS: Inclusion criteria were met by six papers, dealing with radiation treatments performed postoperatively and in exclusive settings. No evaluations were performed on preoperative radiotherapy. CONCLUSIONS: Actually, the standard treatment of PDB reflects oncological principles of breast carcinoma therapy, including the role of breast-preserving surgery. The traditional radiotherapic dose is 50 Gy, with daily fractionation of 2 Gy. Adjuvant radiotherapy following breast preserving surgery represents the current standard of care; prospective studies could be of help in defining the role of exclusive radiotherapy, hypofractionated schemes and smaller target volumes.

Process mining to optimize palliative patient flow in a high-volume radiotherapy department.

INTRODUCTION: In radiotherapy, palliative patients are often suboptimal managed and patients experience long waiting times. Event-logs (recorded local files) of palliative patients, could provide a continuative decision-making system by means of shared guidelines to improve patient flow. Based on an event-log analysis, we aimed to accurately understand how to successively optimize patient flow in palliative care. METHODS: A process mining methodology was applied on palliative patient flow in a high-volume radiotherapy department. Five hundred palliative radiation treatment plans of patients with bone and brain metastases were included in the study, corresponding to 290 patients treated in our department in 2018. Event-logs and the relative attributes were extracted and organized. A process discovery algorithm was applied to describe the real process model, which produced the event-log. Finally, conformance checking was performed to analyze how the acquired event-log database works in a predefined theoretical process model. RESULTS: Based on the process discovery algorithm, 53 (10%) plans had a dose prescription of 8 Gy, 249 (49.8%) plans had a dose prescription of 20 Gy and 159 (31.8%) plans had a dose prescription of 30 Gy. The remaining 39 (7.8%) plans had different dose prescriptions. Considering a median value, conformance checking demonstrated that event-logs work in the theoretical model. CONCLUSIONS: The obtained results partially validate and support the palliative patient care guideline implemented in our department. Process mining can be used to provide new insights, which facilitate the improvement of existing palliative patient care flows.

Stability of dosomics features extraction on grid resolution and algorithm for radiotherapy dose calculation.

PURPOSE: Dosomics is a novel texture analysis method to parameterize regions of interest and to produce dose features that encode the spatial and statistical distribution of radiotherapy dose at higher resolution than organ-level dose-volume histograms. This study investigates the stability of dosomics features extraction, as their variation due to changes of grid resolution and algorithm dose calculation. MATERIAL AND METHODS: Dataset has been generated considering all the possible combinations of four grid resolutions and two algorithms dose calculation of 18 clinical delivered dose distributions, leading to a 144 3D dose distributions dataset. Dosomics features extraction has been performed with an in-house developed software. A total number of 214 dosomics features has been extracted from four different region of interest: PTV, the two closest OARs and a RING structure. Reproducibility and stability of each extracted dosomic feature (Rfe, Sfe), have been analyzed in terms of intraclass correlation coefficient (ICC) and coefficient of variation. RESULTS: Dosomics features extraction was found reproducible (ICC > 0.99). Dosomic features, across the combination of grid resolutions and algorithms dose calculation, are more stable in the RING for all the considered feature's families. Sfe is higher in OARs, in particular for GLSZM features' families. Highest Sfe have been found in the PTV, in particular in the GLCM features' family. CONCLUSION: Stability and reproducibility of dosomics features have been evaluated for a representative clinical dose distribution case mix. These results suggest that, in terms of stability, dosomic studies should always perform a reporting of grid resolution and algorithm dose calculation.

Radiation therapy technologists' involvement and opinion in research: A national survey in Italy.

