Bladder tumour focused adaptive radiotherapy: Clinical outcomes of a phase I dose escalation study.

PURPOSE/OBJECTIVES: We determine the maximum tolerated tumour focused dose (MTD) for the radical treatment of muscle invasive bladder cancer (MIBC) enabled by image guided adaptive radiotherapy (IGART) and long-term clinical outcomes. MATERIALS/METHODS: Fifty-nine patients with T2-T4aN0M0 unifocal urothelial MIBC suitable for daily radical radiotherapy were recruited prospectively to an ethics approved protocol (XX). The uninvolved bladder (PTVbladder) was planned to 52Gy in 32 fractions (f). The bladder tumour (PTVtumour) was planned to an assigned dose level of 68, 70, 72, or 74Gy. If organ at risk (OAR) dose constraints were violated, then PTVtumour was planned to 64Gy. Dose level allocation was determined by concurrent toxicity assessment of all previous patients recruited. Acute toxicity was evaluated using CTCAE v3.0; late toxicity was evaluated using RTOG criteria. The MTD was predefined as the highest dose level with estimated probability of ≤ 15% ≥G3 late toxicity and observed rate <50% acute G3 and <10% acute G4 toxicity. RESULTS: Twenty-six patients were assigned to 68Gy, of whom 6 were planned to 64Gy; 29 patients were assigned to 70Gy of whom 1 was planned to 68Gy, 2 patients were assigned and planned to 72Gy; no patients were assigned to 74Gy. Three patients did not complete treatment as planned, of whom only 1 patient stopped treatment because dose limiting toxicity occurred. The MTD was 70Gy. Acute genitourinary (GU) and gastrointestinal (GI) G3 acute toxicity was seen in 19% and 7% patients respectively. No grade 4 GU or GI toxicity was seen. Late toxicity (any) G3 and G4 was seen in 14% and 2% patients respectively. The 5-year overall survival was 58% (95% CI 44-71%). The bladder preservation rate was 89% (95% CI, 88 to 96%) with 6 patients not retaining native bladder function. CONCLUSION: Bladder tumour focused dose escalation to 70Gy using IGART is feasible with acceptable toxicity. This dose level has been evaluated in a phase II randomised control trial (XXXXX).

Adaptive assessment based on fractional CBCT images for cervical cancer.

PURPOSE: Anatomical and other changes during radiotherapy will cause inaccuracy of dose distributions, therefore the expectation for online adaptive radiation therapy (ART) is high in effectively reducing uncertainties due to intra-variation. However, ART requires extensive time and effort. This study investigated an adaptive assessment workflow based on fractional cone-beam computed tomography (CBCT) images. METHODS: Image registration, synthetic CT (sCT) generation, auto-segmentation, and dose calculation were implemented and integrated into ArcherQA Adaptive Check. The rigid registration was based on ITK open source. The deformable image registration (DIR) method was based on a 3D multistage registration network, and the sCT generation method was performed based on a 2D cycle-consistent adversarial network (CycleGAN). The auto-segmentation of organs at risk (OARs) on sCT images was finished by a deep learning-based auto-segmentation software, DeepViewer. The contours of targets were obtained by the structure-guided registration. Finally, the dose calculation was based on a GPU-based Monte Carlo (MC) dose code, ArcherQA. RESULTS: The dice similarity coefficient (DSCs) were over 0.86 for target volumes and over 0.79 for OARs. The gamma pass rate of ArcherQA versus Eclipse treatment planning system was more than 99% at the 2%/2 mm criterion with a low-dose threshold of 10%. The time for the whole process was less than 3 min. The dosimetric results of ArcherQA Adaptive Check were consistent with the Ethos scheduled plan, which can effectively identify the fractions that need the implementation of the Ethos adaptive plan. CONCLUSION: This study integrated AI-based technologies and GPU-based MC technology to evaluate the dose distributions using fractional CBCT images, demonstrating remarkably high efficiency and precision to support future ART processes.

