Initial analysis of the dosimetric benefit and clinical resource cost of CBCT-based online adaptive radiotherapy for patients with cancers of the cervix or rectum

Unlocking the adaptive advantage: correlation and machine learning classification to identify optimal online adaptive stereotactic partial breast candidates

Objective.Online adaptive radiotherapy (OART) is a promising technique for delivering stereotactic accelerated partial breast irradiation (APBI), as lumpectomy cavities vary in location and size between simulation and treatment. However, OART is resource-intensive, increasing planning and treatment times and decreasing machine throughput compared to the standard of care (SOC). Thus, it is pertinent to identify high-yield OART candidates to best allocate resources.Approach.Reference plans (plans based on simulation anatomy), SOC plans (reference plans recalculated onto daily anatomy), and daily adaptive plans were analyzed for 31 sequential APBI targets, resulting in the analysis of 333 treatment plans. Spearman correlations between 22 reference plan metrics and 10 adaptive benefits, defined as the difference between mean SOC and delivered metrics, were analyzed to select a univariate predictor of OART benefit. A multivariate logistic regression model was then trained to stratify high- and low-benefit candidates.Main results.Adaptively delivered plans showed dosimetric benefit as compared to SOC plans for most plan metrics, although the degree of adaptive benefit varied per patient. The univariate model showed high likelihood for dosimetric adaptive benefit when the reference plan ipsilateral breast V15Gy exceeds 23.5%. Recursive feature elimination identified 5 metrics that predict high-dosimetric-benefit adaptive patients. Using leave-one-out cross validation, the univariate and multivariate models classified targets with 74.2% and 83.9% accuracy, resulting in improvement in per-fraction adaptive benefit between targets identified as high- and low-yield for 7/10 and 8/10 plan metrics, respectively.Significance.This retrospective, exploratory study demonstrated that dosimetric benefit can be predicted using only ipsilateral breast V15Gy on the reference treatment plan, allowing for a simple, interpretable model. Using multivariate logistic regression for adaptive benefit prediction led to increased accuracy at the cost of a more complicated model. This work presents a methodology for clinics wishing to triage OART resource allocation.

The clinical practice and dosimetric outcome of the manual adaptive planning during definitive radiotherapy for cervical cancer

PROPOSE

To evaluate the advantage of the manual adaptive plans comparing to the scheduled plans, and explored clinical factors predicting patients suitable for adaptive strategy.

METHODS AND MATERIALS

Eighty two patients with weekly online cone-beam computed tomography (CBCT) were enrolled. The re-CT simulation was performed after 15 fractions and a manual adaptive plan was developed if a significant deviation of the planning target volume (PTV) was found. To evaluate the dosimetric benefit, D98, homogeneity index (HI) and conformity index (CI) for the planning target volume (PTV), as well as D2cc of the bowel, bladder, sigmoid and rectum were compared between manual adaptive plans and scheduled ones. The clinical factors influencing target motion during radiotherapy were analyzed by chi-square test and logistic regression analysis.

RESULTS

The CI and HI of the manual adaptive plans were significantly superior to the scheduled ones (P = 0.0002, 0.003, respectively), demonstrating a better dose coverage of the target volume. Compared to the scheduled plans, D98 of the manual adaptive plans increased by 3.3% (P = 0.0002), the average of D2cc to the rectum, bladder decreased 0.358 Gy (P = 0.000034) and 0.240 Gy (P = 0.03), respectively. In addition, the chi-square test demonstrated that age, primary tumor volume, and parametrial infiltration were the clinical factors influencing target motion during radiotherapy. Multivariate analysis further identified the large tumor volume (≥ 50cm3, OR = 3.254, P = 0.039) and parametrial infiltration (OR = 3.376, P = 0.018) as the independent risk factors.

CONCLUSION

We found the most significant organ motion happened after 15 fractions during treatment. The manual adaptive plans improved the dose coverage and decreased the OAR doses. Patients with bulky mass or with parametrial infiltration were highly suggested to adaptive strategy during definitive radiotherapy due to the significant organ motion.

Enhancing Safety in AI-Driven Cone Beam CT-based Online Adaptive Radiation Therapy: Development and Implementation of an Interdisciplinary Workflow

Purpose

The emerging online adaptive radiation therapy (OART) treatment strategy based on cone beam computed tomography allows for real-time replanning according to a patient's current anatomy. However, implementing this procedure requires a new approach across the patient's care path and monitoring of the "black box" adaptation process. This study identifies high-risk failure modes (FMs) associated with AI-driven OART and proposes an interdisciplinary workflow to mitigate potential medical errors from highly automated processes, enhance treatment efficiency, and reduce the burden on clinicians.

