A Novel Benchmarking Approach to Assess the Agreement among Radiomic Tools.

Background The translation of radiomic models into clinical practice is hindered by the limited reproducibility of features across software and studies. Standardization is needed to accelerate this process and to bring radiomics closer to clinical deployment. Purpose To assess the standardization level of seven radiomic software programs and investigate software agreement as a function of built-in image preprocessing (eg, interpolation and discretization), feature aggregation methods, and the morphological characteristics (ie, volume and shape) of the region of interest (ROI). Materials and Methods The study was organized into two phases: In phase I, the two Image Biomarker Standardization Initiative (IBSI) phantoms were used to evaluate the IBSI compliance of seven software programs. In phase II, the reproducibility of all IBSI-standardized radiomic features across tools was assessed with two custom Italian multicenter Shared Understanding of Radiomic Extractors (ImSURE) digital phantoms that allowed, in conjunction with a systematic feature extraction, observations on whether and how feature matches between program pairs varied depending on the preprocessing steps, aggregation methods, and ROI characteristics. Results In phase I, the software programs showed different levels of completeness (ie, the number of computable IBSI benchmark values). However, the IBSI-compliance assessment revealed that they were all standardized in terms of feature implementation. When considering additional preprocessing steps, for each individual program, match percentages fell by up to 30%. In phase II, the ImSURE phantoms showed that software agreement was dependent on discretization and aggregation as well as on ROI shape and volume factors. Conclusion The agreement of radiomic software varied in relation to factors that had already been standardized (eg, interpolation and discretization methods) and factors that need standardization. Both dependences must be resolved to ensure the reproducibility of radiomic features and to pave the way toward the clinical adoption of radiomic models. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Steiger in this issue. An earlier incorrect version appeared online and in print. This article was corrected on March 2, 2022.

A novel figure of merit to investigate 68Ga PET/CT image quality based on patient weight and lesion size using Q.Clear reconstruction algorithm: A phantom study.

INTRODUCTION: Q.Clear is a Bayesian penalised-likelihood algorithm that uses a ß-value for positron emission tomography(PET)/computed tomography(CT) image reconstruction(IR). Our study proposes a novel figure of merit, named CRBV, to compare the Q.Clear performances using 68Ga PET/CT image with the ordered-subset-expectation-maximization(OSEM) algorithm and to identify the optimal ß-values for these images using two phantoms mimicking normal and overweight patients. METHODS: NEMA IQ phantom with or without a ring of water-filled plastic bags (NEMAstd and NEMAow, respectively) was acquired and reconstructed with OSEM and Q.Clear at various ß-values and minutes/bed position(min/bp). Contrast recovery(CR), background variability(BV) and CRBV were calculated. Highest CRBV values were used to identify optimal ß-value ranges. RESULTS: Q.Clear with 250 ≤ ß ≤ 800 improved CRBV compared to OSEM for all the investigated spheres and acquisition setups. Outside of this range, Q.Clear still outperformed OSEM with few exceptions depending on spheres diameters and phantoms(e.g.,ß-value = 1600 for diameters ≤ 17 mm using the NEMAow phantom). Regarding the CRBV performance for IR optimization, for the 4 min/bp NEMAstd IR, ß-values = 300 ÷ 350 allowed to simultaneously optimize all diameters(except for the 10 mm); for the NEMAow IR, ß-values = 350 ÷ 500 were needed for diameters > 20 mm, while ß-values = 200 ÷ 250 were selected for the remaining diameters. For the 2 min/bp, ß-value = 500 was suitable for diameters > 17 mm in both NEMAstd and NEMAow IR, while for smaller diameters ß-value = 200 and ß-values = 250 ÷ 350 were obtained for NEMAstd and NEMAow, respectively. CONCLUSION: Almost all tested ß-values of Q.Clear improved the CRBV compared to OSEM. In both phantoms, simulating normal and over-weight patients, optimal ß-values were found according to lesion sizes and investigated acquisition times.

A single centre intercomparison between commercial treatment planning systems for 90Y radioembolization using virtual and experimental phantoms.

