Interfractional Anatomic Changes Research Articles

Using a patient-specific diffusion model to generate CBCT-based synthetic CTs for CBCT-guided adaptive radiotherapy.

Cone beam computed tomography (CBCT) can be used to evaluate the inter-fraction anatomical changes during the entire course for image-guided radiotherapy (IGRT). However, CBCT artifacts from various sources restrict the full application of CBCT-guided adaptive radiation therapy (ART). Inter-fraction anatomical changes during ART, including variations in tumor size and normal tissue anatomy, can affect radiation therapy (RT) efficacy. Acquiring high-quality CBCT images that accurately capture patient- and fraction-specific (PFS) anatomical changes is crucial for successful IGRT. To enhance CBCT image quality, we proposed PFS lung diffusion models (PFS-LDMs). The proposed PFS models use a pre-trained general lung diffusion model (GLDM) as a baseline, which is trained on historical deformed CBCT (dCBCT)-planning CT (pCT) paired data. For a given patient, a new PFS model is fine-tuned on a CBCT-deformed pCT (dpCT) pair after each fraction to learn the PFS knowledge for generating personalized synthetic CT (sCT) with quality comparable to pCT or dpCT. The learned PFS knowledge is the specific mapping relationships, including personal inter-fraction anatomical changes between personalized CBCT-dpCT pairs. The PFS-LDMs were evaluated on an institutional lung cancer dataset, quantified by mean absolute error (MAE), peak signal-to-noise ratio (PSNR), normalized cross-correlation (NCC), and structural similarity index measure (SSIM) metrics. We also compared our PFS-LDMs with a mainstream GAN-based model, demonstrating that our PFS fine-tuning strategy could be applied to existing generative models. Our models showed remarkable improvements across all four evaluation metrics. The proposed PFS-LDMs outperformed the GLDM, demonstrating the effectiveness of our proposed fine-tuning strategy. The PFS model fine-tuned with CBCT images from four prior fractions, reduced the MAE from 103.95 to 15.96 Hounsfield units (HU), and increased the mean PSNR, NCC, and SSIM from 25.36dB to 33.57dB, 0.77 to 0.98, and 0.75 to 0.97, respectively. Applying our PFS fine-tuning strategy to a Cycle GAN model also showed improvements, with all four fine-tuned PFS Cycle GAN (PFS-CG) models outperforming the general Cycle GAN model. Overall, our proposed PFS fine-tuning strategy improved CBCT image quality compared to both the pre-correction and non-fine-tuned general models, with our proposed PFS-LDMs yielding better performance than the GAN-based model across all metrics. Our proposed PFS-LDMs significantly improve CBCT image quality with increased HU accuracy and fewer artifacts, thus better capturing inter-fraction anatomical changes. This lays the groundwork for enabling CBCT-based ART, which could enhance clinical efficiency and achieve personalized high-precision treatment by accounting for inter-fraction anatomical changes.

Comparison of online adaptive and non-adaptive magnetic resonance image-guided radiation therapy in prostate cancer using dose accumulation

