Search Results (87)

In recent decades, technological developments in archaeological geophysics have led to growing data volumes, so that an important bottleneck is now at the stage of data interpretation. The manual delineation and classification of anomalies are time-consuming, and different methods for (semi-)automatic image segmentation have been proposed, based on explicitly formulated rulesets or deep convolutional neural networks (DCNNs). So far, these have not been used widely in archaeological geophysics because of the complexity of the segmentation task (due to the low contrast between archaeological structures and background and the low predictability of the targets). Techniques based on shallow machine learning (e.g., random forests, RFs) have been explored very little in archaeological geophysics, although they are less case-specific than most rule-based methods, do not require large training sets as is the case for DCNNs, and can easily handle 3D data. In this paper, we show their potential for geophysical data analysis. For the classification on the pixel level, we use ilastik, an open-source segmentation tool developed in medical imaging. Algorithms for object classification, manual reclassification, post-processing, vectorisation, and georeferencing were brought together in a Jupyter Notebook, available on GitHub (version 7.3.2). To assess the accuracy of the RF classification applied to geophysical datasets, we compare it with manual interpretation. A quantitative evaluation using the mean intersection over union metric results in scores of ~60%, which only slightly increases after the manual correction of the RF classification results. Remarkably, a similar score results from the comparison between independent manual interpretations. This observation illustrates that quantitative metrics are not a panacea for evaluating machine-generated geophysical data interpretation in archaeology, which is characterised by a significant degree of uncertainty. It also raises the question of how the semantic segmentation of geophysical data (whether carried out manually or with the aid of machine learning) can best be evaluated. Full article

This study focuses on the genesis mechanism of thermal anomalies in the southwestern part of the Anan Depression in the Erlian Basin. Based on magnetotelluric 3D inversion data, a high-resolution electrical resistivity structure model was constructed, revealing the spatial configuration of deep heat sources and thermal pathways. The main conclusions are as follows: (1) Magnetotelluric 3D imaging reveals an elliptical low-resistivity anomaly (Anomaly C: 20 km × 16 km × 5 km, 0–5 Ωm) at depths of ~10–15 km. This anomaly is interpreted as a hypersaline fluid (approximately 400 °C, ~1.5% volume fraction, 3–5 wt.% NaCl), acting as the primary heat source. (2) Upward migration along F1/F3 fault conduits (10–40 Ωm) establishes a continuous pathway to mid-depth reservoirs D1/D2 (~5 km, 5–10 Ωm) and shallow crust. An overlying high-resistivity caprock (40–100 Ωm) seals thermal energy, forming a convective “source-conduit-reservoir-cap” system. (3) Integrated seismic data reveal that heat from the Abaga volcanic melt supplements Anomaly C via conduction through these conduits, combining with mantle-derived heat to form a composite source. This research delineates the interacting genesis mechanism of “deep low-resistivity heat source—medium-low resistivity fault conduit—shallow low-resistivity reservoir—relatively high-resistivity cap rock” in the southwestern A’nan Sag, providing a scientific basis for optimizing geothermal exploration targets and assessing resource potential. Full article

