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Quality of organ at risk (OAR) autosegmentation is often judged by concordance metrics against the human-generated gold standard.However, the ultimate goal is the ability to use unedited autosegmented OARs in treatment planning,while maintaining the plan quality.We tested this approach with head and neck (HN) OARs generated by a prototype deep-learning (DL) model on patients previously treated for oropharyngeal and laryngeal cancer. Forty patients were selected, with all structures delineated by an experienced physician. For each patient, a set of 13 OARs were generated by the DL model. Each patient was re-planned based on original targets and unedited DL-produced OARs.The new dose distributions were then applied back to the manually delineated structures. The target coverage was evaluated with inhomogeneity index (II) and the relative volume of regret. For the OARs, Dice similarity coefficient (DSC) of areas under the DVH curves, individual DVH objectives, and composite continuous plan quality metric (PQM) were compared. The nearly identical primary target coverage for the original and re-generated plans was achieved, with the same II and relative volume of regret values. The average DSC of the areas under the corresponding pairs of DVH curves was 0.97 ± 0.06. The number of critical DVH points which met the clinical objectives with the dose optimized on autosegmented structures but failed when evaluated on the manual ones was 5 of 896 (0.6%). The average OAR PQM score with the re-planned dose distributions was essentially the same when evaluated either on the autosegmented or manual OARs. Thus, rigorous HN treatment planning is possible with OARs segmented by a prototype DL algorithm with minimal, if any, manual editing. [ABSTRACT FROM AUTHOR]

Purpose: A planning strategy was developed and the utility of online‐adaptation with the Ethos CBCT‐guided ring‐gantry adaptive radiotherapy (ART) system was evaluated using retrospective data from Head‐and‐neck (H&N) patients that required clinical offline adaptation during treatment. Methods: Clinical data were used to re‐plan 20 H&N patients (10 sequential boost (SEQ) with separate base and boost plans plus 10 simultaneous integrated boost (SIB)). An optimal approach, robust to online adaptation, for Ethos‐initial plans using clinical goal prioritization was developed. Anatomically‐derived isodose‐shaping helper structures, air‐density override, goals for controlling hotspot location(s), and plan normalization were investigated. Online adaptation was simulated using clinical offline adaptive simulation‐CTs to represent an on‐treatment CBCT. Dosimetric comparisons were based on institutional guidelines for Clinical‐initial versus Ethos‐initial plans and Ethos‐scheduled versus Ethos‐adapted plans. Timing for five components of the online adaptive workflow was analyzed. Results: The Ethos H&N planning approach generated Ethos‐initial SEQ plans with clinically comparable PTV coverage (average PTVHigh V100% = 98.3%, Dmin,0.03cc = 97.9% and D0.03cc = 105.5%) and OAR sparing. However, Ethos‐initial SIB plans were clinically inferior (average PTVHigh V100% = 96.4%, Dmin,0.03cc = 93.7%, D0.03cc = 110.6%). Fixed‐field IMRT was superior to VMAT for 93.3% of plans. Online adaptation succeeded in achieving conformal coverage to the new anatomy in both SEQ and SIB plans that was even superior to that achieved in the initial plans (which was due to the changes in anatomy that simplified the optimization). The average adaptive workflow duration for SIB, SEQ base and SEQ boost was 30:14, 22.56, and 14:03 (min: sec), respectively. Conclusions: With an optimal planning approach, Ethos efficiently auto‐generated dosimetrically comparable and clinically acceptable initial SEQ plans for H&N patients. Initial SIB plans were inferior and clinically unacceptable, but adapted SIB plans became clinically acceptable. Online adapted plans optimized dose to new anatomy and maintained target coverage/homogeneity with improved OAR sparing in a time‐efficient manner. [ABSTRACT FROM AUTHOR]