Background and purposeConventional image-guided radiotherapy (conv-IGRT) is standard in prostate cancer (PC) but does not account for inter-fraction anatomical changes. Online-adaptive magnetic resonance-guided RT (OA-MRgRT) may improve organ-at-risk (OARs) sparing and clinical target volume (CTV) coverage. The aim of this study was to analyze accumulated OAR and target doses in PC after OA-MRgRT and conv-IGRT in comparison to pre-treatment reference planning (refPlan). Material and methodsTen patients with PC, previously treated with OA-MRgRT at the 1.5 T MR-Linac (20x3Gy), were included. Accumulated OA-MRgRT doses were determined by deformably registering all fraction’s MR-images. Conv-IGRT was simulated through rigid registration of the planning computed tomography with each fraction’s MR-image for dose mapping/accumulation. Dose-volume parameters (DVPs), including CTV D50% and D98%, rectum, bladder, urethra, Dmax and V56Gy for OA-MRgRT, conv-IGRT and refPlan were compared using the Wilcoxon signed-rank test. Clinical relevance of accumulated dose differences was analyzed using a normal-tissue complication-probability model. ResultsCTV-DVPs were comparable, whereas OA-MRgRT yielded decreased median OAR-DVPs compared to conv-IGRT, except for bladder V56Gy. OA-MRgRT demonstrated significantly lower median rectum Dmax over conv-IGRT (59.1/59.9 Gy, p = 0.006) and refPlan (60.1 Gy, p = 0.012). Similarly, OA-MRgRT yielded reduced median bladder Dmax compared to conv-IGRT (60.0/60.4 Gy, p = 0.006), and refPlan (61.2 Gy, p = 0.002). Overall, accumulated dose differences were small and did not translate into clinically relevant effects. ConclusionDeformably accumulated OA-MRgRT using 20x3Gy in PC showed significant but small dosimetric differences comparted to conv-IGRT. Feasibility of a dose accumulation methodology was demonstrated, which may be relevant for evaluating future hypo-fractionated OA-MRgRT approaches.

Machine learning automated treatment planning for online magnetic resonance guided adaptive radiotherapy of prostate cancer

Background and purposeNo best practices currently exist for achieving high quality radiation therapy (RT) treatment plan adaptation during magnetic resonance (MR) guided RT of prostate cancer. This study validates the use of machine learning (ML) automated RT treatment plan adaptation and benchmarks it against current clinical RT plan adaptation methods. Materials and methodsWe trained an atlas-based ML automated treatment planning model using reference MR RT treatment plans (42.7 Gy in 7 fractions) from 46 patients with prostate cancer previously treated at our institution. For a held-out test set of 38 patients, retrospectively generated ML RT plans were compared to clinical human-generated adaptive RT plans for all 266 fractions. Differences in dose-volume metrics and clinical objective pass rates were evaluated using Wilcoxon tests (p < 0.05) and Exact McNemar tests (p < 0.05), respectively. ResultsCompared to clinical RT plans, ML RT plans significantly increased sparing and objective pass rates of the rectum, bladder, and left femur. The mean ± standard deviation of rectum D20 and D50 in ML RT plans were 2.5 ± 2.2 Gy and 1.6 ± 1.3 Gy lower than clinical RT plans, respectively, with 14 % higher pass rates; bladder D40 was 4.6 ± 2.9 Gy lower with a 20 % higher pass rate; and the left femur D5 was 0.8 ± 1.8 Gy lower with a 7 % higher pass rate. ConclusionsML automated RT treatment plan adaptation increases robustness to interfractional anatomical changes compared to current clinical adaptive RT practices by increasing compliance to treatment objectives.

Online Adaptive Proton Therapy Facilitated by Artificial Intelligence–Based Autosegmentation in Pencil Beam Scanning Proton Therapy

PurposeOnline adaptive proton therapy (oAPT) is essential to address interfractional anatomical changes in patients receiving pencil beam scanning proton therapy (PBSPT). Artificial intelligence (AI)-based auto-segmentation can increase the efficiency and accuracy. Linear energy transfer (LET)-based biological effect evaluation can potentially mitigate possible adverse events caused by high LET. New spot arrangement based on the verification CT (vCT) can further improve the re-plan quality. We propose an oAPT workflow that incorporates all these functionalities and validate its clinical implementation feasibility with prostate patients. Methods and MaterialsAI-based auto-segmentation tool AccuContourTM (Manteia, Xiamen, China) was seamlessly integrated into oAPT. Initial spot arrangement tool on the vCT for re-optimization was implemented using raytracing. An LET-based biological effect evaluation tool was developed to assess the overlap region of high dose and high LET in selected OARs. Eleven prostate cancer patients were retrospectively selected to verify the efficacy and efficiency of the proposed oAPT workflow. The time cost of each component in the workflow was recorded for analysis. ResultsThe verification plan showed significant degradation of the CTV coverage and rectum and bladder sparing due to the interfractional anatomical changes. Re-optimization on the vCT resulted in great improvement of the plan quality. No overlap regions of high dose and high LET distributions were observed in bladder or rectum in re-plans. 3D Gamma analyses in PSQA confirmed the accuracy of the re-plan doses before delivery (Gamma passing rate = 99.57 ± 0.46%), and after delivery (98.59 ± 1.29%). The robustness of the re-plans passed all clinical requirements. The average time for the complete execution of the workflow was 9.12 ± 0.85 minutes, excluding manual intervention time. ConclusionThe AI-facilitated oAPT workflow was demonstrated to be both efficient and effective by generating a re-plan that significantly improved the plan quality in prostate cancer treated with PBSPT.

