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

Enhancing Delivery Efficiency on the MR-Linac: A Comprehensive Evaluation of Prostate SBRT using VMAT

PURPOSE

Long treatment sessions are a limitation within MRIgART. This work aims for significantly enhancing the delivery efficiency on the MR-linac by introducing dedicated optimization and delivery techniques for VMAT. VMAT plan and delivery quality during MRIgART is compared to step-and-shoot IMRT for prostate SBRT.

METHODS AND MATERIALS

Ten prostate patients previously treated on a 1.5T MR-linac were retrospectively replanned to 36.25 Gy in five fractions using step-and-shoot IMRT and the clinical Hyperion optimizer within Monaco (Hyp-IMRT), the same optimizer with a VMAT technique (Hyp-VMAT), and a research-based optimizer with VMAT (OFL+PGD-VMAT). The plans were then adapted onto each daily MRI dataset using two different optimization strategies to evaluate the ATP workflow: "optimize weights" (IMRT-Weights and VMAT-Weights) and "optimize shapes" (IMRT-Shapes and VMAT-Shapes). Treatment efficiency was evaluated by measuring optimization time, delivery time, and total time (optimization + delivery). Plan quality was assessed by evaluating OAR sparing. Ten patient plans were measured using a modified linac control system to assess delivery accuracy via a gamma analysis (2%/2mm). Delivery efficiency was calculated as average dose rate divided by maximum dose rate.

RESULTS

For Hyp-VMAT and OFL+PGD-VMAT the total time was reduced by 124 ± 140 seconds (p = .020) and 459 ± 110 seconds (p < 0.001), respectively as compared to the clinical Hyp-IMRT group. Speed enhancements were also measured for ATP with reductions in total time of 404 ± 55 (p<0.001) for VMAT-Weights as compared to the clinical IMRT-Shapes group. Bladder and rectum DVH points were within 1.3 % or 0.8 cc for each group. All VMAT plans had gamma passing rates greater than 96 %. The delivery efficiency of VMAT plans was 89.7 ± 2.7 % compared to 50.0 ± 2.2 % for clinical IMRT.

CONCLUSIONS

Incorporating VMAT into MRIgART will significantly reduce treatment session times while maintaining equivalent plan quality.

Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report

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

Custom-Trained Deep Learning-Based Auto-Segmentation for Male Pelvic Iterative CBCT on C-Arm Linear Accelerators

PURPOSE

The purpose of this investigation was to evaluate the clinical applicability of a commercial artificial intelligence-driven deep learning auto-segmentation (DLAS) tool on enhanced iterative cone beam computed tomography (iCBCT) acquisitions for intact prostate and prostate bed treatments.

METHODS AND MATERIALS

DLAS models were trained using 116 iCBCT data sets with manually delineated organs at risk (bladder, femoral heads, and rectum) and target volumes (intact prostate and prostate bed) adhering to institution-specific contouring guidelines. An additional 25 intact prostate and prostate bed iCBCT data sets were used for model testing. Segmentation accuracy relative to a reference structure set was quantified using various geometric comparison metrics and qualitatively evaluated by trained physicists and physicians. These results were compared with those obtained for an additional DLAS-based model trained on planning computed tomography (pCT) data sets and for a deformable image registration (DIR)-based automatic contour propagation method.

RESULTS

In most instances, statistically significant differences in the Dice similarity coefficient (DSC), 95% directed Hausdorff distance, and mean surface distance metrics were observed between the models, as the iCBCT-trained DLAS model outperformed the pCT-trained DLAS model and DIR-based method for all organs at risk and the intact prostate target volume. Mean DSC values for the proposed method were ≥0.90 for these volumes of interest. The iCBCT-trained DLAS model demonstrated a relatively suboptimal performance for the prostate bed segmentation, as the mean DSC value was <0.75 for this target contour. Overall, 90% of bladder, 93% of femoral head, 67% of rectum, and 92% of intact prostate contours generated by the proposed method were deemed clinically acceptable based on qualitative scoring, and approximately 63% of prostate bed contours required moderate or major manual editing to adhere to institutional contouring guidelines.

CONCLUSIONS

The proposed method presents the potential for improved segmentation accuracy and efficiency compared with the DIR-based automatic contour propagation method as commonly applied in CBCT-based dose evaluation and calculation studies.

