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.

Initial needle tracking with the first standalone combined infrared camera - CT system for brachytherapy-analysis of tracking accuracy and uncertainties.

PURPOSE: A prototype infrared camera - cone-beam computed tomography (CBCT) system for tracking in brachytherapy has recently been developed. We evaluated for the first time the corresponding tracking accuracy and uncertainties, and implemented a tracking-based prediction of needles on CBCT scans. METHODS: A marker tool rigidly attached to needles was 3D printed. The precision and accuracy of tool tracking was then evaluated for both static and dynamic scenarios. Euclidean distances between the tracked and CBCT-derived markers were assessed as well. To implement needle tracking, ground truth models of the tool attached to 200 mm and 160 mm needles were matched to the tracked positions in order to project the needles into CBCT scans. Deviations between projected and actual needle tips were measured. Finally, we put our results into perspective with simulations of the system's tracking uncertainties. RESULTS: For the stationary scenario and dynamic movements, we achieved tool-tracking precision and accuracy of 0.04 ± 0.06 mm and 0.16 ± 0.18 mm, respectively. The tracked marker positions differed by 0.52 ± 0.18 mm from the positions determined via CBCT. In addition, the predicted needle tips in air deviated from the actual tip positions by only 1.62 ± 0.68 mm (200 mm needle) and 1.49 ± 0.62 mm (160 mm needle). The simulated tracking uncertainties resulted in tip variations of 1.58 ± 0.91 mm and 1.31 ± 0.69 mm for the 200 mm and 160 mm needles, respectively. CONCLUSION: With the innovative system it was possible to achieve a high tracking and prediction accuracy of marker tool and needles. The system shows high potential for applicator tracking in brachytherapy.

Principles of artificial intelligence in radiooncology.

PURPOSE: In the rapidly expanding field of artificial intelligence (AI) there is a wealth of literature detailing the myriad applications of AI, particularly in the realm of deep learning. However, a review that elucidates the technical principles of deep learning as relevant to radiation oncology in an easily understandable manner is still notably lacking. This paper aims to fill this gap by providing a comprehensive guide to the principles of deep learning that is specifically tailored toward radiation oncology. METHODS: In light of the extensive variety of AI methodologies, this review selectively concentrates on the specific domain of deep learning. It emphasizes the principal categories of deep learning models and delineates the methodologies for training these models effectively. RESULTS: This review initially delineates the distinctions between AI and deep learning as well as between supervised and unsupervised learning. Subsequently, it elucidates the fundamental principles of major deep learning models, encompassing multilayer perceptrons (MLPs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, generative adversarial networks (GANs), diffusion-based generative models, and reinforcement learning. For each category, it presents representative networks alongside their specific applications in radiation oncology. Moreover, the review outlines critical factors essential for training deep learning models, such as data preprocessing, loss functions, optimizers, and other pivotal training parameters including learning rate and batch size. CONCLUSION: This review provides a comprehensive overview of deep learning principles tailored toward radiation oncology. It aims to enhance the understanding of AI-based research and software applications, thereby bridging the gap between complex technological concepts and clinical practice in radiation oncology.

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.

The Segment Anything foundation model achieves favorable brain tumor auto-segmentation accuracy in MRI to support radiotherapy treatment planning.

BACKGROUND: Promptable foundation auto-segmentation models like Segment Anything (SA, Meta AI, New York, USA) represent a novel class of universal deep learning auto-segmentation models that could be employed for interactive tumor auto-contouring in RT treatment planning. METHODS: Segment Anything was evaluated in an interactive point-to-mask auto-segmentation task for glioma brain tumor auto-contouring in 16,744 transverse slices from 369 MRI datasets (BraTS 2020 dataset). Up to nine interactive point prompts were automatically placed per slice. Tumor boundaries were auto-segmented on contrast-enhanced T1w sequences. Out of the three auto-contours predicted by SA, accuracy was evaluated for the contour with the highest calculated IoU (Intersection over Union, "oracle mask," simulating interactive model use with selection of the best tumor contour) and for the tumor contour with the highest model confidence ("suggested mask"). RESULTS: Mean best IoU (mbIoU) using the best predicted tumor contour (oracle mask) in full MRI slices was 0.762 (IQR 0.713-0.917). The best 2D mask was achieved after a mean of 6.6 interactive point prompts (IQR 5-9). Segmentation accuracy was significantly better for high- compared to low-grade glioma cases (mbIoU 0.789 vs. 0.668). Accuracy was worse using the suggested mask (0.572). Stacking best tumor segmentations from transverse MRI slices, mean 3D Dice score for tumor auto-contouring was 0.872, which was improved to 0.919 by combining axial, sagittal, and coronal contours. CONCLUSION: The Segment Anything foundation segmentation model can achieve high accuracy for glioma brain tumor segmentation in MRI datasets. The results suggest that foundation segmentation models could facilitate RT treatment planning when properly integrated in a clinical application.

