First implementation of an innovative infra-red camera system integrated into a mobile CBCT scanner for applicator tracking in brachytherapy-Initial performance characterization.

PURPOSE: To enable a real-time applicator guidance for brachytherapy, we used for the first time infra-red tracking cameras (OptiTrack, USA) integrated into a mobile cone-beam computed tomography (CBCT) scanner (medPhoton, Austria). We provide the first description of this prototype and its performance evaluation. METHODS: We performed assessments of camera calibration and camera-CBCT registration using a geometric calibration phantom. For this purpose, we first evaluated the effects of intrinsic parameters such as camera temperature or gantry rotations on the tracked marker positions. Afterward, calibrations with various settings (sample number, field of view coverage, calibration directions, calibration distances, and lighting conditions) were performed to identify the requirements for achieving maximum tracking accuracy based on an in-house phantom. The corresponding effects on camera-CBCT registration were determined as well by comparing tracked marker positions to the positions determined via CBCT. Long-term stability was assessed by comparing tracking and a ground-truth on a weekly basis for 6 weeks. RESULTS: Robust tracking with positional drifts of 0.02 ± 0.01 mm was feasible using the system after a warm-up period of 90 min. However, gantry rotations affected the tracking and led to inaccuracies of up to 0.70 mm. We identified that 4000 samples and full coverage were required to ensure a robust determination of marker positions and camera-CBCT registration with geometric deviations of 0.18 ± 0.03 mm and 0.42 ± 0.07 mm, respectively. Long-term stability showed deviations of more than two standard deviations from the initial calibration after 3 weeks. CONCLUSION: We implemented for the first time a standalone combined camera-CBCT system for tracking in brachytherapy. The system showed high potential for establishing corresponding workflows.

Process failure mode and effects analysis for external beam radiotherapy: Introducing a literature-based template and a novel action priority.

PURPOSE: The first aim of the study was to create a general template for analyzing potential failures in external beam radiotherapy, EBRT, using the process failure mode and effects analysis (PFMEA). The second aim was to modify the action priority (AP), a novel prioritization method originally introduced by the Automotive Industry Action Group (AIAG), to work with different severity, occurrence, and detection rating systems used in radiation oncology. METHODS AND MATERIALS: The AIAG PFMEA approach was employed in combination with an extensive literature survey to develop the EBRT-PFMEA template. Subsets of high-risk failure modes found through the literature survey were added to the template where applicable. Our modified AP for radiation oncology (RO AP) was defined using a weighted sum of severity, occurrence, and detectability. Then, Monte Carlo simulations were conducted to compare the original AIAG AP, the RO AP, and the risk priority number (RPN). The results of the simulations were used to determine the number of additional corrective actions per failure mode and to parametrize the RO AP to our department's rating system. RESULTS: An EBRT-PFMEA template comprising 75 high-risk failure modes could be compiled. The AIAG AP required 1.7 additional corrective actions per failure mode, while the RO AP ranged from 1.3 to 3.5, and the RPN required 3.6. The RO AP could be parametrized so that it suited our rating system and evaluated severity, occurrence, and detection ratings equally to the AIAG AP. CONCLUSIONS: An adjustable EBRT-PFMEA template is provided which can be used as a practical starting point for creating institution-specific templates. Moreover, the RO AP introduces transparent action levels that can be adapted to any rating system.

"sCT-Feasibility" - a feasibility study for deep learning-based MRI-only brain radiotherapy.

BACKGROUND: Radiotherapy (RT) is an important treatment modality for patients with brain malignancies. Traditionally, computed tomography (CT) images are used for RT treatment planning whereas magnetic resonance imaging (MRI) images are used for tumor delineation. Therefore, MRI and CT need to be registered, which is an error prone process. The purpose of this clinical study is to investigate the clinical feasibility of a deep learning-based MRI-only workflow for brain radiotherapy, that eliminates the registration uncertainty through calculation of a synthetic CT (sCT) from MRI data. METHODS: A total of 54 patients with an indication for radiation treatment of the brain and stereotactic mask immobilization will be recruited. All study patients will receive standard therapy and imaging including both CT and MRI. All patients will receive dedicated RT-MRI scans in treatment position. An sCT will be reconstructed from an acquired MRI DIXON-sequence using a commercially available deep learning solution on which subsequent radiotherapy planning will be performed. Through multiple quality assurance (QA) measures and reviews during the course of the study, the feasibility of an MRI-only workflow and comparative parameters between sCT and standard CT workflow will be investigated holistically. These QA measures include feasibility and quality of image guidance (IGRT) at the linear accelerator using sCT derived digitally reconstructed radiographs in addition to potential dosimetric deviations between the CT and sCT plan. The aim of this clinical study is to establish a brain MRI-only workflow as well as to identify risks and QA mechanisms to ensure a safe integration of deep learning-based sCT into radiotherapy planning and delivery. DISCUSSION: Compared to CT, MRI offers a superior soft tissue contrast without additional radiation dose to the patients. However, up to now, even though the dosimetrical equivalence of CT and sCT has been shown in several retrospective studies, MRI-only workflows have still not been widely adopted. The present study aims to determine feasibility and safety of deep learning-based MRI-only radiotherapy in a holistic manner incorporating the whole radiotherapy workflow. TRIAL REGISTRATION: NCT06106997.