INTRODUCTION: Dedicated Treatment Planning Systems (TPSs) were developed to personalize 90Y-transarterial radioembolization. This study evaluated the agreement among four commercial TPSs assessing volumes of interest (VOIs) volumes and dose metrics. METHODS: A homogeneous (EH) and an anthropomorphic phantom with hot and cold inserts (EA) filled with 99mTc-pertechnetate were acquired with a SPECT/CT scanner. Their virtual versions (VH and VA, respectively) and a phantom with activity inside a single voxel (VK) were generated by an in-house MATLAB script. Images and delineated VOIs were imported into the TPSs to compute voxel-based absorbed dose distributions with various dose deposition approaches: local deposition method (LDM) and dose kernel convolution (DKC) with/without local density correction (LDC). VOI volumes and mean absorbed doses were assessed against their median value across TPSs. Dose-volume histograms (DVHs) and VK-derived dose profiles were evaluated. RESULTS: Small (<2.1 %) and large (up to 42.4 %) relative volume differences were observed on large (>500 ml) and small VOIs, respectively. Mean absorbed doses relative differences were < 3 % except for small VOIs with steep dose gradients (up to 89.1 % in the VA Cold Sphere VOI). Within the same TPS, LDC negligibly affected the mean absorbed dose, while DKC and LDM showed differences up to 63 %. DHVs were mostly overlapped in experimental phantoms, with some differences in the virtual versions. Dose profiles agreed within 1 %. CONCLUSION: TPSs showed an overall good agreement except for small VOI volumes and mean absorbed doses of VOIs with steep dose gradients. These discrepancies should be considered in the dosimetry uncertainty assessment, thus requiring an appropriate harmonization.

A novel tool for predicting the dose distribution of non-sealed 188 Re (Rhenium) resin in non-melanoma skin cancers (NMSC) patients.

BACKGROUND: High-dose rate brachytherapy using a non-sealed 188 Rhenium resin (188 Re) is a recently approved treatment option for non-melanoma skin cancer (NMSC). The treatment goal is to deliver a personalized absorbed dose to the deepest point of neoplastic infiltration corresponding to the minimal target dose. The treatment consists of the application of a 188 Re-based resin over a plastic foil placed on the target skin surface. However, there is no treatment planning tool to assess the 188 Re activity needed for a personalized treatment. PURPOSE: The paper aims to present a novel Monte Carlo (MC)-based tool for 188 Re-based resin activity and dose calculation, experimentally validated using Gafchromic EBT3 films. METHODS: MC simulations were carried out using FLUKA modeling density and composition of 188 Re resin. The MC-based look up table (LUT) was incorporated in an ad hoc developed tool. The proposed tool allows the personalized calculation of treatment parameters (i.e., activity to be dispensed, the treatment duration, and dose volume histograms), according to the target dimension. The proposed tool was compared using Bland-Altman analysis to the previous calculation approaches conducted using VARSKIN in a retrospective cohort of 76 patients. The tool was validated in ad hoc experimental set ups using a stack of calibrated Gafchromic EBT3 films covered by a plastic film and exposed using a homogenous activity distribution of 188 Re eluate and a heterogeneous activity distribution of 188 Re resin mimic the patient treatment. RESULTS: The agreement between the proposed tool and VARSKIN was evaluated on the investigated cohort with median range of target area, target depth, and treatment time equal to 4.8 [1.0-60.1] cm2 , 1.1 [0.2-3.0] mm, and 70 [21-285] min, with a median range of target dose (Gy) of 23.5 [10-54.9]. The calculated minimal target doses, ranged from 1% to 10% for intermediate target depths (1.2 ± 0.7 mm), while showing significant differences in the estimation of superficial (maximal) target doses. The agreement between MC calculation and measurements at different plans in a stack of Gafchromic EBT3 films was within 10% for both the homogenous and heterogeneous activity distribution of 188 Re. Worst agreements were observed for absorbed doses lower than 0.3 Gy. CONCLUSIONS: Our results support the implementation of our MC-based tool in the practical routine for calculating the 188 Re resin activity and treatment parameters necessary for obtaining the prescribed minimal target dose.

PVA-Microbubbles as a Radioembolization Platform: Formulation and the In Vitro Proof of Concept.