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.

Improving the safety of radiotherapy treatment processes via incident-driven FMEA feedback loops.

BACKGROUND: Failure mode and effects analysis (FMEA) is a valuable tool for radiotherapy risk assessment, yet its outputs might be unreliable due to failures not being identified or due to a lack of accurate error rates. PURPOSE: A novel incident reporting system (IRS) linked to an FMEA database was tested and evaluated. The study investigated whether the system was suitable for validating a previously performed analysis and whether it could provide accurate error rates to support the expert occurrence ratings of previously identified failure modes. METHODS: Twenty-three pre-identified failure modes of our external beam radiotherapy process, covering the process steps from patient admission to treatment delivery, were proffered on dedicated FMEA feedback and incident reporting terminals generated by the IRS. The clinical setting involved a computed tomography scanner, dosimetry, and five linacs. Incoming reports were used as basis to identify additional failure modes or confirm initial ones. The Kruskal-Wallis H test was applied to compare the risk priorities of the retrospective and prospective failure modes. Wald's sequential probability ratio test was used to investigate the correctness of the experts' occurrence ratings by means of the number of incoming reports. RESULTS: Over a 15-month period, 304 reports were submitted. There were 0.005 (confidence interval [CI], 0.0014-0.0082) reported incidents per imaging study and 0.0006 (CI, 0.0003-0.0009) reported incidents per treatment fraction. Sixteen additional failure modes could be identified, and their risk priorities did not differ from those of the initial failure modes (p = 0.954). One failure mode occurrence rating could be increased, whereas the other 22 occurrence ratings could not be disproved. CONCLUSIONS: Our approach is suitable for validating FMEAs and deducing additional failure modes on a continual basis. Accurate error rates can only be provided if a sufficient number of reports is available.

Prerequisites for the clinical implementation of a markerless SGRT-only workflow for the treatment of breast cancer patients.

PURPOSE: A markerless workflow for the treatment of breast cancer patients has been introduced and evaluated retrospectively. It includes surface-guided radiation therapy (SGRT)-only positioning for patients with small cone beam CT (CBCT) position corrections during the first five fractions. Prerequisites and the frequency of its clinical application were evaluated, as well as potential benefits in terms of treatment time and dose savings, the frequency of CBCT scans, and the accuracy of the positioning. METHODS: A group of 100 patients treated with the new workflow on two Versa HD linacs has been compared to a matched control group of patients treated with the former workflow, which included prepositioning with skin markings and lasers, SGRT and daily CBCT. The comparison was based on the evaluation of logfiles. RESULTS: Of the patients treated with the new workflow, 40% did not receive daily CBCT scans. This resulted in mean time savings of 97 s, 166 s and 239 s per fraction for the new workflow, for patients treated without daily CBCT and for SGRT-only fractions, respectively, when compared to the old workflow. Dose savings amounted to a weighted computed tomography dose index reduction of CTDIW = 2.56 cGy on average for normofractionated treatment and weekly CBCTs, while for patients not treated with daily CBCT, SGRT-based positioning accuracy was 5.2 mm for the mean translational magnitude, as evaluated by CBCT. CONCLUSION: For 40% of the patients, after five fractions with small CBCT corrections, the workflow could be changed to SGRT-only positioning with weekly CBCT. This leads to imaging dose and time savings and thus also reduced intrafraction motion, potentially increased patient throughput and patient comfort, while assuring appropriate positioning accuracy.

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.

Clinical application of breathing-adapted 4D CT: image quality comparison to conventional 4D CT.

