Radiotherapy planning for nasopharyngeal carcinoma is a complex process due to the proximity of critical structures. Volumetric modulated arc therapy (VMAT) can improve the therapeutic ratio. However, multiple treatment delivery systems offer VMAT with varying technical specifications. This study compares the dosimetric plan quality of 2 systems, Clinac-iX and Halcyon in nasopharyngeal carcinoma. We utilized contrast-enhanced computed tomography (CECT) simulation and magnetic resonance (MR) image datasets from thirty patients with nasopharyngeal carcinoma to contour target volumes and organs at risk (OARs). Two medical physicists independently performed dosimetric planning for Clinac-iX and Halcyon machines, following standard international dosimetric constraints for OARs. We compared plan quality for dosimetric profiles, indices, and plan complexity parameters from both machines. Dosimetric coverage for target volumes and plan quality indices, such as homogeneity, conformity, and coverage, showed no significant differences between Clinac-iX and Halcyon. However, Halcyon demonstrated significantly better OAR sparing, particularly for the spinal cord, optic chiasm, lenses, eyeballs and lower brain volume integral dose (BVID) (p < 0.05). Complexity parameters showed that both systems used a similar number of arcs, but Halcyon had higher monitor units and lower treatment time per fraction owing to higher dose rate. Our study results favor Halcyon for better plan quality regarding critical organ sparing, low brain volume integral dose, and fast treatment delivery. This study can be used as a reference for selecting an optimal treatment delivery system for nasopharyngeal carcinoma patients in centres equipped with multiple linear accelerators.

UNASSIGNED: ZAP-X, a novel and dedicated radiosurgery (SRS) system, has recently emerged, while CyberKnife has solidified its position as a versatile solution for SRS and stereotactic body radiation therapy over the past two decades. This study aims to compare the dosimetric performance and delivery efficiency of ZAP-X and CyberKnife in treating brain metastases of varying target sizes, employing circular collimation.
UNASSIGNED: Twenty-three patients, encompassing a total of 47 brain metastases, were included in the creation of comparative plans of ZAP-X and CyberKnife for analysis. The comparative plans were generated to achieve identical prescription doses for the targets, while adhering to the same dose constraints for organs at risk (OAR). The prescription isodose percentage was optimized within the range of 97-100% for each plan to ensure effective target-volume coverage. To assess plan quality, indices such as conformity, homogeneity, and gradient (CI, HI, and GI) were computed, along with the reporting of total brain volumes receiving 12Gy and 10Gy. Estimated treatment time and monitor units (MUs) were compared between the two modalities in evaluating delivery efficiency.
UNASSIGNED: Overall, CyberKnife achieved better CI and HI, while ZAP-X exhibited better GI and a smaller irradiated volume for the normal brain. The superiority of CyberKnife\'s plan conformity was more pronounced for target size less than 1 cc and greater than 10 cc. Conversely, the advantage of ZAP-X\'s plan dose gradient was more notable for target sizes under 10 cc. The homogeneity of ZAP-X plans, employing multiple isocenters, displayed a strong correlation with the target\'s shape and the planner\'s experience in placing isocenters. Generally, the estimated treatment time was similar between the two modalities, and the delivery efficiency was significantly impacted by the chosen collimation sizes for both modalities.
UNASSIGNED: This study demonstrates that, within the range of target sizes within the patient cohort, plans generated by ZAP-X and CyberKnife exhibit comparable plan quality and delivery efficiency. At present, with the current platform of the two modalities, CyberKnife outperforms ZAP-X in terms of conformity and homogeneity, while ZAP-X tends to produce plans with a more rapid dose falloff.

OBJECTIVE: To validate a fully-automated lexicographic optimization-planning system (mCycle, Elekta) for single-(SL) and multiple-(ML, up to 4 metastases) lesions in intracranial stereotactic radiosurgery (SRS, 21 Gy, single fraction).
METHODS: A pre-determined priority list, Wish-List (WL), represents a dialogue between planner and clinician, establishing strict constraints and pursuing objectives. In order to satisfy the clinical protocol without manual intervention, four patients were required to tweak and fine-tune each WL (SLp, MLp) for coplanar arcs. Thirty-five testing plans (20 SLp, 15 MLp) were automatically re-planned (mCP). Automatic and manual plans were compared including dose constraints, conformality, modulation complexity score (MCS), delivery time, and local gamma analysis (2%/2 mm). To ensure plan clinical acceptability, two radiation oncologists conducted an independent blind plan choice.
RESULTS: Each WL-tuning took 3 days. Estimated median manual plans and mCP calculation time were 8 and 3 h, respectively. Significant increases in SLp and MLp target coverage and conformity were registered. mCP showed a not significant and clinically acceptable higher median brain V12Gy. SLp registered a -5.8% MU decrease with comparable median delivery time (MP 2.0 min, mCP 1.9 min) while MLp showed a +9.8% MU increase and longer delivery time (MP 3.5 min, mCP 4.4 min). mCP MCS resulted significantly higher without affecting gamma passing rates. At blind choice, mCP were preferred in the majority of cases.
CONCLUSIONS: Lexicographic optimization produced acceptable SRS plans with coplanar arcs significantly reducing the overall planning time in cases with up to 4 brain metastases. These planning improvements suggest further investigations by setting high-quality non-coplanar arc plans as a reference.