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

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

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

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.

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.

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

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

Stability analysis of patient-specific 4DCT- and 4DCBCT-based correspondence models.

BACKGROUND: Surrogate-based motion compensation in stereotactic body radiation therapy (SBRT) strongly relies on a constant relationship between an external breathing signal and the internal tumor motion over the course of treatment, that is, a stable patient-specific correspondence model. PURPOSE: This study aims to develop methods for analyzing the stability of correspondence models by integrating planning 4DCT and pretreatment 4D cone-beam computed tomography (4DCBCT) data and assessing the relation to patient-specific clinical parameters. METHODS: For correspondence modeling, a regression-based approach is applied, correlating patient-specific internal motion (vector fields computed by deformable image registration) and external breathing signals (recorded by Varian's RPM and RGSC system). To analyze correspondence model stability, two complementary methods are proposed. (1) Target volume-based analysis: 4DCBCT-based correspondence models predict clinical target volumes (GTV and internal target volume [ITV]) within the planning 4DCT, which are evaluated by overlap and distance measures (Dice similarity coefficient [DSC]/average symmetric surface distance [ASSD]). (2) System matrix-based analysis: 4DCBCT-based regression models are compared to 4DCT-based models using mean squared difference (MSD) and principal component analysis of the system matrices. Stability analysis results are correlated with clinical parameters. Both methods are applied to a dataset of 214 pretreatment 4DCBCT scans (Varian TrueBeam) from a cohort of 46 lung tumor patients treated with ITV-based SBRT (planning 4DCTs acquired with Siemens AS Open and SOMATOM go.OPEN Pro CT scanners). RESULTS: Consistent results across the two complementary analysis approaches (Spearman correlation coefficient of 0.6 / 0.7 $0.6/ 0.7$ between system matrix-based MSD and GTV-based DSC/ASSD) were observed. Analysis showed that stability was not predominant, with 114/214 fraction-wise models not surpassing a threshold of D S C > 0.7 $DSC > 0.7$ for the GTV, and only 14/46 patients demonstrating a D S C > 0.7 $DSC > 0.7$ in all fractions. Model stability did not degrade over the course of treatment. The mean GTV-based DSC is 0.59 ± 0.26 $0.59\pm 0.26$ (mean ASSD of 2.83 ± 3.37 $2.83\pm 3.37$ ) and the respective ITV-based DSC is 0.69 ± 0.20 $0.69\pm 0.20$ (mean ASSD of 2.35 ± 1.81 $2.35\pm 1.81$ ). The clinical parameters showed a strong correlation between smaller tumor motion ranges and increased stability. CONCLUSIONS: The proposed methods identify patients with unstable correspondence models prior to each treatment fraction, serving as direct indicators for the necessity of replanning and adaptive treatment approaches to account for internal-external motion variations throughout the course of treatment.

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 CT to daily cone beam CT (CBCT) using deformable image registration (DIR). 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. .

Fast Monte Carlo dose calculation in proton therapy.

This article examines the critical role of fast Monte Carlo dose calculations in advancing proton therapy techniques, particularly in the context of increasing treatment customization and precision. As adaptive radiotherapy and other patient-specific approaches evolve, the need for accurate and precise dose calculations, essential for techniques like proton-based stereotactic radiosurgery, becomes more prominent. These calculations, however, are time-intensive, with the treatment planning/optimization process constrained by the achievable speed of dose computations. Thus, enhancing the speed of Monte Carlo methods is vital, as it not only facilitates the implementation of novel treatment modalities but also leads to more optimal treatment plans. Today, the state-of-the-art in Monte Carlo dose calculation speeds is 10^{6 - 107protons per second. This review highlights the latest advancements in fast Monte Carlo dose calculations that have led to such speeds, including emerging artificial intelligence-based techniques, and discusses their application in both current and emerging proton therapy strategies.}

Uterus motion analysis for radiotherapy planning optimization. The innovative contribution of on-board hybrid MR imaging.

