Adaptive Radiotherapy Research Articles

284 The influencing factors for adaptive radiotherapy (ART) in head and neck cases: A Retrospective Study

284 The influencing factors for adaptive radiotherapy (ART) in head and neck cases: A Retrospective Study

Dosimetric predictors of acute and late gastrointestinal toxicities in stereotactic online adaptive magnetic resonance-guided radiotherapy (SMART) for locally advanced pancreatic adenocarcinoma

Background and purposeA retrospective evaluation of dosimetric predictors and leveraged dose-volume data for gastrointestinal (GI) toxicities for locally-advanced pancreatic cancer (LAPC) treated with daily stereotactic MRI-guided online-adaptive radiotherapy (SMART). Materials and methods147 patients with LAPC were treated with SMART at our institution between 2018 and 2021. Patients were evaluated using CTCAE V5.0 for RT-related acute (≤3 months) and late (>3 months) toxicities. Each organ at risk (OAR) was matched to a ≥ grade 2 (Gr2+) toxicity endpoint composite group. A least absolute shrinkage selector operator regression model was constructed by dose-volumes per OAR to account for OAR multicollinearity. A receiver operator curve (ROC) analysis was performed for the combined averages of significant toxicity groups to identify critical volumes per dose levels. Results18 of 147 patients experienced Gr2+ GI toxicity. 17 Gr2+ duodenal toxicities were seen; the most significant predictor was a V33Gy odds ratio (OR) of 1.69 per cc (95 % CI 1.14–2.88). 17 Gr2+ small bowel (SB) toxicities were seen; the most significant predictor was a V33Gy OR of 1.60 per cc (95 % CI 1.01–2.53). The AUC was 0.72 for duodenum and SB. The optimal duodenal cut-point was 1.00 cc (true positive (TP): 17.8 %; true negative (TN); 94.9 %). The SB cut-point was 1.75 cc (TP: 16.7 %; TN: 94.3 %). No stomach or large bowel dose toxicity predictors were identified. ConclusionsFor LAPC treated with SMART, the dose-volume threshold of V33Gy for duodenum and SB was associated with Gr2+ toxicities. These metrics can be utilized to guide future dose-volume constraints for patients undergoing upper abdominal SBRT.

483 Image-guided adaptive radiation therapy (IGRT)

483 Image-guided adaptive radiation therapy (IGRT)

Development and validation of an MR-driven dose-of-the-day procedure for online adaptive radiotherapy in upper gastrointestinal cancer patients

Objective. To develop and validate a dose-of-the-day (DOTD) treatment plan verification procedure for liver and pancreas cancer patients treated with an magnetic resonance (MR)-Linac system. Approach. DOTD was implemented as an automated process that uses 3D datasets collected during treatment delivery. Particularly, the DOTD pipeline’s input included the adapt-to-shape (ATS) plan—i.e. 3D-MR dataset acquired at beginning of online session, anatomical contours, dose distribution—and 3D-MR dataset acquired during beam-on (BON). The DOTD automated analysis included (a) ATS-to-BON image intensity-based deformable image registration (DIR), (b) ATS-to-BON contours mapping via DIR, (c) BON-to-ATS contours copying through rigid registration, (d) determining ATS-to-BON dosimetric differences, and (e) PDF report generation. The DIR process was validated by two expert reviewers. ATS-plans were recomputed on BON datasets to assess dose differences. DOTD analysis was performed retrospectively for 75 treatment fractions (12-liver and 5-pancreas patients). Main results. The accuracy of DOTD process relied on DIR and mapped contours quality. Most DIR-generated contours (99.6%) were clinically acceptable. DICE correlated with depreciation of DIR-based region of interest mapping process. The ATS-BON plan difference was found negligible (<1%). The duodenum and large bowel exhibited highest variations, 24% and 39% from fractional values, for 5-fraction liver and pancreas. For liver 1-fraction, a 62% variation was observed for duodenum. Significance. The DOTD methodology provides an automated approach to quantify 3D dosimetric differences between online plans and their delivery. This analysis offers promise as a valuable tool for plan quality assessment and decision-making in the verification stage of the online workflow.

