Online adaptive radiotherapy of urinary bladder cancer with full re-optimization to the anatomy of the day: initial experience and dosimetric benefits

Quality and Safety Considerations for Adaptive Radiation Therapy: An ASTRO White Paper

PURPOSE

Adaptive radiation therapy (ART) is the latest topic in a series of white papers published by the American Society for Radiation Oncology addressing quality processes and patient safety. ART widens the therapeutic index by improving the precision of radiation dose to targets, allowing for dose escalation and/or minimization of dose to normal tissue. ART is performed via offline or online methods; offline ART is the process of replanning a patient's treatment plan between fractions, whereas online ART involves plan adjustment with the patient on the treatment table. This is achieved with in-room imaging capable of assessing anatomic changes and the ability to reoptimize the treatment plan rapidly during the treatment session. Although ART has occurred in its simplest forms in clinical practice for decades, recent technological developments have enabled more clinical applications of ART. With increased clinical prevalence, compressed timelines, and the associated complexity of ART, quality and safety considerations are an important focus area.

METHODS

The American Society for Radiation Oncology convened an interdisciplinary task force to provide expert consensus on key workflows and processes for ART. Recommendations were created using a consensus-building methodology, and task force members indicated their level of agreement based on a 5-point Likert scale, from "strongly agree" to "strongly disagree." A prespecified threshold of ≥75% of raters selecting "strongly agree" or "agree" indicated consensus. Content not meeting this threshold was removed or revised.

SUMMARY

Establishing and maintaining an adaptive program requires a team-based approach, appropriately trained and credentialed specialists, significant resources, specialized technology, and implementation time. A comprehensive quality assurance program must be developed, using established guidance, to make sure all forms of ART are performed in a safe and effective manner. Patient safety when delivering ART is everyone's responsibility, and professional organizations, regulators, vendors, and end users must demonstrate a clear commitment to working together to deliver the highest levels of quality and safety.

Cone Beam Computed Tomography-Guided Online Adaptive Radiation Therapy: Clinical Insights From a Nationwide Staffing Survey

PURPOSE

This study aimed to provide insights into the staffing and workflow requirements for cone beam computed tomography (CBCT)-guided online adaptive radiation therapy (ART) systems to guide institutions in optimizing staffing strategies and to promote broader ART adoption.

METHODS AND MATERIALS

We conducted a nationwide survey to collect data on ART program metrics, clinician roles during online treatment, and physicist staffing models, along with free-text feedback for sharing of insights and challenges. Additionally, we reviewed 26 published articles describing ART workflows across various anatomic sites and performed a literature-based timing analysis to provide further context on workflow efficiency.

RESULTS

We received 19 responses from a range of institutions. Medical schools and university hospitals reported the highest ART patient throughput, averaging 4 patients per machine per day. Overall, most institutions treat 1 to 2 ART patients per machine daily, with average session duration of 1 hour. Therapists are primarily responsible for CBCT scans, whereas physicists oversee almost all ART stages. The physicians are mainly responsible for on-treatment contouring and plan selection/approval. As ART cases increase, more full-time equivalent (FTE) physicists are needed, with >5 cases per day typically requiring an additional FTE. The online adaptive workflow adds about 20 minutes to treatment time compared with image guided radiation therapy, resulting in a total on-table time of ∼40 minutes.

CONCLUSIONS

Implementing ART programs requires careful planning and flexible staffing models to balance resource availability with treatment quality. The findings from this survey highlight the importance of interdisciplinary collaboration, defined clinician roles, and evolving staffing solutions for ART implementation. Medical physicists are essential in all stages of the ART process, with higher adaptive case volumes directly driving the need for additional FTEs to maintain effective workflow and treatment quality. This study's insights can guide health care facilities in establishing efficient and sustainable ART workflows, ultimately enhancing patient care outcomes.

First experiences with an adaptive pelvic radiotherapy system: Analysis of treatment times and learning curve

PURPOSE

The Varian Ethos system allows not only on-treatment-table plan adaptation but also automated contouring with the aid of artificial intelligence. This study evaluates the initial clinical implementation of an adaptive pelvic radiotherapy system, focusing on the treatment times and the associated learning curve.

MATERIAL AND METHODS

We analyzed the data from 903 consecutive treatments for most urogenital cancers at our center. The treatment time was calculated from the time of the first cone-beam computed tomography scan used for replanning until the end of treatment. To calculate whether treatments were generally shorter over time, we divided the date of the first treatment into 3-months quartiles. Differences between the groups were calculated using t-tests.

RESULTS

The mean time from the first cone-beam computed tomography scan to the end of treatment was 25.9min (standard deviation: 6.9min). Treatment time depended on the number of planning target volumes and treatment of the pelvic lymph nodes. The mean time from cone-beam computed tomography to the end of treatment was 37 % longer if the pelvic lymph nodes were treated and 26 % longer if there were more than two planning target volumes. There was a learning curve: in linear regression analysis, both quartiles of months of treatment (odds ratio [OR]: 1.3, 95 % confidence interval [CI]: 1.8-0.70, P<0.001) and the number of planning target volumes (OR: 3.0, 95 % CI: 2.6-3.4, P<0.001) were predictive of treatment time.

CONCLUSION

Approximately two-thirds of the treatments were delivered within 33min. Treatment time was strongly dependent on the number of separate planning target volumes. There was a continuous learning curve.

New Approaches in Radiotherapy

Radiotherapy (RT) has undergone transformative advancements since its inception over a century ago. This review highlights the most promising and impactful innovations shaping the current and future landscape of RT. Key technological advances include adaptive radiotherapy (ART), which tailors treatment to daily anatomical changes using integrated imaging and artificial intelligence (AI), and advanced image guidance systems, such as MR-LINACs, PET-LINACs, and surface-guided radiotherapy (SGRT), which enhance targeting precision and minimize collateral damage. AI and data science further support RT through automation, improved segmentation, dose prediction, and treatment planning. Emerging biological and targeted therapies, including boron neutron capture therapy (BNCT), radioimmunotherapy, and theranostics, represent the convergence of molecular targeting and radiotherapy, offering personalized treatment strategies. Particle therapies, notably proton and heavy ion RT, exploit the Bragg peak for precise tumor targeting while reducing normal tissue exposure. FLASH RT, delivering ultra-high dose rates, demonstrates promise in sparing normal tissue while maintaining tumor control, though clinical validation is ongoing. Spatially fractionated RT (SFRT), stereotactic techniques and brachytherapy are evolving to treat challenging tumor types with enhanced conformality and efficacy. Innovations such as 3D printing, Auger therapy, and hyperthermia are also contributing to individualized and site-specific solutions. Across these modalities, the integration of imaging, AI, and novel physics and biology-driven approaches is redefining the possibilities of cancer treatment. This review underscores the multidisciplinary and translational nature of modern RT, where physics, engineering, biology, and informatics intersect to improve patient outcomes. While many approaches are in various stages of clinical adoption and investigation, their collective impact promises to redefine the therapeutic boundaries of radiation oncology in the coming decade.

Reduction of the planning target volume with daily online adaptive radiotherapy in bladder cancer

INTRODUCTION

External radiation therapy for bladder cancer requires large planning target volumes (PTVs) due to the daily anatomy of the bladder. Online adaptive radiotherapy (oART) can reduce the PTV by considering daily anatomical changes.

PATIENTS AND METHODS

We performed oART in 8 patients with muscle-invasive bladder cancer between June 10, 2022, and April 14, 2023, on an Ethos linear accelerator (Varian, Palo Alto, USA). Using the 496 cone-beam computed tomography (CBCT) images of the fractions, we retrospectively compared the differences in volumetric changes between oART and image-guided and intensity-modulated radiotherapy (IGRT/IMRT). According to our local protocol, for oART, a patient-specific PTV margin was created based on the intrafractional clinical target volume (CTV) changes observed during the first three fractions.

RESULTS

The average duration of treatment was 14.8 min (range 7-49 min). The average volume of the PTV with oART and IGRT/IMRT was 296.8 cm3 (range 114.5-810.4 cm3) and 416.5 cm3 (range 188.2-991.3 cm3), respectively, representing a 30% reduction with oART. This new technique resulted in an average reduction of 43.9% in the volume of unnecessarily irradiated healthy tissues. Geometrical miss of the CTV occurred in 13 fractions with IGRT/IMRT, with an average of 9.4 cm3 of missed volume (range 0.4-56.4 cm3, standard deviation [SD] 15.73), for oART in 7 fractions, with an average missed volume of 4 cm3 (range 0.4-21.2 cm3, SD: 7.6).

CONCLUSION

The use of patient-specific margins in oART allows for reduction of the PTV and dose to healthy tissues while achieving equal or better target coverage.

Patient-specific adaptive planning margin for whole bladder radiation therapy

BACKGROUND

Whole bladder irradiation is an organ preservation treatment approach for muscle-invasive bladder cancer (MIBC). Conventional planning margins, typically 15-20 mm, increase normal tissue toxicity and limit possible dose escalation.

PURPOSE

The study aimed to develop a patient-specific adaptive margin recipe for whole bladder irradiation to minimize the planning target volume (PTV) while preserving adequate dose coverage.

METHODS

Sixteen patients who received whole-bladder irradiation were retrospectively selected for this study. We proposed a patient-specific anisotropic adaptive margin recipe, derived from the first five fractions of kV-CBCTs, to account for inter-fractional bladder changes. This recipe was validated using kV-CBCTs from fractions six to ten and the final five fractions. The goal was to achieve a residual volume, defined as the percentage of daily bladder volume (Vdaily) outside the PTV, of less than 5%. Adaptive and conventional plans were created using proposed and conventional margins, respectively. A dosimetric comparison of targets and organs-at-risk (OARs) was performed between the two approaches.

RESULTS

(Vdaily) decreased throughout the treatment course. The most notable inter-fractional bladder variations were in the superior and anterior directions. The patient-specific anisotropic adaptive margins, averaging 6 mm (± 2.9 mm), achieved a residual volume of less than 5%. Compared to conventional planning, the adaptive approach reduced PTV volume by an average of 135.3 cc (± 46.6 cc). A significant correlation (p < 0.05) was identified between residual volume and adaptive margins in the anterior, superior, left, and right directions. Using the proposed adaptive margins, the median residual volume was 0.71% (interquartile range 0.09%-3.55%), and the median (Vdaily) receiving the prescribed dose was 99.1% (interquartile range 95.3%-99.9%). Adaptive plans demonstrated superior OAR sparing compared to conventional plans.

CONCLUSIONS

The proposed patient-specific adaptive margin recipe for whole bladder irradiation resulted in margins smaller than conventional ones, optimized normal tissue sparing, and maintained adequate PTV coverage.

