This study aimed to evaluate the beam data of Elekta stereotactic radiosurgery (SRS) cone collimators for 6MV and 6MV flattening filter-free (6MVFFF) beams and to assess the feasibility of implementing a shared beam model across beam-matched linear accelerators (linacs). Percentage depth dose (PDD), beam profiles, and output factors were measured using IBA SFD and PTW microDiamond detectors for fixed (current clinical practice) and variable (previous clinical practice) jaw configurations. A Monaco X-ray voxelized Monte Carlo (XVMC)-based SRS model was developed on one linac and validated using SNC SRS MapCHECK and StereoPHANTM. The model's applicability was further tested on a second linac. The depth of maximum dose (Dmax) and PDD beyond Dmax decreased with smaller cones, while penumbra widened for larger cones. Compared to 6MVFFF, 6MV beams exhibited 5% higher in-field off-axis ratios (OARs) and 15% higher out-of-field OARs. The output factors for 6MVFFF exceeded those of 6MV by up to 5.83% (7.5-mm cone). Fixed jaw configurations increased out-of-field OARs by 15% and output factors by 0.57% compared to variable jaws. Measurements from IBA SFD and microDiamond detectors showed excellent agreement in PDD and beam profiles, with output factors differing by less than 2.33%. The Monaco XVMC model achieved >99.10% gamma passing rates (2%/2 mm) and <3.0% central axis point dose differences during validation. Both linacs demonstrated minimal discrepancies when using shared beam models. Fixed jaw settings increase out-of-field scatter and output factors for cones <35 mm. The comprehensive beam data for 6MV and 6MVFFF beams presented in this study provide a valuable reference for commissioning and quality assurance (QA) in clinical practice. IBA SFD and microDiamond detectors are suitable for SRS cone beam data collection and QA when appropriate corrections as per TRS-483 are applied. Shared beam models are feasible for beam-matched linacs, offering a streamlined approach to clinical work.
To evaluate whether a statistical process control (SPC) method can improve the safety and stability of radiotherapy planning for patients with nasopharyngeal carcinoma. A total of 200 patients were retrospectively enrolled and divided into 2 sequential phases. The first phase (100 patients) was used to establish baseline statistical parameters including centerlines and control limits. The second phase (100 patients) used these parameters to guide plan optimization. Dose indicators of organs at risk, target coverage, process stability, and process capability index were analyzed and compared between the 2 phases. After applying SPC, radiation doses to the larynx and parotid glands were significantly reduced, while target volume coverage was adequately maintained. All plans remained within stable statistical control limits, and process capability indices were improved, indicating enhanced process stability and reliability. SPC provides an effective, data-driven, and easy-to-implement tool for improving nasopharyngeal carcinoma radiotherapy planning. It reduces unnecessary radiation exposure to normal tissues, enhances process stability, and promotes consistent high-quality treatment. This method is clinically feasible and suitable for widespread application in routine radiotherapy quality assurance.
To develop and rigorously validate a deep learning framework for CT-free positron emission tomography (PET) attenuation correction in non-small cell lung cancer (NSCLC), with a comprehensive assessment of both quantitative and physical integrity to establish a proof-of-concept for its technical feasibility. A U-Net was trained on a multi-center dataset of 100 NSCLC patients to synthesize attenuation-corrected (AC) from nonattenuation-corrected (NAC) PET data. The framework's performance was evaluated on an independent 30-patient test set. The multi-faceted validation protocol included global image fidelity (peak signal-to-noise ratio [PSNR], structural similarity index measure [SSIM]), quantitative lesion integrity (SUVmax/SUVmean bias, dice similarity coefficient [DSC]), and fundamental physical characteristics (contrast recovery, spatial resolution). Bland-Altman analysis and paired statistical tests were used. The framework generated images with state-of-the-art global fidelity (PSNR: 36.2 dB; SSIM: 0.967). For lesion-specific analysis, the model introduced a negligible and statistically insignificant mean bias in both SUVmax (+0.72%;p=0.067). While SUVmean showed a statistically significant difference due to per-patient aggregation, the absolute bias remained clinically negligible (-1.23%;p=0.005). Spatial accuracy was excellent (mean DSC: 0.89). Critically, physical performance was preserved, with 99.2% contrast recovery and no significant degradation in spatial resolution. Deep learning-based attenuation correction synthesis is a highly promising proof-of-concept for CT-less thoracic PET. By demonstrating quantitative fidelity and preserved image-derived physical characteristics, this work establishes a foundational step toward a prospective emission-only workflow, which has the future potential to enhance patient safety by eliminating CT-associated radiation dose.