Previous plan competitions have largely focused on dose metric assessments. However, whether the submitted plans were realistic and reasonable from a quality assurance (QA) perspective remains unclear. This study aimed to investigate the relationship between aperture-based plan complexity metrics (PCM) in volumetric modulated arc therapy (VMAT) competition plans and clinical treatment plans verified through patient-specific QA (PSQA). In addition, the association of PCMs with plan quality was examined. A head and neck (HN) plan competition was held for Japanese institutions from June 2019 to July 2019, in which 210 competition plans were submitted. Dose distribution quality was quantified based on dose-volume histogram (DVH) metrics by calculating the dose distribution plan score (DDPS). Differences in PCMs between the two VMAT treatment plan groups (HN plan competitions held in Japan and clinically accepted HN VMAT plans through PSQA) were investigated. The mean (± standard deviation) DDPS for the 98 HN competition plans was 158.5 ± 20.6 (maximum DDPS: 200). DDPS showed a weak correlation with PCMs with a maximum r of 0.45 for monitor unit (MU); its correlation with some PCMs was \"very weak.\" Significant differences were found in some PCMs between plans with the highest 20% DDPSs and the remaining plans. The clinical VMAT and competition plans revealed similar distributions for some PCMs. Deviations in PCMs for the two groups were comparable, indicating considerable variability among planners regarding planning skills. The plan complexity for HN VMAT competition plans increased for high-quality plans, as shown by the dose distribution. Direct comparison of PCMs between competition plans and clinically accepted plans showed that the submitted HN VMAT competition plans were realistic and reasonable from the QA perspective. This evaluation may provide a set of criteria for evaluating plan quality in plan competitions.

BACKGROUND: Organ-at-risk (OAR) sparing is often assessed using an overlap volume-based parameter, defined as the ratio of the volume of OAR that overlaps the planning target volume (PTV) to the whole OAR volume. However, this conventional overlap-based predictive parameter (COPP) does not consider the volume relationship between the PTV and OAR.
OBJECTIVE: We propose a new overlap-based predictive parameter that consider the PTV volume. The effectiveness of proposed overlap-based predictive parameter (POPP) is evaluated compared with COPP.
METHODS: We defined as POPP = (overlap volume between OAR and PTV/OAR volume) × (PTV volume/OAR volume). We generated intensity modulated radiation therapy (IMRT) based on step and shoot technique, and volumetric modulated arc therapy (VMAT) plans with the Auto-Planning module of Pinnacle3 treatment planning system (v14.0, Philips Medical Systems, Fitchburg, WI) using the American Association of Physicists in Medicine Task Group (TG119) prostate phantom. The relationship between the position and size of the prostate phantom was systematically modified to simulate various geometric arrangements. The correlation between overlap-based predictive parameters (COPP and POPP) and dose-volume metrics (mean dose, V70Gy, V60Gy, and V37.5 Gy for rectum and bladder) was investigated using linear regression analysis.
RESULTS: Our results indicated POPP was better than COPP in predicting intermediate-dose metrics. The bladder results showed a trend similar to that of the rectum. The correlation coefficient of POPP was significantly greater than that of COPP in < 62 Gy (82% of the prescribed dose) region for IMRT and in < 55 Gy (73% of the prescribed dose) region for VMAT regarding the rectum (p < 0.05).
CONCLUSIONS: POPP is superior to COPP for creating predictive models at an intermediate-dose level. Because rectal bleeding and bladder toxicity can be associated with intermediate-doses as well as high-doses, it is important to predict dose-volume metrics for various dose levels. POPP is a useful parameter for predicting dose-volume metrics and assisting the generation of treatment plans.