Methods and Materials

An interdisciplinary working group was formed to identify safety concerns in each process step using failure mode and effects analysis (FMEA). Based on the FMEA results, the team designed standardized procedures and safety checklists to prevent errors and ensure successful task completion. The Risk Priority Numbers (RPNs) for the top twenty FMs were calculated before and after implementing the proposed workflow to evaluate its effectiveness. Three hundred seventy-four adaptive sessions across 5 treatment sites were performed, and each session was evaluated for treatment safety and FMEA assessment.

Results

The OART workflow has 4 components, each with 4, 8, 13, and 4 sequentially executed tasks and safety checklists. Site-specific template preparation, which includes disease-specific physician directives and Intelligent Optimization Engine template testing, is one of the new procedures introduced. The interdisciplinary workflow significantly reduced the RPNs of the high-risk FMs, with an average decrease of 110 (maximum reduction of 305.5 and minimum reduction of 27.4).

Conclusions

This study underscores the importance of addressing high-risk FMs associated with AI-driven OART and emphasizes the significance of safety measures in its implementation. By proposing a structured interdisciplinary workflow and integrated checklists, the study provides valuable insights into ensuring the safe and efficient delivery of OART while facilitating its effective integration into clinical practice.

Simulation and pre-planning omitted radiotherapy (SPORT): a feasibility study for prostate cancer

This study explored the feasibility of on-couch intensity modulated radiotherapy (IMRT) planning for prostate cancer (PCa) on a cone-beam CT (CBCT)-based online adaptive RT platform without an individualized pre-treatment plan and contours. Ten patients with PCa previously treated with image-guided IMRT (60 Gy/20 fractions) were selected. In contrast to the routine online adaptive RT workflow, a novel approach was employed in which the same preplan that was optimized on one reference patient was adapted to generate individual on-couch/initial plans for the other nine test patients using Ethos emulator. Simulation CTs of the test patients were used as simulated online CBCT (sCBCT) for emulation. Quality assessments were conducted on synthetic CTs (sCT). Dosimetric comparisons were performed between on-couch plans, on-couch plans recomputed on the sCBCT and individually optimized plans for test patients. The median value of mean absolute difference between sCT and sCBCT was 74.7 HU (range 69.5-91.5 HU). The average CTV/PTV coverage by prescription dose was 100.0%/94.7%, and normal tissue constraints were met for the nine test patients in on-couch plans on sCT. Recalculating on-couch plans on the sCBCT showed about 0.7% reduction of PTV coverage and a 0.6% increasing of hotspot, and the dose difference of the OARs was negligible (<0.5 Gy). Hence, initial IMRT plans for new patients can be generated by adapting a reference patient's preplan with online contours, which had similar qualities to the conventional approach of individually optimized plan on the simulation CT. Further study is needed to identify selection criteria for patient anatomy most amenable to this workflow.

Stomach Motion and Deformation: Implications for Preoperative Gastric Cancer Radiation Therapy

PURPOSE

Selection and development of image guided strategies for preoperative gastric radiation therapy requires quantitative knowledge of the various sources of anatomic changes of the stomach. This study aims to investigate the magnitude of interfractional and intrafractional stomach motion and deformation using fiducial markers and 4-dimensional (4D) imaging.

METHODS AND MATERIALS

Fourteen patients who underwent preoperative gastric cancer radiation therapy received 2 to 6 fiducial markers distributed throughout the stomach (total of 54 markers) and additional imaging (ie, 1 planning 4D computed tomography [pCT], 20-25 pretreatment 4D cone beam [CB] CTs, 4-5 posttreatment 4D CBCTs). Marker coordinates on all end-exhale (EE) and end-inhale (EI) scans were obtained after a bony anatomy match. Interfractional marker displacements (ie, between EE pCT and all EE CBCTs) were evaluated for 5 anatomic regions (ie, cardia, small curvature, proximal and distal large curvature, and pylorus). Motion was defined as displacement of the center-of-mass of available markers (COMstomach), deformation as the average difference in marker-pair distances. Interfractional (ie, between EE pCT and all EE CBCTs), respiratory (between EE and EI pCT and CBCTs), and pre-post (pre- and posttreatment EE CBCTs) motion and deformation were quantified.