Simple Summary: Magnetic resonance imaging (MRI) has several advantages over computerized tomography (CT) in the treatment planning of central nervous system (CNS) malignancies. The adoption of hybrid MRI and linear accelerators (MRLs) has allowed for more effective tumor control and reduced unnecessary neurotoxicity through precise daily adaptations. In this review, we provide a summary of the evidence for MRLs in the management of various CNS tumors. Additionally, we discuss the potential of multiparametric MRI and genomically guided radiotherapy to enhance patient outcomes. Magnetic resonance imaging (MRI) provides excellent visualization of central nervous system (CNS) tumors due to its superior soft tissue contrast. Magnetic resonance-guided radiotherapy (MRgRT) has historically been limited to use in the initial treatment planning stage due to cost and feasibility. MRI-guided linear accelerators (MRLs) allow clinicians to visualize tumors and organs at risk (OARs) directly before and during treatment, a process known as online MRgRT. This novel system permits adaptive treatment planning based on anatomical changes to ensure accurate dose delivery to the tumor while minimizing unnecessary toxicity to healthy tissue. These advancements are critical to treatment adaptation in the brain and spinal cord, where both preliminary MRI and daily CT guidance have typically had limited benefit. In this narrative review, we investigate the application of online MRgRT in the treatment of various CNS malignancies and any relevant ongoing clinical trials. Imaging of glioblastoma patients has shown significant changes in the gross tumor volume over a standard course of chemoradiotherapy. The use of adaptive online MRgRT in these patients demonstrated reduced target volumes with cavity shrinkage and a resulting reduction in radiation dose to uninvolved tissue. Dosimetric feasibility studies have shown MRL-guided stereotactic radiotherapy (SRT) for intracranial and spine tumors to have potential dosimetric advantages and reduced morbidity compared with conventional linear accelerators. Similarly, dosimetric feasibility studies have shown promise in hippocampal avoidance whole brain radiotherapy (HA-WBRT). Next, we explore the potential of MRL-based multiparametric MRI (mpMRI) and genomically informed radiotherapy to treat CNS disease with cutting-edge precision. Lastly, we explore the challenges of treating CNS malignancies and special limitations MRL systems face. [ABSTRACT FROM AUTHOR]

Simple Summary: Stereotactic body radiotherapy (SBRT) is an effective radiation therapy technique that heavily relies upon daily image guidance to achieve the necessary precision. Magnetic resonance imaging (MRI) offers significant advantages over computed tomography (CT), which has traditionally been used for daily image guidance for SBRT. Hybrid MRI and linear accelerators (MRLs) allow for the delivery of stereotactic MR-guided adaptive radiotherapy (SMART) and improve patient outcomes for many types of tumors. In this review, we summarized the evidence for SMART as it related to ablative treatments and explored how multi-parametric MRIs could continue to improve patient outcomes. Stereotactic body radiotherapy (SBRT) is an effective radiation therapy technique that has allowed for shorter treatment courses, as compared to conventionally dosed radiation therapy. As its name implies, SBRT relies on daily image guidance to ensure that each fraction targets a tumor, instead of healthy tissue. Magnetic resonance imaging (MRI) offers improved soft-tissue visualization, allowing for better tumor and normal tissue delineation. MR-guided RT (MRgRT) has traditionally been defined by the use of offline MRI to aid in defining the RT volumes during the initial planning stages in order to ensure accurate tumor targeting while sparing critical normal tissues. However, the ViewRay MRIdian and Elekta Unity have improved upon and revolutionized the MRgRT by creating a combined MRI and linear accelerator (MRL), allowing MRgRT to incorporate online MRI in RT. MRL-based MR-guided SBRT (MRgSBRT) represents a novel solution to deliver higher doses to larger volumes of gross disease, regardless of the proximity of at-risk organs due to the (1) superior soft-tissue visualization for patient positioning, (2) real-time continuous intrafraction assessment of internal structures, and (3) daily online adaptive replanning. Stereotactic MR-guided adaptive radiation therapy (SMART) has enabled the safe delivery of ablative doses to tumors adjacent to radiosensitive tissues throughout the body. Although it is still a relatively new RT technique, SMART has demonstrated significant opportunities to improve disease control and reduce toxicity. In this review, we included the current clinical applications and the active prospective trials related to SMART. We highlighted the most impactful clinical studies at various tumor sites. In addition, we explored how MRL-based multiparametric MRI could potentially synergize with SMART to significantly change the current treatment paradigm and to improve personalized cancer care. [ABSTRACT FROM AUTHOR]