A comprehensive quality assurance protocol for electromagnetic tracking in brachytherapy.

BACKGROUND: Electromagnetic tracking (EMT) systems have proven to be a valuable source of information regarding the location and geometry of applicators in patients undergoing brachytherapy (BT). As an important element of an enhanced and individualized pre-treatment verification, EMT can play a pivotal role in detecting treatment errors and uncertainties to increase patient safety. PURPOSE: The purpose of this study is two-fold: to design, develop and test a dedicated measurement protocol for the use of EMT-enabled afterloaders in BT and to collect and compare the data acquired from three different radiation oncology centers in different clinical environments. METHODS: A novel quality assurance (QA) phantom composed of a scaffold with supports to fix the field generator, different BT applicators, and reference sensors (sensor verification tools) was used to assess the precision (jitter error) and accuracy (relative distance errors and target registration error) of the EMT sensor integrated into an afterloader prototype. Measurements were repeated in different environments where EMT measurements are likely to be performed, namely an electromagnetically clean laboratory, a BT suite, an operating room, and, if available, a CT suite and an MRI suite dedicated to BT. RESULTS: The mean positional jitter was consistently under 0.1 mm across all measurement points, with a slight trend of increased jitter at greater distances from the field generator. The mean variability of sensor positioning in the tested tandem and ring gynecological applicator was also below 0.1 mm. The tracking accuracy close to the center of the measurement volume was higher than at its edges. The relative distance error at the center was 0.2-0.3 mm with maximum values reaching 1.2-1.8 mm, but up to 5.5 mm for measurement points close to the edges. In general, similar accuracy results were obtained in the clinical environments and in all investigated institutions (median distance error 0.1-0.4 mm, maximum error 1.0-2.0 mm), however, errors were found to be larger in the CT suite (median distance error up to 1.0 mm, maximum error up to 3.6 mm). CONCLUSION: The presented quality assessment protocol for EMT systems in BT has demonstrated that EMT offers a high-accuracy determination of the applicator/implant geometry even in clinical environments. In addition to that, it has provided valuable insights into the performance of EMT-enabled afterloaders across different radiation oncology centers.

Implementation and validation of 2-D-array based tests in routine linac quality assurance.

PURPOSE: In medical linac quality assurance (QA), to replace film dosimetry with low-resolution 2-D ionization chamber array measurements, to validate the procedures, and to perform a comprehensive sensitivity analysis. METHODS: A 2-D ionization chamber array with a spatial resolution of 7.62 mm was deployed to perform the following tests: Junction tests, MLC transmission test, beam profile constancy vs. gantry angle test, beam profile constancy vs. low dose delivery test, and beam energy constancy vs. low dose delivery test. Test validation and sensitivity analyses based on short- and long-term statistics of the test results were performed. RESULTS: All selected mechanical and dosimetry tests could be successfully performed with a 2-D array. Considering the tolerance limits recommended by the AAPM Task Group 142 report (2009), sensitivities of 99.0% or better and specificities ranging from 99.5% to 99.9% could be achieved in all tests when the proper metrics were chosen. CONCLUSIONS: The results showed that a low-resolution 2-D ionization chamber array could replace film dosimetry without having to sacrifice high test sensitivity. Its implementation in the routine clinical linac QA program may involve considerable QA time savings.

Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce "Imaging in Stereotactic Radiotherapy".