Investigation of the beam width and profile of kilovoltage CBCT using different measurement techniques and analysis of the dosimetric effects of beam parameters

Background

The aim of this study is to investigate the beam width and beam profile of kilovoltage cone beam computed tomography (kV CBCT) using different measurement techniques on an O-ring linear accelerator. The effect of the imaging beam on the dosimetric parameters was analysed.

Materials and methods

The uncertainty of field size adjustment, the dependence of beam width on field size, and the effect of deflection from the isocenter on the beam profile were investigated by ionization chamber detector matrices. The 2D beam profile of the CBCT was analysed by relative ionization chamber measurements.

Results

The average setup uncertainties of the field sizes were 0.3 mm ± 0.02 mm. The dependence of beam width on field size investigation revealed that the largest discrepancies occurred for small field sizes, which are important in determining computed tomography dose index (CTDI) values of the kV CBCT. The beam width deviation between measured and vendor-based data was larger than 1 mm below 40 mm field of view. The pelvis protocol demonstrated the smallest CTDI value difference of 2.3%, yet presented the largest effective dose deviation of 0.12 mSv.

Conclusions

The measured CTDI coefficients were higher than predicted by the manufacturer for all cases. The currently internationally recommended CTDI measurement protocols for CBCT contain no reference to the determination of the beam width as a basic element of the calculations. Based on our measurement results, the beam width parameters affect CTDI: therefore, it would be advisable to apply this type of correction.

Modeling dosimetric benefits from daily adaptive RT for gynecological cancer patients with and without knowledge-based dose prediction

PURPOSE

Daily online adaptive radiotherapy (ART) improves dose metrics for gynecological cancer patients, but the on-treatment process is resource-intensive requiring longer appointments and additional time from the entire adaptive team. To optimize resource allocation, we propose a model to identify high-priority patients.

METHODS

For 49 retrospective cervical and endometrial cancer patients, we calculated two initial plans: the treated standard-of-care (InitialSOC) and a reduced margin initial plan (InitialART) for adapting with the Ethos treatment planning system. Daily doses corresponding to standard and reduced margins (DailySOC and DailyART) were determined by re-segmenting the anatomy based on the treatment CBCT and calculating dose on a synthetic CT. These initial and daily doses were used to estimate the ART benefit (Δ D a i l y ${{\Delta}}Daily$ = DailySOC-DailyART) versus initial plan differences (Δ I n i t i a l ${{\Delta}}Initial$ = InitialSOC-InitialART) via multivariate linear regression. Dosimetric benefits were modeled with initial plan differences (Δ I n i t i a l ${{\Delta}}Initial$ ) ofB o w e l V 40 G y $Bowel\ {{V}_{40Gy}}$ (cc),B l a d d e r D 50 % $Bladder\ {{D}_{50{\mathrm{\% }}}}$ (Gy), andR e c t u m D 50 % $Rectum\ {{D}_{50{\mathrm{\% }}}}$ (Gy). Anatomy (intact uterus or post-hysterectomy), DoseType (simultaneous integrated boost [SIB] vs. single dose), and/or prescription value. To establish a logistic model, we classified the top 10% in each metric as high-benefit patients. We then built a logistic model to predict these patients from the previous predictors. Leave-one-out validation and ROC analysis were used to evaluate the accuracy. To improve the clinical efficiency of this predictive process, we also created knowledge-based plans for the ΔInitial plans (Δ I n i t i a l R P ${{\Delta}}Initia{{l}_{RP}}$ ) and repeated the analysis.

RESULTS

In bothΔ I n i t i a l O r i g ${{\Delta}}Initia{{l}_{Orig}}$ andΔ I n i t i a l R P ${{\Delta}}Initia{{l}_{RP}}$ our multivariate analysis showed low R2 values 0.34-0.52 versus 0.14-0.38. The most significant predictor in each multivariate model was the corresponding ∆Initial metric (e.g.,Δ I n i t i a l ${{\Delta}}Initial$ Bowel (V40 Gy), p < 1e-05). In the logistic model, the metrics with the strongest correlation to the high-benefit patients wereB o w e l V 40 G y $Bowel\ {{V}_{40Gy}}$ (cc),B l a d d e r D 50 % $Bladder\ {{D}_{50{\mathrm{\% }}}}$ (Gy),D o s e T y p e $DoseType$ , andS I B D o s e $SIBDose$ prescription. The models for original and knowledge-based plans had an AUC of 0.85 versus 0.78. The sensitivity and specificity were 0.92/0.72 and 0.69/0.80, respectively.

CONCLUSION

This methodology will allow clinics to prioritize patients for resource-intensive daily online ART.

Cone Beam Online Adaptive Radiation Therapy: A Promising Approach for Gastric Mucosa-Associated Lymphoid Tissue Lymphoma?

Purpose

Daily online adaptive radiation therapy (oART) opens the opportunity to treat gastric mucosa-associated lymphoid tissue (MALT) lymphoma with a reduced margin. This study reports our early experience of cone beam computed tomography (CBCT)-based daily oART treating gastric MALT lymphoma with breath-hold and reduced margins.

Methods and Materials

Ten patients were treated on a CBCT-based oART system. Organs at risk (OARs) and the clinical target volume (CTV) were adjusted based on the daily CBCT. Planning target volume (PTV) was derived from the CTV with a 0.5 to 0.7 cm margin with breath-hold. Multiple beam arrangements were compared during the preplanning phase to ensure minimal monitor unit (MU) for patient comfort and breath-hold reproducibility. For 108 fractions from the 10 patients, the PTV, CTV coverage, and Paddick conformity index (CI) were compared between the adapted and scheduled plans. The MU, Paddick CI, and gradient index were compared using relative percentage differences between the adapted plans and preplans. The OAR doses from 106 fractions across 9 patients were reported for the preplans, adapted plans, and scheduled plans. The time statistics for each step of the clinical workflow were recorded and reported for 93 treatment fractions from 9 patients.

Results

The PTV volume varied from -37.1% to 90.5% (11.7% ± 18.5%) throughout treatments across all patients. The adapted plan was chosen as the treatment plan for each fraction because of superior PTV and CTV coverage while maintaining a similar OAR dose. The PTV and CTV coverage for the adapted and scheduled plans was VRx = 95.0% ± 0.3% versus 64.1 ± 19.6% and VRx = 99.9 ± 0.1% versus 74.0% ± 22.2%, respectively. The adapted plans' MU, Paddick CI, and gradient index were, on average, 4.1%, 0.4%, and -4.2% of the preplan values, respectively. The console's adaptive workflow and physician time were 25 ± 7 and 19 ± 6 minutes, respectively.

Conclusion

A CBCT-based oART system with the proposed workflow is feasible for treating patients with gastric MALT lymphoma using a reduced PTV margin while maintaining excellent target coverage within a reasonable time, resulting in consistent adapted plan quality. This approach can be expanded to a larger cohort of gastrointestinal patients.

Clinical implementation of RTT-only CBCT-guided online adaptive focal radiotherapy for bladder cancer

Purpose

The study assesses the clinical implementation of radiation therapist (RTT)-only Conebeam CT (CBCT)-guided online adaptive focal radiotherapy (oART) for bladder cancer, by describing the training program, analyzing the workflow and monitoring patient experience.

Materials and methods

Bladder cancer patients underwent treatment (20 sessions) on a ring-based linac (Ethos, Varian, a Siemens Healthineers Company, USA). Commencing April 2021, 14 patients were treated by RTTs supervised by the Radiation Oncologist (RO) and Medical Physics Expert (MPE) in a multidisciplinary workflow. From March 2022, 14 patients were treated solely by RTTs. RTT training included target delineation lessons and practicing oART in a simulation environment. We analyzed the efficiency of the RTT-only workflow regarding session time, adjustments by RTTs, attendance of the RO and MPE at the linac, and qualitative assessment of gross tumor volume (GTV) delineation. Patient experience was monitored through questionnaires.

Results

A training program resulted in a skilled team of RTTs, ROs and MPEs.The RTT-only workflow demonstrated shorter session times compared to the multidisciplinary approach. Among 14 patients treated using the RTT-only workflow, RTTs adjusted 99% of bladder volumes and 44% of GTV. 79% of the sessions proceeded without MPEs and ROs. All GTV delineations were RO-approved, thus considered clinically acceptable, and 87% required minor or no adjustments. Patient satisfaction was reported in 18 of 21 cases.

Conclusions

The RTT-only oART workflow for bladder cancer, complemented by a training program and on-call support from ROs and MPEs, demonstrated success. Patient experience is positive. It is currently introduced as standard in our clinic.

Evaluation of artificial intelligence-based autosegmentation for a high-performance cone-beam computed tomography imaging system in the pelvic region

Background and purpose

A novel ring-gantry cone-beam computed tomography (CBCT) imaging system shows improved image quality compared to its conventional version, but its effect on autosegmentation is unknown. This study evaluates the impact of this high-performance CBCT on autosegmentation performance, inter-observer variability, contour correction times and delineation confidence, compared to the conventional CBCT.

Materials and methods

Twenty prostate cancer patients were enrolled in this prospective clinical study. Per patient, one pair of high-performance CBCT and conventional CBCT scans was included. Three observers manually corrected contours generated by the artificial intelligence (AI) model for prostate, seminal vesicles, bladder, rectum and bowel. Differences between AI-based and manual corrected contours were quantified using Dice Similarity Coefficient (DSC) and 95th percentile of Hausdorff distance (HD95). Autosegmentation performance and interobserver variation were compared using a random effects model; correction times and confidence scores using a paired t-test and Wilcoxon signed-rank test, respectively.

Results

Autosegmentation performance showed small, but statistically insignificant differences. Interobserver variability, assessed by the intraclass correlation coefficient, was significantly different across most organs, but these were considered clinically irrelevant (maximum difference = 0.08). Mean contour correction times were similar for both CBCT systems (11:03 versus 11:12 min; p = 0.66). Delineation confidence scores were significantly higher with the high-performance CBCT scans for prostate, seminal vesicles and rectum (4.5 versus 3.5, 4.3 versus 3.5, 4.8 versus 4.3; all p < 0.001).

Conclusion

The high-performance CBCT did not (clinically) improve autosegmentation performance, inter-observer variability or contour correction time compared to conventional CBCT. However, it clearly enhanced user confidence in organ delineation for prostate, seminal vesicles and rectum.

Clinical feasibility of Ethos auto-segmentation for adaptive whole-breast cancer treatment

Introduction

Following a preliminary work validating the technological feasibility of an adaptive workflow with Ethos for whole-breast cancer, this study aims to clinically evaluate the automatic segmentation generated by Ethos.

