A marginal structural model for normal tissue complication probability.

The goal of radiation therapy for cancer is to deliver prescribed radiation dose to the tumor while minimizing dose to the surrounding healthy tissues. To evaluate treatment plans, the dose distribution to healthy organs is commonly summarized as dose-volume histograms (DVHs). Normal tissue complication probability (NTCP) modeling has centered around making patient-level risk predictions with features extracted from the DVHs, but few have considered adapting a causal framework to evaluate the safety of alternative treatment plans. We propose causal estimands for NTCP based on deterministic and stochastic interventions, as well as propose estimators based on marginal structural models that impose bivariable monotonicity between dose, volume, and toxicity risk. The properties of these estimators are studied through simulations, and their use is illustrated in the context of radiotherapy treatment of anal canal cancer patients.

Radiotherapy of prostate and head-and-neck tumour: An optimal treatment planning comparison for intensity modulated radiotherapy and volumetric modulated arctherapy techniques.

OBJECTIVE: To evaluate and compare merits between intensity modulated radiotherapy and volumetric modulated arc-therapy radiotherapy techniques to determine which technique can achieve better treatment plan quality and efficient delivery. METHODS: The retrospective study was conducted at the Radiation Oncology Department of SanBorotlo Hospital, Vicenza, Italy, in 2019, and comprised data from Jan 2019 to Dec 2019 related to prostate and head-and-neck patients in whom Pinnacle³ treatment planning system was used for optimisation with different prescribed doses and target geometries for intensity modulated radiotherapy and volumetric modulated arc-therapy techniques. Treatment plans were simulated using 6MV photon beam of SynergyS® Linac (Linear accelerator). The plan quality was evaluated using dose-volume indices for planning target-volume and organs-at-risk. ArcCHECK™ phantom was used for dose agreement verification between planed and delivered doses. RESULTS: Data of 8 patients was analysed. Intensity modulated radiotherapy and volumetric modulated arc-therapy treatment plan quality for prostate was found to be similar, but volumetric modulated arc-therapy had significant results for maximum dose (p=0.005). Intensity modulated radiotherapy and volumetric modulated arc-therapy plans for head-and-neck achieved adequate target coverage and sparing of organs at risk, and produced clinically acceptable treatment plans. The percentage of target coverage (p=0.001), dose maximum (p=0.013) and conformity index (p=0.000) were significant. A significant gain for all planning target volume dose-volume indices was noted (p<0.05). Volumetric modulated arc-therapy obtained better plan with significant values and improved sparing of organs at risk compared to intensity modulated radiotherapy for both prostate and head-and-neck treatments while maintaining doses to the organs at risk (p<0.05). CONCLUSIONS: Dynamic arc mode of beam delivery provided increased degrees of freedom of volumetric modulated arc-therapy beam intensity modulation, depicting superior dose distribution than intensity modulated radiotherapy.

Image quality comparisons of coil setups in 3T MRI for brain and head and neck radiotherapy simulations.

PURPOSE: MRI is increasingly used for brain and head and neck radiotherapy treatment planning due to its superior soft tissue contrast. Flexible array coils can be arranged to encompass treatment immobilization devices, which do not fit in diagnostic head/neck coils. Selecting a flexible coil arrangement to replace a diagnostic coil should rely on image quality characteristics and patient comfort. We compared image quality obtained with a custom UltraFlexLarge18 (UFL18) coil setup against a commercial FlexLarge4 (FL4) coil arrangement, relative to a diagnostic Head/Neck20 (HN20) coil at 3T. METHODS: The large American College of Radiology (ACR) MRI phantom was scanned monthly in the UFL18, FL4, and HN20 coil setup over 2 years, using the ACR series and three clinical sequences. High-contrast spatial resolution (HCSR), image intensity uniformity (IIU), percent-signal ghosting (PSG), low-contrast object detectability (LCOD), signal-to-noise ratio (SNR), and geometric accuracy were calculated according to ACR recommendations for each series and coil arrangement. Five healthy volunteers were scanned with the clinical sequences in all three coil setups. SNR, contrast-to-noise ratio (CNR) and artifact size were extracted from regions-of-interest along the head for each sequence and coil setup. For both experiments, ratios of image quality parameters obtained with UFL18 or FL4 over those from HN20 were formed for each coil setup, grouping the ACR and clinical sequences. RESULTS: Wilcoxon rank-sum tests revealed significantly higher (p < 0.001) LCOD, IIU and SNR, and lower PSG ratios with UFL18 than FL4 on the phantom for the clinical sequences, with opposite PSG and SNR trends for the ACR series. Similar statistical tests on volunteer data corroborated that SNR ratios with UFL18 (0.58 ± 0.19) were significantly higher (p < 0.001) than with FL4 (0.51 ± 0.18) relative to HN20. CONCLUSIONS: The custom UFL18 coil setup was selected for clinical application in MR simulations due to the superior image quality demonstrated on a phantom and volunteers for clinical sequences and increased volunteer comfort.