INTRODUCTION: This survey describes Italian RTTs' involvement and opinions in research activities related to radiation oncology. Primary aim was to assess the degree of involvement of the national RTTs community in research and to describe how RTTs can integrate their skills collaborating with other professionals. MATERIALS AND METHODS: A ten-items multiple-choice questionnaire, with 2-8 possible responses, was developed by a steering committee and generated on a survey platform. Links were sent via email to Italian RTTs.The questions were divided in 3 domains: demographic data; scientific research and activity; opinions about RTTs role in scientific research. The survey started on October 1, 2018 and ended on January 31, 2019. RESULTS: One hundred thirty-five out of 509 (26.5%) RTTs responded to the questionnaire at its expiring date; 97.73% think to be valid contributors in radiation oncology research, expressing clear interest in "data collection" tasks (52.71%); 38.64% feel unsupported by other professionals in the research team and 59.85% of the respondents are not members in any scientific society. CONCLUSIONS: The role of Italian RTTs in research is heterogeneous. Mainly RTTs in the age range from 30 to 40 years responded to the survey showing their interest in scientific research. This might be related to different informatics and educational skills as well as to personal attitudes. RTTs particular skills, like data management and technical hypothesis generation abilities, are of benefit to realize research projects. Therefore, engaging RTTs in research activities is strongly suggested.

Spatially fractionated radiotherapy (SFRT) targeting the hypoxic tumor segment for the intentional induction of non-targeted effects: An in silico study to exploit a new treatment paradigm.

INTRODUCTION: The possibility of intentionally triggering non targeted effects (NTEs) using spatially fractionated radiotherapy (SFRT) alone or combined with immunotherapy is an intriguing and fascinating area of research. Among different techniques for SFRT, stereotactic body radiotherapy targeting exclusively the central hypoxic segment of bulky tumors, (SBRT-PATHY) might trigger immunogenic cell death more efficiently. This in silico study aims to identify the best possible dosimetric trade-off for prescribing SFRT with volumetric modulated arc (VMAT) based stereotactic radiotherapy (SRT). MATERIAL AND METHODS: Eight spherical volumes defined "Gross Tumor Volumes" (GTVs) were generated with diameters of 3-10 cm (with incremental steps of 1 cm), simulating tumor lesions. The inner third part of each GTV (GTVcentral) was selected to simulate the central hypoxic area and a ring structure was derived around it to simulate the tumor periphery (GTVperipheral). Volumetric modulated arc radiation treatment (VMAT) plans were calculated to deliver a single fraction of 10 Gy to each GTVcentral with different dose prescription methods: target mean and isodose driven (40, 50, 60, 70, 80 and 90%).The volume of GTVperipheral receiving less than 2 Gy was recorded as dosimetric performance indicator. RESULTS: 56 possible dosimetric scenarios were analyzed. The largest percentage of GTVperipheral spared from the dose of 2 Gy was achieved with dose prescription methods to the 70% isodose line for lesions smaller than 6 cm (range 42.9-48.4%) and to the target mean for larger ones (range 52.9-64.5%). CONCLUSIONS: Optimizing the dose prescription method may reduce the dose to tumor periphery in VMAT-based SFRT, thus potentially sparing tumor infiltrating immune cells. The optimal method may vary according to the size of the lesion. This should be taken into account when designing prospective trials using SFRT.

Abscopal effect and interventional oncology: state of art and future perspectives.

OBJECTIVE: The concept of abscopal effect is currently gaining importance in modern oncology, as the link between localized irradiation and triggering of immuno-mediated systemic antitumor effects is getting clearer. An increasing number of reports documented abscopal effect mainly after external beam irradiation. Interventional radiotherapy (IR) may be used with sealed radioactive sources as brachytherapy (BT) or with unsealed radioactive sources as transarterial radioembolization (TARE). The aim of this paper is to review the existing clinical IR data and discuss the mechanisms of the abscopal effect. MATERIALS AND METHODS: A systematic research of the main bibliographic databases (PubMed, WOS, Scopus, and Google Scholar) from the earliest possible date through August 2019 was performed. The search strategy was based on the terms "abscopal effect", "interventional radiotherapy", "brachytherapy" and "TARE". RESULTS: Thirteen titles were identified. Three papers met inclusion criteria and were included in the review. All of them were case reports. CONCLUSIONS: Even though there are still scarce data in literature regarding the association of locoregional interventional treatments with the abscopal effect, this review demonstrates that the immunomodulatory theories, which have been widely used so far for external beam radiotherapy (EBRT), may be actually considered valid also in the contest of IR.