RESULTS

The interfractional marker displacement varied per anatomic region and direction, with systematic and random errors ranging from 1.6-8.8 mm and 2.2-8.2 mm, respectively. Respiratory motion varied per patient (median, 3-dimensional [3D] amplitude 5.2-20.0 mm) and day (interquartile range, 0.8-4.2 mm). Regarding COMstomach motion, respiratory motion was larger than interfractional motion (median, 10.9 vs 8.9 mm; P < .0001; Wilcoxon rank-sum), which was larger than pre-post motion (3.6 mm; P < .0001). Interfractional deformations (median, 5.8 mm) were significantly larger than pre-post deformations (2.6 mm; P < .0001), which were larger than respiratory deformation (1.8 mm; P < .0001).

CONCLUSIONS

The demonstrated sizable stomach motions and deformations during radiation therapy stress the need for generous nonuniform planning target volume margins for preoperative gastric cancer radiation therapy. These margins can be decreased by daily image guidance and adaptive radiation therapy.

Predicting cervical cancer target motion using a multivariate regression model to enable patient selection for adaptive external beam radiotherapy

Background and purpose

Interfraction motion during cervical cancer radiotherapy is substantial in some patients, minimal in others. Non-adaptive plans may miss the target and/or unnecessarily irradiate normal tissue. Adaptive radiotherapy leads to superior dose-volume metrics but is resource-intensive. The aim of this study was to predict target motion, enabling patient selection and efficient resource allocation.

Materials and methods

Forty cervical cancer patients had CT with full-bladder (CT-FB) and empty-bladder (CT-EB) at planning, and daily cone-beam CTs (CBCTs). The low-risk clinical target volume (CTVLR) was contoured. Mean coverage of the daily CTVLR by the CT-FB CTVLR was calculated for each patient. Eighty-three investigated variables included measures of organ geometry, patient, tumour and treatment characteristics. Models were trained on 29 patients (171 fractions). The Two-CT multivariate model could use all available data. The Single-CT multivariate model excluded data from the CT-EB. A univariate model was trained using the distance moved by the uterine fundus tip between CTs, the only method of patient selection found in published cervix plan-of-the-day studies. Models were tested on 11 patients (68 fractions). Accuracy in predicting mean coverage was reported as mean absolute error (MAE), mean squared error (MSE) and R2.

Results

The Two-CT model was based upon rectal volume, dice similarity coefficient between CT-FB and CT-EB CTVLR, and uterine thickness. The Single-CT model was based upon rectal volume, uterine thickness and tumour size. Both performed better than the univariate model in predicting mean coverage (MAE 7 %, 7 % and 8 %; MSE 82 %2, 65 %2, 110 %2; R2 0.2, 0.4, -0.1).

Conclusion

Uterocervix motion is complex and multifactorial. We present two multivariate models which predicted motion with reasonable accuracy using pre-treatment information, and outperformed the only published method.

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.

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.

Evaluation of bladder filling effects on the dose distribution during radiotherapy for cervical cancer based on daily CT images

PURPOSE

This study aimed to assess the effects of bladder filling during cervical cancer radiotherapy on target volume and organs at risk (OARs) dose based on daily computed tomography (daily-CT) images and provide bladder-volume-based dose prediction models.

METHODS

Nineteen patients (475 daily-CTs) comprised the study group, and five patients comprised the validation set (25 daily-CTs). Target volumes and OARs were delineated on daily-CT images and the treatment plan was recalculated accordingly. The deviation from the planning bladder volume (DVB), the correlation between DVB and clinical (CTV)/planning (PTV) target volume in terms of prescribed dose coverage, and the relationship of small bowel volume and bladder dose with the ratio of bladder volume (RVB) were analyzed.

RESULTS

In all cases, the prescribed dose coverage in the CTV was >95% when DVB was <200 cm3 , whereas that in the PTV was >95% when RVB was <160%. The ratio of bladder V45 Gy to the planning bladder V45 Gy (RBV45 ) exhibited a negative linear relationship with RVB (RBV45  = -0.18*RVB + 120.8; R2  = 0.80). Moreover, the ratio of small bowel volume to planning small bowel volume (RVS) exhibited a negative linear relationship with RVB (RVS = -1.06*RVB +217.59; R2  = 0.41). The validation set results showed that the linear model predicted well the effects of bladder volume changes on target volume coverage and bladder dose.

CONCLUSIONS

This study assessed dosimetry and volume effects of bladder filling on target and OARs based on daily-CT images. We established a quantitative relationship between these parameters, providing dose prediction models for cervical cancer radiotherapy.