PURPOSE: 4D CT imaging is an integral part of 4D radiotherapy workflows. However, 4D CT data often contain motion artifacts that mitigate treatment planning. Recently, breathing-adapted 4D CT (i4DCT) was introduced into clinical practice, promising artifact reduction in in-silico and phantom studies. Here, we present an image quality comparison study, pooling clinical patient data from two centers: a new i4DCT and a conventional spiral 4D CT patient cohort. METHODS: The i4DCT cohort comprises 129 and the conventional spiral 4D CT cohort 417 4D CT data sets of lung and liver tumor patients. All data were acquired for treatment planning. The study consists of three parts: illustration of image quality in selected patients of the two cohorts with similar breathing patterns; an image quality expert rater study; and automated analysis of the artifact frequency. RESULTS: Image data of the patients with similar breathing patterns underline artifact reduction by i4DCT compared to conventional spiral 4D CT. Based on a subgroup of 50 patients with irregular breathing patterns, the rater study reveals a fraction of almost artifact-free scans of 89% for i4DCT and only 25% for conventional 4D CT; the quantitative analysis indicated a reduction of artifact frequency by 31% for i4DCT. CONCLUSION: The results demonstrate 4D CT image quality improvement for patients with irregular breathing patterns by breathing-adapted 4D CT in this first corresponding clinical data image quality comparison study.

First clinical experience with a novel, mobile cone-beam CT system for treatment quality assurance in brachytherapy.

BACKGROUND AND PURPOSE: On-site cone-beam computed tomography (CBCT) has gained in importance in adaptive brachytherapy during recent years. Besides treatment planning, there is increased need particularly for image-guidance during interventional procedures and for image-guided treatment quality assurance (QA). For this purpose, an innovative CBCT device was rolled out at our hospital as the first site worldwide. We present the first clinical images and experiences. MATERIALS AND METHODS: The novel CBCT system is constructed of a 121 cm diameter ring gantry, and features a 43.2â€¯× 43.2 cm2 flat-panel detector, wireless remote-control via tablet-PC, and battery-powered maneuverability. Within the first months of clinical operation, we performed CBCT-based treatment QA for a total of 26 patients (8 with breast, 16 with cervix, and 2 with vaginal cancer). CBCT scans were analyzed regarding potential movements of implanted applicators in-situ during the brachytherapy course. RESULTS: With the presented device, treatment QA was feasible for the majority of patients. The CBCT scans of breast patients showed sufficient contrast between implanted catheters and tissue. For gynecologic patients, a distinct visualization of applicators was achieved in general. However, reasonable differentiations of organic soft tissues were not feasible. CONCLUSION: The CBCT system allowed basic treatment QA measures for breast and gynecologic patients. For image-guidance during interventional brachytherapy procedures, the current image quality is not adequate. Substantial performance enhancements are required for intraoperative image-guidance.

QAMaster: A new software framework for phantom-based computed tomography quality assurance.

The regular evaluation of imaging performance of computed tomography (CT) scanners is essential for CT quality assurance. For automation of this process, the software QAMaster was developed at the Universitätsklinikum Erlangen, which provides based on CT scans of the CatPhan® 504 (The Phantom Laboratory, Salem, USA) automated image quality analysis and documentation by evaluating CT number accuracy, spatial linearity, uniformity, contrast-noise-ratio, spatial resolution, noise, and slice thickness. Dose assessment is supported by calculations of the weighted computed tomography dose index (CTDIw ) and weighted cone beam dose index (CBDIw ). QAMaster was tested with CatPhan® 504 scans and compared to manual evaluations of these scans, whereby high consistency of the respective results was observed. The CT numbers, spatial linearity, uniformity, contrast-noise-ratio, noise, and slice thickness deviated by only (0.13 ± 0.25) HU, (0.02 ± 0.05) mm, (-0.01 ± 0.03)%, 0.8 ± 1.8, (0.131 ± 0.05) HU, and (0.004 ± 0.005) mm between both evaluations, respectively. The QAMaster results for spatial resolution did not differ significantly (p = 0.34) from the CatPhan® 504 based manual resolution assessment. Dose computations were fully consistent between QAMaster and manual calculations. Thus, QAMaster proved to be a comprehensive and functional software for performing an automated CT quality assurance routine. QAMaster will be open-source after its release.

Technical evaluation of the cone-beam computed tomography imaging performance of a novel, mobile, gantry-based X-ray system for brachytherapy.