Background/Objectives: Lung cancer is the leading cause of cancer-related mortality worldwide. Accurate radiotherapy (RT) planning alongside chemotherapy and immunotherapy is critical for improving treatment outcomes for inoperable non-metastatic cases. Conventional computed tomography (CT)-based planning may be inadequate for accurately identifying tumor margins and the location of nodal disease. We investigated whether ¹⁸F-labeled fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET-CT) imaging can assist in target volume delineation for primary, nodal, and metastatic disease in the RT planning and overall therapeutic planning of patients. Methods: In this single-center, prospective study, we recruited 34 patients with histologically confirmed locally advanced non-small-cell lung carcinoma (NSCLC). All patients underwent ¹⁸F-FDG PET-CT-based RT simulation. Two sequential RT plans were created by the same radiation oncologist: one based on CT alone and the other PET-CT. Planning target volumes (PTVs) and PET-CT-guided adjustments were analyzed to assess their impact. Standardized protocols for immobilization, imaging, target delineation, and dose prescription were applied. Results: A total of 34 patients (31 males and 3 females) were recruited in the study. ¹⁸F-FDG PET-CT detected distant metastases in 7/34 (20.6%) patients, altering the overall therapeutic plan in 4/34 (11.8%) and allowing radical RT in 3 of them who had oligometastatic disease (8.8%). It modified RT planning in 26/34 (76.5%) patients and clarified malignancy in atelectatic areas. Nodal involvement was identified in 3/34 patients (8.8%) and excluded in 3/34 cases, avoiding unnecessary nodal irradiation. Additional involved nodes were revealed in 12/34 (35.3%) patients, requiring dose escalation. Overall, changes to the tumor PTV were made in 23/30 (76.6%) and to the nodal PTV in 19/30 (63.3%) cases (p < 0.0001). Primary tumor and nodal PTVs increased in 20/34 (66.7%) and 13/34 (43.3%), respectively. Conclusions: ¹⁸F-FDG PET-CT significantly improves RT planning by more precisely defining tumor and nodal volumes, identifying undetected lesions, and guiding dose adaptation. Larger long-term studies are required to confirm potential locoregional control and survival improvements. Full article

Background: The re-irradiation of centrally located lung tumors poses substantial risks due to prior dose exposure and proximity to critical structures. Accurate target delineation is crucial to minimize toxicity and ensure tumor coverage. Four-dimensional positron emission tomography/computed tomography (4D-PET/CT) integrates respiratory motion and metabolic data, offering improved delineation over static imaging. Its clinical utility in re-irradiation remains under-reported. Methods: A 67-year-old male presented with the central recurrence of squamous cell carcinoma in the right upper lobe, embedded in radiation-induced fibrosis, following prior chemoradiotherapy. Delineation using static PET underestimated tumor motion. A 4D-PET/CT-guided Stereotactic Body Radiation Therapy (SBRT) plan was developed with a prescription of 60 Gy in eight fractions. A comparative plan using static PET was generated to assess the dosimetric differences. Results: The internal target volume (ITV) from 4D-PET/CT was nearly double the size of the GTV from static PET, with a 5.1 mm discrepancy in the craniocaudal axis. The 4D-PET-based plan achieved 95.0% PTV coverage, while the static PET-based plan covered only 61.7%, illustrating the risk of underdosage without motion-resolved imaging. The patient completed the treatment without acute or late toxicity and showed a sustained metabolic response at one year (SUVmax from 13.4 to 5.8). Conclusions: This case demonstrates the clinical value of 4D-PET/CT in the SBRT re-irradiation of centrally located lung tumors, particularly in fibrotic regions where anatomical imaging is insufficient. It enabled accurate delineation, improved dosimetric coverage, and safe, effective retreatment. These findings support its integration into planning for complex thoracic re-irradiation. Full article

Background and Objectives: Brain radionecrosis is an under-recognized but potentially life-altering late complication of radiotherapy in patients with locally advanced nasopharyngeal cancer. Temporal lobe radionecrosis and high-dose exposure to the hippocampus are strongly associated with cognitive decline and radiation-induced dementia, negatively impacting patients’ long-term quality of life (QoL). This study aimed to evaluate and compare radiation dose distributions to critical brain structures across three radiotherapy techniques—3D conformal radiotherapy (3D-CRT), intensity-modulated radiotherapy (IMRT), and volumetric-modulated arc therapy (VMAT)—in order to assess potential neurocognitive risks and support hippocampal-sparing protocols. Materials and Methods: Ten patients previously treated with 3D-CRT were retrospectively replanned using IMRT and VMAT techniques on the Eclipse v13.3 (VARIAN) planning system. Bilateral hippocampi and temporal lobes were delineated as organs at risk (OARs) according to the RTOG atlas, and dosimetric parameters including D_max, D_mean, and D_min were recorded. V7.3 values were evaluated for hippocampal avoidance regions. Results: While IMRT and VMAT provided improved target volume coverage and reduced high-dose exposure to many standard OARs, both techniques were associated with increased D_mean and D_min to the hippocampus and temporal lobes compared to 3D-CRT. The highest D_max values to the temporal lobes were observed in 3D-CRT plans, indicating a potential risk of radionecrosis. VMAT plans showed hippocampal mean doses exceeding 10 Gy in some cases, with V7.3 > 40%, breaching established neurocognitive risk thresholds. Conclusions: These findings support the routine delineation of the hippocampus and temporal lobes as OARs in radiotherapy planning for nasopharyngeal cancer. The implementation of hippocampal-sparing strategies, particularly in IMRT and VMAT, is recommended to reduce the risk of radiation-induced cognitive toxicity and preserve long-term QoL in survivors. Full article

Prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA-PET/CT) has emerged as a game-changing imaging modality in prostate cancer, offering superior sensitivity and specificity compared to conventional imaging techniques. Its increasing adoption has significantly influenced radiotherapy decision-making, yet its true clinical impact remains under investigation. This narrative review explores the role of PSMA-PET/CT in guiding radiotherapy decisions across different clinical scenarios, from primary treatment planning to biochemical recurrence and oligometastatic disease. We assess its impact on target delineation, treatment modifications, and overall patient management while addressing existing knowledge gaps. Full article

Goal: This study evaluates the feasibility and outcome of a personalized MRI-based liver SBRT treatment planning platform with the SPION contrast agent Ferumoxytol^® (Sandoz Inc.; Princeton, NJ, USA) to maintain a superior real-time visualization of liver tumors and volumes of functional hepatic parenchyma for radiotherapy planning throughout multi-fractionated liver SBRT with online plan adaptations on an Elekta Unity 1.5 T MR-Linac (Elekta; Stockholm, Sweden). Materials and Methods: Patients underwent SPION-enhanced MRI on the Elekta Unity MR-Linac for improved tumor and functional hepatic parenchyma visualization. An automated contouring algorithm was applied for the delineation and subsequent guided avoidance of functional liver parenchyma volumes (FLVs) on the SPION-enhanced MR-Linac. Radiation dose constraints were adapted exclusively to FLV. Local control, toxicity, and survival were assessed with at least 6-month radiographic follow-up. Pre- and post-transplant outcomes were analyzed in the subset of patients with HCC and hepatic cirrhosis who completed SBRT as a bridge to liver transplant. Model of End-Stage Liver Disease (MELD-Na) was used to score hepatic function before and after SBRT. Results: With a median follow-up of 23 months (range: 3–40 months), 23 HCC patients (26 lesions treated) and 9 patients (14 lesions treated) with hepatic metastases received SBRT (mean dose: 48 Gy, range: 36–54 Gy) in 1–5 fractions. Nearly all patients in this study had pe-existing liver conditions, including hepatic cirrhosis (23), prior TACE (7), prior SBRT (18), or history of hepatic resection (2). Compared to the non-contrast images, SPIONs improved tumor visibility on post-SPION images on the background of negatively enhancing functionally active hepatic parenchyma. Prolonged SPION-contrast retention within hepatic parenchyma enabled per-fraction treatment adaptation throughout the entire multi-fraction treatment course. FLV loss (53%, p < 0.0001) was observed in cirrhotic patients, but functional and anatomic liver volumes remained consistent in non-cirrhotic patients. Mean dose to FLV was maintained within the liver threshold tolerance to radiation in all patients after the optimization of Step-and-Shoot Intensity-Modulated Radiotherapy (SS-IMRT) on the SPION-enhanced MRI-Linac. No radiation-induced liver disease was observed within 6 months post-SBRT, and the MELD-Na score in cirrhotic patients was not significantly elevated at 3-month intervals after SBRT completion. Conclusions: SPION Ferumoxytol^® administered intravenously as an alternative MRI contrast agent on the day of SBRT planning produces a long-lasting contrast effect between tumors and functional hepatic parenchyma for precision targeting and guided avoidance during the entire course of liver SBRT, enabling fast and accurate online plan adaptation on the 1.5 T Elekta Unity MR-Linac. This approach demonstrates a safe and effective bridging therapy for patients with hepatic cirrhosis, leading to low toxicity and favorable transplant outcomes. Full article