Triggering daily online adaptive radiotherapy in the pelvis: Dosimetric effects and procedural implications of trigger parameter-value selection

BACKGROUND

Online adaptive radiotherapy (ART) can address dosimetric consequences of variations in anatomy by creating a new plan during treatment. However, ART is time- and labor-intensive and should be implemented in a resource-conscious way. Adaptive triggers composed of parameter-value pairs may direct the judicious use of online ART.

PURPOSE

This work analyzed our clinical experience using CBCT-based daily online ART to demonstrate how a conceptual framework based on adaptive triggers affects the dosimetric and procedural impact of ART.

METHODS

Sixteen patients across several pelvic sites were treated with CBCT-based daily online ART. Differences in standardized dose metrics were compared between the original plan, the original plan recalculated on the daily anatomy, and an adaptive plan. For each metric, trigger values were analyzed in terms of the proportion of treatments adapted and the distribution of metric values.

RESULTS

Target coverage metrics were compromised due to anatomic variation with the average change per treatment ranging from -0.90 to -0.05 Gy, -0.47 to -0.02 Gy, -0.31 to -0.01 Gy, and -12.45% to -2.65% for PTV D99%, PTV D95%, CTV D99%, and CTV V100%, respectively. These were improved using the adaptive plan (-0.03 to 0.01 Gy, -0.02 to 0.00 Gy, -0.03 to 0.00 Gy, and -4.70% to 0.00%, respectively). Increasingly strict triggers resulted in a non-linear increase in the proportion of treatments adapted and improved the distribution of metric values with diminishing returns. Some organ-at-risk (OAR) metrics were compromised by anatomic variation and improved using the adaptive plan, but changes in most OAR metrics were randomly distributed.

CONCLUSIONS

Daily online ART improved target coverage across multiple pelvic treatment sites and techniques. These effects were larger than those for OAR metrics, suggesting that maintaining target coverage was our primary benefit of CBCT-based daily online ART. Analyses like these can determine online ART triggers from a cost-benefit perspective.

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.

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.

Adaptive Radiation Therapy: A Review of CT-based Techniques

Adaptive radiation therapy is a feedback process by which imaging information acquired over the course of treatment, such as changes in patient anatomy, can be used to reoptimize the treatment plan, with the end goal of improving target coverage and reducing treatment toxicity. This review describes different types of adaptive radiation therapy and their clinical implementation with a focus on CT-guided online adaptive radiation therapy. Depending on local anatomic changes and clinical context, different anatomic sites and/or disease stages and presentations benefit from different adaptation strategies. Online adaptive radiation therapy, where images acquired in-room before each fraction are used to adjust the treatment plan while the patient remains on the treatment table, has emerged to address unpredictable anatomic changes between treatment fractions. Online treatment adaptation places unique pressures on the radiation therapy workflow, requiring high-quality daily imaging and rapid recontouring, replanning, plan review, and quality assurance. Generating a new plan with every fraction is resource intensive and time sensitive, emphasizing the need for workflow efficiency and clinical resource allocation. Cone-beam CT is widely used for image-guided radiation therapy, so implementing cone-beam CT-guided online adaptive radiation therapy can be easily integrated into the radiation therapy workflow and potentially allow for rapid imaging and replanning. The major challenge of this approach is the reduced image quality due to poor resolution, scatter, and artifacts. Keywords: Adaptive Radiation Therapy, Cone-Beam CT, Organs at Risk, Oncology © RSNA, 2023.

Forecasting patient-specific dosimetric benefit from daily online adaptive radiotherapy for cervical cancer

Objective. Adaptive Radiotherapy (ART) is an emerging technique for treating cancer patients which facilitates higher delivery accuracy and has the potential to reduce toxicity. However, ART is also resource-intensive, Requiring extra human and machine time compared to standard treatment methods. In this analysis, we sought to predict the subset of node-negative cervical cancer patients with the greatest benefit from ART, so resources might be properly allocated to the highest-yield patients.Approach. CT images, initial plan data, and on-treatment Cone-Beam CT (CBCT) images for 20 retrospective cervical cancer patients were used to simulate doses from daily non-adaptive and adaptive techniques. We evaluated the coefficient of determination (R2) between dose and volume metrics from initial treatment plans and the dosimetric benefits to theBowelV40Gy,BowelV45Gy,BladderDmean,andRectumDmeanfrom adaptive radiotherapy using reduced 3 mm or 5 mm CTV-to-PTV margins. The LASSO technique was used to identify the most predictive metrics forBowelV40Gy.The three highest performing metrics were used to build multivariate models with leave-one-out validation forBowelV40Gy.Main results. Patients with higher initial bowel doses were correlated with the largest decreases in BowelV40Gyfrom daily adaptation (linear best fit R2= 0.77 for a 3 mm PTV margin and R2= 0.8 for a 5 mm PTV margin). Other metrics had intermediate or no correlation. Selected covariates for the multivariate model were differences in the initialBowelV40GyandBladderDmeanusing standard versus reduced margins and the initial bladder volume. Leave-one-out validation had an R2of 0.66 between predicted and true adaptiveBowelV40Gybenefits for both margins.Significance. The resulting models could be used to prospectively triage cervical cancer patients on or off daily adaptation to optimally manage clinical resources. Additionally, this work presents a critical foundation for predicting benefits from daily adaptation that can be extended to other patient cohorts.