407 Stereotactic magnetic resonance-guided online adaptive radiotherapy in kidney oligometastases

407 Stereotactic magnetic resonance-guided online adaptive radiotherapy in kidney oligometastases

481 The role of RTT in online adaptive radiotherapy

481 The role of RTT in online adaptive radiotherapy

203 Moderated Hypofractionated Adaptive Radiotherapy in Cervical Cancer: A Prospective 1 Clinical Trial

203 Moderated Hypofractionated Adaptive Radiotherapy in Cervical Cancer: A Prospective 1 Clinical Trial

351 Dosimetric benefit review for bladder cancer treatment with iCBCT guided adaptive radiotherapy

351 Dosimetric benefit review for bladder cancer treatment with iCBCT guided adaptive radiotherapy

Deep-learning-based segmentation using individual patient data on prostate cancer radiation therapy.

Organ-at-risk segmentation is essential in adaptive radiotherapy (ART). Learning-based automatic segmentation can reduce committed labor and accelerate the ART process. In this study, an auto-segmentation model was developed by employing individual patient datasets and a deep-learning-based augmentation method for tailoring radiation therapy according to the changes in the target and organ of interest in patients with prostate cancer. Two computed tomography (CT) datasets with well-defined labels, including contoured prostate, bladder, and rectum, were obtained from 18 patients. The labels of the CT images captured during radiation therapy (CT2nd) were predicted using CT images scanned before radiation therapy (CT1st). From the deformable vector fields (DVFs) created by using the VoxelMorph method, 10 DVFs were extracted when each of the modified CT and CT2nd images were deformed and registered to the fixed CT1st image. Augmented images were acquired by utilizing 110 extracted DVFs and spatially transforming the CT1st images and labels. An nnU-net autosegmentation network was trained by using the augmented images, and the CT2nd label was predicted. A patient-specific model was created for 18 patients, and the performances of the individual models were evaluated. The results were evaluated by employing the Dice similarity coefficient (DSC), average Hausdorff distance, and mean surface distance. The accuracy of the proposed model was compared with those of models trained with large datasets. Patient-specific models were developed successfully. For the proposed method, the DSC values of the actual and predicted labels for the bladder, prostate, and rectum were 0.94 ± 0.03, 0.84 ± 0.07, and 0.83 ± 0.04, respectively. We demonstrated the feasibility of automatic segmentation by employing individual patient datasets and image augmentation techniques. The proposed method has potential for clinical application in automatic prostate segmentation for ART.

Robust optimization strategies for contour uncertainties in online adaptive radiation therapy

Objective. Online adaptive radiation therapy requires fast and automated contouring of daily scans for treatment plan re-optimization. However, automated contouring is imperfect and introduces contour uncertainties. This work aims at developing and comparing robust optimization strategies accounting for such uncertainties. Approach. A deep-learning method was used to predict the uncertainty of deformable image registration, and to generate a finite set of daily contour samples. Ten optimization strategies were compared: two baseline methods, five methods that convert contour samples into voxel-wise probabilities, and three methods accounting explicitly for contour samples as scenarios in robust optimization. Target coverage and organ-at-risk (OAR) sparing were evaluated robustly for simplified proton therapy plans for five head-and-neck cancer patients. Results. We found that explicitly including target contour uncertainty in robust optimization provides robust target coverage with better OAR sparing than the baseline methods, without increasing the optimization time. Although OAR doses first increased when increasing target robustness, this effect could be prevented by additionally including robustness to OAR contour uncertainty. Compared to the probability-based methods, the scenario-based methods spared the OARs more, but increased integral dose and required more computation time. Significance. This work proposed efficient and beneficial strategies to mitigate contour uncertainty in treatment plan optimization. This facilitates the adoption of automatic contouring in online adaptive radiation therapy and, more generally, enables mitigation also of other sources of contour uncertainty in treatment planning.

Impact of on-trial IGRT quality assurance in an international adaptive radiotherapy trial for participants with bladder cancer