As yet, there is no systematic review focusing on benefits and issues of commercial deep learning-based auto-segmentation (DLAS) software for prostate cancer (PCa) radiation therapy (RT) planning despite that NRG Oncology has underscored such necessity. This article’s purpose is to systematically review commercial DLAS software product performances for PCa RT planning and their associated evaluation methodology. A literature search was performed with the use of electronic databases on 7 November 2024. Thirty-two articles were included as per the selection criteria. They evaluated 12 products (Carina Medical LLC INTContour (Lexington, KY, USA), Elekta AB ADMIRE (Stockholm, Sweden), Limbus AI Inc. Contour (Regina, SK, Canada), Manteia Medical Technologies Co. AccuContour (Jian Sheng, China), MIM Software Inc. Contour ProtégéAI (Cleveland, OH, USA), Mirada Medical Ltd. DLCExpert (Oxford, UK), MVision.ai Contour+ (Helsinki, Finland), Radformation Inc. AutoContour (New York, NY, USA), RaySearch Laboratories AB RayStation (Stockholm, Sweden), Siemens Healthineers AG AI-Rad Companion Organs RT, syngo.via RT Image Suite and DirectORGANS (Erlangen, Germany), Therapanacea Annotate (Paris, France), and Varian Medical Systems, Inc. Ethos (Palo Alto, CA, USA)). Their results illustrate that the DLAS products can delineate 12 organs at risk (abdominopelvic cavity, anal canal, bladder, body, cauda equina, left (L) and right (R) femurs, L and R pelvis, L and R proximal femurs, and sacrum) and four clinical target volumes (prostate, lymph nodes, prostate bed, and seminal vesicle bed) with clinically acceptable outcomes, resulting in delineation time reduction, 5.7–81.1%. Although NRG Oncology has recommended each clinical centre to perform its own DLAS product evaluation prior to clinical implementation, such evaluation seems more important for AccuContour and Ethos due to the methodological issues of the respective single studies, e.g., small dataset used, etc. Full article

Background: Intra-arterial cerebral infusion (IACI) of radiotherapeutics is a promising treatment for glioblastoma (GBM) recurrence. We investigated the in silico feasibility and safety of Yttrium-90-Poly(vinyl alcohol)-Microbubble (⁹⁰Y-PVA-MB) IACI in patients with recurrent GBM and compared the results with those of external beam radiation therapy (EBRT). Methods: Contrast-enhanced T1-weighted magnetic resonance imaging (T1W-MRI) was used to delineate the tumor volumes and CT scans were used to automatically segment the organs at risk in nine patients with recurrent GBM. Volumetric Modulated Arc Therapy (VMAT) treatment plans were generated using a clinical treatment planning system. Assuming the relative intensity of each voxel from the MR-T1W as a valid surrogate for the post-IACI ⁹⁰Y-PVA-MB distribution, a specific ⁹⁰Y dose voxel kernel was obtained through Monte Carlo (MC) simulations and convolved with the MRI, resulting in a ⁹⁰Y-PVA-MB-based dose distribution that was then compared with the VMAT plans. Results: The physical dose distribution obtained from the simulation of 1GBq of ⁹⁰Y-PVA-MBs was rescaled to ensure that 95% of the prescribed dose was delivered to 95% or 99% of the target (i.e., A95% and A99%, respectively). The calculated activities were A95% = 269.2 [63.6–2334.1] MBq and A99% = 370.6 [93.8–3315.2] MBq, while the mean doses to the target were 58.2 [58.0–60.0] Gy for VMAT, and 123.1 [106.9–153.9] Gy and 170.1 [145.9–223.8] Gy for A95% and A99%, respectively. Additionally, non-target brain tissue was spared in the ⁹⁰Y-PVA-MB treatment compared to the VMAT approach, with a median [range] of mean doses of 12.5 [12.0–23.0] Gy for VMAT, and 0.6 [0.2–1.0] Gy and 0.9 [0.3–1.5] Gy for the ⁹⁰Y treatments assuming A95% and A99%, respectively. Conclusions: ⁹⁰Y-PVA-MB IACI using MR-T1W appears to be feasible and safe, as it enables the delivery of higher doses to tumors and lower doses to non-target volumes compared to the VMAT approach. Full article