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.

Deformed dose restoration to account for tumor deformation and position changes for adaptive proton therapy

BACKGROUND

Online adaptation during intensity-modulated proton therapy (IMPT) can minimize the effect of inter-fractional anatomical changes, but remains challenging because of the complex workflow. One approach for fast and automated online IMPT adaptation is dose restoration, which restores the initial dose distribution on the updated anatomy. However, this method may fail in cases where tumor deformation or position changes occur.

PURPOSE

To develop a fast and robust IMPT online adaptation method named "deformed dose restoration (DDR)" that can adjust for inter-fractional tumor deformation and position changes.

METHODS

The DDR method comprises two steps: (1) calculation of the deformed dose distribution, and (2) restoration of the deformed dose distribution. First, the deformable image registration (DIR) between the initial clinical target volume (CTV) and the new CTV were performed to calculate the vector field. To ensure robustness for setup and range uncertainty and the ability to restore the deformed dose distribution, an expanded CTV-based registration to maintain the dose gradient outside the CTV was developed. The deformed dose distribution was obtained by applying the vector field to the initial dose distribution. Then, the voxel-by-voxel dose difference optimization was performed to calculate beam parameters that restore the deformed dose distribution on the updated anatomy. The optimization function was the sum of total dose differences and dose differences of each field to restore the initial dose overlap of each field. This method only requires target contouring, which eliminates the need for organs at risk (OARs) contouring. Six clinical cases wherein the tumor deformation and/or position changed on repeated CTs were selected. DDR feasibility was evaluated by comparing the results with those from three other strategies, namely, not adapted (continuing the initial plan), adapted by previous dose restoration, and fully optimized.

RESULTS

In all cases, continuing the initial plan was largely distorted on the repeated CTs and the dose-volume histogram (DVH) metrics for the target were reduced due to the tumor deformation or position changes. On the other hand, DDR improved DVH metrics for the target to the same level as the initial dose distribution. Dose increase was seen for some OARs because tumor growth had reduced the relative distance between CTVs and OARs. Robustness evaluation for setup and range uncertainty (3 mm/3.5%) showed that deviation in DVH-bandwidth for CTV D_95% from the initial plan was 0.4% ± 0.5% (Mean ± S.D.) for DDR. The calculation time was 8.1 ± 6.4 min.

CONCLUSIONS

An online adaptation algorithm was developed that improved the treatment quality for inter-fractional anatomical changes and retained robustness for intra-fractional setup and range uncertainty. The main advantage of this method is that it only requires target contouring alone and saves the time for OARs contouring. The fast and robust adaptation method for tumor deformation and position changes described here can reduce the need for offline adaptation and improve treatment efficiency.

Accuracy and Feasibility of Synthetic CT for Lung Adaptive Radiotherapy: A Phantom Study

OBJECTIVES

The respiratory variations will lead to inconsistency between the actual delivery dose and the planning dose. How the minor interfractional amplitude changes affect the geometry and dose delivery accuracy remains to be investigated in the context of lung adaptive radiotherapy.

METHODS

Planning 4-dimensional-computed tomography and kV-cone beam computed tomography were scanned based on the Computerized Imaging Reference Systems phantom, which was employed to simulate the minor interfractional amplitude variations. The corresponding synthetic computed tomography for a particular motion pattern can be generated from Velocity program. Then a clinically meaningful synthetic computed tomography was analyzed through the geometrical and dosimetric assessment.