Introduction: Organ motion (OM) and volumetric changes pose challenges in radiotherapy (RT) for locally advanced cervical cancer (LACC). Magnetic Resonance-guided Radiotherapy (MRgRT) combines improved MRI contrast with adaptive RT plans for daily anatomical changes. Our goal was to analyze cervico-uterine structure (CUS) changes during RT to develop strategies for managing OM. Materials and methods: LACC patients received chemoradiation by MRIdian system with a simultaneous integrated boost (SIB) protocol. Prescription doses of 55-50.6 Gy at PTV1 and 45-39.6 Gy at PTV2 were given in 22 and 25 fractions. Daily MRI scans were co-registered with planning scans and CUS changes were assessed.Six PTVs were created by adding 0.5, 0.7, 1, 1.3, 1.5, and 2 cm margins to the CUS, based on the simulation MRI. Adequate margins were determined to include 95 % of the CUSs throughout the entire treatment in 95 % of patients. Results: Analysis of 15 LACC patients and 372 MR scans showed a 31 % median CUS volume decrease. Asymmetric margins of 2 cm cranially, 0.5 cm caudally, 1.5 cm posteriorly, 2 cm anteriorly, and 1.5 cm on both sides were optimal for PTV, adapting to CUS variations. Post-14th fraction, smaller margins of 0.7 cm cranially, 0.5 cm caudally, 1.3 cm posteriorly, 1.3 cm anteriorly, and 1.3 cm on both sides sufficed. Conclusion: CUS mobility varies during RT, suggesting reduced PTV margins after the third week. MRgRT with adaptive strategies optimizes dose delivery, emphasizing the importance of streamlined IGRT with reduced PTV margins using a tailored MRgRT workflow with hybrid MRI-guided systems.

Robust optimization strategies for contour uncertainties in online adaptive radiation therapy.

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

Multi-institutional experimental validation of online adaptive proton therapy workflows.

OBJECTIVE: To experimentally validate two online adaptive proton therapy (APT) workflows using Gafchromic EBT3 films and optically stimulated luminescent dosimeters (OSLDs) in an anthropomorphic head-and-neck phantom. Approach: A three-field proton plan was optimized on the planning CT of the head-and-neck phantom with 2.0 Gy(RBE) per fraction prescribed to the clinical target volume. Four fractions were simulated by varying the internal anatomy of the phantom. Three distinct methods were delivered: daily adaptive proton therapy researched by the Paul Scherrer Institute (DAPT_PSI), online adaptation researched by the Massachusetts General Hospital (OA_MGH), and a non-adaptive (NA) workflow. All methods were implemented and measured at PSI. DAPT_PSI performed full online replanning based on analytical dose calculation, optimizing to the same objectives as the initial treatment plan. OA_MGH performed Monte-Carlo-based online plan adaptation by only changing the fluences of a subset of proton beamlets, mimicking the planned dose distribution. NA delivered the initial plan with a couch-shift correction based on in-room-imaging. For all 12 deliveries, two films and two sets of OSLDs were placed at different locations in the phantom. Main results: Both adaptive methods showed improved dosimetric results compared to NA. For film measurements in the presence of anatomical variations, the [min-max] gamma pass rates (3%/3 mm) between measured and clinically approved doses were [91.5%-96.1%], [94.0%-95.8%], and [67.2%-93.1%] for DAPT_PSI, OA_MGH, and NA, respectively. The OSLDs confirmed the dose calculations in terms of absolute dosimetry. Between the two adaptive workflows, OA_MGH showed improved target coverage, while DAPT_PSI showed improved normal tissue sparing, particularly relevant for the brainstem. Significance: This is the first multi-institutional study to experimentally validate two different concepts with respect to online adaptive proton therapy workflows. It highlights their respective dosimetric advantages, particularly in managing interfractional variations in patient anatomy that cannot be addressed by non-adaptive methods, such as internal anatomy changes.

Multi-institutional questionnaire-based survey on online adaptive radiotherapy performed using commercial systems in Japan in 2023.