Safety and Efficiency Analysis of Operational Decision-Making During Cone Beam Computed Tomography-Based Online Adaptive Radiation Therapy

Cone beam computed tomography (CBCT)-based online adaptive radiation therapy (ART) is especially beneficial for patients with large interfractional anatomic changes. However, treatment planning and review decisions need to be made at the treatment console in real-time and may be delegated to clinical staff whose conventional scope of practice does not include making such decisions. Therefore, implementation can create new safety risks and inefficiencies. The objective of this work is to systematically analyze the safety and efficiency implications of human decision-making during the treatment session for CBCT-based online ART. The analysis was performed by applying the Systems-Theoretical Process Analysis technique and its extension for human decision-making. Four centers of different CBCT-based online ART practice models comprised the analysis team. The general radiation therapy control structure was refined to model the interactions between routine treatment delivery staff and in-person or remote support staff. The treatment delivery staff perform 6 key control actions. Eighteen undesirable states of those control actions were identified as affecting safety and/or efficiency. In turn, 97 hazardous clinical scenarios were identified, with the control action "prepare and position patient" having the least number of scenarios and "delineate/edit influencer and target structures" having the most. Five of these are specific to either in-person or remote support during the treatment session, and 12 arise from staff support in general. An optimally safe and efficient online ART program should require little to no support staff at the treatment console to reduce staff coordination. Uptraining of the staff already at the treatment console is needed to achieve this goal. Beyond the essential knowledge and skills such as contour editing and the selection of an optimal plan, uptraining should also target the specific cognitive biases identified in this work and the cognitive strategies to overcome these biases. Additionally, technological and organizational changes are necessary.

Optically stimulated luminescence dosimeters for simultaneous measurement of point dose and dose-weighted LET in an adaptive proton therapy workflow.

To demonstrate the suitability of optically stimulated luminescence detectors (OSLDs) for accurate simultaneous measurement of the absolute point dose and dose-weighted linear energy transfer (LETD) in an anthropomorphic phantom for experimental validation of daily adaptive proton therapy. A clinically realistic intensity-modulated proton therapy (IMPT) treatment plan was created based on a CT of an anthropomorphic head-and-neck phantom made of tissue-equivalent material. The IMPT plan was optimized with three fields to deliver a uniform dose to the target volume covering the OSLDs. Different scenarios representing inter-fractional anatomical changes were created by modifying the phantom. An online adaptive proton therapy workflow was used to recover the daily dose distribution and account for the applied geometry changes. To validate the adaptive workflow, measurements were performed by irradiating Al2O3:C OSLDs inside the phantom. In addition to the measurements, retrospective Monte Carlo simulations were performed to compare the absolute dose and dose-averaged LET (LETD) delivered to the OSLDs. The online adaptive proton therapy workflow was shown to recover significant degradation in dose conformity resulting from large anatomical and positioning deviations from the reference plan. The Monte Carlo simulations were in close agreement with the OSLD measurements, with an average relative error of 1.4% for doses and 3.2% for LETD. The use of OSLDs for LET determination allowed for a correction for the ionization quenched response. The OSLDs appear to be an excellent detector for simultaneously assessing dose and LET distributions in proton irradiation of an anthropomorphic phantom. The OSLDs can be cut to almost any size and shape, making them ideal for in-phantom measurements to probe the radiation quality and dose in a predefined region of interest. Although we have presented the results obtained in the experimental validation of an adaptive proton therapy workflow, the same approach can be generalized and used for a variety of clinical innovations and workflow developments that require accurate assessment of point dose and/or average LET.