RESULTS

The image quality of synthetic computed tomography was improved obviously compared with cone beam computed tomography. Mean absolute error was minimized when no significant interfractional motion occurs and Velocity can be qualified for dealing with the regular breathing motion patterns. The mean percent hounsfield unit difference of the synthetic hounsfield unit values per organ relative to the planning 4-dimensional-computed tomography image was 22.3%. Under the same conditions, the mean percent hounsfield unit difference of the cone beam computed tomography hounsfield unit values per organ, relative to the planning 4-dimensional-computed tomography image was 83.9%. Overall, the accuracy of hounsfield unit in synthetic computed tomography was improved obviously and the variability of the synthetic image correlates with the planning 4-dimensional-computed tomography image variability. Meanwhile, the dose-volume histograms between planning 4-dimensional-computed tomography and synthetic computed tomography almost coincided each other, which indicates that Velocity program can qualify lung adaptive radiotherapy well when there were no interfractional respiratory variations. However, for cases with obvious interfractional amplitude change, the volume covered at least by 100% of the prescription dose was only 59.6% for that synthetic image.

CONCLUSION

The synthetic computed tomography images generated from Velocity were close to the real images in anatomy and dosimetry, which can make clinical lung adaptive radiotherapy possible based on the actual patient anatomy during treatment.

Automatic segmentation for plan-of-the-day selection in CBCT-guided adaptive radiation therapy of cervical cancer

Objective.Plan-of-the-day (PoD) adaptive radiation therapy (ART) is based on a library of treatment plans, among which, at each treatment fraction, the PoD is selected using daily images. However, this strategy is limited by PoD selection uncertainties. This work aimed to propose and evaluate a workflow to automatically and quantitatively identify the PoD for cervix cancer ART based on daily CBCT images.Approach.The quantification was based on the segmentation of the main structures of interest in the CBCT images (clinical target volume [CTV], rectum, bladder, and bowel bag) using a deep learning model. Then, the PoD was selected from the treatment plan library according to the geometrical coverage of the CTV. For the evaluation, the resulting PoD was compared to the one obtained considering reference CBCT delineations.Main results.In experiments on a database of 23 patients with 272 CBCT images, the proposed method obtained an agreement between the reference PoD and the automatically identified PoD for 91.5% of treatment fractions (99.6% when considering a 5% margin on CTV coverage).Significance.The proposed automatic workflow automatically selected PoD for ART using deep-learning methods. The results showed the ability of the proposed process to identify the optimal PoD in a treatment plan library.

On the feasibility of improved target coverage without compromising organs at risk using online adaptive stereotactic partial breast irradiation (A-SPBI)

PURPOSE

Describe an early-adopting institution's experience with online adaptive radiation for stereotactic partial breast irradiation.

METHODS AND MATERIALS

Retrospective review of 22 women treated between May 2021 and March 2022 with adaptive stereotactic partial breast irradiation. A total of 106 of 110 fractions were evaluated for dosimetric changes in target coverage and organ-at-risk (OAR) dose. Patient set up with stereotactic wooden frame and adapted per fraction. Treatment and planning times were collected prospectively by radiation therapists.

RESULTS

Scheduled PTV_30 Gy was <95% in 72.1% and <90% in 38.5% of fractions, and both PTV and CTV coverage were improved significantly after adaption, and 83.7% of fractions were delivered as adapted per physician choice. There was no difference in OAR coverage. Average adaptive treatment planning took 15 min and average time-on-couch was 34.4 min.

CONCLUSIONS

Adaptive stereotactic breast irradiation resulted in improved target coverage with equivalent dosing to OARs in an efficient and tolerated treatment time. Improved target coverage allowed for decreased PTV margins compared to prior trial protocols that may improve acute and late toxicities.

Clinical commissioning of an adaptive radiotherapy platform: Results and recommendations

Online adaptive radiotherapy platforms present a unique challenge for commissioning as guidance is lacking and specialized adaptive equipment, such as deformable phantoms, are rare. We designed a novel adaptive commissioning process consisting of end-to-end tests using standard clinical resources. These tests were designed to simulate anatomical changes regularly observed at patient treatments. The test results will inform users of the magnitude of uncertainty from on-treatment changes during the adaptive workflow and the limitations of their systems. We implemented these tests for the cone-beam computed tomography (CT)-based Varian Ethos online adaptive platform. Many adaptive platforms perform online dose calculation on a synthetic CT (synCT). To assess the impact of the synCT generation and online dose calculation on dosimetric accuracy, we conducted end-to-end tests using commonly available equipment: a CIRS IMRT Thorax phantom, PinPoint ionization chamber, Gafchromic film, and bolus. Four clinical scenarios were evaluated: weight gain and weight loss were simulated by adding and removing bolus, internal target shifts were simulated by editing the CTV during the adaptive workflow to displace it, and changes in gas were simulated by removing and reinserting rods in varying phantom locations. The effect of overriding gas pockets during planning was also assessed. All point dose measurements agreed within 2.7% of the calculated dose, with one exception: a scenario simulating gas present in the planning CT, not overridden during planning, and dissipating at treatment. Relative film measurements passed gamma analysis (3%/3 mm criteria) for all scenarios. Our process validated the Ethos dose calculation for online adapted treatment plans. Based on our results, we made several recommendations for our clinical adaptive workflow. This commissioning process used commonly available equipment and, therefore, can be applied in other clinics for their respective online adaptive platforms.