In this study, we aimed to conduct a survey on the current clinical practice of, staffing for, commissioning of, and staff training for online adaptive radiotherapy (oART) in the institutions that installed commercial oART systems in Japan, and to share the information with institutions that will implement oART systems in future. A web-based questionnaire, containing 107 questions, was distributed to nine institutions in Japan. Data were collected from November to December 2023. Three institutions each with the MRIdian (ViewRay, Oakwood Village, OH, USA), Unity (Elekta AB, Stockholm, Sweden), and Ethos (Varian Medical Systems, Palo Alto, CA, USA) systems completed the questionnaire. One institution (MRIdian) had not performed oART by the response deadline. Each institution had installed only one oART system. Hypofractionation, and moderate hypofractionation or conventional fractionation were employed in the MRIdian/Unity and Ethos systems, respectively. The elapsed time for the oART process was faster with the Ethos than with the other systems. All institutions added additional staff for oART. Commissioning periods differed among the oART systems owing to provision of beam data from the vendors. Chambers used during commissioning measurements differed among the institutions. Institutional training was provided by all nine institutions. To the best of our knowledge, this was the first survey about oART performed using commercial systems in Japan. We believe that this study will provide useful information to institutions that installed, are installing, or are planning to install oART systems.

The First Reported Case of Treating the Ultra-Central Thorax With Cone Beam Computed Tomography-Guided Stereotactic Adaptive Radiotherapy (CT-STAR).

Stereotactic body radiotherapy (SBRT) to the central and ultra-central thorax is associated with infrequent but potentially serious adverse events. Adaptive SBRT, which provides more precise treatment planning and inter-fraction motion management, may allow the delivery of ablative doses to ultra-central tumors with effective local control and improved toxicity profiles. Herein, we describe the first reported case of cone beam computed tomography (CBCT)-guided stereotactic adaptive radiotherapy (CT-STAR) in the treatment of ultra-central non-small cell lung cancer (NSCLC) in a prospective clinical trial (NCT05785845). An 80-year-old man with radiographically diagnosed early-stage NSCLC presented for definitive management of an enlarging ultra-central lung nodule. He was prescribed 55 Gy in five fractions with CT-STAR. A simulation was performed using four-dimensional CT, and patients were planned for treatment at end-exhale breath-hold. Treatment plans were generated using a strict isotoxicity approach, which prioritized organ at risk (OAR) constraints over target coverage. During treatment, daily CBCTs were acquired and used to generate adapted contours and treatment plans based on the patient's anatomy-of-the-day, all while the patient was on the treatment table. The initial and adapted plans were compared using dose-volume histograms, and the superior plan was selected for treatment. The adapted plan was deemed superior and used for treatment in three out of five fractions. The adapted plan provided improved target coverage in two fractions and resolved an OAR hard constraint violation in one fraction. We report the successful treatment of a patient with ultra-central NSCLC utilizing CT-STAR. This case report builds on previously published in silico data to support the viability and dosimetric advantages of CT-STAR in the ablative treatment of this challenging tumor location. Further data are needed to confirm the toxicity and efficacy of this technique.

Clinical evaluation of a deep learning CBCT auto-segmentation software for prostate adaptive radiation therapy.