Treatment planning comparison for head and neck cancer between photon, proton, and combined proton–photon therapy – From a fixed beam line to an arc

Background and purposeThis study investigates whether combined proton–photon therapy (CPPT) improves treatment plan quality compared to single-modality intensity-modulated radiation therapy (IMRT) or intensity-modulated proton therapy (IMPT) for head and neck cancer (HNC) patients. Different proton beam arrangements for CPPT and IMPT are compared, which could be of specific interest concerning potential future upright-positioned treatments. Furthermore, it is evaluated if CPPT benefits remain under inter-fractional anatomical changes for HNC treatments. Material and methodsFive HNC patients with a planning CT and multiple (4–7) repeated CTs were studied. CPPT with simultaneously optimized photon and proton fluence, single-modality IMPT, and IMRT treatment plans were optimized on the planning CT and then recalculated and reoptimized on each repeated CT. For CPPT and IMPT, plans with different degrees of freedom for the proton beams were optimized. Fixed horizontal proton beam line (FHB), gantry-like, and arc-like plans were compared. ResultsThe target coverage for CPPT without adaptation is insufficient (average V95%=88.4 %), while adapted plans can recover the initial treatment plan quality for target (average V95%=95.5 %) and organs-at-risk. CPPT with increased proton beam flexibility increases plan quality and reduces normal tissue complication probability of Xerostomia and Dysphagia. On average, Xerostomia NTCP reductions compared to IMRT are −2.7 %/-3.4 %/-5.0 % for CPPT FHB/CPPT Gantry/CPPT Arc. The differences for IMPT FHB/IMPT Gantry/IMPT Arc are + 0.8 %/-0.9 %/-4.3 %. ConclusionCPPT for HNC needs adaptive treatments. Increasing proton beam flexibility in CPPT, either by using a gantry or an upright-positioned patient, improves treatment plan quality. However, the photon component is substantially reduced, therefore, the balance between improved plan quality and costs must be further determined.

Dosimetric Impact of Intrafraction Prostate Motion and Interfraction Anatomical Changes in Dose-Escalated Linac-Based SBRT

The aim of this study was to investigate the impact of intrafraction prostate motion and interfraction anatomical changes on dose metrics and the effect of beam gating and motion correction in dose-escalated Linac-based SBRT. Thirteen patients (56 fractions) with organ-confined prostate cancer underwent dose-escalated FFF-VMAT SBRT. Accurate patient setup was ensured by CBCT, and real-time 3D prostate motion data were obtained using a novel electromagnetic tracking device. Treatment was interrupted when the signals exceeded a 2 mm threshold in any of the three spatial directions and couch position was corrected unless the offset was transient. Prostate trajectories with and without beam gating and motion correction events were reconstructed and analyzed. Rectum and bladder volumes on each daily CBCT were recorded and compared with volumes at simulation. The prostate motion observed for each fraction was incorporated into the patient original treatment plan with an isocenter shift method. Actually, delivered treatments were then obtained by recalculating the reconstructed motion-encoded plan on deformed CTs reflecting the patient CBCT-anatomy of the day. Non-gated treatments were also simulated using the prostate motion data assuming that no treatment interruptions have occurred. Treatment interruptions because of target motion trespassing the predefined threshold occurred in 25 fractions (45%). Rectum and bladder volume changes were relevant in most patients. The mean relative dose differences between actually delivered and planned treatments were -3.0% [-18.5 - 2.8] for CTV D99% and -2.6% [-17.8 - 1.0] for PTV D95% over all 56 fractions. However, the median cumulative CTV coverage with 93% of the prescribed dose turned out to be satisfactory. Urethra sparing was slightly degraded and a mean reduction of rectum and bladder dose was seen in all but two dose metrics: the maximum dose to rectum mucosa and the bladder D40%. Nevertheless, only 2 major deviations in rectum mucosa D0.035cc were observed at the end of the treatment. The greatest contribution to target missing and OARs doses came from the interfraction anatomical variations, while intrafraction prostate motion marginally contributed in gated treatments. In non-gated treatments, further deteriorations by 2.4 - 2.8% in minimum target coverage metrics and by 3.1 - 11.6% in bladder dose parameters would have occurred on average. The implemented motion management strategy and the strict patient preparation regimen, along with current PTV margins, robustness of original treatment plans, and fast FFF beam delivery, ensured no significant degradations of dose metrics due to both intrafraction motion and interfraction anatomical changes. Non-gated treatments would have more widely deteriorated the dosimetry of some individual fractions. Thus, continuous monitoring, beam gating and motion correction are recommended to safely deliver dose-escalated prostate SBRT.