The treatment of central and ultracentral lung tumors with radiotherapy remains an ongoing clinical challenge. The risk of Grade 5 toxicity with ablative radiotherapy doses to these high-risk regions is significant as shown in recent prospective studies. Magnetic resonance (MR) image-guided adaptive radiotherapy (MRgART) is a new technology and may allow the delivery of ablative radiotherapy to these high-risk regions safely. MRgART is able to achieve this by utilizing small treatment margins, real-time gating/tracking and on-table plan adaptation to maintain dose to the tumor but limit dose to critical structures. The process of MRgART is complex and has nuances and challenges for the treatment of lung tumors. We outline the critical steps needed for appropriate delivery of MRgART for lung tumors safely and effectively. [ABSTRACT FROM AUTHOR]

Purpose: Radiomics entails the extraction of quantitative imaging biomarkers (or radiomics features) hypothesized to provide additional pathophysiological and/or clinical information compared to qualitative visual observation and interpretation. This retrospective study explores the variability of radiomics features extracted from images acquired with the 0.35 T scanner of an integrated MRI-Linac. We hypothesized we would be able to identify features with high repeatability and reproducibility over various imaging conditions using phantom and patient imaging studies. We also compared findings from the literature relevant to our results. Methods: Eleven scans of a Magphan® RT phantom over 13 months and 11 scans of a ViewRay Daily QA phantom over 11 days constituted the phantom data. Patient datasets included 50 images from ten anonymized stereotactic body radiation therapy (SBRT) pancreatic cancer patients (50 Gy in 5 fractions). A True Fast Imaging with Steady-State Free Precession (TRUFI) pulse sequence was selected, using a voxel resolution of 1.5 mm × 1.5 mm × 1.5 mm and 1.5 mm × 1.5 mm × 3.0 mm for phantom and patient data, respectively. A total of 1087 shape-based, first, second, and higher order features were extracted followed by robustness analysis. Robustness was assessed with the Coefficient of Variation (CoV < 5%). Results: We identified 130 robust features across the datasets. Robust features were found within each category, except for 2 second-order sub-groups, namely, Gray Level Size Zone Matrix (GLSZM) and Neighborhood Gray Tone Difference Matrix (NGTDM). Additionally, several robust features agreed with findings from other stability assessments or predictive performance studies in the literature. Conclusion: We verified the stability of the 0.35 T scanner of an integrated MRI-Linac for longitudinal radiomics phantom studies and identified robust features over various imaging conditions. We conclude that phantom measurements can be used to identify robust radiomics features. More stability assessment research is warranted. [ABSTRACT FROM AUTHOR]

Head and neck cancers present challenges in radiation treatment planning due to the large number of critical structures near the target(s) and highly heterogeneous tissue composition. While Monte Carlo (MC) dose calculations currently offer the most accurate approximation of dose deposition in tissue, the switch to MC presents challenges in preserving the parameters of care. The differences in dose‐to‐tissue were widely discussed in the literature, but mostly in the context of recalculating the existing plans rather than reoptimizing with the MC dose engine. Also, the target dose homogeneity received less attention. We adhere to strict dose homogeneity objectives in clinical practice. In this study, we started with 21 clinical volumetric‐modulated arc therapy (VMAT) plans previously developed in Pinnacle treatment planning system. Those plans were recalculated "as is" with RayStation (RS) MC algorithm and then reoptimized in RS with both collapsed cone (CC) and MC algorithms. MC statistical uncertainty (0.3%) was selected carefully to balance the dose computation time (1–2 min) with the planning target volume (PTV) dose‐volume histogram (DVH) shape approaching that of a "noise‐free" calculation. When the hot spot in head and neck MC‐based treatment planning is defined as dose to 0.03 cc, it is exceedingly difficult to limit it to 105% of the prescription dose, as we were used to with the CC algorithm. The average hot spot after optimization and calculation with RS MC was statistically significantly higher compared to Pinnacle and RS CC algorithms by 1.2 and 1.0 %, respectively. The 95% confidence interval (CI) observed in this study suggests that in most cases a hot spot of ≤107% is achievable. Compared to the 95% CI for the previous clinical plans recalculated with RS MC "as is" (upper limit 108%), in real terms this result is at least as good or better than the historic plans. [ABSTRACT FROM AUTHOR]