This article presents the results obtained from a high-resolution wide-azimuthal 3D seismic reflection method used for the prediction and detailed exploration of complex ore targets in the Zhezkazgan ore district of Central Kazakhstan. We demonstrate the ability of modern seismic data processing and interpretation systems to identify underground mine objects associated with stratiform copper sandstones and improve geological models. The 3D seismic imaging tools, along with the implementation of a modern seismic processing sequence, allow for the clarification of geological structures in the studied area. The target stratigraphic horizons, large faults, and microtectonic disturbances (small faults and cracks) are clearly delineated in the seismic volumes. The use of seismic attribute analyses on geological data is tested to identify ore horizons and deposits with volumetric predictions of copper mineralization. Recommendations for further exploration drilling were developed, and five new wells were drilled. Copper mineralization was confirmed in all recommended wells. We carried out a marketing review in Kazakhstan and uncovered an increased interest among subsoil use companies in 3D seismic exploration technology to investigate existing mining objects of different genetic types. These results demonstrate the expediency of 3D seismic exploration aimed at identifying ore targets. Full article

As yet, no systematic review on commercial deep learning-based auto-segmentation (DLAS) software for breast cancer radiation therapy (RT) planning has been published, although NRG Oncology has highlighted the necessity for such. The purpose of this systematic review is to investigate the performances of commercial DLAS software packages for breast cancer RT planning and methods for their performance evaluation. A literature search was conducted with the use of electronic databases. Fifteen papers met the selection criteria and were included. The included studies evaluated eight software packages (Limbus Contour, Manteia AccuLearning, Mirada DLCExpert, MVision.ai Contour+, Radformation AutoContour, RaySearch RayStation, Siemens syngo.via RT Image Suite/AI-Rad Companion Organs RT, and Therapanacea Annotate). Their findings show that the DLAS software could contour ten organs at risk (body, contralateral breast, esophagus-overlapping area, heart, ipsilateral humeral head, left and right lungs, liver, and sternum and trachea) and three clinical target volumes (CTVp_breast, CTVp_chestwall, and CTVn_L1) up to the clinically acceptable standard. This can contribute to 45.4%–93.7% contouring time reduction per patient. Although NRO Oncology has suggested that every clinical center should conduct its own DLAS software evaluation before clinical implementation, such testing appears particularly crucial for Manteia AccuLearning, Mirada DLCExpert, and MVision.ai Contour+ as a result of the methodological weaknesses of the corresponding studies such as the use of small datasets collected retrospectively from single centers for the evaluation. Full article

Background/Objectives: To present the technical aspects of contrast-enhanced 4DCT (ce4DCT) simulation for abdominal SBRT. Methods: Twenty-two patients underwent two sequential 4DCT scans: one baseline and one contrast-enhanced with personalized delay time (t_delay) calculated to capture the tumor in the desired contrast phase, based on diagnostic triple-phase CT. The internal target volume (ITV) was delineated on ten contrast phases, and a panel of three experts qualitatively evaluated tumor visibility. Aortic HU values were measured to refine the t_delay for subsequent patients. The commonly used approach of combining triple-phase CT with unenhanced 4DCT was simulated, and differences in target delineation were evaluated by volume, centroid shift, Dice and Jaccard indices, and mean distance agreement (MDA). The margins required to account for motion were calculated. Results: The ce4DCT acquisitions substantially improved tumor visibility over the entire breathing cycle in 20 patients, according to the experts’ unanimous evaluation. The median contrast peak time was 54.5 s, and the washout plateau was observed at 70.3 s, with mean peak and plateau HU values of 292 ± 59 and 169 ± 25. The volumes from the commonly used procedure (ITV2) were significantly smaller than the ce4DCT volumes (ITV1) (p = 0.045). The median centroid shift was 4.7 mm. The ITV1-ITV2 overlap was 69% (Dice index), 53% (Jaccard index), and 2.89 mm (MDA), with the liver volumes showing significantly lower indices compared to the pancreatic volumes (p ≤ 0.011). The margins required to better encompass ITV1 were highly variable, with mean values ≥ 4 mm in all directions except for the left–right axis. Conclusions: The ce4DCT simulation was feasible, resulting in optimal tumor enhancement with minimal resource investment, while significantly mitigating uncertainties in SBRT planning by addressing poor visibility and respiratory motion. Triple-phase 3DCT with unenhanced 4DCT led to high variability in target delineation, making the isotropic margins ineffective. Full article