BACKGROUND: To investigate the capability of a not-yet commercially available fully automated lexicographic optimization (LO) planning algorithm, called mCycle (Elekta AB, Stockholm, Sweden), to further improve the plan quality of an already-validated Wish List (WL) pushing on the organs-at-risk (OAR) sparing without compromising target coverage and plan delivery accuracy.
METHODS: Twenty-four mono-institutional consecutive cervical cancer Volumetric-Modulated Arc Therapy (VMAT) plans delivered between November 2019 and April 2022 (50 Gy/25 fractions) have been retrospectively selected. In mCycle the LO planning algorithm was combined with the a-priori multi-criterial optimization (MCO). Two versions of WL have been defined to reproduce manual plans (WL01), and to improve the OAR sparing without affecting minimum target coverage and plan delivery accuracy (WL02). Robust WLs have been tuned using a subset of 4 randomly selected patients. The remaining plans have been automatically re-planned by using the designed WLs. Manual plans (MP) and mCycle plans (mCP01 and mCP02) were compared in terms of dose distributions, complexity, delivery accuracy, and clinical acceptability. Two senior physicians independently performed a blind clinical evaluation, ranking the three competing plans. Furthermore, a previous defined global quality index has been used to gather into a single score the plan quality evaluation.
RESULTS: The WL tweaking requests 5 and 3 working days for the WL01 and the WL02, respectively. The re-planning took in both cases 3 working days. mCP01 best performed in terms of target coverage (PTV V95% (%): MP 98.0 [95.6-99.3], mCP01 99.2 [89.7-99.9], mCP02 96.9 [89.4-99.5]), while mCP02 showed a large OAR sparing improvement, especially in the rectum parameters (e.g., Rectum D50% (Gy): MP 41.7 [30.2-47.0], mCP01 40.3 [31.4-45.8], mCP02 32.6 [26.9-42.6]). An increase in plan complexity has been registered in mCPs without affecting plan delivery accuracy. In the blind comparisons, all automated plans were considered clinically acceptable, and mCPs were preferred over MP in 90% of cases. Globally, automated plans registered a plan quality score at least comparable to MP.
CONCLUSIONS: This study showed the flexibility of the Lexicographic approach in creating more demanding Wish Lists able to potentially minimize toxicities in RT plans.

This study evaluated the feasibility of using artificial intelligence (AI) segmentation software for volume-modulated arc therapy (VMAT) prostate planning in conjunction with knowledge-based planning to facilitate a fully automated workflow. Two commercially available AI software programs, Radformation AutoContour (Radformation, New York, NY) and Siemens AI-Rad Companion (Siemens Healthineers, Malvern, PA) were used to auto-segment the rectum, bladder, femoral heads, and bowel bag on 30 retrospective clinical cases (10 intact prostate, 10 prostate bed, and 10 prostate and lymph node). Physician-segmented target volumes were transferred to AI structure sets. In-house RapidPlan models were used to generate plans using the original, physician-segmented structure sets as well as Radformation and Siemens AI-generated structure sets. Thus, there were three plans for each of the 30 cases, totaling 90 plans. Following RapidPlan optimization, planning target volume (PTV) coverage was set to 95%. Then, the plans optimized using AI structures were recalculated on the physician structure set with fixed monitor units. In this way, physician contours were used as the gold standard for identifying any clinically relevant differences in dose distributions. One-way analysis of variation (ANOVA) was used for statistical analysis. No statistically significant differences were observed across the three sets of plans for intact prostate, prostate bed, or prostate and lymph nodes. The results indicate that an automated volumetric modulated arc therapy (VMAT) prostate planning workflow can consistently achieve high plan quality. However, our results also show that small but consistent differences in contouring preferences may lead to subtle differences in planning results. Therefore, the clinical implementation of auto-contouring should be carefully validated.