Purpose: Aim of the present study is to characterize a deep learning-based auto-segmentation software (DL) for prostate cone beam computed tomography (CBCT) images and to evaluate its applicability in clinical adaptive radiation therapy routine. Materials and methods: Ten patients, who received exclusive radiation therapy with definitive intent on the prostate gland and seminal vesicles, were selected. Femoral heads, bladder, rectum, prostate, and seminal vesicles were retrospectively contoured by four different expert radiation oncologists on patients CBCT, acquired during treatment. Consensus contours (CC) were generated starting from these data and compared with those created by DL with different algorithms, trained on CBCT (DL-CBCT) or computed tomography (DL-CT). Dice similarity coefficient (DSC), centre of mass (COM) shift and volume relative variation (VRV) were chosen as comparison metrics. Since no tolerance limit can be defined, results were also compared with the inter-operator variability (IOV), using the same metrics. Results: The best agreement between DL and CC was observed for femoral heads (DSC of 0.96 for both DL-CBCT and DL-CT). Performance worsened for low-contrast soft tissue organs: the worst results were found for seminal vesicles (DSC of 0.70 and 0.59 for DL-CBCT and DL-CT, respectively). The analysis shows that it is appropriate to use algorithms trained on the specific imaging modality. Furthermore, the statistical analysis showed that, for almost all considered structures, there is no significant difference between DL-CBCT and human operator in terms of IOV. Conclusions: The accuracy of DL-CBCT is in accordance with CC; its use in clinical practice is justified by the comparison with the inter-operator variability.

Stereotactic Body Radiotherapy (SBRT) to Localised Prostate Cancer in the Era of MRI-Guided Adaptive Radiotherapy: Doses Delivered in the HERMES Trial Comparing Two- and Five-Fraction Treatments.

HERMES is a phase II trial of MRI-guided daily-adaptive radiotherapy (MRIgART) randomising men with localised prostate cancer to either 2-fractions of SBRT with a boost to the tumour or 5-fraction SBRT. In the context of this highly innovative regime the dose delivered must be carefully considered. The first ten patients recruited to HERMES were analysed in order to establish the dose received by the targets and organs at risk (OARS) in the context of intrafraction motion. A regression analysis was performed to measure how the volume of air within the rectum might further impact rectal dose secondary to the electron return effect (ERE). One hundred percent of CTV target objectives were achieved on the MRI taken prior to beam-on-time. The post-delivery MRI showed that high-dose CTV coverage was achieved in 90% of sub-fractions (each fraction is delivered in two sub-fractions) in the 2-fraction cohort and in 88% of fractions the 5-fraction cohort. Rectal D1 cm3 was the most exceeded constraint; three patients exceeded the D1 cm3 < 20.8 Gy in the 2-fraction cohort and one patient exceeded the D1 cm3 < 36 Gy in the 5-fraction cohort. The volume of rectal gas within 1 cm of the prostate was directly proportional to the increase in rectal D1 cm3, with a strong (R = 0.69) and very strong (R = 0.90) correlation in the 2-fraction and 5-fraction cohort respectively. Dose delivery specified in HERMES is feasible, although for some patients delivered doses to both target and OARs may vary from those planned.

The Investigating Image Registration Accuracy and Contour Propagation for Adaptive Radiotherapy Purposes in Line with the Task Group No. 132 Recommendation.

Purpose: Image registration is a crucial component of the adaptive radiotherapy workflow. This study investigates the accuracy of the deformable image registration (DIR) and contour propagation features of SmartAdapt, an application in the Eclipse treatment planning system (TPS) version 16.1. Materials and Methods: The registration accuracy was validated using the Task Group No. 132 (TG-132) virtual phantom, which features contour evaluation and landmark analysis based on the quantitative criteria recommended in the American Association of Physicists in Medicine TG-132 report. The target registration error, Dice similarity coefficient (DSC), and center of mass displacement were used as quantitative validation metrics. The performance of the contour propagation feature was evaluated using clinical datasets (head and neck, pelvis, and chest) and an additional four-dimensional computed tomography (CT) dataset from TG-132. The primary planning and the second CT images were appropriately registered and deformed. The DSC was used to find the volume overlapping between the deformed contours and the radiation oncologist (RO)-drawn contour. The clinical value of the DIR-generated structure was reviewed and scored by an experienced RO to make a qualitative assessment. Results: The registration accuracy fell within the specified tolerances. SmartAdapt exhibited a reasonably propagated contour for the chest and head-and-neck regions, with DSC values of 0.80 for organs at risk. Misregistration is frequently observed in the pelvic region, which is specified as a low-contrast region. However, 78% of structures required no modification or minor modification, demonstrating good agreement between contour comparison and the qualitative analysis. Conclusions: SmartAdapt has adequate efficiency for image registration and contour propagation for adaptive purposes in various anatomical sites. However, there should be concern about its performance in regions with low contrast and small volumes.