Linear accelerator-based stereotactic radiosurgery and stereotactic radiotherapy (SRS/SRT) are commonly used in the treatment of ocular malignancies. However, a substantial portion of the treatment planning process relies on manual plan optimization to achieve acceptable plan quality, leading to increased planning time and variability among planners. In this work, we demonstrate the feasibility of adapting a single-fraction model to a multifraction-capable knowledge-based planning model for ocular malignancies using noncoplanar treatment geometries. This approach has the potential to significantly improve planning efficiency for ocular SRS/SRT treatments. A previously validated HyperArc-based RapidPlan model for single-fraction (25 Gy) ocular SRS was adapted and further trained to handle 3- and 5-fraction prescriptions (42 Gy/3 Fx and 50 Gy/5 Fx). The knowledge-based planning (KBP) model was trained on 86 synthetic HyperArc plans and retrospectively tested on 24 datasets. Treatment planning was performed in the Varian Eclipse treatment planning system with the Acuros XB dose algorithm. Metrics included the Radiation Therapy Oncology Group conformity index, Paddick conformity index, gradient index, heterogeneity index, organ-at-risk (OAR) doses, and delivery accuracy via portal dosimetry patient-specific quality assurance (QA) and an in-house Monte Carlo second check. Across 1-, 3-, and 5-fraction ocular SRS/SRT regimens, the KBP model-based plans produced comparable target conformity, gradient, homogeneity, and coverage metrics, with no clinically meaningful differences between fractionation schemes. Differences in mean target dose (∼1%) were negligible. Most OAR constraints were met; optic nerve and lacrimal gland sparing were consistently achievable except when the OARs were included within the planning target volume, while lens and skin constraints were more challenging. Plan optimization was efficient (median ∼14 minutes), delivery times decreased with increased fractionation, and all KBP plans met patient-specific QA criteria with high pass rates during end-to-end testing and validation. These results demonstrate that a single RapidPlan model can generate high-quality ocular SRS plans across 1-, 3-, and 5-fraction schemes. The rapid generation of these KBP plans allows multiple fractionation schemes to be explored on a per-patient basis in a timely manner that would otherwise be clinically impractical with conventional manual planning.
Proton beam therapy (PBT) offers the advantage of delivering high doses of localized radiation therapy while sparing surrounding normal tissue, making it highly suitable for thoracic malignancies. However, the precision of PBT also makes it susceptible to treatment-related changes in the tumor or target volume, patient anatomy, and surrounding tissues, necessitating adaptive replanning. This study retrospectively analyzed the treatment plans of 180 thoracic cancer patients treated at an academic proton therapy center between 2020 and 2023. We investigated whether treatment planning dosimetric parameters, such as robustness, dose maximum, and doses to organs at risk in initial plans, can predict the need for adaptive replanning. Significant predictors identified include clinical target volume (CTV), heart volume, plan Dmax, mean lung dose, lung V20, lung V5, mean heart dose, heart V50, and spinal cord Dmax. Among those parameters, CTV and heart volume independently predict the need for replanning, and the cutoff values are 191 cc and 888 cc, respectively. Per 100-cc increase, odds of replanning increased by 15% for CTV volume (OR 1.15; 95% CI, 1.02 to 1.31) and 26% for heart volume (OR 1.26; 95% CI, 1.03 to 1.55). Our results suggest that monitoring these parameters can help identify plans that require closer scrutiny and more frequent scanning during the course of treatment to evaluate and adjust initial plans. This study contributes to optimizing the scheduling of quality assurance CT (QACT) scans, enhancing patient care by predicting which patients are likely to benefit from adaptive replanning.