An operator-independent quality assurance system for automatically generated structure sets

Objective. This study describes geometry-based and intensity-based tools for quality assurance (QA) of automatically generated structures for online adaptive radiotherapy, and designs an operator-independent traffic light system that identifies erroneous structure sets.Approach.A cohort of eight head and neck (HN) patients with daily CBCTs was selected for test development. Radiotherapy contours were propagated from planning computed tomography (CT) to daily cone beam CT (CBCT) using deformable image registration. These propagated structures were visually verified for acceptability. For each CBCT, several error scenarios were used to generate what were judged unacceptable structures. Ten additional HN patients with daily CBCTs and different error scenarios were selected for validation. A suite of tests based on image intensity, intensity gradient, and structure geometry was developed using acceptable and unacceptable HN planning structures. Combinations of one test applied to one structure, referred to as structure-test combinations, were selected for inclusion in the QA system based on their discriminatory power. A traffic light system was used to aggregate the structure-test combinations, and the system was evaluated on all fractions of the ten validation HN patients.Results.The QA system distinguished between acceptable and unacceptable fractions with high accuracy, labeling 294/324 acceptable fractions as green or yellow and 19/20 unacceptable fractions as yellow or red.Significance.This study demonstrates a system to supplement manual review of radiotherapy planning structures. Automated QA is performed by aggregating results from multiple intensity- and geometry-based tests.

Artificial intelligence for treatment delivery: image-guided radiotherapy

Radiation therapy (RT) is a highly digitized field relying heavily on computational methods and, as such, has a high affinity for the automation potential afforded by modern artificial intelligence (AI). This is particularly relevant where imaging is concerned and is especially so during image-guided RT (IGRT). With the advent of online adaptive RT (ART) workflows at magnetic resonance (MR) linear accelerators (linacs) and at cone-beam computed tomography (CBCT) linacs, the need for automation is further increased. AI as applied to modern IGRT is thus one area of RT where we can expect important developments in the near future. In this review article, after outlining modern IGRT and online ART workflows, we cover the role of AI in CBCT and MRI correction for dose calculation, auto-segmentation on IGRT imaging, motion management, and response assessment based on in-room imaging.

Adaptive-Driven CT Simulation-Free Soft Tissue Stereotactic Body Radiation Therapy: A Single-Patient Case Report

Online adaptive radiotherapy (ART) enables accommodation for variations in patient setup and anatomical changes, allowing for fractional replanning for target coverage, organ at risk (OAR) sparing, and application of CT simulation-free (SF) workflows. SF workflows bypass the conventional simulation CT scan at the potential trade-off in dosimetric uncertainty. ART can alleviate many of these uncertainties, and this work extends previous experience with an Ethos adaptive cone-beam computed tomography (CBCT)-based SF process to treating a unique bony and soft tissue case with stereotactic body radiation therapy (SBRT). The patient is an 83-year-old male with metastatic prostate cancer, presenting with metastases near the right posterior ischium and a right perirectal lymph node. The patient's history includes multiple radiation treatments and androgen deprivation therapy (ADT). Rising prostate-specific antigen(PSA) levels and new metastases identified via positron emission tomography (PET)/CT prostate-specific membrane antigen (PSMA) led to SBRT re-irradiation, considered safe due to the time lapse since previous treatments. Using a HyperSight-equipped Ethos ART system, an SF SBRT workflow utilized the patient's recent PET/CT images for target and OAR delineation. A nine-field adaptive intensity-modulated radiotherapy(IMRT) treatment plan was generated to deliver 3600 Gy in three fractions with a primary focus to limit the dose to proximal OARs and the previously treated region. At the adaptive treatment, the patient is positioned based on anatomical marks, and axial images from HyperSight CBCT are used to contour the OARs and targets. These modified contours accommodate daily variations and are used to recalculate the reference plan and generate a new adapted plan. The adapted plan is selected if coverage improvement and OAR sparing are achieved. For each newly adapted plan, Ethos-generated synthetic CT is reviewed prior to treatment to verify no errors occurred in the deformable propagation between the reference image and the fractional CBCT. For this patient, the adapted plan was selected for all fractions due to improved target coverage, particularly of the soft tissue target, and OAR sparing. The patient tolerated the treatment well and demonstrated a good response on three-month follow-up PSMA PET/CT imaging. This case highlights the efficacy of CBCT-driven SF ART in complex re-irradiation scenario. Future enhancements in the Ethos treatment planning system, including direct dose computation on HyperSight CBCT images, will streamline SF workflows and expand their applicability. Careful consideration of potential on-unit OAR changes and target motion remains crucial for successful SF ART applications.

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.