Material and methods

Twenty patients initially treated on a TrueBeam accelerator for different breast cancer indications (right/left, lumpectomy/mastectomy) were replanned using the Ethos® emulator. The adaptive workflow was performed using 5 randomly selected extended CBCTs per patient. The contours generated by artificial intelligence (AI) included both breasts, the heart, and the lungs. The target volumes, specifically the tumor bed (CTV_Boost), internal mammary chain (CTV_IMC), and clavicular nodes (CTV_Nodes), were generated through rigid propagation. The CTV_Breast corresponds to the ipsilateral breast, excluding 5mm from the skin. Two radiation oncologists independently repeated the workflow and qualitatively assessed the accuracy of the contours using a scoring system from 3 (contour to be redone) to 0 (no correction needed). Quantitative evaluation was carried out using the Dice Similarity Coefficient (DSC), Hausdorff Distance (HD), surface Dice (sDSC) and the Added Path Length (APL). The interobserver variability (IOV) between the two observers was also assessed and served as a reference. Lastly, the dosimetric impact of contour correction was evaluated. The physician-validated contours were transferred onto the plans automatically generated by Ethos in adaptive mode. The dose prescription was 52.2Gy in 18 fractions for the boost, 42.3Gy for the breast, IMC, and nodes. The CTV/PTV margin was 2mm for all volumes, except for the IMC (5mm). Dose coverage (D98%) was assessed for the CTVs, while specific parameters for organs at risk (OAR) were evaluated: mean dose and V17Gy (relative volume receiving at least 17Gy) for the ipsilateral lung, mean dose and D2cc (dose received by 2cc volume) for the heart, the contralateral lung and breast.

Results

The qualitative analysis showed that no correction or only minor corrections were needed for 98.6% of AI-generated contours and 86.7% of the target volumes. Regarding the quantitative analysis, Ethos' contour generation outperformed inter-observer variability for all structures in terms of DSC, HD, sDSC and APL. Target volume coverage was achieved for 97.9%, 96.3%, 94.2% and 68.8% of the breast, IMC, nodes and boost CTVs, respectively. As for OARs, no significant differences in dosimetric parameters were observed.

Conclusion

This study shows high accuracy of segmentation performed by Ethos for breast cancer, except for the CTV_Boost. Contouring practices for adaptive sessions were revised following this study to improve outcomes.

Personalizing radiotherapy with adaptive radiotherapy: Interest and challenges

Adaptive radiotherapy (ART) is a recent development in radiotherapy technology and treatment personalization that allows treatment to be tailored to the daily anatomical changes of patients. While it was until recently only performed "offline", i.e. between two radiotherapy sessions, it is now possible during ART to perform a daily online adaptive process for a given patient. Therefore, ART allows a daily customization to ensure optimal coverage of the treatment target volumes with minimized margins, taking into account only the uncertainties related to the adaptive process itself. This optimization appears particularly relevant in case of daily variations in the positioning of the target volume or of the organs at risk (OAR) associated with a proximity of these volumes and a tenuous therapeutic index. ART aims to minimize severe acute and late toxicity and allows tumor dose escalation. These new achievements have been possible thanks to technological development, the contribution of new multimodal and onboard imaging modalities and the integration of artificial intelligence tools for the contouring, planning and delivery of radiation therapy. Online ART is currently available on two types of radiotherapy machines: MR-linear accelerators and recently CBCT-linear accelerators. We will first describe the benefits, advantages, constraints and limitations of each of these two modalities, as well as the online adaptive process itself. We will then evaluate the clinical situations for which online adaptive radiotherapy is particularly indicated on MR- and CBCT-linear accelerators. Finally, we will detail some challenges and possible solutions in the development of online ART in the coming years.

Clinical evaluation of the convolutional neural network‑based automatic delineation tool in determining the clinical target volume and organs at risk in rectal cancer radiotherapy

Delineating the clinical target volume (CTV) and organs at risk (OARs) is crucial in rectal cancer radiotherapy. However, the accuracy of manual delineation (MD) is variable and the process is time consuming. Automatic delineation (AD) may be a solution to produce quicker and more accurate contours. In the present study, a convolutional neural network (CNN)-based AD tool was clinically evaluated to analyze its accuracy and efficiency in rectal cancer. CT images were collected from 148 supine patients in whom tumor stage and type of surgery were not differentiated. The rectal cancer contours consisted of CTV and OARs, where the OARs included the bladder, left and right femoral head, left and right kidney, spinal cord and bowel bag. The MD contours reviewed and modified together by a senior radiation oncologist committee were set as the reference values. The Dice similarity coefficient (DSC), Jaccard coefficient (JAC) and Hausdorff distance (HD) were used to evaluate the AD accuracy. The correlation between CT slice number and AD accuracy was analyzed, and the AD accuracy for different contour numbers was compared. The time recorded in the present study included the MD time, AD time for different CT slice and contour numbers and the editing time for AD contours. The Pearson correlation coefficient, paired-sample t-test and unpaired-sample t-test were used for statistical analyses. The results of the present study indicated that the DSC, JAC and HD for CTV using AD were 0.80±0.06, 0.67±0.08 and 6.96±2.45 mm, respectively. Among the OARs, the highest DSC and JAC using AD were found for the right and left kidney, with 0.91±0.06 and 0.93±0.04, and 0.84±0.09 and 0.88±0.07, respectively, and HD was lowest for the spinal cord with 2.26±0.82 mm. The lowest accuracy was found for the bowel bag. The more CT slice numbers, the higher the accuracy of the spinal cord analysis. However, the contour number had no effect on AD accuracy. To obtain qualified contours, the AD time plus editing time was 662.97±195.57 sec, while the MD time was 3294.29±824.70 sec. In conclusion, the results of the present study indicate that AD can significantly improve efficiency and a higher number of CT slices and contours can reduce AD efficiency. The AD tool provides acceptable CTV and OARs for rectal cancer and improves efficiency for delineation.

Minimizing human interference in an online fully automated daily adaptive radiotherapy workflow for bladder cancer

PURPOSE

The aim was to study the potential for an online fully automated daily adaptive radiotherapy (RT) workflow for bladder cancer, employing a focal boost and fiducial markers. The study focused on comparing the geometric and dosimetric aspects between the simulated automated online adaptive RT (oART) workflow and the clinically performed workflow.

METHODS

Seventeen patients with muscle-invasive bladder cancer were treated with daily Cone Beam CT (CBCT)-guided oART. The bladder and pelvic lymph nodes (CTVelective) received a total dose of 40 Gy in 20 fractions and the tumor bed received an additional simultaneously integrated boost (SIB) of 15 Gy (CTVboost). During the online sessions a CBCT was acquired and used as input for the AI-network to automatically delineate the bladder and rectum, i.e. influencers. These influencers were employed to guide the algorithm utilized in the delineation process of the target. Manual adjustments to the generated contours are common during this clinical workflow prior to plan reoptimization and RT delivery. To study the potential for an online fully automated workflow, the oART workflow was repeated in a simulation environment without manual adjustments. A comparison was made between the clinical and automatic contours and between the treatment plans optimized on these clinical (Dclin) and automatic contours (Dauto).

RESULTS

The bladder and rectum delineated by the AI-network differed from the clinical contours with a median Dice Similarity Coefficient of 0.99 and 0.92, a Mean Distance to Agreement of 1.9 mm and 1.3 mm and a relative volume of 100% and 95%, respectively. For the CTVboost these differences were larger, namely 0.71, 7 mm and 78%. For the CTVboost the median target coverage was 0.42% lower for Dauto compared to Dclin. For CTVelective this difference was 0.03%. The target coverage of Dauto met the clinical requirement of the CTV-coverage in 65% of the sessions for CTVboost and 95% of the sessions for the CTVelective.

CONCLUSIONS

While an online fully automated daily adaptive RT workflow shows promise for bladder treatment, its complexity becomes apparent when incorporating a focal boost, necessitating manual checks to prevent potential underdosage of the target.

A Personalized Anisotropic Margin for Cervical Cancer Radiation Therapy Under the Guidance of Daily Iterative Cone-Beam Computed Tomography (iCBCT)

Online adaptive radiation therapy (ART) eliminates interfraction uncertainties by adaption before each treatment session. However, intrafraction motions still exist and could become more severe due to long treatment time. Large isotropic margins can ensure clinical target volume (CTV) coverage but at the cost of more organs at risk damage. In this study, we proposed a novel personalized anisotropic margin search algorithm for cervical cancer radiation therapy under the guidance of daily iterative cone-beam computed tomography (iCBCT) to find the optimal margin values for each patient, which achieves the smallest possible planning target volume (PTV) and maintains CTV coverage. Twenty-two online Ethos ART treatment sessions were included for analysis. Two iCBCT scans were taken in each session. The first one (iCBCT1) was taken after positioning, and the second one (iCBCT2) was taken before beam delivery. Corresponding CTV1 and CTV2 were contoured in the two scans. In each session, minimal isotropic margins were first searched by iteratively increasing the magnitude until the resulting PTViso covers 99% of CTV2. Afterward, the margin values in all six directions were decreased iteratively until CTV2 coverage was smaller than 99% to get the personalized margin and target volume PTVint. In addition, the uterus was considered separately, and different margins were found for it and the remaining CTV, respectively, to reduce the target volume of PTVsep further. PTViso, PTVint, and PTVsep were compared in terms of CTV2 coverage and absolute volume. The algorithm successfully generated PTViso, PTVint, and PTVsep for all online ART treatment sessions. The mean ± SD values for PTViso 5mm, PTViso 10mm, PTViso 15mm, PTVint, and PTVsep were 1,074.0 ± 78.1, 1,519.5 ± 100.4, 2,006.4 ± 122.5, 929.3 ± 73.4, and 845.1 ± 72.5 mL, respectively. The volume difference between PTVint and PTVsep was significant (p < 0.001). All the PTVs ensured an average coverage larger than 99%, and the differences between any two PTVs were insignificant. This study proposed a novel personalized anisotropic margin search algorithm for cervical cancer online ART. Compared to the conventional 5 or 10 mm isotropic margins, the personalized anisotropic margin reduced PTV volume by 13.5% and 38.8%, respectively; if the uterus was considered separately, the volume can be further reduced by 21.3% and 44.3%, respectively, while CTV coverage was still maintained. This algorithm could reduce target volume and potentially spare normal tissue better than isotropic margin expansion.