Optimizing photon radiotherapy techniques is crucial in the integrated treatment of lung cancer. We prospectively evaluated the clinical implementation of the robust optimization (RO) technique in comparison with the conventional planning target volume (PTV) optimization (PTVO) technique. Unresectable stage III non-small cell lung cancer (NSCLC) or limited small cell lung cancer patients undergoing definitive radiotherapy were eligible. For each patient, 2 planning approaches were compared: (1) internal target volume (ITV)-based RO, with 0.5 cm setup uncertainties in cardinal directions around ITV and (2) PTVO, with PTV = ITV+0.5 cm isotropic expansion. Comparison included nominal and robust target coverage (TC), healthy tissue sparing, and, for NSCLC patients, estimated dose to immune cells (EDIC) and normal tissue complication probability (NTCP) values for pulmonary, esophageal toxicity, and 24-month mortality. Robustness evaluation (RE) acceptance criteria were ITV V95% ≥ 95% and spinal cord maximum dose < 45 Gy in all perturbed scenarios. Each enrolled patient was actually treated with the plan (RO or standard PTVO) that was judged superior in terms of TC and organs at risk (OAR) sparing. The Wilcoxon test was used for data analysis. p < 0.05 was considered statistically significant. Between June 2024 and June 2025, 24 patients were prospectively enrolled. Nominal TC metrics were comparable between RO and PTVO. Lungs, heart, and esophagus doses were significantly reduced with RO. RO significantly reduced EDIC (p = 0.002), pulmonary (p = 0.0015), and esophageal (p = 0.003) NTCP values. TC and cord maximum dose acceptance criteria at RE were fulfilled in 99.4%/99.4% and in 100%/91% of the perturbed scenarios for RO and PTVO, respectively. At planning comparison, the RO was selected for the actual clinical treatment and delivery in 21 (87%) patients. The first clinical implementation of RO for lung cancer radiotherapy was feasible and promising; RO represents a valid alternative to PTVO in this setting.
Treating at breath-hold has been used to mitigate dose to the organs at risk while maintaining target stability and dose coverage. The breath-hold technique has been used in conjunction with stereotactic body irradiation for the treatment of lung lesions. However, utilizing a breath-hold technique does not help to decrease dose to the ribs when the target is in proximity to the chest wall. The researchers in this case study aimed to demonstrate an alternative route to reduce dose to the chest wall via a novel method of splitting the course of treatment between the inhalation breath-hold and exhalation breath-hold phases of breathing. In this study, the tumor position and movement throughout the respiratory cycle gave ample opportunity to deliver an ablative dose while also decreasing dose to the chest wall and ribs utilizing this "split-course" technique. To minimize the dose and potential for side effects, the course of treatment was divided into 4 fractions of inhalation breath-hold treatment and 4 fractions of exhalation breath-hold treatment. This plan was designed specifically for the patient to help reduce late side effects from radiation therapy. The split-course treatment method significantly decreased the dose to the chest wall and rib. The patient was followed up with evaluations over 9 months after treatment and indicated no pain in the chest.