This proof-of-concept study lays the foundations for the development of a delivery strategy for radioactive lanthanides, such as Yttrium-90, against recurrent glioblastoma. Our appealing hypothesis is that by taking advantage of the combination of biocompatible polyvinyl alcohol (PVA) microbubbles (MBs) and endovascular radiopharmaceutical infusion, a minimally invasive selective radioembolization can be achieved, which can lead to personalized treatments limiting off-target toxicities for the normal brain. The results show the successful formulation strategy that turns the ultrasound contrast PVA-shelled microbubbles into a microdevice, exhibiting good loading efficiency of Yttrium cargo by complexation with a bifunctional chelator. The selective targeting of Yttrium-loaded MBs on the glioblastoma-associated tumor endothelial cells can be unlocked by the biorecognition between the overexpressed αVß3 integrin and the ligand Cyclo(Arg-Gly-Asp-D-Phe-Lys) at the PVA microbubble surface. Hence, we show the suitability of PVA MBs as selective Y-microdevices for in situ injection via the smallest (i.e., 1.2F) neurointerventional microcatheter available on the market and the accumulation of PVA MBs on the HUVEC cell line model of integrin overexpression, thereby providing ~6 × 10-15 moles of Y90 per HUVEC cell. We further discuss the potential impact of using such versatile PVA MBs as a new therapeutic chance for treating glioblastoma multiforme recurrence.

Stereotactic Arrhythmia Radioablation (STAR): A Multidisciplinary Narrative Minireview of Preclinical Studies.

The aim of this narrative review of the literature was to collect and analyze the results of the published preclinical studies on stereotactic arrhythmia radioablation (STAR) in the treatment of refractory cardiac arrhythmias. A literature search was conducted on PubMed using the following terms: ("stereotactic" OR "SBRT" OR "SABR" OR "radioablation" OR "radiosurgery") AND ("arrhythmia" OR "tachycardia"). Preclinical and pathological reports published in English without time limit, comprising studies of STAR in animal models and histological analyzes of explanted animal and human hearts were included. The analyzed studies confirm that doses lower than 25 Gy seem to produce sub-optimal therapeutic results whereas doses >35 Gy are less safe in terms of radiation-induced toxicity. However, long-term results (>1 year) are still missing and reporting outcomes based on low dose irradiation (≤15 Gy). Finally, STAR proved to be an effective therapy in the analyzed studies despite the irradiation of rather different cardiac targets. Therefore, additional studies are needed to: 1) compare the outcomes of STAR at doses of 25 Gy versus 30 Gy; 2) evaluate the long-term results (>1 year) in animal models irradiated at doses similar to those used in the clinic; 3) define the optimal target.

How smart is artificial intelligence in organs delineation? Testing a CE and FDA-approved Deep-Learning tool using multiple expert contours delineated on planning CT images.

Background: A CE- and FDA-approved cloud-based Deep learning (DL)-tool for automatic organs at risk (OARs) and clinical target volumes segmentation on computer tomography images is available. Before its implementation in the clinical practice, an independent external validation was conducted. Methods: At least a senior and two in training Radiation Oncologists (ROs) manually contoured the volumes of interest (VOIs) for 6 tumoral sites. The auto-segmented contours were retrieved from the DL-tool and, if needed, manually corrected by ROs. The level of ROs satisfaction and the duration of contouring were registered. Relative volume differences, similarity indices, satisfactory grades, and time saved were analyzed using a semi-automatic tool. Results: Seven thousand seven hundred sixty-five VOIs were delineated on the CT images of 111 representative patients. The median (range) time for manual VOIs delineation, DL-based segmentation, and subsequent manual corrections were 25.0 (8.0-115.0), 2.3 (1.2-8) and 10.0 minutes (0.3-46.3), respectively. The overall time for VOIs retrieving and modification was statistically significantly lower than for manual contouring (p<0.001). The DL-tool was generally appreciated by ROs, with 44% of vote 4 (well done) and 43% of vote 5 (very well done), correlated with the saved time (p<0.001). The relative volume differences and similarity indexes suggested a better inter-agreement of manually adjusted DL-based VOIs than manually segmented ones. Conclusions: The application of the DL-tool resulted satisfactory, especially in complex delineation cases, improving the ROs inter-agreement of delineated VOIs and saving time.