Cone-Beam Computed Tomography-Guided Online Adaptive Radiotherapy: Promising Results for Bladder Cancer Case

Bladder radiotherapy is challenging due to daily anatomical variations and unpredictable bladder filling, particularly affecting tumors in the cranial part. Conventional radiotherapy requires large planning target volume margins to manage these uncertainties, but this can expose healthy tissue to high radiation doses, increasing the risk of acute and late toxicity. Our aim was to study the potential to limit high-dose exposure to healthy tissue by comparing daily online adaptive radiotherapy (oART) with conventional, non-adaptive radiotherapy (non-ART). The comparison was performed on a bladder cancer patient treated with a simultaneous integrated boost while having a challenging tumor location in the cranial part of the bladder. Liquid fiducial markers aided during the localization of the tumor bed to deliver this focal boost. The dose distribution of oART fractions performed in the clinic was compared with simulated non-ART fractions on the post-treatment cone-beam computed tomography (CBCT). The results showed that while maintaining target coverage of the bladder and gross tumor volume in 100% of the fractions for both workflows, the high dose exposure to organs-at-risk was lower for oART. The small bowel received statistically significantly (p ≤ 0.05) less dose with oART compared to non-ART, with a median volume difference of 20 cm3 receiving 95% of the prescribed dose (55 Gy). The total volume of tissue outside the target receiving 95% of the prescribed dose was also smaller for oART compared to non-ART (p ≤ 0.05). The follow-up of two years showed that the patient had no long-term toxicity effects. Therefore, CBCT-guided oART has been shown to offer a conformal treatment for a challenging patient and can provide a clear advantage in the treatment of bladder cancer.

Implementation of Cone Beam Computed Tomography-Guided Online Adaptive Radiotherapy for Challenging Trimodal Therapy in Bladder Preservation: A Report of Two Cases

Muscle invasive bladder cancer (MIBC) is an aggressive disease with a high risk of metastasis. Bladder preservation with trimodality therapy (TMT) is an option for well-selected patients or poor cystectomy candidates. Cone beam computed tomography (CBCT)-guided online adaptive radiotherapy (oART) shows promise in improving the dose to treatment targets while better sparing organs at risk (OARs). The following series presents two cases in which the capabilities of a CBCT-guided oART platform were leveraged to meet clinical challenges. The first case describes a patient with synchronous MIBC and high-risk prostate cancer with challenging target-OAR interfaces. The second recounts the case of a patient with a history of low dose rate (LDR) brachytherapy to the prostate who was later diagnosed with MIBC and successfully treated with CBCT-guided oART with reduced high-dose volume bladder targeting. To date, both patients report minimal side effects and are without disease recurrence. These cases illustrate how CBCT-guided online adaptive systems may efficiently aid radiation oncologists in treating patients with more complex clinical scenarios who desire bladder-sparing therapy.

Prospective risk analysis of the online-adaptive artificial intelligence-driven workflow using the Ethos treatment system

PURPOSE

The recently introduced Varian Ethos system allows adjusting radiotherapy treatment plans to anatomical changes on a daily basis. The system uses artificial intelligence to speed up the process of creating adapted plans, comes with its own software solutions and requires a substantially different workflow. A detailed analysis of possible risks of the associated workflow is presented.

METHODS

A prospective risk analysis of the adaptive workflow with the Ethos system was performed using Failure Modes and Effects Analysis (FMEA). An interprofessional team collected possible adverse events and evaluated their severity as well as their chance of occurrence and detectability. Measures to reduce the risks were discussed.

RESULTS

A total of 122 events were identified, and scored. Within the 20 events with the highest-ranked risks, the following were identified: Challenges due to the stand-alone software solution with very limited connectivity to the existing record and verify software and digital patient file, unfamiliarity with the new software and its limitations and the adaption process relying on results obtained by artificial intelligence. The risk analysis led to the implementation of additional quality assurance measures in the workflow.

CONCLUSIONS

The thorough analysis of the risks associated with the new treatment technique was the basis for designing details of the workflow. The analysis also revealed challenges to be addressed by both, the vendor and customers. On the vendor side, this includes improving communication between their different software solutions. On the customer side, this especially includes establishing validation strategies to monitor the results of the black box adaption process making use of artificial intelligence.

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

BACKGROUND

Radical 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.

METHODS

Forty 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.

RESULTS

Mean 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).

CONCLUSIONS

This 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.

Feasibility of Ethos adaptive treatments of lung tumors and associated quality assurance

MOTIVATION

Online adaptive radiotherapy with Ethos is based on the anatomy determined from daily cone beam computed tomography (CBCT) images. Dose optimization and computation are performed on the density map of a synthetic CT (sCT), a deformable registration of the initial planning CT (pCT) onto the current CBCT. Large density changes as present in the lung region are challenging the system.

METHODS

Treatment plans for Ethos were created and delivered for 1, 2, and 3 cm diameter lung lesions in an anthropomorphic phantom, combining different insets in the pCT and during adaptive and non-adaptive treatment sessions. Primary and secondary dose calculations as well as back-projected dose from portal images were evaluated.

RESULTS

Density changes due to changed insets were not considered in the sCTs. This resulted in errors in the dose; for example, -15.9% of the mean dose for a plan when changing from a 3 cm inset in the pCT to 1 cm at the time of treatment. Secondary dose calculation is based on the sCT and could therefore not reveal these dose errors. However, dose calculation on the CBCT, either as a recalculation in the treatment planning system or as pre-treatment quality assurance (QA) before the treatment, indicated the differences. EPID in-vivo QA also reported discrepancies between calculated and delivered dose distributions.

CONCLUSIONS

An incorrect density distribution in the sCT has an impact on the dose calculation accuracy in the adaptive treatment workflow with the Ethos system. Additional quality checks of the sCT can detect such errors.

Bringing online adaptive radiotherapy to a standard C-arm linac

Current online adaptive radiotherapy (oART) workflows require dedicated equipment. Our aim was to develop and implement an oART workflow for a C-arm linac which can be performed using standard clinically available tools. A workflow was successfully developed and implemented. Three patients receiving palliative radiotherapy for bladder cancer were treated, with 33 of 35 total fractions being delivered with the cone-beam computed tomography (CBCT)-guided oART workflow. Average oART fraction duration was 24 min from start of CBCT acquisition to end of beam on. This work shows how oART could be performed without dedicated equipment, broadening oART availability for application at existing treatment machines.

Artificial intelligence-generated targets and inter-observer variation in online adaptive radiotherapy of bladder cancer

Background and purpose

Daily target re-delineation in online adaptive radiotherapy (oART) introduces uncertainty. The aim of this study was to evaluate artificial intelligence (AI) generated contours and inter-observer target variation among radiotherapy technicians in cone-beam CT (CBCT) guided oART of bladder cancer.

Materials and methods

For each of 10 consecutive patients treated with oART for bladder cancer, one CBCT was randomly selected and retrospectively included. The bladder (CTV-T) was AI-segmented (CTV-TAI). Seven radiotherapy technicians independently reviewed and edited CTV-TAI, generating CTV-TADP. Contours were benchmarked against a ground truth contour (CTV-TGT) delineated blindly from scratch. CTV-TADP and CTV-TAI were compared to CTV-TGT using volume, dice similarity coefficient, and bidirectional local distance. Dose coverage (D99%>95 %) of CTV-TGT was evaluated for treatment plans optimized for CTV-TAI and CTV-TADP with clinical margins. Inter-observer variation among CTV-TADP was assessed using coefficient of variation and generalized conformity index.

Results

CTV-TGT ranged from 48.7 cm3 to 211.6 cm3. The median [range] volume difference was 4.5 [-17.8, 42.4] cm3 for CTV-TADP and -15.5 [-54.2, 4.3] cm3 for CTV-TAI, compared to CTV-TGT. Corresponding dice similarity coefficients were 0.87 [0.71, 0.95] and 0.84 [0.64, 0.95]. CTV-TGT was adequately covered in 68/70 plans optimized on CTV-TADP and in 6/10 plans optimized on CTV-TAI with clinical margins. The median [range] coefficient of variation was 0.08 [0.05, 0.11] and generalized conformity index was 0.78 [0.71, 0.88] among CTV-TADP.

Conclusions

Target re-delineation in CBCT-guided oART of bladder cancer demonstrated non-isotropic inter-observer variation. Manual adjustment of AI-generated contours was necessary to cover ground truth targets.

Feasibility of surface-guidance combined with CBCT for intra-fractional breath-hold motion management during Ethos RT

PURPOSE

High-quality CBCT and AI-enhanced adaptive planning techniques allow CBCT-guided stereotactic adaptive radiotherapy (CT-STAR) to account for inter-fractional anatomic changes. Studies of intra-fractional respiratory motion management with a surface imaging solution for CT-STAR have not been fully conducted. We investigated intra-fractional motion management in breath-hold Ethos-based CT-STAR and CT-SBRT (stereotactic body non-adaptive radiotherapy) using optical surface imaging combined with onboard CBCTs.

METHODS

Ten cancer patients with mobile lower lung or upper abdominal malignancies participated in an IRB-approved clinical trial (Phase I) of optical surface image-guided Ethos CT-STAR/SBRT. In the clinical trial, a pre-configured gating window (± 2 mm in AP direction) on optical surface imaging was used for manually triggering intra-fractional CBCT acquisition and treatment beam irradiation during breath-hold (seven patients for the end of exhalation and three patients for the end of inhalation). Two inter-fractional CBCTs at the ends of exhalation and inhalation in each fraction were acquired to verify the primary direction and range of the tumor/imaging-surrogate (donut-shaped fiducial) motion. Intra-fractional CBCTs were used to quantify the residual motion of the tumor/imaging-surrogate within the pre-configured breath-hold window in the AP direction. Fifty fractions of Ethos RT were delivered under surface image-guidance: Thirty-two fractions with CT-STAR (adaptive RT) and 18 fractions with CT-SBRT (non-adaptive RT). The residual motion of the tumor was quantified by determining variations in the tumor centroid position. The dosimetric impact on target coverage was calculated based on the residual motion.

RESULTS

We used 46 fractions for the analysis of intra-fractional residual motion and 43 fractions for the inter-fractional motion analysis due to study constraints. Using the image registration method, 43 pairs of inter-fractional CBCTs and 100 intra-fractional CBCTs attached to dose maps were analyzed. In the motion range study (image registration) from the inter-fractional CBCTs, the primary motion (mean ± std) was 16.6 ± 9.2 mm in the SI direction (magnitude: 26.4 ± 11.3 mm) for the tumors and 15.5 ± 7.3 mm in the AP direction (magnitude: 20.4 ± 7.0 mm) for the imaging-surrogate, respectively. The residual motion of the tumor (image registration) from intra-fractional breath-hold CBCTs was 2.2 ± 2.0 mm for SI, 1.4 ± 1.4 mm for RL, and 1.3 ± 1.3 mm for AP directions (magnitude: 3.5 ± 2.1 mm). The ratio of the actual dose coverage to 99%, 90%, and 50% of the target volume decreased by 0.95 ± 0.11, 0.96 ± 0.10, 0.99 ± 0.05, respectively. The mean percentage of the target volume covered by the prescribed dose decreased by 2.8 ± 4.4%.