A pilot study of function-based radiation therapy planning for lung cancer using hyperpolarized xenon-129 ventilation MRI.

PURPOSE: Radiation-induced lung injury (RILI) is a common side effect in patients with non-small cell lung cancer (NSCLC) treated with radiotherapy. Minimizing irradiation into highly functional areas of the lung may reduce the occurrence of RILI. The aim of this study is to evaluate the feasibility and utility of hyperpolarized xenon-129 magnetic resonance imaging (MRI), an imaging tool for evaluation of the pulmonary function, to guide radiotherapy planning. METHODS: Ten locally advanced NSCLC patients were recruited. Each patient underwent a simulation computed tomography (CT) scan and hyperpolarized xenon-129 MRI, then received 64 Gyin 32 fractions for radiotherapy. Clinical contours were drawn on CT. Lung regions with good ventilation were contoured based on the MRI. Two intensity-modulated radiation therapy plans were made for each patient: an anatomic plan (Plan-A) based on CT alone and a function-based plan (Plan-F) based on CT and MRI results. Compared to Plan-A, Plan-F was generated with two additional steps: (1) beam angles were carefully chosen to minimize direct radiation entering well-ventilated areas, and (2) additional optimization criteria were applied to well-ventilated areas to minimize dose exposure. V20Gy , V10Gy , V5Gy , and the mean dose in the lung were compared between the two plans. RESULTS: Plan-A and Plan-F were both clinically acceptable and met similar target coverage and organ-at-risk constraints (p > 0.05) except for the ventilated lungs. Compared with Plan-A, V5Gy (Plan-A: 30.7 ± 11.0%, Plan-F: 27.2 ± 9.3%), V10Gy (Plan-A: 22.0 ± 8.6%, Plan-F: 19.3 ± 7.0%), and V20Gy (Plan-A: 12.5 ± 5.6%, Plan-F: 11.0 ± 4.1%) for well-ventilated lung areas were significantly reduced in Plan-F (p < 0.05). CONCLUSION: In this pilot study, function-based radiotherapy planning using hyperpolarized xenon-129 MRI is demonstrated to be feasible in 10 patients with NSCLC with the potential to reduce radiation exposure in well-ventilated areas of the lung defined by hyperpolarized xenon-129 MRI.

Attention-aware 3D U-Net convolutional neural network for knowledge-based planning 3D dose distribution prediction of head-and-neck cancer.