A novel tool for motion-related dose inaccuracies reduction in 99mTc-MAA SPECT/CT images for SIRT planning.

INTRODUCTION: In Selective Internal Radiation Therapy (SIRT), 90Y is administered to primary/secondary hepatic lesions. An accurate pre-treatment planning using 99mTc-MAA SPECT/CT allows the assessment of its feasibility and of the activity to be injected. Unfortunately, SPECT/CT suffers from patient-specific respiratory motion which causes artifacts and absorbed dose inaccuracies. In this study, a data-driven solution was developed to correct the respiratory motion. METHODS: The tool realigns the barycenter of SPECT projection images and shifts them to obtain a fine registration with the attenuation map. The tool was validated using a modified dynamic phantom with several breathing patterns. We compared the absorbed dose distributions derived from uncorrected(Dm)/corrected(Dc) images with static ones(Ds) in terms of γ-passing rates, 210 Gy isodose volumes, dose-volume histograms and percentage differences of mean doses (i.e., ΔD¯m and ΔD¯c, respectively). The tool was applied to twelve SIRT patients and the Bland-Altman analysis was performed on mean doses. RESULTS: In the phantom study, the agreement between Dc and Ds was higher (γ-passing rates generally > 90%) than Dm and Ds. The isodose volumes in Dc were closer than Dm to Ds, with differences up to 10% and 30% respectively. A reduction from a median ΔD¯m = -19.3% to ΔD¯c = -0.9%, from ΔD¯m = -42.8% to ΔD¯c = -7.0% and from ΔD¯m = 1586% to ΔD¯c = 47.2% was observed in liver-, tumor- and lungs-like structures. The Bland-Altman analysis on patients showed variations (±50 Gy) and (±4 Gy) between D¯c and D¯m of tumor and lungs, respectively. CONCLUSION: The proposed tool allowed the correction of 99mTc-MAA SPECT/CT images, improving the accuracy of the absorbed dose distribution.

Everything You Always Wanted to Know about Sarcopenia but Were Afraid to Ask: A Quick Guide for Radiation Oncologists (Impact of Sarcopenia in Radiotherapy: The AFRAID Project).

Sarcopenia (SP) is a syndrome characterized by age-associated loss of skeletal muscle mass and function. SP worsens both acute and late radiation-induced toxicity, prognosis, and quality of life. Myosteatosis is a pathological infiltration of muscle tissue by adipose tissue which often precedes SP and has a proven correlation with prognosis in cancer patients. Sarcopenic obesity is considered a "hidden form" of SP (due to large fat mass) and is independently related to higher mortality and worse complications after surgery and systemic treatments with worse prognostic impact compared to SP alone. The evaluation of SP is commonly based on CT images at the level of the middle of the third lumbar vertebra. On this scan, all muscle structures are contoured and then the outlined surface area is calculated. Several studies reported a negative impact of SP on overall survival in patients undergoing RT for tumors of the head and neck, esophagus, rectum, pancreas, cervix, and lung. Furthermore, several appetite-reducing side effects of RT, along with more complex radiation-induced mechanisms, can lead to SP through, but not limited to, reduced nutrition. In particular, in pediatric patients, total body irradiation was associated with the onset of SP and other changes in body composition leading to an increased risk of cardiometabolic morbidity in surviving adults. Finally, some preliminary studies showed the possibility of effectively treating SP and preventing the worsening of SP during RT. Future studies should be able to provide information on how to prevent and manage SP before, during, or after RT, in both adult and pediatric patients.

Improving total body irradiation with a dedicated couch and 3D-printed patient-specific lung blocks: A feasibility study.