CONCLUSION

We demonstrated the intra-fractional motion-managed treatment strategy in breath-hold Ethos CT-STAR/SBRT using optical surface imaging and CBCT. While the controlled residual tumor motion measured at 3.5 mm exceeded the predetermined setup value of 2 mm, it is important to note that this motion still fell within the clinically acceptable range defined by the PTV margin of 5 mm. Nonetheless, additional caution is needed with intra-fractional motion management in breath-hold Ethos CT-STAR/SBRT using optical surface imaging and CBCT.

ROAR-A: re-optimization based Online Adaptive Radiotherapy of anal cancer, a prospective phase II trial protocol

BACKGROUND

Chemo-radiotherapy with curative intent for anal cancer has high complete remission rates, but acute treatment-related gastrointestinal (GI) toxicity is significant. Toxicity occurs due to irradiation of surrounding normal tissue. Current radiotherapy requires the addition of large planning margins to the radiation field to ensure target coverage regardless of the considerable organ motion in the pelvic region. This increases the irradiated volume and radiation dose to the surrounding normal tissue and thereby toxicity. Online adaptive radiotherapy uses artificial intelligence to adjust the treatment to the anatomy of the day. This allows for the reduction of planning margins, minimizing the irradiated volume and thereby radiation to the surrounding normal tissue.This study examines if cone beam computed tomography (CBCT)-guided oART with daily automated treatment re-planning can reduce acute gastrointestinal toxicity in patients with anal cancer.

METHODS/DESIGN

The study is a prospective, single-arm, phase II trial conducted at Copenhagen University Hospital, Herlev and Gentofte, Denmark. 205 patients with local only or locally advanced anal cancer, referred for radiotherapy with or without chemotherapy with curative intent, are planned for inclusion. Toxicity and quality of life are reported with Common Terminology Criteria of Adverse Events and patient-reported outcome questionnaires, before, during, and after treatment. The primary endpoint is a reduction in the incidence of acute treatment-related grade ≥ 2 diarrhea from 36 to 25% after daily online adaptive radiotherapy compared to standard radiotherapy. Secondary endpoints include all acute and late toxicity, overall survival, and reduction in treatment interruptions.

RESULTS

Accrual began in January 2022 and is expected to finish in January 2026. Primary endpoint results are expected to be available in April 2026.

DISCUSSION

This is the first study utilizing online adaptive radiotherapy to treat anal cancer. We hope to determine whether there is a clinical benefit for the patients, with significant reductions in acute GI toxicity without compromising treatment efficacy.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05438836. Danish Ethical Committee: H-21028093.

Clinical Workflow of Cone Beam Computer Tomography-Based Daily Online Adaptive Radiotherapy with Offline Magnetic Resonance Guidance: The Modular Adaptive Radiotherapy System (MARS)

PURPOSE

The Ethos (Varian Medical Systems) radiotherapy device combines semi-automated anatomy detection and plan generation for cone beam computer tomography (CBCT)-based daily online adaptive radiotherapy (oART). However, CBCT offers less soft tissue contrast than magnetic resonance imaging (MRI). This work aims to present the clinical workflow of CBCT-based oART with shuttle-based offline MR guidance.

METHODS

From February to November 2023, 31 patients underwent radiotherapy on the Ethos (Varian, Palo Alto, CA, USA) system with machine learning (ML)-supported daily oART. Moreover, patients received weekly MRI in treatment position, which was utilized for daily plan adaptation, via a shuttle-based system. Initial and adapted treatment plans were generated using the Ethos treatment planning system. Patient clinical data, fractional session times (MRI + shuttle transport + positioning, adaptation, QA, RT delivery) and plan selection were assessed for all fractions in all patients.

RESULTS

In total, 737 oART fractions were applied and 118 MRIs for offline MR guidance were acquired. Primary sites of tumors were prostate (n = 16), lung (n = 7), cervix (n = 5), bladder (n = 1) and endometrium (n = 2). The treatment was completed in all patients. The median MRI acquisition time including shuttle transport and positioning to initiation of the Ethos adaptive session was 53.6 min (IQR 46.5-63.4). The median total treatment time without MRI was 30.7 min (IQR 24.7-39.2). Separately, median adaptation, plan QA and RT times were 24.3 min (IQR 18.6-32.2), 0.4 min (IQR 0.3-1,0) and 5.3 min (IQR 4.5-6.7), respectively. The adapted plan was chosen over the scheduled plan in 97.7% of cases.

CONCLUSION

This study describes the first workflow to date of a CBCT-based oART combined with a shuttle-based offline approach for MR guidance. The oART duration times reported resemble the range shown by previous publications for first clinical experiences with the Ethos system.

Evaluating contouring accuracy and dosimetry impact of current MRI-guided adaptive radiation therapy for brain metastases: a retrospective study

BACKGROUND

Magnetic resonance imaging (MRI) guided adaptive radiotherapy (MRgART) has gained increasing attention, showing clinical advantages over conventional radiotherapy. However, there are concerns regarding online target delineation and modification accuracy. In our study, we aimed to investigate the accuracy of brain metastases (BMs) contouring and its impact on dosimetry in 1.5 T MRI-guided online adaptive fractionated stereotactic radiotherapy (FSRT).

METHODS

Eighteen patients with 64 BMs were retrospectively evaluated. Pre-treatment 3.0 T MRI scans (gadolinium contrast-enhanced T1w, T1c) and initial 1.5 T MR-Linac scans (non-enhanced online-T1, T2, and FLAIR) were used for gross target volume (GTV) contouring. Five radiation oncologists independently contoured GTVs on pre-treatment T1c and initial online-T1, T2, and FLAIR images. We assessed intra-observer and inter-observer variations and analysed the dosimetry impact through treatment planning based on GTVs generated by online MRI, simulating the current online adaptive radiotherapy practice.

RESULTS

The average Dice Similarity Coefficient (DSC) for inter-observer comparison were 0.79, 0.54, 0.59, and 0.64 for pre-treatment T1c, online-T1, T2, and FLAIR, respectively. Inter-observer variations were significantly smaller for the 3.0 T pre-treatment T1c than for the contrast-free online 1.5 T MR scans (P < 0.001). Compared to the T1c contours, the average DSC index of intra-observer contouring was 0.52‒0.55 for online MRIs. For BMs larger than 3 cm3, visible on all image sets, the average DSC indices were 0.69, 0.71 and 0.64 for online-T1, T2, and FLAIR, respectively, compared to the pre-treatment T1c contour. For BMs < 3 cm3, the average visibility rates were 22.3%, 41.3%, and 51.8% for online-T1, T2, and FLAIR, respectively. Simulated adaptive planning showed an average prescription dose coverage of 63.4‒66.9% when evaluated by ground truth planning target volumes (PTVs) generated on pre-treatment T1c, reducing it from over 99% coverage by PTVs generated on online MRIs.

CONCLUSIONS

The accuracy of online target contouring was unsatisfactory for the current MRI-guided online adaptive FSRT. Small lesions had poor visibility on 1.5 T non-contrast-enhanced MR-Linac images. Contour inaccuracies caused a one-third drop in prescription dose coverage for the target volume. Future studies should explore the feasibility of contrast agent administration during daily treatment in MRI-guided online adaptive FSRT procedures.

Improved Dosimetry with Daily Online Adaptive Radiotherapy for Cervical Cancer: Waltzing the Pear

AIMS

Standard of care radiotherapy for locally advanced cervical cancer includes large margins to ensure the uterocervix remains within the treatment fields over the course of treatment. Daily online cone-beam adaptive radiotherapy corrects for interfractional changes by adjusting the plan to match the target position during each treatment session, thus allowing for significantly reduced clinical target volume (CTV) to planning target volume (PTV) margins. We hypothesise that reduced margins from daily online adaptive radiotherapy will reduce organ at risk dose without compromising target coverage.

MATERIALS AND METHODS

Ten patients with cervical cancer (stage IIB-IIIC2) were treated with definitive chemoradiation using daily online cone-beam adaptive radiotherapy in 25-27 fractions. Initial and all adapted treatment plans were generated with CTV to PTV margins versus standard of care image-guided radiotherapy (IGRT) plans as follows: cervix/uterus/gross tumour volume (0.5 versus 1.5 cm), parametria/vagina (0.5 versus 1.0 cm) and nodal chains and gross nodes (0.5 versus 0.5 cm). IGRT plans were created and copied to synthetic computed tomography scans and contours generated from each daily adapted fraction. The dosimetry of each clinically treated online adapted fraction was compared with emulated IGRT plans. Statistical significance was defined as P < 0.05.

RESULTS

Daily online cone-beam adaptive radiotherapy significantly improves bowel bag dosimetry compared with IGRT, with a reduction in V40 by an average of 91.3 cm3 [V40 (-6.2%) and V45 (-6.1%)]. The daily adapted plans showed significant improvements in bladder and rectum [V40 (-25.2% and -36.0%) and V30 (-9.7% and -17.1%), respectively]. Additionally, bone marrow had a significantly reduced dose [V10 (-2.7%) and V20 (-3.3%)]. Daily online cone-beam adaptive radiotherapy improved uterocervix CTV coverage and reduced hotspots compared with IGRT [D95% (+1.6%) and Dmax (-0.9%)].

CONCLUSIONS

Reduced CTV to PTV margins achievable with daily online adaptive radiotherapy improves organ at risk dosimetry and target coverage when compared with standard of care IGRT for locally advanced cervical cancer. The clinical impact of improved dosimetry is currently undergoing investigation.

Artificial intelligence applied to image-guided radiation therapy (IGRT): a systematic review by the Young Group of the Italian Association of Radiotherapy and Clinical Oncology (yAIRO)

INTRODUCTION

The advent of image-guided radiation therapy (IGRT) has recently changed the workflow of radiation treatments by ensuring highly collimated treatments. Artificial intelligence (AI) and radiomics are tools that have shown promising results for diagnosis, treatment optimization and outcome prediction. This review aims to assess the impact of AI and radiomics on modern IGRT modalities in RT.

METHODS

A PubMed/MEDLINE and Embase systematic review was conducted to investigate the impact of radiomics and AI to modern IGRT modalities. The search strategy was "Radiomics" AND "Cone Beam Computed Tomography"; "Radiomics" AND "Magnetic Resonance guided Radiotherapy"; "Radiomics" AND "on board Magnetic Resonance Radiotherapy"; "Artificial Intelligence" AND "Cone Beam Computed Tomography"; "Artificial Intelligence" AND "Magnetic Resonance guided Radiotherapy"; "Artificial Intelligence" AND "on board Magnetic Resonance Radiotherapy" and only original articles up to 01.11.2022 were considered.