On Route to Chimeric Antigen Receptor T-cell (CAR T) Therapy, Less Is More: Adaptive Bridging Radiotherapy in Large B-cell Lymphoma

CD19-targeted chimeric antigen receptor (CAR) T-cell therapy has appreciably advanced treatment for relapsed or refractory large B-cell lymphoma (LBCL). During the critical interim of four to six weeks, until CAR T-cells are ready, radiation therapy (RT) can be used to control the disease. We present the case of a 64-year-old female with relapsed/refractory diffuse large B-cell lymphoma (DLBCL) who received adaptive RT for bilateral adrenal masses as a bridging strategy before undergoing CAR T-cell therapy and enrolled in an adaptive RT clinical trial. A plan was developed to deliver up to five once-weekly fractions (5 Gy per fraction) of CT-based online adaptive RT (Varian Ethos with HyperSight imaging, Varian Medical Systems, Palo Alto, CA). The patient experienced rapid symptomatic relief, with no RT-related toxicities. The patient received RT at only half of the sessions (two out of four sessions) due to excellent tumor shrinkage on cone-beam CT (CBCT). As such, the patient was treated at a lower total dose (10 Gy) than she otherwise would have received with standard RT. Post-RT PET/CT showed significant disease regression, compatible with partial response, prior to CAR T-cell infusion. This case shows the successful application of adaptive RT as bridging therapy prior to CAR T-cell therapy, and we expect the results of this adaptive RT trial to guide the future of adaptive RT in relapsed/refractory B-cell lymphomas.

Harnessing the Power of Radiotherapy for Lung Cancer: A Narrative Review of the Evolving Role of Magnetic Resonance Imaging Guidance

Compared with computed tomography (CT), magnetic resonance imaging (MRI) traditionally plays a very limited role in lung cancer management, although there is plenty of room for improvement in the current CT-based workflow, for example, in structures such as the brachial plexus and chest wall invasion, which are difficult to visualize with CT alone. Furthermore, in the treatment of high-risk tumors such as ultracentral lung cancer, treatment-associated toxicity currently still outweighs its benefits. The advent of MR-Linac, an MRI-guided radiotherapy (RT) that combines MRI with a linear accelerator, could potentially address these limitations. Compared with CT-based technologies, MR-Linac could offer superior soft tissue visualization, daily adaptive capability, real-time target tracking, and an early assessment of treatment response. Clinically, it could be especially advantageous in the treatment of central/ultracentral lung cancer, early-stage lung cancer, and locally advanced lung cancer. Increasing demands for stereotactic body radiotherapy (SBRT) for lung cancer have led to MR-Linac adoption in some cancer centers. In this review, a broad overview of the latest research on imaging-guided radiotherapy (IGRT) with MR-Linac for lung cancer management is provided, and development pertaining to artificial intelligence is also highlighted. New avenues of research are also discussed.

Experience with patient-specific quality assurance of dosimetrist-led online adaptive prostate SBRT

INTRODUCTION

The aim of this study was to assess the results of the local pre-treatment verifications of online adaptive prostate SBRT plans performed by dosimetrists METHODS AND MATERIALS: Prostate SBRT treatments are planned in our department using an online adaptive method developed and validated by our group. The adaptive plans were computed on the daily CBCT scan using the Acuros XB v. 16.1 algorithm of the Varian Eclipse treatment planning system. Adaptive plans consisted of a single VMAT with 6 MV flattening-filter-free (FFF) energy performed on a Varian TrueBeam linac. Pre-treatment verification of the adaptive "plan-of-the-day" (POD) created in each treatment session was performed using the Mobius 3D v. 3.1 secondary dose calculation program (M3D). Commissioning of M3D included the tuning of the dosimetric leaf gap correction (DLGc) parameter. Generic and specific DLGc values were then derived using a set of plans for typical sites (prostate, head and neck, brain, lung and bone palliative) and another set were determined for specific online SBRT PODs (gDLGc and sDLGc, respectively). The first 50 prostate patients treated with the PACE-B schedule (5 × 7.25 Gy) were included, i.e., 250 adaptive SBRT PODs were collected in this study. For each online adaptive POD, a global 3D gamma comparison between the Eclipse 3D dose and the M3D dose in the patient CBCT was performed. Gamma passing rates (GPRs) for the whole external patient contour (Body) and the PTV were recorded, using the 5 % global /3 mm criteria. The target mean dose and target coverage differences between the Eclipse and M3D doses were also analyzed (ΔDmean and ΔD90 %, respectively). The accuracy of M3D was assessed against PRIMO Monte Carlo software. Twenty-five online prostate SBRT PODs were randomly selected from the set of 250 adaptive plans and simulated with PRIMO.

RESULTS

Values of -1 mm and -0.14 mm were found as optimal gDLGc and sDLGc, respectively. Over the 250 online adaptive PODs, excellent GPR values ∼ 100 % were obtained for the Body and PTV structures, regardless the type of DLGc used. The use of the sDLGc instead of the gDLGc provided better results for ΔDmean (0.1 % ± 0.5% vs. -1.9 ± 0.7 %) and ΔD90 % (-1.0 % ± 0.5 %. vs. -3.5 % ± 0.8 %). This issue was also observed when M3D calculations were compared to PRIMO simulations.

CONCLUSIONS

M3D can be effectively used for independent pre-treatment verifications of online adaptive prostate SBRT plans. The use of a specific DLGc value is advised for this SBRT online adaptive technique.