Purpose: To monitor intrafraction motion during spine stereotactic body radiotherapy(SBRT) treatment delivery with readily available technology, we implemented triggered kV imaging using the on-board imager(OBI) of a modern medical linear accelerator with an advanced imaging package. Methods: Triggered kV imaging for intrafraction motion management was tested with an anthropomorphic phantom and simulated spine SBRT treatments to the thoracic and lumbar spine. The vertebral bodies and spinous processes were contoured as the image guided radiotherapy(IGRT) structures specific to this technique. Upon each triggered kV image acquisition, 2D projections of the IGRT structures were automatically calculated and updated at arbitrary angles for display on the kV images. Various shifts/rotations were introduced in x, y, z, pitch, and yaw. Gantry-angle-based triggering was set to acquire kV images every 45°. A group of physicists/physicians(n = 10) participated in a survey to evaluate clinical efficiency and accuracy of clinical decisions on images containing various phantom shifts. This method was implemented clinically for treatment of 42 patients(94 fractions) with 15 second time-based triggering. Result: Phantom images revealed that IGRT structure accuracy and therefore utility of projected contours during triggered imaging improved with smaller CT slice thickness. Contouring vertebra superior and inferior to the treatment site was necessary to detect clinically relevant phantom rotation. From the survey, detectability was proportional to the shift size in all shift directions and inversely related to the CT slice thickness. Clinical implementation helped evaluate robustness of patient immobilization. Based on visual inspection of projected IGRT contours on planar kV images, appreciable intrafraction motion was detected in eleven fractions(11.7%). Discussion: Feasibility of triggered imaging for spine SBRT intrafraction motion management has been demonstrated in phantom experiments and implementation for patient treatments. This technique allows efficient, non-invasive monitoring of patient position using the OBI and patient anatomy as a direct visual guide. [ABSTRACT FROM AUTHOR]

Purpose: To investigate (i) the dosimetric leaf gap (DLG) and the effect of the "trailing distance" between leaves from different multileaf collimator (MLC) layers in Halcyon systems and (ii) the ability of the currently available treatment planning systems (TPSs) to approximate this effect. Methods: DICOM plans with transmission beams and sweeping gap tests were created in Python for measuring the DLG for each MLC layer independently and for both layers combined. In clinical Halcyon plans both MLC layers are interchangeably used and leaves from different layers are offset, thus forming a trailing pattern. To characterize the impact of such configuration, new tests called "trailing sweeping gaps" were designed and created where the leaves from one layer follow the leaves from the other layer at a fixed "trailing distance" t between the tips. Measurements were carried out on five Halcyons SX2 from different institutions and calculations from both the Eclipse and RayStation TPSs were compared with measurements. Results: The dose accumulated during a sweeping gap delivery progressively increased with the trailing distance t. We call this "the trailing effect." It is most pronounced for t between 0 and 5 mm, although some changes were obtained up to 20 mm. The dose variation was independent of the gap size. The measured DLG values also increased with t up to 20 mm, again with the steepest variation between 0 and 5 mm. Measured DLG values were negative at t = 0 (the leaves from both layers at the same position) but changed sign for t ≥ 1 mm, in line with the positive DLG sign usually observed with single‐layer rounded‐end MLCs. The Eclipse TPS does not explicitly model the leaf tip and, as a consequence, could not predict the dose reduction due to the trailing effect. This resulted in dose discrepancies up to +10% and −8% for the 5 mm sweeping gap and up to ±5% for the 10 mm one depending on the distance t. RayStation implements a simple model of the leaf tip that was able to approximate the trailing effect and improved the agreement with measured doses. In particular, with a prototype version of RayStation that assigned a higher transmission at the leaf tip the agreement with measured doses was within ±3% even for the 5 mm gap. The five Halcyon systems behaved very similarly but differences in the DLG around 0.2 mm were found across different treatment units and between MLC layers from the same system. The DLG for the proximal layer was consistently higher than for the distal layer, with differences ranging between 0.10 mm and 0.24 mm. Conclusions: The trailing distance between the leaves from different layers substantially affected the doses delivered by sweeping gaps and the measured DLG values. Stacked MLCs introduce a new level of complexity in TPSs, which ideally need to implement an explicit model of the leaf tip in order to reproduce the trailing effect. Dynamic tests called "trailing sweeping gaps" were designed that are useful for characterizing and commissioning dual‐layer MLC systems. [ABSTRACT FROM AUTHOR]