RESULTS

A total of 402 studies were obtained using the previously mentioned search strategy on PubMed and Embase. The analysis was performed on a total of 84 papers obtained following the complete selection process. Radiomics application to IGRT was analyzed in 23 papers, while a total 61 papers were focused on the impact of AI on IGRT techniques.

DISCUSSION

AI and radiomics seem to significantly impact IGRT in all the phases of RT workflow, even if the evidence in the literature is based on retrospective data. Further studies are needed to confirm these tools' potential and provide a stronger correlation with clinical outcomes and gold-standard treatment strategies.

Empirical analysis of a plan-of-the-day strategy to approximate daily online reoptimization for prostate CBCT-guided adaptive radiotherapy

PURPOSE

Adaptive radiotherapy (ART) can improve the dose delivered to the patient in the presence of anatomic variations. However, the required time, effort, and clinical resources are intensive. This work analyzed a plan-of-the-day (POD) approach on clinical patients treated with online ART to explore implementations that balance dosimetric benefit and clinical resource cost.

METHODS

Eight patients treated to the prostate and proximal seminal vesicles with 26 fractions of CBCT-guided, daily online ART were retrospectively analyzed. With a plan library composed of daily adaptive plans from the initial week of treatment and the original plan, the effect of a POD approach starting the following week was investigated by simulating use of these previously generated plans under 3- and 6-degree-of-freedom patient alignment. The plan selected for each treatment was that from the library that maximized the Dice similarity coefficient of the clinical target volume with that of the current treatment fraction. The resulting distribution of several target coverage and organ-at-risk dose metrics are described relative to those achieved with the daily online reoptimized adaptive technique.

RESULTS

The values of target coverage and organ-at-risk dose metrics varied across patients and metrics. The POD schemas closely approximated the reference values from a fully reoptimized adaptive plan yet required less than 20% of the reoptimization effort. The POD schemas also had a much greater effect on target coverage metrics than 6-degree-of-freedom registration did. Organ-at-risk dose metrics also varied considerably across patients but did not exhibit a consistent dependence on the particular schema.

CONCLUSIONS

POD schemas were able to achieve the vast majority of the dosimetric benefit of daily online ART with a small fraction of the online reoptimization effort. Strategies like this might allow for more practical and strategic implementation of ART so as to benefit a greater number of patients.

Evaluation and correlation of patient movement during online adaptive radiotherapy with CBCT and a surface imaging system

PURPOSE

With the clinical implementation of kV-CBCT-based daily online-adaptive radiotherapy, the ability to monitor, quantify, and correct patient movement during adaptive sessions is paramount. With sessions lasting between 20-45 min, the ability to detect and correct for small movements without restarting the entire session is critical to the adaptive workflow and dosimetric outcome. The purpose of this study was to quantify and evaluate the correlation of observed patient movement with machine logs and a surface imaging (SI) system during adaptive radiation therapy.

METHODS

Treatment machine logs and SGRT registration data log files for 1972 individual sessions were exported and analyzed. For each session, the calculated shifts from a pre-delivery position verification CBCT were extracted from the machine logs and compared to the SGRT registration data log files captured during motion monitoring. The SGRT calculated shifts were compared to the reported shifts of the machine logs for comparison for all patients and eight disease site categories.

RESULTS

The average (±STD) net displacement of the SGRT shifts were 2.6 ± 3.4 mm, 2.6 ± 3.5 mm, and 3.0 ± 3.2 in the lateral, longitudinal, and vertical directions, respectively. For the treatment machine logs, the average net displacements in the lateral, longitudinal, and vertical directions were 2.7 ± 3.7 mm, 2.6 ± 3.7 mm, and 3.2 ± 3.6 mm. The average difference (Machine-SGRT) was -0.1 ± 1.8 mm, 0.2 ± 2.1 mm, and -0.5 ± 2.5 mm for the lateral, longitudinal, and vertical directions. On average, a movement of 5.8 ± 5.6 mm and 5.3 ± 4.9 mm was calculated prior to delivery for the CBCT and SGRT systems, respectively. The Pearson correlation coefficient between CBCT and SGRT shifts was r = 0.88. The mean and median difference between the treatment machine logs and SGRT log files was less than 1 mm for all sites.

CONCLUSION

Surface imaging should be used to monitor and quantify patient movement during adaptive radiotherapy.

Comparison of Ethos template-based planning and AI-based dose prediction: General performance, patient optimality, and limitations

PURPOSE

Ethos proposes a template-based automatic dose planning (Etb) for online adaptive radiotherapy. This study evaluates the general performance of Etb for prostate cancer, as well as the ability to generate patient-optimal plans, by comparing it with another state-of-the-art automatic planning method, i.e., deep learning dose prediction followed by dose mimicking (DP + DM).

MATERIALS

General performances and capability to produce patient-optimal plan were investigated through two studies: Study-S1 generated plans for 45 patients using our initial Ethos clinical goals template (EG_init), and compared them to manually generated plans (MG). For study-S2, 10 patients which showed poor performances at study-S1 were selected. S2 compared the quality of plans generated with four different methods: 1) Ethos initial template (EG_init_selected), 2) Ethos updated template-based on S1 results (EG_upd_selected), 3) DP + DM, and 4) MG plans.

RESULTS

EG_init plans showed satisfactory performance for dose level above 50 Gy: reported mean metrics differences (EG_init minus MG) never exceeded 0.6 %. However, lower dose levels showed loosely optimized metrics, mean differences for V30Gy to rectum and V20Gy to anal canal were of 6.6 % and 13.0 %. EG_init_selected showed amplified differences in V30Gy to rectum and V20Gy to anal canal: 8.5 % and 16.9 %, respectively. These dropped to 5.7 % and 11.5 % for EG_upd_selected plans but strongly increased V60Gy to rectum for 2 patients. DP + DM plans achieved differences of 3.4 % and 4.6 % without compromising any V60Gy.

CONCLUSION

General performances of Etb were satisfactory. However, optimizing with template of goals might be limiting for some complex cases. Over our test patients, DP + DM outperformed the Etb approach.

A head and neck treatment planning strategy for a CBCT-guided ring-gantry online adaptive radiotherapy system

PURPOSE

A planning strategy was developed and the utility of online-adaptation with the Ethos CBCT-guided ring-gantry adaptive radiotherapy (ART) system was evaluated using retrospective data from Head-and-neck (H&N) patients that required clinical offline adaptation during treatment.

METHODS

Clinical data were used to re-plan 20 H&N patients (10 sequential boost (SEQ) with separate base and boost plans plus 10 simultaneous integrated boost (SIB)). An optimal approach, robust to online adaptation, for Ethos-initial plans using clinical goal prioritization was developed. Anatomically-derived isodose-shaping helper structures, air-density override, goals for controlling hotspot location(s), and plan normalization were investigated. Online adaptation was simulated using clinical offline adaptive simulation-CTs to represent an on-treatment CBCT. Dosimetric comparisons were based on institutional guidelines for Clinical-initial versus Ethos-initial plans and Ethos-scheduled versus Ethos-adapted plans. Timing for five components of the online adaptive workflow was analyzed.

RESULTS

The Ethos H&N planning approach generated Ethos-initial SEQ plans with clinically comparable PTV coverage (average PTVHigh V100%  = 98.3%, Dmin,0.03cc  = 97.9% and D0.03cc  = 105.5%) and OAR sparing. However, Ethos-initial SIB plans were clinically inferior (average PTVHigh V100%  = 96.4%, Dmin,0.03cc  = 93.7%, D0.03cc  = 110.6%). Fixed-field IMRT was superior to VMAT for 93.3% of plans. Online adaptation succeeded in achieving conformal coverage to the new anatomy in both SEQ and SIB plans that was even superior to that achieved in the initial plans (which was due to the changes in anatomy that simplified the optimization). The average adaptive workflow duration for SIB, SEQ base and SEQ boost was 30:14, 22.56, and 14:03 (min: sec), respectively.

CONCLUSIONS

With an optimal planning approach, Ethos efficiently auto-generated dosimetrically comparable and clinically acceptable initial SEQ plans for H&N patients. Initial SIB plans were inferior and clinically unacceptable, but adapted SIB plans became clinically acceptable. Online adapted plans optimized dose to new anatomy and maintained target coverage/homogeneity with improved OAR sparing in a time-efficient manner.

Feasibility study of adaptive radiotherapy with Ethos for breast cancer

Purpose

The aim of this study was to assess the feasibility of online adaptive radiotherapy with Ethos for breast cancer.

Materials and methods

This retrospective study included 20 breast cancer patients previously treated with TrueBeam. All had undergone breast surgery for different indications (right/left, lumpectomy/mastectomy) and were evenly divided between these four cases, with five extended cone beam computed tomography (CBCT) scans per patient. The dataset was used in an Ethos emulator to test the full adaptive workflow. The contours generated by artificial intelligence (AI) for the influencers (left and right breasts and lungs, heart) and elastic or rigid propagation for the target volumes (internal mammary chain (IMC) and clavicular lymph nodes (CLNs)) were compared to the initial contours delineated by the physician using two metrics: Dice similarity coefficient (DICE) and Hausdorff 95% distance (HD95). The repeatability of influencer generation was investigated. The times taken by the emulator to generate contours, optimize plans, and calculate doses were recorded. The quality of the scheduled and adapted plans generated by Ethos was assessed using planning target volume (PTV) coverage, homogeneity indices (HIs), and doses to organs at risk (OARs) via dose-volume histogram (DVH) metrics. Quality assurance (QA) of the treatment plans was performed using an independent portal dosimetry tool (EpiQA) and gamma index.

Results

On average, the DICE for the influencers was greater than 0.9. Contours resulting from rigid propagation had a higher DICE and a lower HD95 than those resulting from elastic deformation but remained below the values obtained for the influencers: DICE values were 0.79 ± 0.11 and 0.46 ± 0.17 for the CLN and IMC, respectively. Regarding the repeatability of the influencer segmentation, the DICE was close to 1, and the mean HD95 was strictly less than 0.15 mm. The mean time was 73 ± 4 s for contour generation per AI and 80 ± 9 s for propagations. The average time was 53 ± 3 s for dose calculation and 125 ± 9 s for plan optimization. A dosimetric comparison of scheduled and adapted plans showed a significant difference in PTV coverage: dose received by 95% of the volume (D95%) values were higher and closer to the prescribed doses for adapted plans. Doses to organs at risk were similar. The average gamma index for quality assurance of adapted plans was 99.93 ± 0.38 for a 3%/3mm criterion.

Conclusion

This study comprehensively evaluated the Ethos® adaptive workflow for breast cancer and its potential technical limitations. Although the results demonstrated the high accuracy of AI segmentation and the superiority of adapted plans in terms of target volume coverage, a medical assessment is still required.