PURPOSE: Deep learning-based knowledge-based planning (KBP) methods have been introduced for radiotherapy dose distribution prediction to reduce the planning time and maintain consistent high-quality plans. This paper presents a novel KBP model using an attention-gating mechanism and a three-dimensional (3D) U-Net for intensity-modulated radiation therapy (IMRT) 3D dose distribution prediction in head-and-neck cancer. METHODS: A total of 340 head-and-neck cancer plans, representing the OpenKBP-2020 AAPM Grand Challenge data set, were used in this study. All patients were treated with the IMRT technique and a dose prescription of 70 Gy. The data set was randomly divided into 64%/16%/20% as training/validation/testing cohorts. An attention-gated 3D U-Net architecture model was developed to predict full 3D dose distribution. The developed model was trained using the mean-squared error loss function, Adam optimization algorithm, a learning rate of 0.001, 120 epochs, and batch size of 4. In addition, a baseline U-Net model was also similarly trained for comparison. The model performance was evaluated on the testing data set by comparing the generated dose distributions against the ground-truth dose distributions using dose statistics and clinical dosimetric indices. Its performance was also compared to the baseline model and the reported results of other deep learning-based dose prediction models. RESULTS: The proposed attention-gated 3D U-Net model showed high capability in accurately predicting 3D dose distributions that closely replicated the ground-truth dose distributions of 68 plans in the test set. The average value of the mean absolute dose error was 2.972 ± 1.220 Gy (vs. 2.920 ± 1.476 Gy for a baseline U-Net) in the brainstem, 4.243 ± 1.791 Gy (vs. 4.530 ± 2.295 Gy for a baseline U-Net) in the left parotid, 4.622 ± 1.975 Gy (vs. 4.223 ± 1.816 Gy for a baseline U-Net) in the right parotid, 3.346 ± 1.198 Gy (vs. 2.958 ± 0.888 Gy for a baseline U-Net) in the spinal cord, 6.582 ± 3.748 Gy (vs. 5.114 ± 2.098 Gy for a baseline U-Net) in the esophagus, 4.756 ± 1.560 Gy (vs. 4.992 ± 2.030 Gy for a baseline U-Net) in the mandible, 4.501 ± 1.784 Gy (vs. 4.925 ± 2.347 Gy for a baseline U-Net) in the larynx, 2.494 ± 0.953 Gy (vs. 2.648 ± 1.247 Gy for a baseline U-Net) in the PTV_70, and 2.432 ± 2.272 Gy (vs. 2.811 ± 2.896 Gy for a baseline U-Net) in the body contour. The average difference in predicting the D99 value for the targets (PTV_70, PTV_63, and PTV_56) was 2.50 ± 1.77 Gy. For the organs at risk, the average difference in predicting the D m a x ${D_{max}}$ (brainstem, spinal cord, and mandible) and D m e a n ${D_{mean}}$ (left parotid, right parotid, esophagus, and larynx) values was 1.43 ± 1.01 and 2.44 ± 1.73 Gy, respectively. The average value of the homogeneity index was 7.99 ± 1.45 for the predicted plans versus 5.74 ± 2.95 for the ground-truth plans, whereas the average value of the conformity index was 0.63 ± 0.17 for the predicted plans versus 0.89 ± 0.19 for the ground-truth plans. The proposed model needs less than 5 s to predict a full 3D dose distribution of 64 × 64 × 64 voxels for a new patient that is sufficient for real-time applications. CONCLUSIONS: The attention-gated 3D U-Net model demonstrated a capability in predicting accurate 3D dose distributions for head-and-neck IMRT plans with consistent quality. The prediction performance of the proposed model was overall superior to a baseline standard U-Net model, and it was also competitive to the performance of the best state-of-the-art dose prediction method reported in the literature. The proposed model could be used to obtain dose distributions for decision-making before planning, quality assurance of planning, and guiding-automated planning for improved plan consistency, quality, and planning efficiency.

Assessment of the effects of different dental restorative materials on radiotherapy dose distribution: A phantom study.

Background: One of the most specific effects of high-density dental restorative materials on head & neck cancer radiotherapy is generating variations on isodose distributions. These variations might have an impact on the accuracy and effectiveness of the radiation treatment. The aim of this study is investigating the possible dosimetric effect of six different restorative materials on isodose distributions in head & neck radiotherapy planning process. Materials and Methods: A special phantom was developed and twenty-one caries-free human third molars (a control group + six different restorative materials) were used for the measurements. After acquiring the computed tomography (CT) images, seven treatment plans were created. Hounsfield Unit (HU) numbers, horizontal line dose profile (HLDP) and vertical line dose profiles (VLDPs) were compared with the control group. Results: The amalgam sample deformed the HU numbers in CT images. The median HU value for the S4 material was considerably different than the other samples. The median values were quite close for the remaining samples. For the amalgam sample, the mean of the calculated median isodose values for HLDP and VLDP at 3.5 cm away from the isocenter line were lower than the mean of the control group 4.03% and 6.94%, respectively (for HLDP with tooth numbers of 36 and 38 P = 0.025 and P < 0.001, respectively; for VLDP P < 0.001). In C-S1 comparison results, the statistically significant differences were found for the measurement point at 1 cm away from the isocenter (P = 0.037, P = 0.002, and P = 0.018 for the tooth numbers 36, 37, and 38, respectively). In C-S2 and C-S6 comparisons, there was a statistically significant difference for tooth number 36 (P = 0.035 and P = 0.003, respectively). Conclusions: The findings of the present study showed that amalgam should not be used in head & neck cancer patients who are planned to have radiation therapy. A high viscosity glass ionomer cement (GIC) and a ceramic reinforced GIC sample can be used instead of amalgam to minimize the distorting effect on isodose distributions.