PURPOSE: A novel, mobile cone-beam computed tomography (CBCT) system for image-guided adaptive brachytherapy was recently deployed at our hospital as worldwide first site. Prior to the device's clinical operation, a profound characterization of its imaging performance was conducted. This was essential to optimize both the imaging workflow and image quality for achieving the best possible clinical outcomes. We present the results of our investigations. METHODS: The novel CBCT-system features a ring gantry with 121 cm clearance as well as a 43.2 × 43.2 cm2 flat-panel detector, and is controlled via a tablet-personal computer (PC). For evaluating its imaging performance, the geometric reproducibility as well as imaging fidelity, computed tomography (CT)-number accuracy, uniformity, contrast-noise-ratio (CNR), noise characteristics, and spatial resolution as fundamental image quality parameters were assessed. As dose metric the weighted cone-beam dose index (CBDIw ) was measured. Image quality was evaluated using standard quality assurance (QA) as well as anthropomorphic upper torso and breast phantoms. Both in-house and manufacturer protocols for abdomen, pelvis, and breast imaging were examined. RESULTS: Using the in-house protocols, the QA phantom scans showed altogether a high image quality, with high CT-number accuracy (R2  > 0.97) and uniformity (<12 Hounsfield Unit (HU) cupping), reasonable noise and imaging fidelity, and good CNR at bone-tissue transitions of up to 28:1. Spatial resolution was strongly limited by geometric instabilities of the device. The breast phantom scans fulfilled clinical requirements, whereas the abdomen and pelvis scans showed severe artifacts, particularly at air/bone-tissue transitions. CONCLUSION: With the novel CBCT-system, achieving a high image quality appears possible in principle. However, adaptations of the standard protocols, performance enhancements in image reconstruction referring to artifact reductions, as well as the extinction of geometric instabilities are imperative.

Quality assurance and long-term stability of a novel 3-in-1 X-ray system for brachytherapy.

PURPOSE: A novel, mobile 3-in-1 X-ray system featuring radiography, fluoroscopy, and cone-beam computed tomography (CBCT) has been launched for brachytherapy recently. Currently, there is no quality assurance (QA) procedure explicitly applicable to this system equipped with innovative technologies such as dynamic jaws and motorized lasers. We developed a dedicated QA procedure and, based on its performance for a duration of 6 months, provide an assessment of the device's stability over time. METHODS: With the developed QA procedure, we assessed the system's planar and CBCT-imaging performance by investigating geometric accuracy, CT-number stability, contrast-noise-ratio, uniformity, spatial resolution, low-contrast detectability, dynamic range, and X-ray exposure using dedicated phantoms. Furthermore, we evaluated geometric stability by using the flexmap-approach and investigated the device's laser- and jaw-positioning accuracy with an in-house test phantom. CBCT- and planar-imaging protocols for pelvis, breast, and abdomen imaging were examined. RESULTS: Planar- and CBCT-imaging performances were widely stable with a geometric accuracy ≤1 mm, CT-number stability of up to 46 HU, and uniformity variations of up to 48 HU over time. For planar imaging, low-contrast detectability and dynamic range exceeded current recommendations. Although geometric stability was considered tolerable, partly substantial positioning inaccuracies of up to more than 120 mm and -13 mm were obtained for lasers and jaws, respectively. X-ray exposure showed small variations of ≤0.56 µGy and ≤0.76 mGy for planar- and CBCT-imaging, respectively. The conductance of the QA procedure allowed a smooth evaluation of the system's overall performance. CONCLUSION: We developed a QA workflow for a novel 3-in-1 X-ray system allowing to assess the device's imaging and hardware performance. The system showed in general a reasonable imaging performance and stability over time, whereas improvements regarding laser and jaw accuracy are strictly required.

Low- vs. high-dose radiotherapy in Graves' ophthalmopathy: a retrospective comparison of long-term results.

PURPOSE: Radiotherapy represents an effective treatment option in Graves' ophthalmopathy (GO), leading to palliation of clinical symptoms. However, there are only a limited number of trials comparing the effectiveness of low- vs. high-dose radiotherapy. METHODS: We analyzed 127 patients treated with radiotherapy for stage 3/4 GO (NOSPECS classification). Patients were treated with single doses of 2.0 Gy (cumulative dose 20 Gy) until 2007, afterwards a single dose of 0.8 Gy (cumulative dose 4.8 Gy) was applied. With a median follow-up-time of 9.0 years, the treatment efficacy (overall improvement, sense of eye pressure, lid edema, ocular motility, exophthalmos, subjective vision, and diplopia) and adverse effects were analyzed by a standardized survey. RESULTS: Overall, 63.8% described improvement of symptoms after radiotherapy. No significant differences in overall treatment response and improvement of main outcome measures between low- or high-dose radiotherapy treatments are detectable, while low-dose radiotherapy leads significantly more often to retreatment (13.1% vs. 1.7%, p = 0.016). The main independent predictor of treatment response is the presence of lid edema (odds ratio, OR, 3.53; p = 0.006). CONCLUSION: At long-term follow-up, the majority of patients reported palliation of symptoms with limited adverse effects, suggesting clinical effectiveness of radiotherapy for amelioration of GO symptoms independent of low- or high-dose radiotherapy.