Accurate Magnetic Resonance Imaging (MRI) simulation is fundamental for high-precision stereotactic radiosurgery and fractionated stereotactic radiotherapy, collectively referred to as stereotactic radiotherapy (SRT), to deliver doses of high biological effectiveness to well-defined cranial targets. Multiple MRI hardware related factors as well as scanner configuration and sequence protocol parameters can affect the imaging accuracy and need to be optimized for the special purpose of radiotherapy treatment planning. MRI simulation for SRT is possible for different organizational environments including patient referral for imaging as well as dedicated MRI simulation in the radiotherapy department but require radiotherapy-optimized MRI protocols and defined quality standards to ensure geometrically accurate images that form an impeccable foundation for treatment planning. For this guideline, an interdisciplinary panel including experts from the working group for radiosurgery and stereotactic radiotherapy of the German Society for Radiation Oncology (DEGRO), the working group for physics and technology in stereotactic radiotherapy of the German Society for Medical Physics (DGMP), the German Society of Neurosurgery (DGNC), the German Society of Neuroradiology (DGNR) and the German Chapter of the International Society for Magnetic Resonance in Medicine (DS-ISMRM) have defined minimum MRI quality requirements as well as advanced MRI simulation options for cranial SRT.

Investigating the impact of breast positioning control on physical treatment parameters in multi-catheter breast brachytherapy.

PURPOSE: To assess the effects of a workflow for reproducible patient and breast positioning on implant stability during high-dose-rate multi-catheter breast brachytherapy. METHODS: Thirty patients were treated with our new positioning control workflow. Implant stability was evaluated based on a comparison of planning-CTs to control-CTs acquired halfway through the treatment. To assess geometric stability, button-button distance variations as well as Euclidean dwell position deviations were evaluated. The latter were also quantified within various separated regions within the breast to investigate the location-dependency of implant alterations. Furthermore, dosimetric variations to target volume and organs at risk (ribs, skin) as well as isodose volume changes were analyzed. Results were compared to a previously treated cohort of 100 patients. RESULTS: With the introduced workflow, the patient fraction affected by button-button distance variations > 5 mm and by dwell position deviations > 7 mm were reduced from 37% to 10% and from 30% to 6.6%, respectively. Implant stability improved the most in the lateral to medial breast regions. Only small stability enhancements were observed regarding target volume dosimetry, but the stability of organ at risk exposure became substantially higher. D0.2ccm skin dose variations > 12.4% and D0.1ccm rib dose variations > 6.7% were reduced from 11% to 0% and from 16% to 3.3% of all patients, respectively. CONCLUSION: Breast positioning control improved geometric and dosimetric implant stability for individual patients, and thus enhanced physical plan validity in these cases.

Toward a deep learning-based magnetic resonance imaging only workflow for postimplant dosimetry in I-125 seed brachytherapy for prostate cancer.

BACKGROUND AND PURPOSE: The current standard imaging-technique for creating postplans in seed prostate brachytherapy is computed tomography (CT), that is associated with additional radiation exposure and poor soft tissue contrast. To establish a magnetic resonance imaging (MRI) only workflow combining improved tissue contrast and high seed detectability, a deep learning-approach for automatic seed segmentation on MRI-scans was developed. MATERIAL AND METHODS: Patients treated with I-125 seed brachytherapy received a postplan-CT and a 1.5 T MRI-scan on nominal day 30 after implantation. For MRI-based seed visualization, DIXON-sequences were acquired and deep learning-based quantitative susceptibility maps (QSM) were generated from 3D-gradient-echo-sequences from 20 patients. Seed segmentations created on CT served as ground truth. For automatic seed segmentation on MRI, a 3D nnU-net model was trained using QSM and DIXON, both solely and combined. RESULTS: Of the implanted seeds 94.8 ± 2.4% were detected with deep learning automatic segmentation entrained on both QSM and DIXON data. Models trained on the individual sequence data-sets performed worse with detection rates of 87.5 ± 2.6% or 88.6 ± 7.5% for QSM and DIXON respectively. The seed centers identified on CT versus QSM and DIXON were on average 1.8 ± 1.3 mm apart. Postimplant dosimetry for evaluation of positioning inaccuracies revealed only small variations of up to 0.4 ± 4.26 Gy in D90 (dose 90% of the prostate receives) between the standard CT-approach and our MRI-only workflow. CONCLUSION: The proposed deep learning-based MRI-only workflow provided a promisingly accurate and robust seed localization and thus has the potential to compete with current state-of-the-art CT-based postimplant dosimetry in the future.

Benchmarking ChatGPT-4 on a radiation oncology in-training exam and Red Journal Gray Zone cases: potentials and challenges for ai-assisted medical education and decision making in radiation oncology.