Accuracy of surface-guided patient setup for conventional radiotherapy of brain and nasopharynx cancer.

PURPOSE: To evaluate the accuracy of surface-guided radiotherapy (SGRT) in cranial patient setup by direct comparison between optical surface imaging (OSI) and cone-beam computed tomography (CBCT), before applying SGRT-only setup for conventional radiotherapy of brain and nasopharynx cancer. METHODS AND MATERIALS: Using CBCT as reference, SGRT setup accuracy was examined based on 269 patients (415 treatments) treated with frameless cranial stereotactic radiosurgery (SRS) during 2018-2019. Patients were immobilized in customized head molds and open-face masks and monitored using OSI during treatment. The facial skin area in planning CT was used as OSI region of interest (ROI) for automatic surface alignment and the skull was used as the landmark for automatic CBCT/CT registration. A 6 degrees of freedom (6DOF) couch was used. Immediately after CBCT setup, an OSI verification image was captured, recording the SGRT setup differences. These differences were analyzed in 6DOFs and as a function of isocenter positions away from the anterior surface to assess OSI-ROI bias. The SGRT in-room setup time was estimated and compared with CBCT and orthogonal 2D kilovoltage (2DkV) setups. RESULTS: The SGRT setup difference (magnitude) is found to be 1.0 ± 2.5 mm and 0.1˚±1.4˚ on average among 415 treatments and within 5 mm/3˚ with greater than 95% confidence level (P < 0.001). Outliers were observed for very-posterior isocenters: 15 differences (3.6%) are >5.0mm and 9 (2.2%) are >3.0˚. The setup differences show minor correlations (|r| < 0.45) between translational and rotational DOFs and a minor increasing trend (<1.0 mm) in the anterior-to-posterior direction. The SGRT setup time is 0.8 ± 0.3 min, much shorter than CBCT (5 ± 2 min) and 2DkV (2 ± 1 min) setups. CONCLUSION: This study demonstrates that SGRT has sufficient accuracy for fast in-room patient setup and allows real-time motion monitoring for beam holding during treatment, potentially useful to guide radiotherapy of brain and nasopharynx cancer with standard fractionation.

Knowledge-based radiation treatment planning: A data-driven method survey.

This paper surveys the data-driven dose prediction methods investigated for knowledge-based planning (KBP) in the last decade. These methods were classified into two major categories-traditional KBP methods and deep-learning (DL) methods-according to their techniques of utilizing previous knowledge. Traditional KBP methods include studies that require geometric or anatomical features to either find the best-matched case(s) from a repository of prior treatment plans or to build dose prediction models. DL methods include studies that train neural networks to make dose predictions. A comprehensive review of each category is presented, highlighting key features, methods, and their advancements over the years. We separated the cited works according to the framework and cancer site in each category. Finally, we briefly discuss the performance of both traditional KBP methods and DL methods, then discuss future trends of both data-driven KBP methods to dose prediction.

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.

Non-rigid image registration of 4D-MRI data for improved delineation of moving tumors.