To compare target coverage, dose gradient, organ-at-risk (OAR) sparing, and low-dose bath between CyberKnife (CK) and noncoplanar linac-based techniques, including noncoplanar volumetric modulated arc therapy (VMAT) and noncoplanar three-dimensional conformal radiotherapy (3DCRT), for left-sided accelerated partial breast irradiation (APBI). Fifteen patients previously treated with CyberKnife for left-sided APBI were retrospectively replanned using noncoplanar VMAT and noncoplanar 3DCRT on the Monaco treatment planning system. All plans were generated using a 2-mm dose calculation grid and normalized to achieve comparable target coverage (V98% ≥ 95% of the prescribed dose of 30 Gy in 5 fractions). Dose-volume parameters for planning target volume (PTV), OARs, gradient index (GI), conformity index (CI), and low-dose bath volumes were analyzed. Statistical comparison was performed using paired two-tailed t-tests. CyberKnife demonstrated significantly superior dose conformity and gradient, with the lowest GI (2.65) compared with VMAT (3.22) and 3DCRT (3.52) (p < 0.01). Mean doses and low-dose volumes (V3 to V20 Gy) to the heart, left anterior descending (LAD) coronary artery, and left ventricle (LV), ipsilateral lung, contralateral lung, contralateral breast, and chest wall were significantly lower with CyberKnife. However, the use of noncoplanar beam arrangements in VMAT and 3DCRT resulted in clinically acceptable dose fall-off and comparable GI values, particularly between noncoplanar VMAT and 3DCRT. Target coverage metrics (V98% and V100%) were comparable across all techniques. CyberKnife provides superior dose gradient and reduced low-dose bath for left-sided APBI. Nevertheless, noncoplanar VMAT and noncoplanar 3DCRT demonstrate favorable and clinically acceptable dosimetric performance, indicating that noncoplanar linac-based techniques may serve as viable alternatives where CyberKnife is unavailable.
Knowledge-based planning (KBP) has been widely adopted to improve plan quality, consistency, and efficiency in prostate volumetric-modulated arc therapy (VMAT), but adaptation to different prescription regimens often requires rebuilding separate models, which may be impractical in routine clinical settings. This study investigated the practical feasibility of reusing a KBP model across prescription regimens with nonequivalent dose-constraint systems in prostate VMAT. A model trained for conventional fractionation (78 Gy in 39 fractions) was evaluated using a 3-step framework consisting of closed-loop validation for reproducibility, open-loop validation for generalizability to previously unseen patients, and cross-prescription validation for reuse in moderate hypofractionation (60 Gy in 20 fractions) planned under a different clinical constraint framework. Model-generated plans were compared with manual plans using target dose metrics, organ-at-risk dose-volume indices, and plan quality metric scores. The model reproduced the dosimetric characteristics of the training dataset under standardized conditions and maintained clinically acceptable dosimetric performance in independent cases. When reused for a different prescription regimen, the model achieved comparable overall plan quality and acceptable organ-at-risk sparing, despite slight reductions in target dose homogeneity. These results suggest that KBP model reuse may reduce the need for repeated model rebuilding and provide a practical approach to efficient and standardized prostate VMAT planning, particularly in institutions with limited case numbers or limited resources for model development and maintenance.
The aim of the study was to evaluate the dosimetric effects of different virtual beam block combinations on target coverage, organ at risk (OAR) sparing, and delivery efficiency in helical tomotherapy (HT) for extranodal nasal-type NK/T-cell lymphoma (ENKTCL-NT). In addition, normal tissue complication probability (NTCP) modeling was used to assess the biological impact on OARs and to inform optimal treatment planning strategies. Twenty-six patients with stage I-II ENKTCL-NT were retrospectively analyzed. Three virtual beam block configurations for the lens and eyeball-B-OFF, B-LEN, and B-L&E-were generated. Dosimetric parameters of the target volume, physical and biological indices of OARs, monitor units (MUs), and beam-on time (BOT) were compared among the plans. Dose delivery accuracy was verified using the ArcCHECK phantom. All 3 plans achieved clinically acceptable target coverage without significant differences in target dosimetric parameters. Compared with B-OFF, B-LEN significantly reduced the maximum dose (Dmax), mean dose (Dmean), equivalent uniform dose (EUD), and NTCP of the bilateral lenses (all p < 0.05) but did not significantly affect the eyeball dose (p > 0.05). B-L&E provided further protection: relative to B-LEN, it reduced the Dmax of the left and right lenses by 3.4% and 5.9%, Dmean by 5.0% and 4.9%, and median NTCP by 10.3% and 21.4%, respectively (all p < 0.05). It also significantly lowered the Dmax and Dmean of the eyeballs (p < 0.05). No significant differences were observed among the 3 plans for the brainstem, spinal cord, optic chiasm, or optic nerves (p > 0.05). Compared with B-OFF, B-L&E increased the MUs by 17.9% and BOT by 58 s (19.0%). Gamma passing rates (3%/2 mm) exceeded 90% for all the plans, meeting the American Association of Physicists in Medicine Task Group No. 218 (AAPM TG-218) clinical criteria. The virtual beam block technique in HT effectively reduces radiation exposure to the lens and eyeball while maintaining target coverage in ENKTCL-NT. The B-L&E configuration offers the greatest OAR protection, and B-LEN may be preferable when shorter treatment times are required.