Dosimetric Advantages of Online Adaptative Radiotherapy for Cervical Cancer on 1.5T MR-Linac

Online adaptative radiotherapy (ART) strategy can be applied to account for inter-fraction organ motion while limiting organ at risk (OAR) dose. This study aims to evaluate tumor target and OARs inter- and intrafraction motion using online MRI during the full course of MR-Linac radiotherapy fractions. Furthermore, quantify the dosimetric consequences of online adaptative compared with non-adaptative radiotherapy (non-ART) in cervical cancer. Six cervix cancer patients were treated with 150 fractions on the 1.5 T Unity MR-Linac. Each fraction, pre-treatment MRI scans were obtained at the start of every treatment session, and post-treatment MRI scans were obtained at the end of every treatment session. A total 300 MR images were included in this study and the CTV, bladder and rectum were delineated on each MRI by the same radiation oncologist. The inter-fraction and intrafraction changes of contours were evaluated by dice similarity coefficient (DSC), Hausdorff distance (HD), volume difference (ΔV). The reference treatment plans were generated using step-and-shoot IMRT and utilized 9 beam groups on original CT. Then, the online adaptative treatment plans were obtained by re-optimizing based on the contours on daily pre-treatment MRI by "adapt to shape" workflow using the same beam parameters and optimization objectives from the reference plans. Non-ART plans for each patient were generated by recalculating the dose from the reference plans on daily online MRI by "adapt to position" workflow. CTV coverage and OARs constraints were used to compare ART and non-ART plans. The results showed that large inter-fraction anatomical changes limited the efficacy of radiation therapy (CTV: DSC: 0.89±0.03, HD: 20.83±5.05mm, ΔV: 1.21%±5.44%; Bladder: DSC: 0.68±0.18, HD: 30.58±15.75mm, ΔV: -10.17%±61.19%; Rectum: DSC: 0.69±0.09, HD: 22.98±12.03mm, ΔV: 21.01%±20.59%).The intrafraction anatomical changes were smaller (CTV: DSC: 0.96±0.01, HD: 8.85±3.54mm, ΔV: -0.64%±1.90%; Bladder: DSC: 0.90±0.07, HD: 14.62±9.56mm, ΔV: 19.83%±21.71%; Rectum: DSC: 0.98±0.04, HD: 2.90±4.27mm, ΔV: 0.13%±5.04%) . Non-ART showed inadequate primary CTV coverage in 30% of the daily fractions. Online adaptative plans improved CTV coverage significantly (p<0.001) to 99%. Compared with non-ART, online ART decreased the fraction dose to bladder and rectum indicated by significant (p<0.001) improvements for daily D50%, D2% and Dmean. In cervical cancer radiotherapy, a non-adaptive strategy led to inadequate target coverage for individual patients. Online adaptative radiotherapy corrected for day-to-day anatomical variations and resulted in adequate target coverage in all fractions. The dose to rectum and bladder was decreased significantly when applying online adaptative radiotherapy.