Implementation of a dedicated 1.5 T MR scanner for radiotherapy treatment planning featuring a novel high-channel coil setup for brain imaging in treatment position.

PURPOSE: To share our experiences in implementing a dedicated magnetic resonance (MR) scanner for radiotherapy (RT) treatment planning using a novel coil setup for brain imaging in treatment position as well as to present developed core protocols with sequences specifically tuned for brain and prostate RT treatment planning. MATERIALS AND METHODS: Our novel setup consists of two large 18-channel flexible coils and a specifically designed wooden mask holder mounted on a flat tabletop overlay, which allows patients to be measured in treatment position with mask immobilization. The signal-to-noise ratio (SNR) of this setup was compared to the vendor-provided flexible coil RT setup and the standard setup for diagnostic radiology. The occurrence of motion artifacts was quantified. To develop magnetic resonance imaging (MRI) protocols, we formulated site- and disease-specific clinical objectives. RESULTS: Our novel setup showed mean SNR of 163 ± 28 anteriorly, 104 ± 23 centrally, and 78 ± 14 posteriorly compared to 84 ± 8 and 102 ± 22 anteriorly, 68 ± 6 and 95 ± 20 centrally, and 56 ± 7 and 119 ± 23 posteriorly for the vendor-provided and diagnostic setup, respectively. All differences were significant (p > 0.05). Image quality of our novel setup was judged suitable for contouring by expert-based assessment. Motion artifacts were found in 8/60 patients in the diagnostic setup, whereas none were found for patients in the RT setup. Site-specific core protocols were designed to minimize distortions while optimizing tissue contrast and 3D resolution according to indication-specific objectives. CONCLUSION: We present a novel setup for high-quality imaging in treatment position that allows use of several immobilization systems enabling MR-only workflows, which could reduce unnecessary dose and registration inaccuracies.

Region of interest optimization for radiation therapy of breast cancer.

PURPOSE: The goal of this study was to investigate how the choice of the region of interest (ROI) affects the registration results of surface imaging for daily positioning of breast cancer patients. METHODS: The AlignRT system (VisionRT, London) and the XVI Cone beam CT (CBCT; Elekta, Stockholm) installed on two Versa HD linacs (Elekta) were used in this study, which included 28 patients (160 fractions). In the clinical workflow, patients were prepositioned with AlignRT and then shifted in 6 degrees of freedom (DOF) according to the CBCT. A new reference capture was taken immediately afterward. Retrospectively, the surface capture resulting from prepositioning was registered to the latest reference capture. By varying the ROI used for registration, the surface-based results were optimized in terms of minimizing the deviation to the clinically applied CBCT shifts. Two sets of ROIs were used: one obtained by applying a variable margin to the breast surface, another by combining ROIs of anatomical structures, including the sternum and contralateral breast. RESULTS: Registration results showed significant differences from one ROI to another. Generally, the results improved with increasing ROI size, especially for rotational DOFs. ROIs, including the axilla or supraclavicular lymph drainage region, did not yield an improved registration result. On the other hand, an ROI comprising the breast surface, sternum, and a belt caudal to the breasts decreased the average magnitude of the translational and rotational deviations by 6.6% and 30.8% (p < 0.01), respectively, compared to the breast surface only results. CONCLUSION: The influence of the ROI choice on surface imaging registration results was analyzed and the surface-based shifts were compared to clinically applied CBCT shifts. An optimal ROI for the treatment of breast cancer patients, consisting of the breast surface, sternum, and a belt, was identified.

Adaptive radiotherapy and the dosimetric impact of inter- and intrafractional motion on the planning target volume for prostate cancer patients.