OBJECTIVE: To identify the problems in clinical radiotherapy planning for cervical cancer through quantitative evaluation of the radiotherapy plans to improve the quality of the plans and the radiotherapy process.
METHODS: We selected the clinically approved and administered radiotherapy plans for 227 cervical cancer patients undergoing external radiotherapy at Sun Yat-sen University Cancer Center from May, 2019 to January, 2022. These plans were transferred from the treatment planning system to the Plan IQTM workstation. The plan quality metrics were determined based on the guidelines of ICRU83 report, the GEC-ESTRO Working Group, and the clinical requirements of our center and were approved by a senior clinician. The problems in the radiotherapy plans were summarized and documented, and those with low scores were re-planned and the differences were analyzed.
RESULTS: We identified several problems in the 277 plans by quantitative evaluation. Inappropriate target volume selection (with scores < 60) in terms of GTV, PGTV (CI) and PGTV (V66 Gy) was found in 10.6%, 65.2%, and 1% of the plans, respectively; and the PGTV (CI), GTV, and PCTV (D98%, HI) had a score of 0 in 0.4%, 10.1%, 0.4%, 0.4% of the plans, respectively. The problems in the organs at risk (OARs) involved mainly the intestines (the rectum, small intestine, and colon), found in 20.7% of the plans, and in occasional cases, the rectum, small intestine, colon, kidney, and the femoral head had a score of 0. Senior planners showed significantly better performance than junior planners in PGTV (V60 Gy, D98%), PCTV (CI), and CTV (D98%) (P≤0.046) especially in terms of spinal cord and small intestine protection (P≤0.034). The bowel (the rectum, small intestine and colon) dose was significantly lower in the prone plans than supine plans (P < 0.05), and targets coverage all met clinical requirements. Twenty radiotherapy plans with low scores were selected for re-planning. The re-planned plans had significantly higher GTV (Dmin) and PTV (V45 Gy, D98%) (P < 0.05) with significantly reduced doses of the small intestines (V40 Gy vs V30 Gy), the colon (V40 Gy vs V30 Gy), and the bladder (D35%) (P < 0.05).
CONCLUSIONS: Quantitative evaluation of the radiotherapy plans can not only improve the quality of radiotherapy plan, but also facilitate risk management of the radiotherapy process.

Toxicity from cervical brachytherapy has been demonstrated to correlate with the D2cm3 of the bladder, rectum, and bowel. This suggests a simplified version of knowledge-based planning investigating the relationship of the overlap distance for 2cm3 and the D2cm3 from planning may be possible. This work demonstrates the feasibility of simple knowledge-based planning to predict the D2cm3, detect suboptimal plans, and improve plan quality.
The overlap volume histogram (OVH) method was used to determine the distance for 2cm3 of overlap between the OAR and CTV_HR. Linear plots modeled the OAR D2cm3 and 2cm3 overlap distance. Two datasets of 20 patients (plans from 43 insertions in each dataset) were used to create two independent models, and the performance of each model was compared using cross-validation. Doses were scaled to ensure consistent CTV_HR D90 values. The predicted D2cm3 is entered as the maximum constraint in the inverse planning algorithm.
Mean bladder D2cm3 decreased by 2.9% for the models from each dataset, mean rectal D2cm3 decreased 14.9% for the model from dataset 1 and 6.0% for the model from dataset 2, mean sigmoid D2cm3 decreased 10.7% for the model from dataset 1 and 6.1% for the model from dataset 2, mean bowel D2cm3 decreased 4.1% for the model from dataset 1 but no statistically significant difference was observed for the model from dataset 2.
A simplified knowledge-based planning method was used to predict D2cm3 and was able to automate optimization of brachytherapy plans for locally advanced cervical cancer.

OBJECTIVE: To assess the impact of the planner\'s experience and optimization algorithm on the plan quality and complexity of total marrow and lymphoid irradiation (TMLI) delivered by means of volumetric modulated arc therapy (VMAT) over 2010-2022 at our institute.
METHODS: Eighty-two consecutive TMLI plans were considered. Three complexity indices were computed to characterize the plans in terms of leaf gap size, irregularity of beam apertures, and modulation complexity. Dosimetric points of the target volume (D2%) and organs at risk (OAR) (Dmean) were automatically extracted to combine them with plan complexity and obtain a global quality score (GQS). The analysis was stratified based on the different optimization algorithms used over the years, including a knowledge-based (KB) model. Patient-specific quality assurance (QA) using Portal Dosimetry was performed retrospectively, and the gamma agreement index (GAI) was investigated in conjunction with plan complexity.
RESULTS: Plan complexity significantly reduced over the years (r = -0.50, p < 0.01). Significant differences in plan complexity and plan dosimetric quality among the different algorithms were observed. Moreover, the KB model allowed to achieve significantly better dosimetric results to the OARs. The plan quality remained similar or even improved during the years and when moving to a newer algorithm, with GQS increasing from 0.019 ± 0.002 to 0.025 ± 0.003 (p < 0.01). The significant correlation between GQS and time (r = 0.33, p = 0.01) indicated that the planner\'s experience was relevant to improve the plan quality of TMLI plans. Significant correlations between the GAI and the complexity metrics (r = -0.71, p < 0.01) were also found.
CONCLUSIONS: Both the planner\'s experience and algorithm version are crucial to achieve an optimal plan quality in TMLI plans. Thus, the impact of the optimization algorithm should be carefully evaluated when a new algorithm is introduced and in system upgrades. Knowledge-based strategies can be useful to increase standardization and improve plan quality of TMLI treatments.