The main focus of the recommended spatial accuracy tests for the multi‐leaf collimators (MLC) is calibration of the leaf position along the movement direction and overall alignment to the radiation isocenter. No explicit attention was typically paid to the alignment of the leaves from the opposing banks in the direction orthogonal to movement. This paper is a case study demonstrating that verification of such alignment at the time of acceptance testing is prudent. The original standard MLC (SMLC) on an MRIdian MRI‐guided linac (ViewRay Inc., Mountain View, CA, USA) was upgraded to a high‐speed MLC (HSMLC), which is supposed to be mechanically identical to the SMLC except for the higher drive screw pitch. The results of the end‐to‐end IMRT tests demonstrated unacceptable dosimetric results exemplified by an average and maximum ion chamber (IC) point dose error in the high‐dose low‐gradient region of 2.5 ± 1.4% and 4.6%, respectively. Before the upgrade, those values were 0.3 ± 0.7% and 0.9%, respectively. An exhaustive analysis of possible failure modes eventually zeroed in on the average misalignment of about 1 mm in the Y (along the couch) direction between the right and left upper MLC banks. The MLC was replaced, reducing the Y‐direction misalignment to 0.4 mm. As a result, the average and maximum IC dose‐errors became acceptable 1.0 ± 0.7% and 1.6%, respectively. Simple film and/or chamber array tests during acceptance testing can easily detect Y‐direction misalignments between opposing leaves banks measuring a fraction of a mm at isocenter. Left undetected, such misalignment can cause nontrivial dosimetric consequences. [ABSTRACT FROM AUTHOR]

Abstract Purpose Frequently, three-dimensional (3D) conformal beams are used in lung cancer stereotactic body radiotherapy (SBRT). Recently, volumetric modulated arc therapy (VMAT) was introduced as a new treatment modality. VMAT techniques shorten delivery time, reducing the possibility of intrafraction target motion. However dose distributions can be quite different from standard 3D therapy. This study quantifies those differences, with focus on VMAT plans using unflattened photon beams. Methods A total of 15 lung cancer patients previously treated with 3D or VMAT SBRT were randomly selected. For each patient, non-coplanar 3D, coplanar and non-coplanar VMAT and flattening filter free VMAT (FFF-VMAT) plans were generated to meet the same objectives with 50 Gy covering 95% of the PTV. Two dynamic arcs were used in each VMAT plan. The couch was set at ± 5° to the 0° straight position for the two non-coplanar arcs. Pinnacle version 9.0 (Philips Radiation Oncology, Fitchburg WI) treatment planning system with VMAT capabilities was used. We analyzed the conformity index (CI), which is the ratio of the total volume receiving at least the prescription dose to the target volume receiving at least the prescription dose; the conformity number (CN) which is the ratio of the target coverage to CI; and the gradient index (GI) which is the ratio of the volume of 50% of the prescription isodose to the volume of the prescription isodose; as well as the V20, V5, and mean lung dose (MLD). Paired non-parametric analysis of variance tests with post-tests were performed to examine the statistical significance of the differences of the dosimetric indices. Results Dosimetric indices CI, CN and MLD all show statistically significant improvement for all studied VMAT techniques compared with 3D plans (p < 0.05). V5 and V20 show statistically significant improvement for the FFF-VMAT plans compared with 3D (p < 0.001). GI is improved for the FFF-VMAT and the non-coplanar VMAT plans (p < 0.01 and p < 0.05 respectively) while the coplanar VMAT plans do not show significant difference compared to 3D plans. Dose to the target is typically more homogeneous in FFF-VMAT plans. FFF-VMAT plans require more monitor units than 3D or non-coplanar VMAT ones. Conclusion Besides the advantage of faster delivery times, VMAT plans demonstrated better conformity to target, sharper dose fall-off in normal tissues and lower dose to normal lung than the 3D plans for lung SBRT. More monitor units are often required for FFF-VMAT plans.