Purpose: The potential of large language models in medicine for education and decision-making purposes has been demonstrated as they have achieved decent scores on medical exams such as the United States Medical Licensing Exam (USMLE) and the MedQA exam. This work aims to evaluate the performance of ChatGPT-4 in the specialized field of radiation oncology. Methods: The 38th American College of Radiology (ACR) radiation oncology in-training (TXIT) exam and the 2022 Red Journal Gray Zone cases are used to benchmark the performance of ChatGPT-4. The TXIT exam contains 300 questions covering various topics of radiation oncology. The 2022 Gray Zone collection contains 15 complex clinical cases. Results: For the TXIT exam, ChatGPT-3.5 and ChatGPT-4 have achieved the scores of 62.05% and 78.77%, respectively, highlighting the advantage of the latest ChatGPT-4 model. Based on the TXIT exam, ChatGPT-4's strong and weak areas in radiation oncology are identified to some extent. Specifically, ChatGPT-4 demonstrates better knowledge of statistics, CNS & eye, pediatrics, biology, and physics than knowledge of bone & soft tissue and gynecology, as per the ACR knowledge domain. Regarding clinical care paths, ChatGPT-4 performs better in diagnosis, prognosis, and toxicity than brachytherapy and dosimetry. It lacks proficiency in in-depth details of clinical trials. For the Gray Zone cases, ChatGPT-4 is able to suggest a personalized treatment approach to each case with high correctness and comprehensiveness. Importantly, it provides novel treatment aspects for many cases, which are not suggested by any human experts. Conclusion: Both evaluations demonstrate the potential of ChatGPT-4 in medical education for the general public and cancer patients, as well as the potential to aid clinical decision-making, while acknowledging its limitations in certain domains. Owing to the risk of hallucinations, it is essential to verify the content generated by models such as ChatGPT for accuracy.

Deep Learning and Registration-Based Mapping for Analyzing the Distribution of Nodal Metastases in Head and Neck Cancer Cohorts: Informing Optimal Radiotherapy Target Volume Design.

We introduce a deep-learning- and a registration-based method for automatically analyzing the spatial distribution of nodal metastases (LNs) in head and neck (H/N) cancer cohorts to inform radiotherapy (RT) target volume design. The two methods are evaluated in a cohort of 193 H/N patients/planning CTs with a total of 449 LNs. In the deep learning method, a previously developed nnU-Net 3D/2D ensemble model is used to autosegment 20 H/N levels, with each LN subsequently being algorithmically assigned to the closest-level autosegmentation. In the nonrigid-registration-based mapping method, LNs are mapped into a calculated template CT representing the cohort-average patient anatomy, and kernel density estimation is employed to estimate the underlying average 3D-LN probability distribution allowing for analysis and visualization without prespecified level definitions. Multireader assessment by three radio-oncologists with majority voting was used to evaluate the deep learning method and obtain the ground-truth distribution. For the mapping technique, the proportion of LNs predicted by the 3D probability distribution for each level was calculated and compared to the deep learning and ground-truth distributions. As determined by a multireader review with majority voting, the deep learning method correctly categorized all 449 LNs to their respective levels. Level 2 showed the highest LN involvement (59.0%). The level involvement predicted by the mapping technique was consistent with the ground-truth distribution (p for difference 0.915). Application of the proposed methods to multicenter cohorts with selected H/N tumor subtypes for informing optimal RT target volume design is promising.

Plan robustness analysis for threshold determination of SGRT-based intrafraction motion control in 3DCRT breast cancer radiation therapy.

PURPOSE: The goal of this study was to obtain maximum allowed shift deviations from planning position in six degrees of freedom (DOF), that can serve as threshold values in surface guided radiation therapy (SGRT) of breast cancer patients. METHODS: The robustness of conformal treatment plans of 50 breast cancer patients against 6DOF shifts was investigated. For that, new dose distributions were calculated on shifted computed tomography scans and evaluated with respect to target volume and spinal cord dose. Maximum allowed shift values were identified by imposing dose constraints on the target volume dose coverage for 1DOF, and consecutively, for 6DOF shifts using an iterative approach and random sampling. RESULTS: Substantial decreases in target dose coverage and increases of spinal cord dose were observed. Treatment plans showed highly differing robustness for different DOFs or treated area. The sensitivity was particularly high if clavicular lymph nodes were irradiated, for shifts in lateral, vertical, roll or yaw direction, and showed partly pronounced asymmetries. Threshold values showed similar properties with an absolute value range of 0.8 mm to 5 mm and 1.4° to 5°. CONCLUSION: The robustness analysis emphasized the necessity of taking differences between DOFs and asymmetrical sensitivities into account when evaluating the dosimetric impact of position deviations. It also highlighted the importance of rotational shifts, especially if clavicular lymph nodes were irradiated. A practical approach of determining 6DOF shift limits was introduced and a set of threshold values applicable for SGRT based patient motion control was identified.