BACKGROUND: To increase the image quality of end-expiratory and end-inspiratory phases of retrospective respiratory self-gated 4D MRI data sets using non-rigid image registration for improved target delineation of moving tumors. METHODS: End-expiratory and end-inspiratory phases of volunteer and patient 4D MRI data sets are used as targets for non-rigid image registration of all other phases using two different registration schemes: In the first, all phases are registered directly (dir-Reg) while next neighbors are successively registered until the target is reached in the second (nn-Reg). Resulting data sets are quantitatively compared using diaphragm and tumor sharpness and the coefficient of variation of regions of interest in the lung, liver, and heart. Qualitative assessment of the patient data regarding noise level, tumor delineation, and overall image quality was performed by blinded reading based on a 4 point Likert scale. RESULTS: The median coefficient of variation was lower for both registration schemes compared to the target. Median dir-Reg coefficient of variation of all ROIs was 5.6% lower for expiration and 7.0% lower for inspiration compared with nn-Reg. Statistical significant differences between the two schemes were found in all comparisons. Median sharpness in inspiration is lower compared to expiration sharpness in all cases. Registered data sets were rated better compared to the targets in all categories. Over all categories, mean expiration scores were 2.92 ± 0.18 for the target, 3.19 ± 0.22 for nn-Reg and 3.56 ± 0.14 for dir-Reg and mean inspiration scores 2.25 ± 0.12 for the target, 2.72 ± 215 0.04 for nn-Reg and 3.78 ± 0.04 for dir-Reg. CONCLUSIONS: In this work, end-expiratory and inspiratory phases of a 4D MRI data sets are used as targets for non-rigid image registration of all other phases. It is qualitatively and quantitatively shown that image quality of the targets can be significantly enhanced leading to improved target delineation of moving tumors.

[Efficient Commissioning of the Radiotherapy Treatment Planning System with the Golden Beam Data].

Commissioning of a linear accelerator (Linac) and treatment planning systems (RTPs) for clinical use is complex and time-consuming, typically 3-4 months in total. However, based on clinical needs and economics, hospitals desire early clinical starts for patients, and various studies have been conducted for shortening the preparation period. One of the methods to shorten the period is using golden beam data (GBD). The purpose of this study was to shorten the commissioning period without reducing accuracy and to simplify commissioning works while improving safety. We conducted commissioning of the RTPs before installing the Linac using GBD, and carried out verification immediately after the acceptance test. We used TrueBeam STx (Varian Medical Systems) and Eclipse (ver. 13.7, Varian Medical Systems) for RTPs and anisotropic analysis algorithm (AAA) and AcurosXB (AXB) for calculation algorithms. The difference between GBD and the measured beam data was 0.0 ± 0.2% [percentage depth dose (PDDs) ] and -0.1 ± 0.2% (Profiles) with X-ray, and -1.2 ± 1.3% (PDDs) with electrons. The difference between the calculated dose and the measured dose was 0.1 ± 0.3% (AAA) and 0.0 ± 0.3% (AXB) under homogeneous conditions, and 0.7 ± 1.4% (AAA) and 0.6 ± 1.1% (AXB) under heterogeneous conditions. We took 43 days from the end of the acceptance test to the start of clinical use. We found that the preparation period for clinical use can be shortened without reducing the accuracy, by thinning out the number of measurement items using GBD.

Respiratory-gated (4D) contrast-enhanced FDG PET-CT for radiotherapy planning of lower oesophageal carcinoma: feasibility and impact on planning target volume.