The Halcyon™ platform is self‐contained, combining a treatment planning (Eclipse) system TPS) with information management and radiation delivery components. The standard TPS beam model is configured and locked down by the vendor. A portal dosimetry‐based system for patient‐specific QA (PSQA) is also included. While ensuring consistency across the user base, this closed model may not be optimal for every department. We set out to commission independent TPS (RayStation 9B, RaySearch Laboratories) and PSQA (PerFraction, Sun Nuclear Corp.) systems for use with the Halcyon linac. The output factors and PDDs for very small fields (0.5 × 0.5 cm2) were collected to augment the standard Varian dataset. The MLC leaf‐end parameters were estimated based on the various static and dynamic tests with simple model fields and honed by minimizing the mean and standard deviation of dose difference between the ion chamber measurements and RayStation Monte Carlo calculations for 15 VMAT and IMRT test plans. Two chamber measurements were taken per plan, in the high (isocenter) and lower dose regions. The ratio of low to high doses ranged from 0.4 to 0.8. All percent dose differences were expressed relative to the local dose. The mean error was 0.0 ± 1.1% (TG119‐style confidence limit ± 2%). Gamma analysis with the helical diode array using the standard 3%Global/2mm criteria resulted in the average passing rate of 99.3 ± 0.5% (confidence limit 98.3%–100%). The average local dose error for all detectors across all plans was 0.2% ± 5.3%. The ion chamber results compared favorably with our recalculation with Eclipse and PerFraction, as well as with several published Eclipse reports. Dose distribution gamma analysis comparisons between RayStation and PerFraction with 2%Local/2mm criteria yielded an average passing rate of 98.5% ± 0.8% (confidence limit 96.9%–100%). It is feasible to use the Halcyon accelerator with independent planning and verification systems without sacrificing dosimetric accuracy. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to characterize pre-treatment non-contrast computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) based radiomics signatures predictive of pathological response and clinical outcomes in rectal cancer patients treated with neoadjuvant chemoradiotherapy (NACR T). Materials and methods: An exploratory analysis was performed using pre-treatment non-contrast CT and PET imaging dataset. The association of tumor regression grade (TRG) and neoadjuvant rectal (NAR) score with pre-treatment CT and PET features was assessed using machine learning algorithms. Three separate predictive models were built for composite features from CT + PET. Results: The patterns of pathological response were TRG 0 (n = 13; 19.7%), 1 (n = 34; 51.5%), 2 (n = 16; 24.2%), and 3 (n = 3; 4.5%). There were 20 (30.3%) patients with low, 22 (33.3%) with intermediate and 24 (36.4%) with high NAR scores. Three separate predictive models were built for composite features from CT + PET and analyzed separately for clinical endpoints. Composite features with α = 0.2 resulted in the best predictive power using logistic regression. For pathological response prediction, the signature resulted in 88.1% accuracy in predicting TRG 0 vs. TRG 1-3; 91% accuracy in predicting TRG 0-1 vs. TRG 2-3. For the surrogate of DFS and OS, it resulted in 67.7% accuracy in predicting low vs. intermediate vs. high NAR scores. Conclusion: The pre-treatment composite radiomics signatures were highly predictive of pathological response in rectal cancer treated with NACR T. A larger cohort is warranted for further validation. [ABSTRACT FROM AUTHOR]