Plan robustness evaluation strategies in whole-pelvic proton therapy for high-risk prostate cancer patients within a randomised clinical trial

Background Inter-fractional anatomical changes challenge robust delivery of whole-pelvic proton therapy for high-risk prostate cancer. Pre-treatment robust evaluation (PRE) takes uncertainties in isocenter shifts and distal beam edge in treatment plans into account. Using weekly control computed tomography scans (cCTs), the aim of this study was to evaluate the PRE strategy by comparing to an off-line during-treatment robust evaluation (DRE) while also assessing plan robustness with respect to protocol planning constraints. Material and methods Treatment plans and cCTs from ten patients included in the pilot phase of the PROstate PROTON Trial 1 were analysed. Treatment planning followed protocol guidelines with 78 Gy to the primary clinical target volume (CTVp) and 56 Gy to the elective target (CTVe) in 39 fractions. Recalculations of the treatment plans were performed for a total of 64 cCTs and dose/volume measures corresponding to clinical constraints were evaluated for this DRE against the simulated scenario interval from the PRE. Results Of the 64 cCTs, 59 showed DRE CTVp measures within the robustness range from the PRE; this was also the case for 39 of the cCTs for the CTVe measures. However, DRE CTVe coverage was still within constraints for 57 of the 64 cCTs. DRE dose/volume measures for CTVp fulfilled target coverage constraints in 59 of 64 cCTs. All DRE measures for the rectum, bladder, and bowel were inside the PRE range in 63, 39, and 31 cCTs, respectively. Conclusion The PRE strategy predicted the DRE scenarios for CTVp and rectum. CTVe, bladder, and bowel showed more complex anatomical variations than simulated by the PRE isocenter shift. Both original and recalculated nominal treatment plans showed robust treatment delivery in terms of target coverage.

CBCT-based deformable dose accumulation of external beam radiotherapy in cervical cancer

Background: Delivered radiotherapy doses do not exactly match those planned for a course of treatment, largely due to inter-fraction changes in anatomy. In this study, accumulated delivered dose was calculated for a sample of cervical cancer patients, by deformably registering daily cone beam computed tomography (CBCT) images to the planning computed tomography (CT) scan. Planned and accumulated doses were compared for the clinical target volume (CTV), bladder, and rectum. Material and Methods: For 10 patients receiving 45 Gy in 25 fractions of external beam radiotherapy, daily dose distributions were calculated on CBCT. These images were deformed onto the planning CT and the dose was accumulated using Velocity 4.1 (Varian Medical Systems, Palo Alto, USA). The quality of deformable image registration was evaluated visually and by calculating Dice similarity coefficients and mean distance to agreement. Results: V95%>99% was achieved for the primary CTV in 9/10 patients for the planned dose distribution and 7/10 patients for the accumulated dose distribution. Primary CTV coverage by 95% of the prescription dose was reduced in one patient, due to an increase in anterior-posterior separation. Comparison of planned and accumulated dose volume histograms (DVHs) for the bladder and rectum found agreement within 5% at low and intermediate doses, but differences exceeded 20% at higher doses. Direct addition of CBCT DVHs was seen to be a poor estimate for the accumulated DVH at higher doses. Conclusion: Computation of delivered radiotherapy dose that accounts for inter-fraction anatomical changes is important for establishing dose-effect relationships. Updating delivered dose distributions after each fraction would support informed clinical decision making on any potential treatment interventions.

Dose mimicking based strategies for online adaptive proton therapy of head and neck cancer