Stereotactic body radiation therapy (SBRT) is increasingly utilized for low and intermediate grade prostate cancer, offering advantages in reducing toxicities to critical structures and improving dose conformity. However, minimizing bladder toxicity remains challenging due to the organ's close proximity to the target. The Varian Edge linear accelerator utilizes high-resolution 2.5 mm multileaf collimators, enabling enhanced beam shaping and potentially improving organ at risk sparing. Limited data exist on the dosimetric impact of prostate SBRT planned with the Varian Edge linear accelerator. The goal of this study was to evaluate bladder toxicity in prostate SBRT planning by comparing treatment plans generated for delivery on the Varian TrueBeam and Varian Edge linear accelerators. It was hypothesized that plans utilizing the Varian Edge linear accelerator would result in a volume of the bladder receiving 34 Gy (V34 Gy) ≤ 5 cubic centimeters (cc), volume of the bladder receiving 37 Gy ≤ 5 cc, dose to the most exposed 1 cc (D1 cc) of the bladder ≤ 38.06 Gy, and maximum dose to 0.03 cc (D0.03 cc) of the bladder ≤ 38.06 Gy. Ten patients were retrospectively analyzed, and the results demonstrated significant reductions in the V34 Gy and V37 Gy of the bladder for the plans designed for delivery on the Varian Edge linear accelerator. There were no meaningful differences observed for the D1 cc and D0.03 cc. While the Varian Edge linear accelerator provides measurable dosimetric advantages in reducing intermediate dosing to the bladder, larger prospective studies with long-term follow-up are needed to determine whether these reductions translate into improved quality of life and reduced urinary toxicity.
To describe the feasibility and clinical implementation of hypofractionated Magnetic Resonance-guided Radiotherapy (MRgRT) using an MR-Linac system in a newly diagnosed glioblastoma (GBM) patient, with a focus on adaptive planning, tumor volume dynamics, and workflow efficiency. A 74-year-old male with GBM underwent gross total resection followed by MRgRT. Treatment planning used high-resolution MR and CT fusion. Online adaptation was performed using "adapt-to-shape" and "adapt-to-position" protocols. Target volumes were delineated using co-registered postoperative imaging. Volumetric changes and treatment workflow metrics were recorded. The patient completed 15 fractions of hypofractionated RT (40.05 Gy in 2.67 Gy/fraction) without delays or complications. Adaptive MRgRT enabled precise target coverage and accounted for significant anatomical changes. The gross tumor volume (GTV) increased from 32.25 cc postoperatively to 69.55 cc at fraction 6 (+112.32%), with corresponding increases in CTV and PTV. T2/FLAIR abnormalities also expanded by up to +83.67%. Median treatment time per fraction was 27.1 minutes (range: 19.3 to 68.5), with imaging, contouring, and planning contributing most to extended durations during adaptive fractions. Treatment was well tolerated, with only grade 2 asthenia reported. This case illustrates the feasibility and potential clinical value of MRgRT for GBM. Real-time adaptive planning enables clinicians to respond dynamically to tumor and cavity changes, potentially improving target coverage and reducing toxicity. Further studies are warranted to assess its impact on outcomes and to explore the integration of functional imaging into adaptive workflows.