Clinical practicality and patient performance for surface-guided automated VMAT gating for DIBH breast cancer radiotherapy

BACKGROUND AND PURPOSE

To evaluate the performance of automated surface-guided gating for left-sided breast cancer with DIBH and VMAT.

MATERIALS AND METHODS

Patients treated in the first year after introduction of DIBH with VMAT were retrospectively considered for analysis. With automated surface-guided gating the beam automatically switches on/off, if the surface region of interest moved in/out the gating tolerance (±3 mm, ±3°). Patients were coached to hold their breath as long as comfortably possible. Depending on the patient's preference, patients received audio instructions during treatment delivery. Real-time positional variations of the breast/chest wall surface with respect to the reference surface were collected, for all three orthogonal directions. The durations and number of DIBHs needed to complete dose delivery, and DIBH position variations were determined. To evaluate an optimal gating window threshold, smaller tolerances of ±2.5 mm, ±2.0 mm, and ±1.5 mm were simulated.

RESULTS

525 fractions from 33 patients showed that median DIBH duration was 51 s (range: 30-121 s), and median 4 DIBHs per fraction were needed to complete VMAT dose delivery. Median intra-DIBH stability and intrafractional DIBH reproducibility approximated 1.0 mm in each direction. No large differences were found between patients who preferred to perform the DIBH procedure with (n = 21) and without audio-coaching (n = 12). Simulations demonstrated that gating window tolerances could be reduced from ±3.0 mm to ±2.0 mm, without affecting beam-on status.

CONCLUSION

Independent of the use of audio-coaching, this study demonstrates that automated surface-guided gating with DIBH and VMAT proved highly efficient. Patients' DIBH performance far exceeded our expectations compared to earlier experiences and literature. Furthermore, gating window tolerances could be reduced.

Evaluation of Motion Artifact Correction Technique for Cone-Beam Computed Tomography Image Considering Blood Vessel Geometry

Background: In this study, we present a quantitative method to evaluate the motion artifact correction (MAC) technique through the morphological analysis of blood vessels in the images before and after MAC. Methods: Cone-beam computed tomography (CBCT) scans of 37 patients who underwent transcatheter chemoembolization were obtained, and images were reconstructed with and without the MAC technique. First, two interventional radiologists selected the blood vessels corrected by MAC. We devised a motion-corrected index (MCI) metric that analyzed the morphology of blood vessels in 3D space using information on the centerline of blood vessels, and the blood vessels selected by the interventional radiologists were quantitatively evaluated using MCI. In addition, these blood vessels were qualitatively evaluated by two interventional radiologists. To validate the effectiveness of the devised MCI, we compared the MCI values in a blood vessel corrected by MAC and one non-corrected by MAC. Results: The visual evaluation revealed that motion correction was found in the images of 23 of 37 patients (62.2%), and a performance evaluation of MAC was performed with 54 blood vessels in 23 patients. The visual grading analysis score was 1.56 ± 0.57 (radiologist 1) and 1.56 ± 0.63 (radiologist 2), and the proposed MCI was 0.67 ± 0.11, indicating that the vascular morphology was well corrected by the MAC. Conclusions: We verified that our proposed method is useful for evaluating the MAC technique of CBCT, and the MAC technique can correct the blood vessels distorted by the patient's movement and respiration.

The accuracy of artificial intelligence deformed nodal structures in cervical online cone-beam-based adaptive radiotherapy

Background and Purpose

Online cone-beam-based adaptive radiotherapy (ART) adjusts for anatomical changes during external beam radiotherapy. However, limited cone-beam image quality complicates nodal contouring. Despite this challenge, artificial-intelligence guided deformation (AID) can auto-generate nodal contours. Our study investigated the optimal use of such contours in cervical online cone-beam-based ART.

Materials and Methods

From 136 adaptive fractions across 21 cervical cancer patients with nodal disease, we extracted 649 clinically-delivered and AID clinical target volume (CTV) lymph node boost structures. We assessed geometric alignment between AID and clinical CTVs via dice similarity coefficient, and 95% Hausdorff distance, and geometric coverage of clinical CTVs by AID planning target volumes by false positive dice. Coverage of clinical CTVs by AID contour-based plans was evaluated using D100, D95, V100%, and V95%.

Results

Between AID and clinical CTVs, the median dice similarity coefficient was 0.66 and the median 95 % Hausdorff distance was 4.0 mm. The median false positive dice of clinical CTV coverage by AID planning target volumes was 0. The median D100 was 1.00, the median D95 was 1.01, the median V100% was 1.00, and the median V95% was 1.00. Increased nodal volume, fraction number, and daily adaptation were associated with reduced clinical CTV coverage by AID-based plans.

Conclusion

In one of the first reports on pelvic nodal ART, AID-based plans could adequately cover nodal targets. However, physician review is required due to performance variation. Greater attention is needed for larger, daily-adapted nodes further into treatment.

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.