Background and purposeRadiotherapy trial quality assurance (RT QA) is crucial for ensuring the safe and reliable delivery of radiotherapy trials, and minimizing inter-institutional variations. While previous studies focused on outlining and planning quality assurance (QA), this work explores the process of Image-Guided Radiotherapy (IGRT), and adaptive radiotherapy.This study presents findings from during-accrual QA in the RAIDER trial, evaluating concordance between online and offline plan selections for bladder cancer participants undergoing adaptive radiotherapy. RAIDER had two seamless stages; stage 1 assessed adherence to dose constraints of dose escalated radiotherapy (DART) and stage 2 assessed safety. The RT QA programme was updated from stage 1 to stage 2. Materials and methodsData from all participants in the adaptive arms (standard dose adaptive radiotherapy (SART) and DART) of the trial was requested (33 centres across the UK, Australia and New Zealand). Data collection spanned September 2015 to December 2022 and included the plans selected online, on Cone-Beam Computed Tomography (CBCT) data. Concordance with the plans selected offline by the independent RT QA central reviewer was evaluated. ResultsAnalysable data was received for 72 participants, giving a total of 884 CBCTs. The overall concordance rate was 83% (723/884). From stage 1 to stage 2 the concordance in the plans selected improved from 75% (369/495) to 91% (354/389). ConclusionDuring-accrual IGRT QA positively influenced plan selection concordance, highlighting the need for ongoing support when introducing a new technique. Overall, it contributes to advancing the understanding and implementation of QA measures in adaptive radiotherapy trials.

The added value of a new high-performance ring-gantry CBCT imaging system for prostate cancer patients

Background and purposeA novel Cone-Beam Computed Tomography (CBCT) named HyperSight provides superior CBCT image quality compared to conventional ring gantry CBCT imaging, and it is suitable for dose calculations for prostate cancer, but it comes with considerable additional costs. The aim of this study was to determine the added value of HyperSight CBCT imaging compared to conventional CBCT imaging in terms of organ visibility in the male pelvic region. Materials and methodsTwenty prostate cancer patients were included in this prospective clinical study. For each patient three CBCT pairs, consisting of HyperSight and conventional CBCT scans acquired on consecutive days, were included. CBCT scans were evaluated by four observers in terms of visibility of the prostate, bladder, rectum and seminal vesicles. Visibility was scored on a 1-to-5 scale and by annotating axial slices where the organs were hard to delineate. Lastly, observers indicated whether the CBCT scans were of sufficient quality for an online adaptive radiation therapy workflow. ResultsAll four organs were better visible on HyperSight CBCT scans compared to conventional CBCT scans. The mean visibility scores increased from 3.1 to 4.5 on a 1––5 scale of and the mean number of annotated slices reduced from 4.5 to 1.1. 99% Of the HyperSight CBCT scans were considered suitable for an online adaptive workflow vs 25–83% for the conventional CBCT scans. ConclusionHyperSight CBCT scans yielded a visibility of prostate, bladder, rectum and seminal vesicles comparable to planning CT scans and, can replace a repeat planning CT scan in case of anatomical changes requiring a new treatment plan.

Charged Gold Nanoparticles for Target Identification-Alignment and Automatic Segmentation of CT Image-Guided Adaptive Radiotherapy in Small Hepatocellular Carcinoma.

Because of the challenges posed by anatomical uncertainties and the low resolution of plain computed tomography (CT) scans, implementing adaptive radiotherapy (ART) for small hepatocellular carcinoma (sHCC) using artificial intelligence (AI) faces obstacles in tumor identification-alignment and automatic segmentation. The current study aims to improve sHCC imaging for ART using a gold nanoparticle (Au NP)-based CT contrast agent to enhance AI-driven automated image processing. The synthesized charged Au NPs demonstrated notable in vitro aggregation, low cytotoxicity, and minimal organ toxicity. Over time, an in situ sHCC mouse model was established for in vivo CT imaging at multiple time points. The enhanced CT images processed using 3D U-Net and 3D Trans U-Net AI models demonstrated high geometric and dosimetric accuracy. Therefore, charged Au NPs enable accurate and automatic sHCC segmentation in CT images using classical AI models, potentially addressing the technical challenges related to tumor identification, alignment, and automatic segmentation in CT-guided online ART.

Adaptive radiotherapy for muscle invasive bladder cancer: a retrospective audit of two bladder filling protocols