Semiconductor dosimeters are ubiquitous in modern external-beam radiation therapy. They possess key features. The response, electronically available in real time, is stable and linear with absorbed dose for given irradiation conditions; the radiation-sensitive volume can be rather small in size, while retaining mechanical strength and high sensitivity. We describe three common semiconductor dosimeters: diodes, metal-oxide-semiconductor field-effect transistors and diamonds. We discuss in detail their operation principles and applications in modern external-beam radiation therapy, primarily with megavoltage photon beams. We also explore their use in proton and heavy ion therapy, and in experimental radiotherapy techniques such as synchrotron-based micro-beam radiation therapy. [ABSTRACT FROM AUTHOR]

Introduction: Innovative biomarkers to predict treatment response in rectal cancer would be helpful in optimizing personalized treatment approaches. In this study, we aimed to develop and validate a CT-based radiomic imaging biomarker to predict pathological response.Methods: We used two independent cohorts of rectal cancer patients to develop and validate a CT-based radiomic imaging biomarker predictive of treatment response. A total of 91 rectal cancer cases treated from 2009 to 2018 were assessed for the tumour regression grade (TRG) (0 = pathological complete response, pCR; 1 = moderate response; 2 = partial response; 3 = poor response). Exploratory analysis was performed by combining pre-treatment non-contrast CT images and patterns of TRG. The models built from the training cohort were further assessed using the independent validation cohort.Results: The patterns of pathological response in training and validation groups were TRG 0 (n = 14, 23.3%; n = 6, 19.4%), 1 (n = 31, 51.7%; n = 15, 48.4%), 2 (n = 12, 20.0%; n = 7, 22.6%) and 3 (n = 3, 5.0%; n = 3, 9.7%), respectively. Separate predictive models were built and analysed from CT features for pathological response. For pathological response prediction, the model including 8 radiomic features by random forest method resulted in 83.9% accuracy in predicting TRG 0 vs TRG 1-3 in validation.Conclusion: The pre-treatment CT-based radiomic signatures were developed and validated in two independent cohorts. This imaging biomarker provided a promising way to predict pCR and select patients for non-operative management. [ABSTRACT FROM AUTHOR]

Linac calibration is done in water, but patients are comprised primarily of soft tissue. Conceptually, and specified in NRG/RTOG trials, dose should be reported as dose‐to‐muscle to describe the dose to the patient. Historically, the dose‐to‐water of the linac calibration was often converted to dose‐to‐muscle for patient calculations through manual application of a 0.99 dose‐to‐water to dose‐to‐muscle correction factor, applied during the linac clinical reference calibration. However, many current treatment planning system (TPS) dose calculation algorithms approximately provide dose‐to‐muscle (tissue), making application of a manual scaling unnecessary. There is little guidance on when application of a scaling factor is appropriate, resulting in highly inconsistent application of this scaling by the community. In this report we provide guidance on the steps necessary to go from the linac absorbed dose‐to‐water calibration to dose‐to‐muscle in patient, for various commercial TPS algorithms. If the TPS does not account for the difference between dose‐to‐water and dose‐to‐muscle, then TPS reference dose scaling is warranted. We have tabulated the major vendors' TPS in terms of whether they approximate dose‐to‐muscle or calculate dose‐to‐water and recommend the correction factor required to report dose‐to‐muscle directly from the TPS algorithm. Physicists should use this report to determine the applicable correction required for specifying the reference dose in their TPS to achieve this goal and should remain attentive to possible changes to their dose calculation algorithm in the future. [ABSTRACT FROM AUTHOR]