BACKGROUND: To assess the feasibility and potential impact on target delineation of respiratory-gated (4D) contrast-enhanced 18Fluorine fluorodeoxyglucose (FDG) positron emission tomography - computed tomography (PET-CT), in the treatment planning position, for a prospective cohort of patients with lower third oesophageal cancer. METHODS: Fifteen patients were recruited into the study. Imaging included 4D PET-CT, 3D PET-CT, endoscopic ultrasound and planning 4D CT. Target volume delineation was performed on 4D CT, 4D CT with co-registered 3D PET and 4D PET-CT. Planning target volumes (PTV) generated with 4D CT (PTV4DCT), 4D CT co-registered with 3D PET-CT (PTV3DPET4DCT) and 4D PET-CT (PTV4DPETCT) were compared with multiple positional metrics. RESULTS: Mean PTV4DCT, PTV3DPET4DCT and PTV4DPETCT were 582.4 ± 275.1 cm3, 472.5 ± 193.1 cm3 and 480.6 ± 236.9 cm3 respectively (no significant difference). Median DICE similarity coefficients comparing PTV4DCT with PTV3DPET4DCT, PTV4DCT with PTV4DPETCT and PTV3DPET4DCT with PTV4DPETCT were 0.85 (range 0.65-0.9), 0.85 (range 0.69-0.9) and 0.88 (range 0.79-0.9) respectively. The median sensitivity index for overlap comparing PTV4DCT with PTV3DPET4DCT, PTV4DCT with PTV4DPETCT and PTV3DPET4DCT with PTV4DPETCT were 0.78 (range 0.65-0.9), 0.79 (range 0.65-0.9) and 0.89 (range 0.68-0.94) respectively. CONCLUSIONS: Planning 4D PET-CT is feasible with careful patient selection. PTV generated using 4D CT, 3D PET-CT and 4D PET-CT were of similar volume, however, overlap analysis demonstrated that approximately 20% of PTV3DPETCT and PTV4DPETCT are not included in PTV4DCT, leading to under-coverage of target volume and a potential geometric miss. Additionally, differences between PTV3DPET4DCT and PTV4DPETCT suggest a potential benefit for 4D PET-CT. TRIAL REGISTRATION: ClinicalTrials.gov Identifier - NCT02285660 (Registered 21/10/2014).

Considerations for using data envelopment analysis for the assessment of radiotherapy treatment plan quality.

Purpose The operations research method of data envelopment analysis (DEA) shows promise for assessing radiotherapy treatment plan quality. The purpose of this paper is to consider the technical requirements for using DEA for plan assessment. Design/methodology/approach In total, 41 prostate treatment plans were retrospectively analysed using the DEA method. The authors investigate the impact of DEA weight restrictions with reference to the ability to differentiate plan performance at a level of clinical significance. Patient geometry influences plan quality and the authors compare differing approaches for managing patient geometry within the DEA method. Findings The input-oriented DEA method is the method of choice when performing plan analysis using the key undesirable plan metrics as the DEA inputs. When considering multiple inputs, it is necessary to constrain the DEA input weights in order to identify potential plan improvements at a level of clinical significance. All tested approaches for the consideration of patient geometry yielded consistent results. Research limitations/implications This work is based on prostate plans and individual recommendations would therefore need to be validated for other treatment sites. Notwithstanding, the method that requires both optimised DEA weights according to clinical significance and appropriate accounting for patient geometric factors is universally applicable. Practical implications DEA can potentially be used during treatment plan development to guide the planning process or alternatively used retrospectively for treatment plan quality audit. Social implications DEA is independent of the planning system platform and therefore has the potential to be used for multi-institutional quality audit. Originality/value To the authors' knowledge, this is the first published examination of the optimal approach in the use of DEA for radiotherapy treatment plan assessment.

Current status of remote radiotherapy treatment planning in Japan: findings from a national survey†.

The purpose of this study was to investigate the status of remote-radiotherapy treatment planning (RRTP) in Japan through a nationwide questionnaire survey. The survey was conducted between 29 June and 4 August 2022, at 834 facilities in Japan that were equipped with linear accelerators. The survey utilized a Google form that comprised 96 questions on facility information, information about the respondent, utilization of RRTP between facilities, usage for telework and the inclination to implement RRTPs in the respondent's facility. The survey analyzed the utilization of the RRTP system in four distinct implementation types: (i) utilization as a supportive facility, (ii) utilization as a treatment facility, (iii) utilization as a teleworker outside of the facility and (iv) utilization as a teleworker within the facility. The survey response rate was 58.4% (487 facilities responded). Among the facilities that responded, 10% (51 facilities) were implementing RRTP. 13 served as supportive facilities, 23 as treatment facilities, 17 as teleworkers outside of the facility and 5 as teleworkers within the facility. In terms of system usage between supportive and treatment facilities, 70-80% of the participants utilized the system for emergencies or as overtime work for external workers. A substantial number of facilities (38.8%) reported that they were unfamiliar with RRTP implementation. The survey showed that RRTP utilization in Japan is still limited, with a significant number of facilities unfamiliar with the technology. The study highlights the need for greater understanding and education about RRTP and financial funds of economical compensation.