BackgroundRadical radiotherapy for muscle-invasive bladder cancer (MIBC) is challenging due to large variations in bladder shape, size and volume during treatment, with drinking protocols often employed to mitigate geometric uncertainties. Utilising adaptive radiotherapy together with CBCT imaging to select a treatment plan that best fits the bladder target and reduce normal tissue irradiation is an attractive option to compensate for anatomical changes. The aim of this retrospective study was to compare a bladder empty (BE) protocol to a bladder filling (BF) protocol with regards to variations in target volumes, plan of the day (PoD) selection and plan dosimetry throughout treatment.MethodsForty patients were included in the study; twenty were treated with a BE protocol and twenty with a BF protocol to a total prescribed dose of 55 Gy in 20 fractions. Small, medium and large bladder plans were generated using three different CTV to PTV margins. Bladder (CTV) volumes were delineated on planning CTs and online pre-treatment CBCTs. Differences in CTV volumes throughout treatment, plan selection, PTV volumes and resulting dose metrics were compared for both protocols.ResultsMean bladder volume differed significantly on both the planning CTs and online pre-treatment CBCTs between the protocols (p < 0.05). Significant differences in bladder volumes were observed between the planning CT and pre-treatment CBCTs for BF (p < 0.05) but not for BE (p = 0.11). Both protocols saw a significant decrease in bladder volume between first and final treatment fractions (p < 0.05). Medium plans were preferentially selected for BE whilst when using the BF protocol the small plan was chosen most frequently. With no significant change to PTV coverage between the protocols, the volume of body receiving 25.0–45.8 Gy was found to be significantly smaller for BE patients (p < 0.05).ConclusionsThis work provides evidence in favour of a BE protocol compared to a BF protocol for radical radiotherapy for MIBC. The smaller treatment volumes observed in the BE protocol led to reduced OAR and total body doses and were also observed to be more consistent throughout the treatment course. These results highlight improvements in dosimetry for patients who undergo a BE protocol for MIBC.

Evaluation of knowledge-based planning models for male pelvic CBCT-based online adaptive radiotherapy on conventional linear accelerators.

To assess the practicality of employing a commercial knowledge-based planning tool (RapidPlan) to generate adapted intact prostate and prostate bed volumetric modulated arc therapy (VMAT) plans on iterative cone-beam computed tomography (iCBCT) datasets. Intact prostate and prostate bed RapidPlan models were trained utilizing planning data from 50 and 44 clinical cases, respectively. To ensure that refined models were capable of producing adequate clinical plans with a single optimization, models were tested with 50 clinical planning CT datasets by comparing dose-volume histogram (DVH) and plan quality metric (PQM) values between clinical and RapidPlan-generated plans. The RapidPlan tool was then used to retrospectively generate adapted VMAT plans on daily iCBCT images for 20 intact prostate and 15 prostate bed cases. As before, DVH and PQM metrics were utilized to dosimetrically compare scheduled (iCBCT Verify) and adapted (iCBCT RapidPlan) plans. Timing data was collected to further evaluate the feasibility of integrating this approach within an online adaptive radiotherapy workflow. Model testing results confirmed the models were capable of producing VMAT plans within a single optimization that were overall improved upon or dosimetrically comparable to original clinical plans. Direct application of RapidPlan on iCBCT datasets produced satisfactory intact prostate and prostate bed plans with generally improved target volume coverage/conformality and rectal sparing relative to iCBCT Verify plans as indicated by DVH values, though bladder metrics were marginally increased on average. Average PQM values for iCBCT RapidPlans were significantly improved compared to iCBCT Verify plans. The average time required [in mm:ss] to generate adapted plans was 06:09±02:06 (intact) and 07:12±01:04 (bed). This study demonstrated the feasibility of leveraging RapidPlan to expeditiously generate adapted VMAT intact prostate and prostate bed plans on iCBCT datasets. In general, adapted plans were dosimetrically improved relative to scheduled plans, emphasizing the practicality of the proposed approach.

Stereotactic Magnetic Resonance–Guided Daily Adaptive Radiation Therapy for Localized Prostate Cancer: Acute and Late Patient-Reported Toxicity Outcomes

ObjectiveTo report acute and late bowel, urinary and sexual dysfunction patient reported outcome measures (PROMS), amongst localised prostate cancer patients who underwent Stereotactic MRI-guided daily adaptive radiotherapy (SMART). MethodsAll patients who completed a baseline 12 item Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE), before undergoing 36.25 Gy in 5 fractions by SMART, were subsequently followed up with the same graded questionnaire at set time points. Latest PSA levels were recorded. The percentage of patients who reported no change from their baseline AE or reported a new ≥ ‘frequent’ or’ severe’ AE grade during follow up was calculated. The maximum PRO-CTCAE grade for each item was recorded for each patient. The percentage of toxicity levels for each separate AE item at set time points were calculated. ResultsThe total number of patients was 69 with a median follow-up of 27 months. Median age of cohort 73 (range 54-85). The median pre-treatment PSA, T stage and Gleason score was 7.5 mmol/l (4.5-32 mmol/l), T2b (T2-T3b) and Gleason Score of 7 (3+4, range: 6-9) respectively. No patient had biochemical failure during follow up. Regarding bowel symptoms, >80% of men reported no change from baseline toxicity during follow up. New ≥ frequent diarrhoea was reported in 9% of patients. ‘Almost constant’ diarrhoea peaked at 1 month but was absent at >33 months. Regarding urinary symptoms, increased urinary urgency was the most common complaint (39%). 20% of men reported new ≥ frequent urinary urgency incidence peaking at 1 month but absent at >33 months. New “severe” sexual dysfunction was seen in 26% of patients and was persistent at >33 months. ConclusionOur study is one the largest patient reported outcomes study post prostate SMART. It shows acceptable levels of toxicity even up to 2 years post treatment.

Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report

Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomography (CT) is integral for treatment planning, offering electron density data crucial for accurate dose calculations. However, accurately representing patient anatomy is challenging, especially in adaptive radiotherapy, where CT is not acquired daily. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast. Still, it lacks electron density information, while cone beam CT (CBCT) lacks direct electron density calibration and is mainly used for patient positioning.Adopting MRI-only or CBCT-based adaptive radiotherapy eliminates the need for CT planning but presents challenges. Synthetic CT (sCT) generation techniques aim to address these challenges by using image synthesis to bridge the gap between MRI, CBCT, and CT. The SynthRAD2023 challenge was organized to compare synthetic CT generation methods using multi-center ground truth data from 1080 patients, divided into two tasks: (1) MRI-to-CT and (2) CBCT-to-CT. The evaluation included image similarity and dose-based metrics from proton and photon plans.The challenge attracted significant participation, with 617 registrations and 22/17 valid submissions for tasks 1/2. Top-performing teams achieved high structural similarity indices (≥0.87/0.90) and gamma pass rates for photon (≥98.1%/99.0%) and proton (≥97.3%/97.0%) plans. However, no significant correlation was found between image similarity metrics and dose accuracy, emphasizing the need for dose evaluation when assessing the clinical applicability of sCT.SynthRAD2023 facilitated the investigation and benchmarking of sCT generation techniques, providing insights for developing MRI-only and CBCT-based adaptive radiotherapy. It showcased the growing capacity of deep learning to produce high-quality sCT, reducing reliance on conventional CT for treatment planning.

Role of adaptive radiotherapy during concomitant chemoradiotherapy for limited-stage small-cell lung cancer.

Tumor shrinkage is frequently observed during conventionally fractionated chemoradiotherapy for limited-stage small-cell lung cancer (SCLC). The specific goals of this study are to evaluate the gross tumor volume (GTV) changes due to treatment-induced tumor reduction during the course of radiotherapy (RT) and to examine its potential use in adaptive radiotherapy (ART) for tumor dose escalation or normal tissue sparing in patients with SCLC. A total of 10 patients with SCLC eligible for chemoradiotherapy underwent computed tomography (CT) scan after Fractions 13 and 23 (at nominal doses of 23.4 Gy and 41.4 Gy, respectively). The GTV was delineated on the repeat CT scans, and two treatment plans were generated with or without adaptation to tumor shrinkage during RT for each patient. Dosimetric and volumetric analyses were performed. The average GTV reduction observed over 13 fractions was 58.5% (range: 13.2%-92.3%; P < 0.001) and over 23 fractions was 70% (range: 36.9%-84.5%; P < 0.001). Compared with the plan without adaptation, ART resulted in mean lung dose relative decreases of 8.7%, mean lung volume receiving ≥20 Gy relative decreases of 5%, mean lung volume receiving ≥5Gy relative decreases of 10%, mean medulla spinalis dose relative decreases of 21 cGy, mean esophagus volume receiving ≥50 Gy relative decreases of 19%, and mean heart volume receiving ≥42 Gy relative decreases of 13%. The benefits of ART were the greatest for tumor volumes ≥30 cm3 and are directly dependent on GTV reduction during treatment. ART for SCLC achieved a significant benefit in terms of organ at risk (OAR) and dose escalation.