A systematic review on clinical adaptive radiotherapy for head and neck cancer

INTRODUCTION

Head and neck cancer (HNC) patients' anatomy may undergo significant changes during radiotherapy (RT). This potentially affects dose distribution and compromises conformity between planned and delivered dose. Adaptive radiotherapy (ART) is a promising technique to overcome this problem but requires a significant workload. This systematic review aims to estimate the clinical and dosimetric benefits of ART using prospective data.

MATERIAL AND METHODS

A search on PubMed and Web of Science according to the PRISMA guidelines was made on Feb 6, 2023. Search string used was: 'adaptive radiotherapy head neck cancer'. English language filter was applied. All studies were screened for inclusion on title and abstract, and the full text was read and discussed in the research group in case of uncertainty. Inclusion criteria were a prospective ART strategy for HNC investigating clinical or dosimetric outcomes.

RESULTS

A total of 1251 articles were identified of which 15 met inclusion criteria. All included studies were published between 2010 and 2023 with a substantial diversity in design, endpoints, and nomenclature. The number of patients treated with ART was small with a median of 20 patients per study (range 4 to 86), undergoing 1-2 replannings. Mean dose to the parotid glands was reduced by 0.4-7.1 Gy. Maximum dose to the spinal cord was reduced by 0.5-4.6 Gy. Only five studies reported clinical outcome and disease control was excellent. Data on toxicity were ambiguous with some studies indicating reduced acute toxicity and xerostomia, while others found reduced quality of life in patients treated with ART.

CONCLUSION

The literature on clinical ART in HNC is limited. ART is associated with small reductions in doses to organs at risk, but the influence on toxicity and disease control is uncertain. There is a clear need for larger, prospective trials with a well-defined control group.

Fractionation versus Adaptation for Compensation of Target Volume Changes during Online Adaptive Radiotherapy for Bladder Cancer: Answers from a Prospective Registry

Online adaptive radiotherapy (ART) allows adaptation of the dose distribution to the anatomy captured by with pre-adaptation imaging. ART is time-consuming, and thus intra-fractional deformations can occur. This prospective registry study analyzed the effects of intra-fraction deformations of clinical target volume (CTV) on the equivalent uniform dose (EUDCTV) of focal bladder cancer radiotherapy. Using margins of 5-10 mm around CTV on pre-adaptation imaging, intra-fraction CTV-deformations found in a second imaging study reduced the 10th percentile of EUDCTV values per fraction from 101.1% to 63.2% of the prescribed dose. Dose accumulation across fractions of a series was determined with deformable-image registration and worst-case dose accumulation that maximizes the correlation of cold spots. A strong fractionation effect was demonstrated-the EUDCTV was above 95% and 92.5% as determined by the two abovementioned accumulation methods, respectively, for all series of dose fractions. A comparison of both methods showed that the fractionation effect caused the EUDCTV of a series to be insensitive to EUDCTV-declines per dose fraction, and this could be explained by the small size and spatial variations of cold spots. Therefore, ART for each dose fraction is unnecessary, and selective ART for fractions with large inter-fractional deformations alone is sufficient for maintaining a high EUDCTV for a radiotherapy series.

Online adaptive radiotherapy for bladder cancer using a simultaneous integrated boost and fiducial markers

PURPOSE

The aim was to assess the feasibility of online adaptive radiotherapy (oART) for bladder cancer using a focal boost by focusing on the quality of the online treatment plan and automatic target delineation, duration of the workflow and performance in the presence of fiducial markers for tumor bed localization.

METHODS

Fifteen patients with muscle invasive bladder cancer received daily oART with Cone Beam CT (CBCT), artificial intelligence (AI)-assisted automatic delineation of the daily anatomy and online plan reoptimization. The bladder and pelvic lymph nodes received a total dose of 40 Gy in 20 fractions, the tumor received an additional simultaneously integrated boost (SIB) of 15 Gy. The dose distribution of the reference plan was calculated for the daily anatomy, i.e. the scheduled plan. Simultaneously, a reoptimization of the plan was performed i.e. the adaptive plan. The target coverage and V95% outside the target were evaluated for both plans. The need for manual adjustments of the GTV delineation, the duration of the workflow and the influence of fiducial markers were assessed.

RESULTS

All 300 adaptive plans met the requirement of the CTV-coverage V95%≥98% for both the boost (55 Gy) and elective volume (40 Gy). For the scheduled plans the CTV-coverage was 53.5% and 98.5%, respectively. Significantly less tissue outside the targets received 55 Gy in case of the adaptive plans as compared to the scheduled plans. Manual corrections of the GTV were performed in 67% of the sessions. In 96% of these corrections the GTV was enlarged and resulted in a median improvement of 1% for the target coverage. The median on-couch time was 22 min. A third of the session time consisted of reoptimization of the treatment plan. Fiducial markers were visible on the CBCTs and aided the tumor localization.

CONCLUSIONS

AI-driven CBCT-guided oART aided by fiducial markers is feasible for bladder cancer radiotherapy treatment including a SIB. The quality of the adaptive plans met the clinical requirements and fiducial markers were visible enabling consistent daily tumor localization. Improved automatic delineation to lower the need for manual corrections and faster reoptimization would result in shorter session time.

Review of cone beam computed tomography based online adaptive radiotherapy: current trend and future direction

Adaptive radiotherapy (ART) was introduced in the late 1990s to improve the accuracy and efficiency of therapy and minimize radiation-induced toxicities. ART combines multiple tools for imaging, assessing the need for adaptation, treatment planning, quality assurance, and has been utilized to monitor inter- or intra-fraction anatomical variations of the target and organs-at-risk (OARs). Ethos™ (Varian Medical Systems, Palo Alto, CA), a cone beam computed tomography (CBCT) based radiotherapy treatment system that uses artificial intelligence (AI) and machine learning to perform ART, was introduced in 2020. Since then, numerous studies have been done to examine the potential benefits of Ethos™ CBCT-guided ART compared to non-adaptive radiotherapy. This review will explore the current trends of Ethos™, including improved CBCT image quality, a feasible clinical workflow, daily automated contouring and treatment planning, and motion management. Nevertheless, evidence of clinical improvements with the use of Ethos™ are limited and is currently under investigation via clinical trials.

[Bladder preservation treatments for bladder cancer: Trimodality therapy, an overview of clinical practices in 2023]

Bladder cancer is the most frequent tumor of the urinary tract. Patients diagnosed at a stage when the tumor has spread into or through the muscle layer of the bladder wall are usually treated with cystectomy. The evolution of cancer treatments, related to the development of alternative treatment options to the historical surgical standard and to the implication of the patient as an actor in decision-making, trends towards organ and function preservation without sacrificing efficacy. Trimodality therapy, which is a maximal transurethral resection of the tumor followed by concurrent chemoradiation, is an interesting therapeutic alternative for patients unfit for surgery and for those wishing to benefit from organ preservation. Radiotherapy offers excellent treatment possibilities for muscle-invasive bladder cancer. In selected T2-stage patients fit for trimodality therapy, it has an equivalent oncological outcome compared to cystectomy while having less severe complications and offering organ preservation. It remains feasible in inoperable patients while offering significant perspectives of relapse-free survival. Finally, it also is an efficient palliative treatment in patients where mid-term local control and hemostasis are sought after.

Evaluation of the Ethos synthetic computed tomography for bolus-covered surfaces

PURPOSE

Ethos allows online adaption of radiotherapy treatment plans. Dose is calculated on synthetic computed tomographies (sCT), CT-like images generated by deforming planning CTs (pCT) onto daily cone beam CTs (CBCT) acquired during treatment sessions. Errors in sCT density distribution may lead to dose calculation errors. sCT correctness was investigated for bolus-covered surfaces.

METHODS

pCTs were recorded of a slab phantom covered with bolus of different thicknesses and with air gaps introduced by spacer rings of variable diameters and heights. Treatment plans were irradiated following the adaptive workflow with different bolus configurations present in the pCT and CBCT. sCT densities were compared to those of the pCT for the same air gap size. Additionally, the neck region of an anthropomorphic phantom was imaged using a plane standard bolus versus an individual bolus adapted to the phantom's outer contour.

RESULTS

Varying bolus thickness by 5 mm between pCT and CBCT was reproduced in the sCT within 2 mm accuracy. Different air gaps in pCT and CBCT resulted in highly variable bolus thickness in the sCT with a typical error of 5 mm or more. In extreme cases, air gaps were filled with bolus material density in the sCT or the phantom was unrealistically deformed near changed bolus geometries. Changes in bolus thickness and deformation also occurred in the anthropomorphic phantom.

CONCLUSION

sCTs must be critically examined and included in plan-specific quality assurance. The use of tight-fitting air gap-free bolus should be preferred to increase the similarity between sCT and CBCT.

Initial clinical experience building a dual CT- and MR-guided adaptive radiotherapy program

Introduction

Our institution was the first in the world to clinically implement MR-guided adaptive radiotherapy (MRgART) in 2014. In 2021, we installed a CT-guided adaptive radiotherapy (CTgART) unit, becoming one of the first clinics in the world to build a dual-modality ART clinic. Herein we review factors that lead to the development of a high-volume dual-modality ART program and treatment census over an initial, one-year period.

Materials and Methods

The clinical adaptive service at our institution is enabled with both MRgART (MRIdian, ViewRay, Inc, Mountain View, CA) and CTgART (ETHOS, Varian Medical Systems, Palo Alto, CA) platforms. We analyzed patient and treatment information including disease sites treated, radiation dose and fractionation, and treatment times for patients on these two platforms. Additionally, we reviewed our institutional workflow for creating, verifying, and implementing a new adaptive workflow on either platform.

Results

From October 2021 to September 2022, 256 patients were treated with adaptive intent at our institution, 186 with MRgART and 70 with CTgART. The majority (106/186) of patients treated with MRgART had pancreatic cancer, and the most common sites treated with CTgART were pelvis (23/70) and abdomen (20/70). 93.0% of treatments on the MRgART platform were stereotactic body radiotherapy (SBRT), whereas only 72.9% of treatments on the CTgART platform were SBRT. Abdominal gated cases were allotted a longer time on the CTgART platform compared to the MRgART platform, whereas pelvic cases were allotted a shorter time on the CTgART platform when compared to the MRgART platform. Our adaptive implementation technique has led to six open clinical trials using MRgART and seven using CTgART.

Conclusions

We demonstrate the successful development of a dual platform ART program in our clinic. Ongoing efforts are needed to continue the development and integration of ART across platforms and disease sites to maximize access and evidence for this technique worldwide.