Treatment planning for patients with low rectal cancer in a multicenter prospective organ preservation study.

BACKGROUND: Non-surgical management of rectal cancer relies on (chemo)radiotherapy as the definitive treatment modality. This study reports and evaluates the clinical high dose radiotherapy treatment plans delivered to patients with low resectable rectal cancer in a Danish multicenter trial. METHODS: The Danish prospective multicenter phase II Watchful Waiting 2 trial (NCT02438839) investigated definitive chemoradiation for non-surgical management of low rectal cancer. Three Danish centers participated in the trial and committed to protocol-specified treatment planning and delivery requirements. The protocol specified a dose of 50.4 Gy in 28 fractions to the elective volume (CTV-/PTV-E) and a concomitant boost of 62 Gy in 28 fractions to the primary target volume (CTV-/PTV-T). RESULTS: The trial included 108 patients, of which 106 treatment plans were available for retrospective analysis. Dose coverage planning goals for the main target structures were fulfilled for 94% of the treatment plans. However, large intercenter differences in doses to organs-at-risk (OARs) were seen, especially for the intestines. Five patients had a V60Gy>10 cm3 for the intestines and two patients for the bladder. CONCLUSION: Prescribed planning goals for target coverage were fulfilled for 94% of the treatment plans, however analysis of OAR doses and volumes indicated intercenter variations. Dose escalation to 62 Gy (as a concomitant boost to the primary tumor) introduced no substantial high dose volumes (>60 Gy) to the bladder and intestines. The treatment planning goals may be used for future prospective evaluation of highdose radiotherapy for organ preservation for low rectal cancer.

CycleSeg: Simultaneous synthetic CT generation and unsupervised segmentation for MR-only radiotherapy treatment planning of prostate cancer.

BACKGROUND: MR-only radiotherapy treatment planning is an attractive alternative to conventional workflow, reducing scan time and ionizing radiation. It is crucial to derive the electron density map or synthetic CT (sCT) from MR data to perform dose calculations to enable MR-only treatment planning. Automatic segmentation of relevant organs in MR images can accelerate the process by preventing the time-consuming manual contouring step. However, the segmentation label is available only for CT data in many cases. PURPOSE: We propose CycleSeg, a unified framework that generates sCT and corresponding segmentation from MR images without access to MR segmentation labels METHODS: CycleSeg utilizes the CycleGAN formulation to perform unpaired synthesis of sCT and image alignment. To enable MR (sCT) segmentation, CycleSeg incorporates unsupervised domain adaptation by using a pseudo-labeling approach with feature alignment in semantic segmentation space. In contrast to previous approaches that perform segmentation on MR data, CycleSeg could perform segmentation on both MR and sCT. Experiments were performed with data from prostate cancer patients, with 78/7/10 subjects in the training/validation/test sets, respectively. RESULTS: CycleSeg showed the best sCT generation results, with the lowest mean absolute error of 102.2 and the lowest Fréchet inception distance of 13.0. CycleSeg also performed best on MR segmentation, with the highest average dice score of 81.0 and 81.1 for MR and sCT segmentation, respectively. Ablation experiments confirmed the contribution of the proposed components of CycleSeg. CONCLUSION: CycleSeg effectively synthesized CT and performed segmentation on MR images of prostate cancer patients. Thus, CycleSeg has the potential to expedite MR-only radiotherapy treatment planning, reducing the prescribed scans and manual segmentation effort, and increasing throughput.

Dosimetric Comparison and Selection Criteria of Intensity-Modulated Proton Therapy and Intensity-Modulated Radiation Therapy for Adaptive Re-Plan in T3-4 Nasopharynx Cancer Patients.