Development and clinical implementation of a digital system for risk assessments for radiation therapy.

Before introducing new treatment techniques, an investigation of hazards due to unintentional radiation exposures is a reasonable activity for proactively increasing patient safety. As dedicated software is scarce, we developed a tool for risk assessment to design a quality management program based on best practice methods, i.e., process mapping, failure modes and effects analysis and fault tree analysis. Implemented as a web database application, a single dataset was used to describe the treatment process and its failure modes. The design of the system and dataset allowed failure modes to be represented both visually as fault trees and in a tabular form. Following the commissioning of the software for our department, previously conducted risk assessments were migrated to the new system after being fully re-assessed which revealed a shift in risk priorities. Furthermore, a weighting factor was investigated to bring risk levels of the migrated assessments into perspective. The compensation did not affect high priorities but did re-prioritize in the midrange of the ranking. We conclude that the tool is suitable to conduct multiple risk assessments and concomitantly keep track of the overall quality management activities.

Estimating follow-up CTs from geometric deformations of catheter implants in interstitial breast brachytherapy: A feasibility study using electromagnetic tracking.

BACKGROUND: Electromagnetic tracking (EMT) systems have been shown to provide valuable information on the geometry of catheter implants in breast cancer patients undergoing interstitial brachytherapy (iBT). In the context of an extended patient-specific, pre-treatment verification, EMT can play a key role in determining the potential need and, if applicable, the appropriate time for treatment adaptation. To detect dosimetric shortcomings the relative position between catheters, and target volume and critical structures must be known. Since EMT cannot provide the anatomical context and standard imaging techniques such as cone-beam CT are not yet available in most brachytherapy suites, it is not possible to detect anatomic changes on a daily or fraction basis, so the need for adaptive planning cannot be identified. PURPOSE: The aim of this feasibility study is to develop and evaluate a technique capable of estimating follow-up CTs at any time based on the initial treatment planning CT (PCT) and surrogate information about changes of the implant geometry from an EMT system. METHODS: A deformation vector field is calculated from two different implant reconstructions acquired in treatment position through EMT, the first immediately after the PCT and the second at another time point during the course of treatment. The calculation is based on discrete displacement vectors of pairs of control and target points. These are extrapolated by means of different radial basis functions in order to cover the entire CT volume. The adequate parameters for the calculation of the deformation field were identified. By warping the PCT according to the deformation field, one obtains an estimated CT (ECT) that reflects the geometric changes. For the proof of concept, ECTs were computed for the time point of the clinical follow-up CT (FCT) that is embedded in the treatment workflow after the fourth fraction. RESULTS: ECT and clinical FCTs of 20 patients were compared to each other quantitatively in terms of absolute Hounsfield unit differences in the planning target volume (PTV) and in a convex hull (CH) enclosing the catheters. The median differences were 31.2  and 29.5 HU for the CH and the PTV, respectively. CONCLUSION: The proposed ECT approach was able to approximate the "anatomy of the day" and therefore, in principle, allows a dosimetric appraisal of the treatment plan quality before each fraction. In this way, it can contribute to a more detailed patient-specific quality assurance in iBT of the breast and help to identify the timing for a potential treatment adaptation.

Localization of reference points in electromagnetic tracking data and their application for treatment error detection in interstitial breast brachytherapy.