Advantages and robustness of partial VMAT with prone position for neoadjuvant rectal cancer evaluated by CBCT-based offline adaptive radiotherapy

BACKGROUND AND PURPOSE

This study aims to explore the advantages and robustness of the partial arc combined with prone position planning technique for radiotherapy in rectal cancer patients. Adaptive radiotherapy is recalculated and accumulated on the synthesis CT (sCT) obtained by deformable image registration between planning CT and cone beam CT (CBCT). Full and partial volume modulation arc therapy (VMAT) with the prone position on gastrointestinal and urogenital toxicity, based on the probability of normal tissue complications (NTCP) model in rectal cancer patients were evaluated.

MATERIALS AND METHODS

Thirty-one patients were studied retrospectively. The contours of different structures were outlined in 155 CBCT images. First, full VMAT (F-VMAT) and partial VMAT (P-VMAT) planning techniques were designed and calculated using the same optimization constraints for each individual patient. The Acuros XB (AXB) algorithm was used in order to generate more realistic dose distributions and DVH, considering the air cavities. Second, the Velocity 4.0 software was used to fuse the planning CT and CBCT to obtain the sCT. Then, the AXB algorithm was used in the Eclipse 15.6 software to conduct re-calculation based on the sCT to obtain the corresponding dose. Furthermore, the NTCP model was used to analyze its radiobiological side effects on the bladder and the bowel bag.

RESULTS

With a CTV coverage of 98%, when compared with F-VMAT, P-VMAT with the prone position technique can effectively reduce the mean dose of the bladder and the bowel bag. The NTCP model showed that the P-VMAT combined with the prone planning technique resulted in a significantly lower complication probability of the bladder (1.88 ± 2.08 vs 1.62 ± 1.41, P = 0.041) and the bowel bag (1.28 ± 1.70 vs 0.95 ± 1.52, P < 0.001) than the F-VMAT. In terms of robustness, P-VMAT was more robust than F-VMAT, considering that less dose and NTCP variation was observed in the CTV, bladder and bowel bag.

CONCLUSION

This study analyzed the advantages and robustness of the P-VMAT in the prone position from three aspects, based on the sCT fused by CBCT. Whether it is in regards to dosimetry, radiobiological effects or robustness, P-VMAT in the prone position has shown comparative advantages.

Implementing cone-beam computed tomography-guided online adaptive radiotherapy in cervical cancer

Background and purpose

Adaptive radiotherapy (ART) in locally advanced cervical cancer (LACC) has shown promising outcomes. This study investigated the feasibility of cone-beam computed tomography (CBCT)-guided online ART (oART) for the treatment of LACC.

Material and methods

The quality of the automated radiotherapy treatment plans and artificial intelligence (AI)-driven contour delineation for LACC on a novel CBCT-guided oART system were assessed. Dosimetric analysis of 200 simulated oART sessions were compared with standard treatment. Feasibility of oART was assessed from the delivery of 132 oART fractions for the first five clinical LACC patients. The simulated and live oART sessions compared a fixed planning target volume (PTV) margin of 1.5 cm around the uterus-cervix clinical target volume (CTV) with an internal target volume-based approach. Workflow timing measurements were recorded.

Results

The automatically-generated 12-field intensity-modulated radiotherapy plans were comparable to manually generated plans. The AI-driven organ-at-risk (OAR) contouring was acceptable requiring, on average, 12.3 min to edit, with the bowel performing least well and rated as unacceptable in 16 % of cases. The treated patients demonstrated a mean PTV D98% (+/-SD) of 96.7 (+/- 0.2)% for the adapted plans and 94.9 (+/- 3.7)% for the non-adapted scheduled plans (p<10^-5). The D2cc (+/-SD) for the bowel, bladder and rectum were reduced by 0.07 (+/- 0.03)Gy, 0.04 (+/-0.05)Gy and 0.04 (+/-0.03)Gy per fraction respectively with the adapted plan (p <10^-5). In the live.setting, the mean oART session (+/-SD) from CBCT acquisition to beam-on was 29 +/- 5 (range 21-44) minutes.

Conclusion

CBCT-guided oART was shown to be feasible with dosimetric benefits for patients with LACC. Further work to analyse potential reductions in PTV margins is ongoing.

Toward real-time automatic treatment planning (RTTP) with a one-step 3D fluence map prediction method and (nonorthogonal) convolution technique

PURPOSE

To establish and evaluate a (quasi) real-time automated treatment planning (RTTP) strategy utilizing a one-step full 3D fluence map prediction model based on a nonorthogonal convolution operation for rectal cancer radiotherapy.

METHODS

The RTTP approach directly extracts 3D projections from volumetric CT and anatomical data according to the beam incident direction. A 3D deep learning model with a nonorthogonal convolution operation was established that takes projections in cone beam space as input, extracts the features along and around the ray-trace path, and outputs a predicted fluence map (PFM) for each beam. The PFM is then converted to the MLC sequence with deliverable MUs to generate the final treatment plan. A total of 314 rectal adenocarcinoma patients with 2198 projection data samples were used in model training and validation. An extra 20 patients were used to test the feasibility of the RTTP method by comparing the plan quality, efficiency, deliverability performance, and physician blinded review results with the manual plans.

RESULTS

Overall, the RTTP plans met the clinical dose criteria for target coverage, conformity, homogeneity, and organ-at-risk dose sparing. Compared to manual plans, the RTTP plans showed increases in PTV D_1% by only 2.33% (p < 0.001) and a decrease in PTV D_99% by 0.45% (p < 0.05). The RTTP plans showed a dose increase in the bladder, with a V₅₀ of 14.01 ± 11.75% vs. 10.74 ± 8.51%, respectively, and no significant increases in the femoral head with the mean dose. The planning efficiency was improved in RTTP planning, with 39 s vs. 944 s in fluence map generation; the deliverability performance was saved by 1.91% (p < 0.001) in total MU. According to the blinded plan review by our physician, 55% of RTTP plans can be directly used in clinical radiotherapy treatment.

CONCLUSION

The quasi RTTP method improves the planning efficiency and deliverability performance while maintaining a plan quality close to that of the optimized manual plans in rectal radiotherapy.

A survey of practice patterns for adaptive particle therapy for interfractional changes

Background and purpose

Anatomical changes may compromise the planned target coverage and organs-at-risk dose in particle therapy. This study reports on the practice patterns for adaptive particle therapy (APT) to evaluate current clinical practice and wishes and barriers to further implementation.

Materials and methods

An institutional questionnaire was distributed to PT centres worldwide (7/2020-6/2021) asking which type of APT was used, details of the workflow, and what the wishes and barriers to implementation were. Seventy centres from 17 countries participated. A three-round Delphi consensus analysis (10/2022) among the authors followed to define recommendations on required actions and future vision.

Results

Out of the 68 clinically operational centres, 84% were users of APT for at least one treatment site with head and neck being most common. APT was mostly performed offline with only two online APT users (plan-library). No centre used online daily re-planning. Daily 3D imaging was used for APT by 19% of users. Sixty-eight percent of users had plans to increase their use or change their technique for APT. The main barrier was "lack of integrated and efficient workflows". Automation and speed, reliable dose deformation for dose accumulation and higher quality of in-room volumetric imaging were identified as the most urgent task for clinical implementation of online daily APT.

Conclusion

Offline APT was implemented by the majority of PT centres. Joint efforts between industry research and clinics are needed to translate innovations into efficient and clinically feasible workflows for broad-scale implementation of online APT.

Knowledge-based adaptive planning quality assurance using dosimetric indicators for stereotactic adaptive radiotherapy for pancreatic cancer

INTRODUCTION

We aimed to develop knowledge-based tools for robust adaptive radiotherapy (ART) planning to determine on-table adaptive DVH metric variations or planning process errors for stereotactic pancreatic ART. We developed volume-based dosimetric identifiers to identify deviations of ART plans from simulation plans.

MATERIALS AND METHODS

Two patient cohorts who were treated on MR-Linac for pancreas cancer were included in this retrospective study; a training cohort and a validation cohort. All patients received 50 Gy in 5 fractions. PTV-OPT was generated by subtracting the critical organs plus a 5 mm-margin from PTV. Several metrics that potentially can identify failure-modes were calculated including PTV & PTV_OPT V95% and PTV & PTV_OPT D95%/D5%. The difference between each DVH metric in each adaptive plan with the DVH metric in simulation plan was calculated. The 95% confidence interval (CI) of the variations in each DVH metric was calculated for the patient training cohort. Variations in DVH metrics that exceeded the 95% CI for all fractions in training and validation cohort were flagged for retrospective investigation for root-cause analysis to determine their predictive power for identifying failure-modes.

RESULTS

The CIs for the PTV & PTV_OPT V95% and PTV & PTV_OPT D95%/D5% were ± 13%, ± 5%, ± 0.1, ± 0.03, respectively. We estimated the positive predictive value and negative predictive value of our method to be 77% and 89%, respectively, for the training cohort, and 80% for both in the validation cohort.

DISCUSSION

We developed dosimetric indicators for ART planning QA to identify population-based deviations or planning errors during online adaptive process for stereotactic pancreatic ART. This technology may be useful as an ART clinical trial QA tool and improve overall ART quality at an institution.

Online adaptive radiotherapy of anal cancer: Normal tissue sparing, target propagation methods, and first clinical experience

BACKGROUND AND PURPOSE

Online adaptive radiotherapy (oART) potentially spares OARs as PTV margins are reduced. This study evaluates dosimetric benefits, compared to standard non-adaptive radiotherapy (non-ART), target propagation methods, and first clinical treatments of CBCT-guided oART of anal cancer.

MATERIALS AND METHODS

Treatment plans with standard non-ART and reduced oART PTV margins were retrospectively generated for 23 consecutive patients with anal cancer. For five patients randomly selected among the 23 patients, weekly CBCT-guided oART sessions were simulated, where the targets were either deformed or rigidly propagated. Preferred target propagation method and dose to OARs were evaluated. Ten consecutive patients with anal cancer were treated with CBCT-guided oART. Target propagation methods and oART procedure time were evaluated.

RESULTS

For the retrospective treatment plans, oART resulted in median reductions in bowel bag V_45Gy of 11.4 % and bladder V_35Gy of 16.1%. Corresponding values for the simulated sessions were 7.5% and 27.1%. In the simulated sessions, 35% of all targets were deformed while 65% were rigidly propagated. Manual editing and rigid propagation were necessary to obtain acceptable target coverage. In the clinical treatments, the primary and some elective targets were rigidly propagated, while other targets were deformed. The median oART procedure time, measured from CBCT acquisition to completion of plan review and QA, was 23 min.

CONCLUSIONS

Simulated oART reduced the dose to OARs, indicating potential reduction in toxicity. Rigid propagation of targets was necessary to reduce the need for manual edit. Clinical treatments demonstrated that oART of anal cancer is feasible but time-consuming.