Introduction: Total body irradiation (TBI) is an important component of the conditioning regimen in patients undergoing hematopoietic stem cell transplants. TBI is used in very few patients and therefore it is generally delivered with standard linear accelerators (LINACs) and not with dedicated devices. Severe pulmonary toxicity is the most common adverse effect after TBI, and patient-specific lead blocks are used to reduce mean lung dose. In this context, online treatment setup is crucial to achieve precise positioning of the lung blocks. Therefore, in this study we aim to report our experience at generating 3D-printed patient-specific lung blocks and coupling a dedicated couch (with an integrated onboard image device) with a modern LINAC for TBI treatment. Material and methods: TBI was planned and delivered (2Gy/fraction given twice a day, over 3 days) to 15 patients. Online images, to be compared with planned digitally reconstructed radiographies, were acquired with the couch-dedicated Electronic Portal Imaging Device (EPID) panel and imported in the iView software using a homemade Graphical User Interface (GUI). In vivo dosimetry, using Metal-Oxide Field-Effect Transistors (MOSFETs), was used to assess the setup reproducibility in both supine and prone positions. Results: 3D printing of lung blocks was feasible for all planned patients using a stereolithography 3D printer with a build volume of 14.5×14.5×17.5 cm3. The number of required pre-TBI EPID-images generally decreases after the first fraction. In patient-specific quality assurance, the difference between measured and calculated dose was generally<2%. The MOSFET measurements reproducibility along each treatment and patient was 2.7%, in average. Conclusion: The TBI technique was successfully implemented, demonstrating that our approach is feasible, flexible, and cost-effective. The use of 3D-printed patient-specific lung blocks have the potential to personalize TBI treatment and to refine the shape of the blocks before delivery, making them extremely versatile.

Dose-Effects Models for Space Radiobiology: An Overview on Dose-Effect Relationships.

Space radiobiology is an interdisciplinary science that examines the biological effects of ionizing radiation on humans involved in aerospace missions. The dose-effect models are one of the relevant topics of space radiobiology. Their knowledge is crucial for optimizing radioprotection strategies (e.g., spaceship and lunar space station-shielding and lunar/Mars village design), the risk assessment of the health hazard related to human space exploration, and reducing damages induced to astronauts from galactic cosmic radiation. Dose-effect relationships describe the observed damages to normal tissues or cancer induction during and after space flights. They are developed for the various dose ranges and radiation qualities characterizing the actual and the forecast space missions [International Space Station (ISS) and solar system exploration]. Based on a Pubmed search including 53 papers reporting the collected dose-effect relationships after space missions or in ground simulations, 7 significant dose-effect relationships (e.g., eye flashes, cataract, central nervous systems, cardiovascular disease, cancer, chromosomal aberrations, and biomarkers) have been identified. For each considered effect, the absorbed dose thresholds and the uncertainties/limitations of the developed relationships are summarized and discussed. The current knowledge on this topic can benefit from further in vitro and in vivo radiobiological studies, an accurate characterization of the quality of space radiation, and the numerous experimental dose-effects data derived from the experience in the clinical use of ionizing radiation for diagnostic or treatments with doses similar to those foreseen for the future space missions. The growing number of pooled studies could improve the prediction ability of dose-effect relationships for space exposure and reduce their uncertainty level. Novel research in the field is of paramount importance to reduce damages to astronauts from cosmic radiation before Beyond Low Earth Orbit exploration in the next future. The study aims at providing an overview of the published dose-effect relationships and illustrates novel perspectives to inspire future research.

Basic of machine learning and deep learning in imaging for medical physicists.

The manuscript aims at providing an overview of the published algorithms/automation tool for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed using the query string to identify the proposed approaches (algorithms/automation tools) for artificial intelligence (machine and deep learning) in a 5-year period. The distribution of manuscript in the various disciplines and the investigated image types according to the AI approaches are presented. The limitation and opportunity of AI application in the clinical practice or in the next future research is discussed.

A novel tool for assessing the correlation of internal/external markers during SGRT guided stereotactic ablative radiotherapy treatments.