BACKGROUND: Electromagnetic tracking (EMT) is a promising technology that holds great potential to advance patient-specific pre-treatment verification in interstitial brachytherapy (iBT). It allows easy determination of the implant geometry without line-of-sight restrictions and without dose exposure to the patient. What it cannot provide, however, is a link to anatomical landmarks, such as the exit points of catheters or needles on the skin surface. These landmarks are required for the registration of EMT data with other imaging modalities and for the detection of treatment errors such as incorrect indexer lengths, and catheter or needle shifts. PURPOSE: To develop an easily applicable method to detect reference points in the positional data of the trajectory of an EMT sensor, specifically the exit points of catheters in breast iBT, and to apply the approach to pre-treatment error detection. METHODS: Small metal objects were attached to catheter fixation buttons that rest against the breast surface to intentionally induce a local, spatially limited perturbation of the magnetic field on which the working principle of EMT relies. This perturbation can be sensed by the EMT sensor as it passes by, allowing it to localize the metal object and thus the catheter exit point. For the proof-of-concept, different small metal objects (magnets, washers, and bushes) and EMT sensor drive speeds were used to find the optimal parameters. The approach was then applied to treatment error detection and validated in-vitro on a phantom. Lastly, the in-vivo feasibility of the approach was tested on a patient cohort of four patients to assess the impact on the clinical workflow. RESULTS: All investigated metal objects were able to measurably perturb the magnetic field, which resulted in missing sensor readings, that is two data gaps, one for the sensor moving towards the tip end and one when retracting from there. The size of the resulting data gaps varied depending on the choice of gap points used for calculation of the gap size; it was found that the start points of the gaps in both directions showed the smallest variability. The median size of data gaps was ⩽8 mm for all tested materials and sensor drive speeds. The variability of the determined object position was ⩽0.5 mm at a speed of 1.0 cm/s and ⩽0.7 mm at 2.5 cm/s, with an increase up to 2.3 mm at 5.0 cm/s. The in-vitro validation of the error detection yielded a 100% detection rate for catheter shifts of ≥2.2 mm. All simulated wrong indexer lengths were correctly identified. The in-vivo feasibility assessment showed that the metal objects did not interfere with the routine clinical workflow. CONCLUSIONS: The developed approach was able to successfully detect reference points in EMT data, which can be used for registration to other imaging modalities, but also for treatment error detection. It can thus advance the automation of patient-specific, pre-treatment quality assurance in iBT.

Synthetic CTs for MRI-only brain RT treatment: integration of immobilization systems.

PURPOSE: Auxiliary devices such as immobilization systems should be considered in synthetic CT (sCT)-based treatment planning (TP) for MRI-only brain radiotherapy (RT). A method for auxiliary device definition in the sCT is introduced, and its dosimetric impact on the sCT-based TP is addressed. METHODS: T1-VIBE DIXON was acquired in an RT setup. Ten datasets were retrospectively used for sCT generation. Silicone markers were used to determine the auxiliary devices' relative position. An auxiliary structure template (AST) was created in the TP system and placed manually on the MRI. Various RT mask characteristics were simulated in the sCT and investigated by recalculating the CT-based clinical plan on the sCT. The influence of auxiliary devices was investigated by creating static fields aimed at artificial planning target volumes (PTVs) in the CT and recalculated in the sCT. The dose covering 50% of the PTV (D50) deviation percentage between CT-based/recalculated plan (∆D50[%]) was evaluated. RESULTS: Defining an optimal RT mask yielded a ∆D50[%] of 0.2 ± 1.03% for the PTV and between -1.6 ± 3.4% and 1.1 ± 2.0% for OARs. Evaluating each static field, the largest ∆D50[%] was delivered by AST positioning inaccuracy (max: 3.5 ± 2.4%), followed by the RT table (max: 3.6 ± 1.2%) and the RT mask (max: 3.0 ± 0.8% [anterior], 1.6 ± 0.4% [rest]). No correlation between ∆D50[%] and beam depth was found for the sum of opposing beams, except for (45°â€¯+ 315°). CONCLUSION: This study evaluated the integration of auxiliary devices and their dosimetric influence on sCT-based TP. The AST can be easily integrated into the sCT-based TP. Further, we found that the dosimetric impact was within an acceptable range for an MRI-only workflow.

External-Beam-Accelerated Partial-Breast Irradiation Reduces Organ-at-Risk Doses Compared to Whole-Breast Irradiation after Breast-Conserving Surgery.