Secondary neutron and gamma radiation in proton therapy raise concerns regarding out-of-field doses and heightened risks of secondary malignancies, particularly in pediatric cases. This study aims to develop and validate a novel 3-dimensional (3D) printed, tissue-equivalent phantom designed to enhance the precision of absorbed dose measurements and improve treatment planning in proton therapy. The phantom was fabricated using advanced 3D printing technology to mimic the radiological properties of human tissues, including electron density and proton stopping power. Thermoluminescent detectors (TLDs) were embedded at designated locations to measure doses resulting from proton irradiation. The γ-ray dose distribution inside the phantom was verified by comparison with Monte Carlo simulations using the GATE toolkit to ensure consistency and reliability. Measured dose distributions demonstrated strong consistency with simulations. Within the treatment field, the dose distribution exhibited high precision, while secondary doses featured a sharp decline beyond 6 cm from the target center. Doses fell below 5 mSv/Gy(RBE) within 1 cm of the boundary and continued to taper off to 0.05∼0.15 mSv/Gy(RBE) further away. Neutron dose equivalents were recorded at less than 1.5 mSv/Gy(RBE) between 5∼10 cm, declining below 1.0 mSv/Gy(RBE) beyond 10 cm. The 3D-printed phantom demonstrated high reliability and accuracy in dosimetry. It represents a robust tool for quality assurance in proton therapy planning and for evaluating patient-specific out-of-field doses. The model is expected to improve the safety and efficacy of radiation therapy, addressing critical concerns relevant to vulnerable populations. Furthermore, the measured out-of-field neutron doses were compared with the results from published studies to verify the rationality of the experimental data, which could provide a reference for the secondary neutron risk assessment of low-energy proton radiotherapy.
Accurate Adaptive Aperture (AA) leaf positioning is essential for some proton therapy systems to ensure precise dose delivery and patient safety. However, conventional quality assurance (QA) methods can be suboptimal or inefficient for routinely assessing the dynamic nature of AA in the Mevion S250i HYPERSCAN system. This study introduces a novel automated QA method to verify AA positions utilizing a scintillation detector. A specialized QA plan consisting of 7 rectangular fields was generated in the RayStation treatment planning system (TPS) and delivered using the Mevion S250i HYPERSCAN proton therapy system. Dose distributions were measured with an IBA Lynx PT scintillation detector. A MATLAB-based software tool automated the analysis of leaf positions, full-width half maximum (FWHM), and valley positions by comparing measured dose distributions with TPS calculations. Leaf positioning errors between measured and planned values demonstrated excellent agreement, with deviations mostly below 1 mm. Quantitative analysis of FWHM, valley positions, field centers, and delivery log data revealed average differences well within submillimeter tolerances, confirming the high accuracy and reproducibility of AA leaf positioning. The developed QA method provides an efficient and robust solution for routine verification of AA leaf positions in the Mevion S250i HYPERSCAN system, ensuring the reliability of proton beam-shaping for clinical treatments.
To determine whether multicriteria optimization (MCO) improves volumetric-modulated arc therapy (VMAT) plans for head-and-neck cancer compared with standard optimization in terms of dosimetry, treatment efficiency, and patient-specific quality assurance (QA). Ten clinically treated patients with oropharyngeal carcinoma each received 2 dual-arc 6-MV VMAT plans in RayStation v8A: one standard optimization plan and one MCO plan. Dose-volume endpoints included D98%, D50%, D2%, homogeneity index, and conformity index for each planning target volume, as well as mean or maximum doses to 23 organs at risk. Efficiency was assessed by total monitor units and delivery time. Pretreatment QA was performed using the OCTAVIUS-4D system, with global and local gamma passing rates (3%/3 mm and 3%/2 mm, 10% threshold) recorded. Computed tomography was used only for routine setup verification and repositioning. Paired data were analyzed using the Wilcoxon signed-rank test (α = 0.05). MCO significantly enhanced target coverage and uniformity (e.g., planning target volume-70: D98% + 1.3 Gy; homogeneity index 0.04 ± 0.01 vs 0.09 ± 0.02; conformity index 0.98 ± 0.02 vs 0.85 ± 0.04; all p ≤ 0.005). Mean parotid dose fell by 2.5 Gy and spinal cord D0.01cc by 1.4 Gy (p ≤ 0.005). MCO lowered monitor units by 19% (579 ± 127 vs 714 ± 170; p = 0.017) and reduced delivery time. All plans exceeded a 95% gamma passing rate, MCO showed marginally higher agreement under both global and local normalization (p < 0.01). MCO in RayStation yields more homogeneous and conformal VMAT plans, better spares critical structures, and increases delivery efficiency while maintaining excellent QA metrics. These advantages support its routine clinical adoption for complex head-and-neck radiotherapy cases.