INTRODUCTION: An in-house developed tool was implemented and validated to investigate the skin surface, hepatic dome, and target displacement for stereotactic ablative radiotherapy (SABR) of thoracic/abdominal lesions using a Surface Guided Radiation Therapy (SGRT) system combined with 4D- images. MATERIALS AND METHODS: Fourteen consecutive patients with tumors near the hepatic dome undergoing SABR treatments were analyzed. For each patient, a planning 4D-CT and five 4D-CBCT images were acquired. The C-RAD technology was also used to register/monitor the position of the skin reference point (SRP) as an external marker representative of patient breathing. The 4D images were imported in the developed tool, and the absolute maximum height (Pmax,dome) of the hepatic dome on the ten respiratory phases was semi-automatically detected. Similarly, the contour of the skin surface was extracted in correspondence with the SRP position. The tool has been validated using an ad hoc modified moving phantom with pre-selected amplitudes and numbers of cycles. The Pearson correlation coefficients and Bland-Altman plots were calculated. RESULTS: There was a strong correlation between the skin motion amplitude based on 4D-CBCT and the C-RAD in all the patients (0.90 ± 0.08). Similarly, the mean ± SD of Pearson correlation coefficients of skin and Pmax,dome movements registered by 4D-CT and 4D-CBCT were 0.90 ± 0.05 and 0.94 ± 0.05, respectively. The mean ± SD of Pearson correlation coefficients comparing the skin and Pmax,dome displacements within each imaging modality were 0.88 ± 0.05 and 0.90 ± 0.05 for 4D-CT and 4D-CBCT, respectively. The SRP displacement during the set-up imaging and the treatment delivery were similar in all the investigated patients. Similar results were obtained for the ad hoc modified phantom in the preliminary validation phase. CONCLUSION: The strong correlation between the tumor/ hepatic dome and skin displacements confirms that the SGRT approach can be considered appropriate for intra- and inter-fraction motion management in SABR therapy.

Definition of Local Recurrence Site in Resected Pancreatic Adenocarcinoma: A Multicenter Study (DOLORES-1).

The study aimed to generate a local failure (LF) risk map in resected pancreatic cancer (PC) and validate the results of previous studies, proposing new guidelines for PC postoperative radiotherapy clinical target volume (CTV) delineation. Follow-up computer tomography (CT) of resected PC was retrospectively reviewed by two radiologists identifying LFs and plotting them on a representative patient CT scan. The percentages of LF points randomly extracted based on CTV following the RTOG guidelines and based on the LF database were 70% and 30%, respectively. According to the Kernel density estimation, an LF 3D distribution map was generated and compared with the results of previous studies using a Dice index. Among the 64 resected patients, 59.4% underwent adjuvant treatment. LFs closer to the root of the celiac axis (CA) or the superior mesenteric artery (SMA) were reported in 32.8% and 67.2% cases, respectively. The mean (± standard deviation) distances of LF points to CA and SMA were 21.5 ± 17.9 mm and 21.6 ± 12.1 mm, respectively. The Dice values comparing our iso-level risk maps corresponding to 80% and 90% of the LF probabilistic density and the CTVs-80 and CTVs-90 of previous publications were 0.45-0.53 and 0.58-0.60, respectively. According to the Kernel density approach, a validated LF map was proposed, modeling a new adjuvant CTV based on a PC pattern of failure.

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

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

Automatic genetic planning for volumetric modulated arc therapy: A large multi-centre validation for prostate cancer.

PURPOSE: The first clinical genetic autoplanning algorithm (Genetic Planning Solution, GPS) was validated in ten radiotherapy centres for prostate cancer VMAT by comparison with manual planning (Manual). METHODS: Although there were large differences among centres in planning protocol, GPS was tuned with the data of a single centre and then applied everywhere without any centre-specific fine-tuning. For each centre, ten Manual plans were compared with autoGPS plans, considering dosimetric plan parameters and the Clinical Blind Score (CBS) resulting from blind clinician plan comparisons. AutoGPS plans were used as is, i.e. there was no patient-specific fine-tuning. RESULTS: For nine centres, all ten plans were clinically acceptable. In the remaining centre, only one plan was acceptable. For the 91% acceptable plans, differences between Manual and AutoGPS in target coverage were negligible. OAR doses were significantly lower in AutoGPS plans (p < 0.05); rectum D15% and Dmean were reduced by 8.1% and 17.9%, bladder D25% and Dmean by 5.9% and 10.3%. According to clinicians, 69% of the acceptable AutoGPS plans were superior to the corresponding Manual plan. In case of preferred Manual plans (31%), perceived advantages compared to autoGPS were minor. QA measurements demonstrated that autoGPS plans were deliverable. A quick configuration adjustment in the centre with unacceptable plans rendered 100% of plans acceptable. CONCLUSION: A novel, clinically applied genetic autoplanning algorithm was validated in 10 centres for in total 100 prostate cancer patients. High quality plans could be generated at different centres without centre-specific algorithm tuning.