In order to evaluate organ-at-risk (OAR) doses in external-beam-accelerated partial-breast irradiation (APBI) compared to standard whole-breast irradiation (WBI) after breast-conserving surgery. Between 2011 and 2021, 170 patients with early breast cancer received APBI within a prospective institutional single-arm trial. The prescribed dose to the planning treatment volume was 38 Gy in 10 fractions on 10 consecutive working days. OAR doses for the contralateral breast, the ipsilateral, contralateral, and whole lung, the whole heart, left ventricle (LV), and the left anterior descending coronary artery (LAD), and for the spinal cord and the skin were assessed and compared to a control group with real-world data from 116 patients who underwent WBI. The trial was registered at the German Clinical Trials Registry, DRKS-ID: DRKS00004417. Compared to WBI, APBI led to reduced OAR doses for the contralateral breast (0.4 ± 0.6 vs. 0.8 ± 0.9 Gy, p = 0.000), the ipsilateral (4.3 ± 1.4 vs. 9.2 ± 2.5 Gy, p = 0.000) and whole mean lung dose (2.5 ± 0.8 vs. 4.9 ± 1.5 Gy, p = 0.000), the mean heart dose (1.6 ± 1.6 vs. 1.7 ± 1.4 Gy, p = 0.007), the LV V23 (0.1 ± 0.4 vs. 1.4 ± 2.6%, p < 0.001), the mean LAD dose (2.5 ± 3.4 vs. 4.8 ± 5.5 Gy, p < 0.001), the maximum spinal cord dose (1.5 ± 1.1 vs. 4.5 ± 5.7 Gy, p = 0.016), and the maximum skin dose (39.6 ± 1.8 vs. 49.1 ± 5.8 Gy, p = 0.000). APBI should be recommended to suitable patients to minimize the risk of secondary tumor induction and the incidence of consecutive major cardiac events.

Cone-beam CT imaging with laterally enlarged field of view based on independently movable source and detector.

BACKGROUND: CBCT imaging with field of views (FOVs) exceeding the size of scans acquired in the conventional imaging geometry, i.e. with opposing source and detector, is of high clinical importance for many medical fields. A novel approach for enlarged FOV scanning with one full-scan (EnFOV360) or two short-scans (EnFOV180) using an O-arm system arises from non-isocentric imaging based on independent source and detector rotations. PURPOSE: The presentation, description, and experimental validation of this novel approach and the novel scanning techniques EnFOV360 and EnFOV180 for an O-arm system forms the scope of this work. METHODS: We describe the EnFOV360, EnFOV180, and non-isocentric imaging techniques for the acquisition of laterally extended FOVs. For their experimental validation, scans of dedicated quality assurance as well as anthropomorphic phantoms were acquired, with the phantoms being placed both within the tomographic plane and at the longitudinal FOV border with and without lateral shifts from the gantry center. Based on this, geometric accuracy, contrast-noise-ratio (CNR) of different materials, spatial resolution, noise characteristics, as well as CT number profiles were quantitatively assessed. Results were compared to scans performed with the conventional imaging geometry. RESULTS: With EnFOV360 and EnFOV180, we increased the in-plane size of acquired FOVs from 250 × 250 mm2 obtained for the conventional imaging geometry to up to 400 × 400 mm2 for the performed measurements. Geometric accuracy was very high for all scanning techniques with mean values ≤0.21 ± 0.11 mm. CNR and spatial resolution were comparable between isocentric and non-isocentric full-scans as well as EnFOV360, whereas substantial image quality deteriorations in this respect were observed for EnFOV180. Image noise in the isocenter was lowest for conventional full-scans with 13.4 ± 0.2 HU. For laterally shifted phantom positions, noise increased for conventional scans and EnFOV360, whereas noise reductions were observed for EnFOV180. Considering the anthropomorphic phantom scans, both EnFOV360 and EnFOV180 were comparable to conventional full-scans. CONCLUSION: Both enlarged FOV techniques have high potential for imaging laterally extended FOVs. EnFOV360 revealed an image quality comparable to conventional full-scans in general. EnFOV180 showed an inferior performance particularly regarding CNR and spatial resolution.

Deep learning for automatic head and neck lymph node level delineation provides expert-level accuracy.

Background: Deep learning-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still underinvestigated in academic literature. In particular, there is no publicly available open-source solution for large-scale autosegmentation of HN_LNL in the research setting. Methods: An expert-delineated cohort of 35 planning CTs was used for training of an nnU-net 3D-fullres/2D-ensemble model for autosegmentation of 20 different HN_LNL. A second cohort acquired at the same institution later in time served as the test set (n = 20). In a completely blinded evaluation, 3 clinical experts rated the quality of deep learning autosegmentations in a head-to-head comparison with expert-created contours. For a subgroup of 10 cases, intraobserver variability was compared to the average deep learning autosegmentation accuracy on the original and recontoured set of expert segmentations. A postprocessing step to adjust craniocaudal boundaries of level autosegmentations to the CT slice plane was introduced and the effect of autocontour consistency with CT slice plane orientation on geometric accuracy and expert rating was investigated. Results: Blinded expert ratings for deep learning segmentations and expert-created contours were not significantly different. Deep learning segmentations with slice plane adjustment were rated numerically higher (mean, 81.0 vs. 79.6, p = 0.185) and deep learning segmentations without slice plane adjustment were rated numerically lower (77.2 vs. 79.6, p = 0.167) than manually drawn contours. In a head-to-head comparison, deep learning segmentations with CT slice plane adjustment were rated significantly better than deep learning contours without slice plane adjustment (81.0 vs. 77.2, p = 0.004). Geometric accuracy of deep learning segmentations was not different from intraobserver variability (mean Dice per level, 0.76 vs. 0.77, p = 0.307). Clinical significance of contour consistency with CT slice plane orientation was not represented by geometric accuracy metrics (volumetric Dice, 0.78 vs. 0.78, p = 0.703). Conclusions: We show that a nnU-net 3D-fullres/2D-ensemble model can be used for highly accurate autodelineation of HN_LNL using only a limited training dataset that is ideally suited for large-scale standardized autodelineation of HN_LNL in the research setting. Geometric accuracy metrics are only an imperfect surrogate for blinded expert rating.