Potential utility of cone-beam CT-guided adaptive radiotherapy under end-exhalation breath-hold conditions for pancreatic cancer

PURPOSE

The purpose of this study was to demonstrate the potential utility of cone-beam computed tomography (CBCT)-guided online adaptive radiotherapy (ART) under end-exhalation breath-hold (EE-BH) conditions for pancreatic cancer (PC).

METHODS

Eleven PC patients who underwent 15-fraction volumetric-modulated arc therapy under EE-BH conditions were included. Planning CT images and daily 165 CBCT images were imported into a dedicated treatment planning system. The prescription dose was set to 48 Gy in 15 fractions. The reference plan was automatically generated along with predefined clinical goals. After segmentation was completed on CBCT images, two different plans were generated: One was an adapted (ADP) plan in which re-optimization was performed on the anatomy of the day, and the other was a scheduled (SCH) plan, which was the same as the reference plan. The dose distributions calculated using the synthetic CT created from both planning CT and CBCT were compared between the two plans. Independent calculation-based quality assurance was also performed for the ADP plans, with a gamma passing rate of 3%/3 mm.

RESULTS

All clinical goals were successfully achieved during the reference plan generation. Of the 165 sessions, gross tumor volume D_98% and clinical target volume D_98% were higher in 100 (60.1%) and 122 (74.0%) ADP fractions. In each fraction, the V_3 Gy  < 1 cm³ of the stomach and duodenum was violated in 47 (28.5%) and 48 (29.1%), respectively, of the SCH fractions, whereas no violations were observed in the ADP fractions. There were statistically significant differences in the dose-volume indices between the SCH and ADP fractions (p < 0.05). The gamma passing rates were above 95% in all ADP fractions.

CONCLUSIONS

The CBCT-guided online ART under EE-BH conditions successfully reduced the dose to the stomach and duodenum while maintaining target coverage.

Dosimetric and feasibility evaluation of a CBCT-based daily adaptive radiotherapy protocol for locally advanced cervical cancer

PURPOSE

Evaluate a cone-beam computed tomography (CBCT)-based daily adaptive platform in cervical cancer for multiple endpoints: (1) physics contouring accuracy of daily CTVs, (2) CTV coverage with adapted plans and reduced PTV margins versus non-adapted plans with standard-of-care (SOC) margins, (3) dosimetric improvements to CTV and organs-at-risk (OARs), and (4) on-couch time.

METHODS AND MATERIALS

Using a Varian Ethos™ emulator and KV-CBCT scans, we simulated the doses 15 retrospective cervical cancer patients would have received with/without online adaptation for five fractions. We compared contours and doses from SOC plans (5-15 mm CTV-to-PTV margins) to adapted plans (3 mm margins). Auto-segmented CTVs and OARs were reviewed and edited by trained physicists. Physics-edited targets were evaluated by an oncologist. Time spent reviewing and editing auto-segmented structures was recorded. Metrics from the CTV (D99%), bowel (V45Gy, V40Gy), bladder (D50%), and rectum (D50%) were compared.

RESULTS

The physician approved the physics-edited CTVs for 55/75 fractions; 16/75 required reductions, and 4/75 required CTV expansions. CTVs were encapsulated by unadapted, SOC PTVs for 56/75 (72%) fractions-representative of current clinical practice. CTVs were completely covered by adapted 3 mm PTVs for 71/75 (94.6%) fractions. CTV D99% values for adapted plans were comparable to non-adapted SOC plans (average difference of -0.9%), while all OAR metrics improved with adaptation. Specifically, bowel V45Gy and V40Gy decreased on average by 87.6 and 109.4 cc, while bladder and rectum D50% decreased by 37.7% and 35.8%, respectively. The time required for contouring and calculating an adaptive plan for 65/75 fractions was less than 20 min (range: 1-29 min).