Using a novel joint inversion approach, this study tackles the challenge of accurately characterizing subsurface electrical resistivity in vineyards, a critical and strategic aspect of precision viticulture. For the first time, we integrate 3D Galvanic Contact Resistivity with multi-2D Capacitively Coupled Resistivity data. Conducted in a prestigious Sangiovese vineyard in Montalcino (Tuscany, Italy), the data are analyzed utilizing a single algorithm capable of inverting Capacitively Coupled Resistivity, Galvanic Contact Resistivity, and joint datasets. This approach combines data sensitive to different depths and spatial resolutions, resulting in a comprehensive analysis of soil resistivity variations and moisture distribution, thus providing a detailed and coherent subsurface model. The joint inversion produced a high spatial resolution 3D resistivity model with a density of 20.21 data/m³. This model significantly enhances subsurface characterization, delineating root systems and correlating water distribution with resistivity patterns, showing relative variations sometimes greater than 50%. This method reduced data misfit more effectively than individual inversions and identified a low-resistivity volume (<20 Ω·m), extending from northeast to south, indicating the presence of subsurface water. The systematic alternation of high and low resistivity across vineyard rows highlights the impact of soil management activities on resistivity and supports targeted interventions for vineyard health. Full article

Groundwater depletion in Bangladesh’s Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km² study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km²), 47.68% (3617.13 km²), 37.12% (2816.13 km²), and 5.97% (452.70 km²) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 × 10⁶ m³/year, constituting 22.7% of the total precipitation volume (11,227 × 10⁶ m³/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200–1400 mm/year) and high slope (6–40%). Conversely, very good recharge potential is associated with high rainfall zones (1800–2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation. Full article

Background/Objectives: The objective of this study was to assess the connection between the systemic inflammation response index (SIRI) values and failure patterns of patients with IDH wild-type glioblastoma (GB) who underwent radiotherapy (RT) with FLAIR-based gross tumor volume (GTV) delineation. Methods: Seventy-one patients who received RT at a dose of 60 Gy to the GTV and 50 Gy to the clinical target volume (CTV) and had documented recurrence were retrospectively analyzed. Each patient’s maximum distance of recurrence (MDR) from the GTV was documented in whichever plane it extended the farthest. The failure patterns were described as intra-GTV, in-CTV/out-GTV, distant, and intra-GTV and distant. For analytical purposes, the failure pattern was categorized into two groups, namely Group 1, intra-GTV or in-CTV/out-GTV, and Group 2, distant or intra-GTV and distant. The SIRI was calculated before surgery and corticosteroid administration. A receiver operating characteristic (ROC) curve analysis was used to determine the optimal SIRI cut-off that distinguishes between the different failure patterns. Results: Failure occurred as follows: intra-GTV in 40 (56.3%), in-CTV/out-GTV in 4 (5.6%), distant in 18 (25.4%), and intra-GTV + distant in 9 (12.7%) patients. The mean MDR was 13.5 mm, and recurrent lesions extended beyond 15 mm in only seven patients. Patients with an SIRI score ≥ 3 demonstrated a significantly higher incidence of Group 1 failure patterns than their counterparts with an SIRI score < 3 (74.3% vs. 50.0%; p = 0.035). Conclusions: The present results show that using the SIRI with a cut-off value of ≥3 significantly predicts failure patterns. Additionally, the margin for the GTV can be safely reduced to 15 mm when using FLAIR-based target delineation in patients with GB. Full article