On the implant stability in adaptive multi-catheter breast brachytherapy: Establishment of a decision-tree for treatment re-planning.

BACKGROUND AND PURPOSE: To assess implant stability and identify causes of implant variations during high-dose-rate multi-catheter breast brachytherapy. MATERIALS AND METHODS: Planning-CTs were compared to control-CTs acquired halfway through the treatment for 100 patients. For assessing geometric stability, Fréchet-distance and button-to-button distance changes of all catheters as well as variations of Euclidean distances and convex hulls of all dwell positions were determined. The CTs were inspected to identify the causes of geometric changes. Dosimetric effects were evaluated by target volume transfers and re-contouring of organs at risk. The dose non-uniformity ratio (DNR), 100% and 150% isodose volumes (V100 and V150), coverage index (CI), and organ doses were calculated. Correlations between the examined geometric and dosimetric parameters were assessed. RESULTS: Fréchet-distance and dwell position deviations >2.5 mm as well as button-to-button distance changes >5 mm were detected for 5%, 2%, and 6.3% of catheters, but for 32, 17, and 37 patients, respectively. Variations occurred enhanced in the lateral breast and close to the ribs, e.g. due to different arm positions. Only small dosimetric effects with median DNR, V100, and CI variations of -0.01 ± 0.02, (-0.5 ± 1.3)ccm, and (-1.4 ± 1.8)% were observed in general. Skin dose exceeded recommended levels for 12 of 100 patients. Various correlations between geometric and dosimetric implant stability were found, based on which decision-tree regarding treatment re-planning was established. CONCLUSION: Multi-catheter breast brachytherapy shows a high implant stability in general, but considering skin dose changes is important. To increase implant stability for individual patients, we plan to investigate patient immobilization aids during treatments.

Seed-displacements in the immediate post-implant phase in permanent prostate brachytherapy.

PURPOSE: To investigate differences in seed-displacements between the immediate post-implant phase (day 0-1) and the time to post-plan computed tomography (CT) (day 1-30) in seed prostate brachytherapy. MATERIALS AND METHODS: Seed positions were identified on the intra-operatively created ultrasound-based treatment plan (day 0) and CT scans of day 1 and 30 for 33 patients. The day 1 (30) seed arrangement was registered onto the day 0 (1) arrangement using a seed-only approach. Based on a 1:1 assignment of seeds via the Kuhn-Munkres algorithm, seed-displacements were analyzed. Displacements were evaluated depending on strand-length and anatomical implant location. Resulting dosimetric effects were calculated. RESULTS: Seed-displacements in the immediate post-implant phase (median displacements: 3.8 ± 3.6 mm) were stronger than in the time to post-plan CT (2.1 ± 2.6 mm) and enhanced along the superior-inferior direction. From day 0 to 1, strands containing one (7.3 ± 5.4 mm) or two (8.1 ± 5.8 mm) seeds showed larger displacements than strands of higher lengths (up to 4.2 ± 7.0 mm), whereas no length-dependency was found to day 30. Seeds implanted in base and apex tended to move towards the prostate midzone during both time periods. D90 (dose that 90% of prostate receives) was with variations of 2 ± 15 Gy more stable from day 1 to 30 than in the immediate post-implant phase (-18 ± 11 Gy). CONCLUSION: Seed-displacements in the immediate post-implant phase was enhanced compared to day 1-30. This may result from uncertainties in the gold-standard ultrasound-based treatment planning and implantation. Adaptive implantation workflows appear useful for ensuring high implant stability from the beginning.