CT-guided online adaptive stereotactic body radiotherapy for pancreas ductal adenocarcinoma: Dosimetric and initial clinical experience

Purpose/ObjectivesRetrospective analysis suggests that dose escalation to a biologically effective dose of more than 70 Gy may improve overall survival in patients with pancreatic ductal adenocarcinoma (PDAC), but such treatments in practice are limited by proximity of organs at risk (OARs). We hypothesized that CT-guided online adaptive radiotherapy (OART) can account for interfraction movement of OARs and allow for safe delivery of ablative doses. Materials/MethodsThis is a single institution retrospective analysis of patients with PDAC treated with OART on the Ethos platform (Varian Medical Systems, a Siemens Healthineers Company, Palo Alto). All patients were treated to 40 Gy in 5 fractions. PTV overlapping with a 5 mm planning risk volume expansion on the stomach, duodenum and bowel received 25 Gy. Initial treatment plans were created conventionally. For each fraction, PTV and OAR volumes were recontoured with AI assistance after initial cone beam CT (CBCT). The adapted plan was calculated, underwent QA, and then compared to the scheduled plan. A second CBCT was obtained prior to delivery of the selected plan. Total treatment time (first CBCT to end of radiation delivery) and active physician time (first to second CBCT) were recorded. PTV_4000 V95 %, PTV_2500 V9 5%, and D0.03 cc to stomach, duodenum and bowel were reported for scheduled (S) and adapted (A) plans. CTCAEv5.0 toxicities were recorded. Statistical analysis was performed using a two-sided T test and α of 0.05. Results21 patients with unresectable or locally-recurrent PDAC were analyzed, with a total of 105 fractions. Average total time was 29 min and 16 s (16:36–49:40) and average active physician time was 19:41 min (9:25–39:34). All fractions were treated with adapted plans. 97 % of adapted plans met PTV_4000 V95.0 % >95.0 % coverage goal and 100 % of adapted plans met OAR dose constraints. Median follow up was 6.6 months. Only 1 patient experienced acute grade 3+ toxicity directly attributable to radiation. Only 1 patient experienced late grade 3+ toxicity directly attributable to radiation. ConclusionsDaily CT-based OART was associated with significantly reduced dose OARs while achieving superior PTV coverage. Given the relatively quick total treatment time, radiation delivery was generally well tolerated and easily incorporated into the clinic workflow. Our initial clinical experience demonstrates OART allows for safe dose escalation in the treatment of PDAC.

Using Scorecards to Tune Ethos Directive Templates: An Adaptive Radiation Therapy Individualized Approach-Cervix Dosimetric Planning Study

The Adaptive Radiation Therapy Individualized Approach-Cervix clinical trial uses predefined clinical directive templates (CDTs) combined with RapidPlan dose-volume histogram estimations (DVHe) to guide plan optimization in the Ethos treatment planning system. The dosimetric scorecard is a scoring tool that quantifies improvements in plan quality after physicians have precisely expressed their complete clinical intent. To our knowledge, this is the first study to use the dosimetric scorecard tool to tune an Ethos CDT to improve resulting plan quality. Iterative replanning was used to modify the draft CDT (CDT-1) in Ethos 1.1 to generate a new CDT (CDT-2) that maximized the clinical consensus scorecard's total score compared with CDT-1. CDT-2 was established, and resulting plans were compared with and without a DVHe. Additional fixed field intensity modulated radiation therapy beam geometries were compared between CDT-1 and CDT-2, both with DVHe. After obtaining favorable results when comparing CDT-1 versus CDT-2 for 2 test cases, 10 additional cases were retrospectively identified and tested. CDT-2 reduced organ at risk doses without compromising planning target volume coverage in the initial test cases. When combined with DVHe, CDT-2 marginally outperformed CDT-1. Plan quality further improved with a 19-field geometry. In the expanded analysis, CDT-2 achieved higher scores than CDT-1 in most cases, with the 19-field approach showing superiority. Optimization and calculation time increased by 1.9 minutes, monitor unit (MU)/field decreased by 44.4, whereas beam-on time increased by 2.8 minutes when increasing fields to 19 from 9. Reoptimization with Ethos 1.1 Maintenance Release 1 resulted in decreased MU and minimal score changes. The scorecard is an effective tool to adjust an Ethos CDT to improve the average calculated plan quality. It also allowed for easy evaluation of the dosimetric impact of other planning parameters (beam arrangements and use of DVHe) to identify the best approach. Using a finely tuned CDT is expected to improve planning efficiency and decrease intrainstitutional plan quality variability, benefiting cone beam computed tomography-guided adaptive radiation therapy.