PURPOSE: To investigate the dosimetric influence of daily interfractional (inter) setup errors and intrafractional (intra) target motion on the planning target volume (PTV) and the possibility of an offline adaptive radiotherapy (ART) method to correct larger patient positioning uncertainties in image-guided radiotherapy for prostate cancer (PCa). MATERIALS AND METHODS: A CTV (clinical target volume)-to-PTV margin ranging from 15 mm in LR (left-right) and SI (superior-inferior) and 5-10 mm in AP (anterior-posterior) direction was applied to all patients. The dosimetric influence of this margin was retrospectively calculated by analysing systematic and random components of inter and intra errors of 31 consecutive intermediate- and high-risk localized PCa patients using daily cone beam computed tomography and kV/kV (kilo-Voltage) imaging. For each patient inter variation was assessed by observing the first 4 treatment days, which led to an offline ART-based treatment plan in case of larger variations. RESULTS: Systematic inter uncertainties were larger (1.12 in LR, 2.28 in SI and 1.48 mm in AP) than intra systematic errors (0.44 in LR, 0.69 in SI and 0.80 mm in AP). Same findings for the random error in SI direction with 3.19 (inter) and 2.30 mm (intra), whereas in LR and AP results were alike with 1.89 (inter) and 1.91 mm (intra) and 2.10 (inter) and 2.27 mm (intra), respectively. The calculated margin revealed dimensions of 4-5 mm in LR, 8-9 mm in SI and 6-7 mm in AP direction. Treatment plans which had to be adapted showed smaller variations with 1.12 (LR) and 1.72 mm (SI) for Σ and 4.17 (LR) and 3.75 mm (SI) for σ compared to initial plans with 1.77 and 2.62 mm for Σ and 4.46 and 5.39 mm for σ in LR and SI, respectively. CONCLUSION: The currently clinically used margin of 15 mm in LR and SI and 5-10 mm in AP direction includes inter and intra uncertainties. The results show that offline ART is feasible which becomes a necessity with further reductions in PTV margins.

Magnetic resonance imaging for brain stereotactic radiotherapy : A review of requirements and pitfalls.

Due to its superior soft tissue contrast, magnetic resonance imaging (MRI) is essential for many radiotherapy treatment indications. This is especially true for treatment planning in intracranial tumors, where MRI has a long-standing history for target delineation in clinical practice. Despite its routine use, care has to be taken when selecting and acquiring MRI studies for the purpose of radiotherapy treatment planning. Requirements on MRI are particularly demanding for intracranial stereotactic radiotherapy, where accurate imaging has a critical role in treatment success. However, MR images acquired for routine radiological assessment are frequently unsuitable for high-precision stereotactic radiotherapy as the requirements for imaging are significantly different for radiotherapy planning and diagnostic radiology. To assure that optimal imaging is used for treatment planning, the radiation oncologist needs proper knowledge of the most important requirements concerning the use of MRI in brain stereotactic radiotherapy. In the present review, we summarize and discuss the most relevant issues when using MR images for target volume delineation in intracranial stereotactic radiotherapy.

Automation of radiation treatment planning : Evaluation of head and neck cancer patient plans created by the Pinnacle3 scripting and Auto-Planning functions.

BACKGROUND: Intensity-modulated radiotherapy (IMRT) techniques are now standard practice. IMRT or volumetric-modulated arc therapy (VMAT) allow treatment of the tumor while simultaneously sparing organs at risk. Nevertheless, treatment plan quality still depends on the physicist's individual skills, experiences, and personal preferences. It would therefore be advantageous to automate the planning process. This possibility is offered by the Pinnacle3 treatment planning system (Philips Healthcare, Hamburg, Germany) via its scripting language or Auto-Planning (AP) module. MATERIALS AND METHODS: AP module results were compared to in-house scripts and manually optimized treatment plans for standard head and neck cancer plans. Multiple treatment parameters were scored to judge plan quality (100 points = optimum plan). Patients were initially planned manually by different physicists and re-planned using scripts or AP. RESULTS AND DISCUSSION: Script-based head and neck plans achieved a mean of 67.0 points and were, on average, superior to manually created (59.1 points) and AP plans (62.3 points). Moreover, they are characterized by reproducibility and lower standard deviation of treatment parameters. Even less experienced staff are able to create at least a good starting point for further optimization in a short time. However, for particular plans, experienced planners perform even better than scripts or AP. Experienced-user input is needed when setting up scripts or AP templates for the first time. Moreover, some minor drawbacks exist, such as the increase of monitor units (+35.5% for scripted plans). CONCLUSION: On average, automatically created plans are superior to manually created treatment plans. For particular plans, experienced physicists were able to perform better than scripts or AP; thus, the benefit is greatest when time is short or staff inexperienced.