Performance of commercially available deformable image registration platforms for contour propagation using patient-based computational phantoms: A multi-institutional study.

PURPOSE: To investigate the performance of various algorithms for deformable image registration (DIR) to propagate regions of interest (ROIs) using multiple commercial platforms. METHODS AND MATERIALS: Thirteen institutions participated in the study with six commercial platforms: RayStation (RaySearch Laboratories, Stockholm, Sweden), MIM (Cleveland, OH, USA), VelocityAI and Smart Adapt (Varian Medical Systems, Palo Alto, CA, USA), Mirada XD (Mirada Medical Ltd, Oxford, UK), and ABAS (Elekta AB, Stockholm, Sweden). The DIR algorithms were tested on synthetic images generated with the ImSimQA package (Oncology Systems Limited, Shrewsbury, UK) by applying two specific Deformation Vector Fields (DVF) to real patient data-sets. Head-and-neck (HN), thorax, and pelvis sites were included. The accuracy of the algorithms was assessed by comparing the DIR-mapped ROIs from each center with those of reference, using the Dice Similarity Coefficient (DSC) and Mean Distance to Conformity (MDC) metrics. Statistical inference on validation results was carried out in order to identify the prognostic factors of DIR performances. RESULTS: DVF intensity, anatomic site and participating center were significant prognostic factors of DIR performances. Sub-voxel accuracy was obtained in the HN by all algorithms. Large errors, with MDC ranging up to 6 mm, were observed in low-contrast regions that underwent significant deformation, such as in the pelvis, or large DVF with strong contrast, such as the clinical tumor volume (CTV) in the lung. Under these conditions, the hybrid DIR algorithms performed significantly better than the free-form intensity based algorithms and resulted robust against intercenter variability. CONCLUSIONS: The performances of the systems proved to be site specific, depending on the DVF type and the platforms and the procedures used at the various centers. The pelvis was the most challenging site for most of the algorithms, which failed to achieve sub-voxel accuracy. Improved reproducibility was observed among the centers using the same hybrid registration algorithm.

A meta-analysis of the abscopal effect in preclinical models: Is the biologically effective dose a relevant physical trigger?

BACKGROUND: Preclinical in vivo studies using small animals are considered crucial in translational cancer research and clinical implementation of novel treatments. This is of paramount relevance in radiobiology, especially for any technological developments permitted to deliver high doses in single or oligo-fractionated regimens, such as stereotactic ablative radiotherapy (SABR). In this context, clinical success in cancer treatment needs to be guaranteed, sparing normal tissue and preventing the potential spread of disease or local recurrence. In this work we introduce a new dose-response relationship based on relevant publications concerning preclinical models with regard to delivered dose, fractionation schedule and occurrence of biological effects on non-irradiated tissue, abscopal effects. METHODS: We reviewed relevant publications on murine models and the abscopal effect in radiation cancer research following PRISMA methodology. In particular, through a log-likelihood method, we evaluated whether the occurrence of abscopal effects may be related to the biologically effective dose (BED). To this aim, studies accomplished with different tumor histotypes were considered in our analysis including breast, colon, lung, fibrosarcoma, pancreas, melanoma and head and neck cancer. For all the tumors, the α / ß ratio was assumed to be 10 Gy, as generally adopted for neoplastic cells. RESULTS: Our results support the hypothesis that the occurrence rate of abscopal effects in preclinical models increases with BED. In particular, the probability of revealing abscopal effects is 50% when a BED of 60 Gy is generated. CONCLUSION: Our study provides evidence that SABR treatments associated with high BEDs could be considered an effective strategy in triggering the abscopal effect, thus shedding light on the promising outcomes revealed in clinical practice.