Clinical Outcomes of Online Adaptive Magnetic Resonance-Guided Stereotactic Body Radiotherapy of Adrenal Metastases from a Single Institution.

(1) Background: Recent publications foster stereotactic body radiotherapy (SBRT) in patients with adrenal oligometastases or oligoprogression. However, local control (LC) after non-adaptive SBRT shows the potential for improvement. Online adaptive MR-guided SBRT (MRgSBRT) improves tumor coverage and organ-at-risk (OAR) sparing. Long-term results of adaptive MRgSBRT are still sparse. (2) Methods: Adaptive MRgSBRT was performed on a 0.35 T MR-Linac. LC, overall survival (OS), progression-free survival (PFS), overall response rate (ORR), and toxicity were assessed. (3) Results: 35 patients with 40 adrenal metastases were analyzed. The median gross tumor volume was 30.6 cc. The most common regimen was 10 fractions at 5 Gy. The median biologically effective dose (BED10) was 75.0 Gy. Plan adaptation was performed in 98% of all fractions. The median follow-up was 7.9 months. One local failure occurred after 16.6 months, resulting in estimated LC rates of 100% at one year and 90% at two years. ORR was 67.5%. The median OS was 22.4 months, and the median PFS was 5.1 months. No toxicity > CTCAE grade 2 occurred. (4) Conclusions: LC and ORR after adrenal adaptive MRgSBRT were excellent, even in a cohort with comparably large metastases. A BED10 of 75 Gy seems sufficient for improved LC in comparison to non-adaptive SBRT.

Stereotactic Magnetic Resonance-Guided Daily Adaptive SABR (SMART) for Localised Non-Metastatic Pancreatic Cancer: First Reported Clinical Outcomes From the UK.

AIMS: Prognosis of locally advanced pancreatic cancer (LAPC) remains poor with limited therapeutic options. Radiation therapy in pancreatic cancer has been restricted by the disease's proximity to radiosensitive organs at risk (OAR). However, stereotactic magnetic resonance-guided adaptive radiation therapy (SMART) has demonstrated promise in delivering ablative doses safely. We sought to report clinical outcomes from a UK-based Compassionate Access Programme that provided access to SMART to patients with LAPC. MATERIALS AND METHODS: This was a registry retrospective study conducted at a single centre with access to SMART. Patients with LAPC were treated with prescription dose of 40 Gy in 5 fractions. The planning objective was that 98% of PTV received ≥95% of the prescribed dose, prioritising duodenal, stomach and bowel UK SABR consortium constraints. Daily online adaptation was performed using magnetic resonance guidance and on-table re-optimisation. 0-3 months and > 3-month post-treatment-related toxicities, local progression-free survival, metastatic-free survival and overall survival were evaluated. RESULTS: 55 patients were treated with SMART at our institution from 2020 to 2022. Median follow-up from date of diagnosis was 17 months (range 5-37 months). Median age was 69.87% of patients underwent induction chemotherapy. 71% of patients reported 0-1 grade acute toxicity only. No grade >3 acute toxicity was reported. 5 patients (9%) reported a grade 3 toxicity (fatigue, nausea, abdominal pain, duodenal stricture). No grade >3 toxicity after 3 months was reported. 6 (10%) of patients had grade 3 toxicity (fatigue, nausea, abdominal pain, duodenal haemorrhage). Median local PFS post diagnosis was 17 months (95% CI 15.3-18.7). Median OS post diagnosis was 19 months (95% CI 15.9-22.1). One-year local control post SMART was 65%. CONCLUSION: This is the first UK-reported experience of MR-guided daily adaptive pancreatic SABR. SMART shows promise in delivering ablative doses with acceptable toxicity rates and good clinical outcomes.