Fast kV-switching dual-energy CT (DECT) has been demonstrated to more accurately predict relative stopping power (RSP) for proton therapy planning over the conventional method of HU-RSP conversion using single-energy CT (SECT). It is essential to evaluate the improvement in tissue characterization, reduction in range uncertainties, and accuracy in the dose calculation. In this study, treatment plans are calculated in a phantom on SECT and DECT. A dosimetric comparison to a ground truth reference model is evaluated. SECT and DECT scans were taken of a cylindrical head phantom, which contained 10 different inserts. Eight separate single-field plans were optimized to target a central planning target volume (PTV), each ranging through a different insert. A ground truth reference scan was created based on the known geometry, density, and composition of the phantom and inserts. The plans were recalculated without re-optimization onto the reference scan. The difference in dose and range is calculated from the nominal plan to the reference plan to evaluate the accuracy of RSP calculation using DECT compared to SECT. The D95 for the PTV resulted in an average percent relative error of -0.56% ± 0.19% in DECT and -0.79% ± 0.39% in SECT when calculated on the reference CT. The DECT average dose to the organs at risks 1 mm distal and proximal to the PTV was more accurate than SECT for all plans except for the plan that ranged through breast and adipose. The average difference in range when calculated on the reference image is 0.20 mm ± 0.75 mm compared to an average range change of 1.01 mm ± 1.10 mm planned with SECT. The positive value indicates over-ranging in the reference scan into distal structures. Plans calculated with DECT compared to the reference plan showed decreased range error in proximal and distal structures than the plans calculated using SECT. The average dose difference from DECT to the reference plan was less than in SECT. This suggests DECT potential as a more accurate means of calculating RSP for proton therapy treatment planning over conventional SECT.
The effectiveness of carbon ion radiotherapy (C-ion RT) is influenced by the computational grid resolution and range-modulation strategies used during treatment planning. The study aimed to evaluate the dosimetric effects of grid resolution and range pull-back (shift) on tumor target coverage and organs-at-risk (OARs) sparing, establish the anatomical site-specific range safety margins or error tolerance. Dose-volume parameters for spot-scanning (SS) and uniform-scanning (US) carbon ion plans were evaluated using an in-house treatment planning system (TPS) at grid resolutions of 1 to 4 mm. A range pull-back, intentionally set between 1 and 5 mm in 1-mm increments, was introduced. Logistic regression models were employed to characterize the dose response relationships between range pull-back and dose metrics of target and OARs. US plans demonstrated relatively stable target coverage in D95 and D98 metrics (ΔD95US = 0.12 %, ΔD98US = 0.86 % when comparing 4 to 1 mm grids), whereas SS plans showed a slight decline in these coverage metrics (ΔD95SS = 1.09 %, ΔD98SS = 1.59 % for 4 mm versus 1 mm grids). OAR dose-volume parameters remained highly consistent at 1 to 2 mm grids but exhibited significant deviations at 3 to 4 mm grids. The range safety margins were routinely established as ±1 mm for thoracic targets, ±2 mm for head-and-neck targets, ±3 mm for abdominal targets, and ±2 to 3 mm for pelvic targets. Based on our findings, a 2 mm computational grid is recommended in most clinical scenarios of carbon ion radiotherapy, and a 1 mm grid is preferred for targets adjacent to serial OARs or small targets near critical OARs. Implementing anatomic site-specific range safety margins can reduce radiation-induced adverse events while preserving relative biological effectiveness (RBE)-weighted dose coverage within the tumor target.