BACKGROUND: Proton therapy requires caution when treating patients with targets near neural structures. Intuitive and quantitative guidelines are needed to support decision-making concerning the treatment modality. This study compared dosimetric profiles of intensity-modulated proton therapy (IMPT) and intensity-modulated radiation therapy (IMRT) using helical tomotherapy (HT) for adaptive re-planning in cT3-4 nasopharyngeal cancer (NPCa) patients, aiming to establish criteria for selecting appropriate treatment modalities. METHODS: HT and IMPT plans were generated for 28 cT3-4 NPCa patients undergoing definitive radiotherapy. Dosimetric comparisons were performed for target coverage and high-priority organs at risk (OARs). The correlation between dosimetric parameters and RT modality selection was analyzed with the target OAR distances. RESULTS: Target coverages were similar, while IMPT achieved better dose spillage. HT was more favorable for brainstem D1, optic chiasm Dmax, optic nerves Dmax, and p-cord D1. IMPT showed advantages for oral cavity Dmean. Actually, 14 IMPT and 14 HT plans were selected as adaptive plans, with IMPT allocated to most cT3 patients (92.9% vs. 42.9%, p = 0.013). The shortest distances from the target to neural structures were negatively correlated with OAR doses. Receiver operating characteristic curve analyses were carried out to discover the optimal cut-off values of the shortest distances between the target and the OARs (temporal lobes and brainstem), which were 0.75 cm (AUC = 0.908, specificity = 1.00) and 0.85 cm (AUC = 0.857, specificity = 0.929), respectively. CONCLUSIONS: NPCa patients with cT4 tumor or with the shortest distance between the target and critical neural structures < 0.8 cm were suboptimal candidates for IMPT adaptive re-planning. These criteria may improve resource utilization and clinical outcomes.

A systematic review of 4D magnetic resonance imaging techniques for abdominal radiotherapy treatment planning.

Background and purpose: Four-dimensional magnetic resonance imaging (4DMRI) has gained interest as an alternative to the current standard for motion management four-dimensional tomography (4DCT) in abdominal radiotherapy treatment planning (RTP). This review aims to assess the 4DMRI literature in abdomen, focusing on technical considerations and the validity of using 4DMRI for patients within radiotherapy protocols. Materials and methods: The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive search was performed across the Medline, Embase, Scopus, and Web of Science databases, covering all years up to December 31, 2023. The studies were grouped into two categories: 4DMRI reconstructed from 3DMRI acquisition; and 4DMRI reconstructed from multi-slice 2DMRI acquisition. Results: A total of 39 studies met the inclusion criteria and were analysed to provide key findings. Key findings were 4DMRI had the potential to improve abdominal RTP for patients by providing accurate tumour definition and motion assessment compared to 4DCT. 4DMRI reconstructed from 3DMRI acquisition showed promise as a feasible approach for motion management in abdominal RTP regarding spatial resolution. Currently,the slice thickness achieved on 4DMRI reconstructed from multi-slice 2DMRI acquisitions was unsuitable for clinical purposes. Lastly, the current barriers for clinical implementation of 4DMRI were the limited availability of validated commercial solutions and the lack of larger cohort comparative studies to 4DCT for target delineation and plan optimisation. Conclusion: 4DMRI showed potential improvements in abdominal RTP, but standards and guidelines for the use of 4DMRI in radiotherapy were required to demonstrate clinical benefits.

Shifting-field-of-view technique enhancing the inflow effect for identifying tumor/vessel boundaries in MRI for radiotherapy treatment planning.

This study presents two cases of tumors in contact with the inferior vena cava during radiotherapy, and introduces a clinically useful technique for identifying tumor boundaries adjacent to blood vessels by adjusting the position of the field-of-view (FOV) to enhance the inflow effect in magnetic resonance imaging. We named this technique "Shifting-FOV." This method consists of three steps: (1) remove the upper and lower saturation pulses outside the FOV, (2) align the FOV to position the lower edge of the imaging slab as close to the tumor as possible, and (3) manually adjust the table position to locate the tumor at the center of the magnetic field. The proposed method allowed for accurate identification of the tumor/vessel boundaries in both cases. This is a useful technique that can be readily applied to other facilities. Furthermore, images obtained using this technique may enable accurate tumor contouring in radiotherapy treatment planning.

Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?

Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is 'clinical acceptability'? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of 'clinical acceptability' and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.