A high‐resolution diode array has been comprehensively evaluated. It consists of 1013 point diode detectors arranged on the two 7.7 × 7.7 cm2 printed circuit boards (PCBs). The PCBs are aligned face to face in such a way that the active volumes of all diodes are in the same plane. All individual correction factors required for accurate dosimetry have been validated for conventional and flattening filter free (FFF) 6MV beams. That included diode response equalization, linearity, repetition rate dependence, field size dependence, angular dependence at the central axis and off‐axis in the transverse, sagittal, and multiple arbitrary planes. In the end‐to‐end tests the array and radiochromic film dose distributions for SRS‐type multiple‐target plans were compared. In the equalization test (180° rotation), the average percent dose error between the normal and rotated positions for all diodes was 0.01% ± 0.1% (range −0.3 to 0.4%) and −0.01% ± 0.2% (range −0.9 to 0.9%) for 6 MV and 6MV FFF beams, respectively. For the axial angular response, corrected dose stayed within 2% from the ion chamber for all gantry angles, until the beam direction approached the detector plane. In azimuthal direction, the device agreed with the scintillator within 1% for both energies. For multiple combinations of couch and gantry angles, the average percent errors were −0.00% ± 0.6% (range: −2.1% to 1.6%) and −0.1% ± 0.5% (range −1.6% to 2.1%) for the 6MV and 6MV FFF beams, respectively. The measured output factors were largely within 2% of the scintillator, except for the 5 mm 6MV beam showing a 3.2% deviation. The 2%/1 mm gamma analysis of composite SRS measurements produced the 97.2 ± 1.3% (range 95.8‐98.5%) average passing rate against film. Submillimeter (≤0.5 mm) dose profile alignment with film was demonstrated in all cases. [ABSTRACT FROM AUTHOR]

Abstract: A commercial semi‐empirical volumetric dose verification system (PerFraction [PF], Sun Nuclear Corp.) extracts multi‐leaf collimator positions from the electronic portal imaging device movies collected during a pre‐treatment run, while the rest of the delivered control point information is harvested from the accelerator log files. This combination is used to reconstruct dose on a patient CT dataset with a fast superposition/convolution algorithm. The method was validated for single‐isocenter multi‐target SRS VMAT treatments against absolute radiochromic film measurements in a cylindrical phantom. The targets ranged in size from 0.8 to 3.6 cm and in number from 3 to 10 per plan. A total of 17 films rotated at different angles around the cylinder axis were analyzed. Each of 27 total targets was intercepted by at least one film, and 2–4 different films were analyzed per plan. Film dose was always scaled to the ion chamber measurement in a high‐dose, low‐gradient area deliberately created at the isocenter. The planar dose agreement between PF and film using 3%(Global dose‐difference normalization)/1 mm gamma analysis was on average 99.2 ± 1.1%. The point dose difference in the low‐gradient area in the middle of every target was below 3%, while PF‐reconstructed and film dose centroids for individual targets showed submillimeter agreement when measured on a well aligned accelerator. Volumetrically, all voxels in all plans agreed between PF and the primary treatment planning system at the 3%/1 mm level. With proper understanding of its advantages and shortcomings, the tool can be applied to patient‐specific QA in routine radiosurgical clinical practice. [ABSTRACT FROM AUTHOR]

Abstract: The AAPM TG 132 Report enumerates important steps for validation of the medical image registration process. While the Report outlines the general goals and criteria for the tests, specific implementation may be obscure to the wider clinical audience. We endeavored to provide a detailed step‐by‐step description of the quantitative tests’ execution, applied as an example to a commercial software package (Mirada Medical, Oxford, UK), while striving for simplicity and utilization of readily available software. We demonstrated how the rigid registration data could be easily extracted from the DICOM registration object and used, following some simple matrix math, to quantify accuracy of rigid translations and rotations. The options for validating deformable image registration (DIR) were enumerated, and it was shown that the most practically viable ones are comparison of propagated internal landmark points on the published datasets, or of segmented contours that can be generated locally. The multimodal rigid registration in our example did not always result in the desired registration error below ½ voxel size, but was considered acceptable with the maximum errors under 1.3 mm and 1°. The DIR target registration errors in the thorax based on internal landmarks were far in excess of the Report recommendations of 2 mm average and 5 mm maximum. On the other hand, evaluation of the DIR major organs’ contours propagation demonstrated good agreement for lung and abdomen (Dice Similarity Coefficients, DSC, averaged over all cases and structures of 0.92 ± 0.05 and 0.91 ± 0.06, respectively), and fair agreement for Head and Neck (average DSC = 0.73 ± 0.14). The average for head and neck is reduced by small volume structures such as pharyngeal constrictor muscles. Even these relatively simple tests show that commercial registration algorithms cannot be automatically assumed sufficiently accurate for all applications. Formalized task‐specific accuracy quantification should be expected from the vendors. [ABSTRACT FROM AUTHOR]