CONCLUSIONS

Improved dose metrics with daily adaption could translate to reduced toxicity while maintaining tumor control. Training physicists to perform contouring edits could minimize the time physicians are required at adaptive sessions improving clinical efficiency. All emulated adaptive sessions were completed within 30 min however extra time will be required for patient setup, image acquisition, and treatment delivery.

Dosimetric Impact of Inter-Fraction Variability in the Treatment of Breast Cancer: Towards New Criteria to Evaluate the Appropriateness of Online Adaptive Radiotherapy

Purpose

As a discipline in its infancy, online adaptive RT (ART) needs new ontologies and ad hoc criteria to evaluate the appropriateness of its use in clinical practice. In this experience, we propose a predictive model able to quantify the dosimetric impact due to daily inter-fraction variability in a standard RT breast treatment, to identify in advance the treatment fractions where patients might benefit from an online ART approach.

Methods

The study was focused on right breast cancer patients treated using standard adjuvant RT on an artificial intelligence (AI)-based linear accelerator. Patients were treated with daily CBCT images and without online adaptation, prescribing 40.05 Gy in 15 fractions, with four IMRT tangential beams. ESTRO guidelines were followed for the delineation on planning CT (pCT) of organs at risk and targets. For each patient, all the CBCT images were rigidly aligned to pCT: CTV and PTV were manually re-contoured and the original treatment plan was recalculated. Various radiological parameters were measured on CBCT images, to quantify inter-fraction variability present in each RT fraction after the couch shifts compensation. The variation of these parameters was correlated with the variation of V95% of PTV (ΔV95%) using the Wilcoxon Mann–Whitney test. Fractions where ΔV95% > 2% were considered as adverse events. A logistic regression model was calculated considering the most significant parameter, and its performance was quantified with a receiver operating characteristic (ROC) curve.

Results

A total of 75 fractions on 5 patients were analyzed. The body variation between daily CBCT and pCT along the beam axis with the highest MU was identified as the best predictor (p = 0.002). The predictive model showed an area under ROC curve of 0.86 (95% CI, 0.82–0.99) with a sensitivity of 85.7% and a specificity of 83.8% at the best threshold, which was equal to 3 mm.

Conclusion

A novel strategy to identify treatment fractions that may benefit online ART was proposed. After image alignment, the measure of body difference between daily CBCT and pCT can be considered as an indirect estimator of V95% PTV variation: a difference larger than 3 mm will result in a V95% decrease larger than 2%. A larger number of observations is needed to confirm the results of this hypothesis-generating study.

Initial analysis of the dosimetric benefit and clinical resource cost of CBCT-based online adaptive radiotherapy for patients with cancers of the cervix or rectum

Purpose

This provides a benchmark of dosimetric benefit and clinical cost of cone‐beam CT‐based online adaptive radiotherapy (ART) technology for cervical and rectal cancer patients.

Methods

An emulator of a CBCT‐based online ART system was used to simulate more than 300 treatments for 13 cervical and 15 rectal cancer patients. CBCT images were used to generate adaptive replans. To measure clinical resource cost, the six phases of the workflow were timed. To evaluate the dosimetric benefit, changes in dosimetric values were assessed. These included minimum dose (Dmin) and volume receiving 95% of prescription (V95%) for the planning target volume (PTV) and the clinical target volume (CTV), and maximum 2 cc's (D2cc) of the bladder, bowel, rectum, and sigmoid colon.

Results

The average duration of the workflow was 24.4 and 9.2 min for cervical and rectal cancer patients, respectively. A large proportion of time was dedicated to editing target contours (13.1 and 2.7 min, respectively). For cervical cancer patients, the replan changed the Dmin to the PTVs and CTVs for each fraction 0.25 and 0.25 Gy, respectively. The replan changed the V95% by 9.2 and 7.9%. The D2cc to the bladder, bowel, rectum, and sigmoid colon for each fraction changed −0.02, −0.08, −0.07, and −0.04 Gy, respectively. For rectal cancer patients, the replan changed the Dmin to the PTVs and CTVs for each fraction of 0.20 and 0.24 Gy, respectively. The replan changed the V95% by 4.1 and 1.5%. The D2cc to the bladder and bowel for each fraction changed 0.02 and −0.02 Gy, respectively.

Conclusions

Dosimetric benefits can be achieved with CBCT‐based online ART that is amenable to conventional appointment slots. The clinical significance of these benefits remains to be determined. Managing contours was the primary factor affecting the total duration and is imperative for safe and effective adaptive radiotherapy.