Objective. To compare a not adapted (NA) robust planning strategy with three fully automated online adaptive proton therapy (OAPT) workflows based on the same optimization method: dose mimicking (DM). The added clinical value and limitations of the OAPT methods are investigated for head and neck cancer (HNC) patients. Approach. The three OAPT strategies aimed at compensating for inter-fractional anatomical changes by mimiking different dose distributions on corrected cone beam CT images (corrCBCTs). Order by complexity, the OAPTs were: (1) online adaptive dose restoration (OADR) where the approved clinical dose on the planning-CT (pCT) was mimicked, (2) online adaptation using DM of the deformed clinical dose from the pCT to corrCBCTs (OADEF), and (3) online adaptation applying DM to a predicted dose on corrCBCTs (OAML). Adaptation was only applied in fractions where the target coverage criteria were not met (D98% < 95% of the prescribed dose). For 10 HNC patients, the accumulated dose distributions over the 35 fractions were calculated for NA, OADR, OADEF, and OAML. Main results. Higher target coverage was observed for all OAPT strategies compared to no adaptation. OADEF and OAML outperformed both NA and OADR and were comparable in terms of target coverage to initial clinical plans. However, only OAML provided comparable NTCP values to those from the clinical dose without statistically significant differences. When the NA initial plan was evaluated on corrCBCTs, 51% of fractions needed adaptation. The adaptation rate decreased significantly to 25% when the last adapted plan with OADR was selected for delivery, to 16% with OADEF, and to 21% with OAML. The reduction was even greater when the best plan among previously generated adapted plans (instead of the last one) was selected. Significance. The implemented OAPT strategies provided superior target coverage compared to no adaptation, higher OAR sparing, and fewer required adaptations.

Inter-fraction deformable image registration using unsupervised deep learning for CBCT-guided abdominal radiotherapy

Objective. CBCTs in image-guided radiotherapy provide crucial anatomy information for patient setup and plan evaluation. Longitudinal CBCT image registration could quantify the inter-fractional anatomic changes, e.g. tumor shrinkage, and daily OAR variation throughout the course of treatment. The purpose of this study is to propose an unsupervised deep learning-based CBCT-CBCT deformable image registration which enables quantitative anatomic variation analysis. Approach. The proposed deformable registration workflow consists of training and inference stages that share the same feed-forward path through a spatial transformation-based network (STN). The STN consists of a global generative adversarial network (GlobalGAN) and a local GAN (LocalGAN) to predict the coarse- and fine-scale motions, respectively. The network was trained by minimizing the image similarity loss and the deformable vector field (DVF) regularization loss without the supervision of ground truth DVFs. During the inference stage, patches of local DVF were predicted by the trained LocalGAN and fused to form a whole-image DVF. The local whole-image DVF was subsequently combined with the GlobalGAN generated DVF to obtain the final DVF. The proposed method was evaluated using 100 fractional CBCTs from 20 abdominal cancer patients in the experiments and 105 fractional CBCTs from a cohort of 21 different abdominal cancer patients in a holdout test. Main Results. Qualitatively, the registration results show good alignment between the deformed CBCT images and the target CBCT image. Quantitatively, the average target registration error calculated on the fiducial markers and manually identified landmarks was 1.91 ± 1.18 mm. The average mean absolute error, normalized cross correlation between the deformed CBCT and target CBCT were 33.42 ± 7.48 HU, 0.94 ± 0.04, respectively. Significance. In summary, an unsupervised deep learning-based CBCT-CBCT registration method is proposed and its feasibility and performance in fractionated image-guided radiotherapy is investigated. This promising registration method could provide fast and accurate longitudinal CBCT alignment to facilitate inter-fractional anatomic changes analysis and prediction.

A probabilistic deep learning model of inter-fraction anatomical variations in radiotherapy

Objective. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. To assess the need for adaptation, motion models can be used to simulate dominant motion patterns and assess anatomical robustness before delivery. Traditionally, such models are based on principal component analysis (PCA) and are either patient-specific (requiring several scans per patient) or population-based, applying the same set of deformations to all patients. We present a hybrid approach which, based on population data, allows to predict patient-specific inter-fraction variations for an individual patient. Approach. We propose a deep learning probabilistic framework that generates deformation vector fields warping a patient's planning computed tomography (CT) into possible patient-specific anatomies. This daily anatomy model (DAM) uses few random variables capturing groups of correlated movements. Given a new planning CT, DAM estimates the joint distribution over the variables, with each sample from the distribution corresponding to a different deformation. We train our model using dataset of 312 CT pairs with prostate, bladder, and rectum delineations from 38 prostate cancer patients. For 2 additional patients (22 CTs), we compute the contour overlap between real and generated images, and compare the sampled and ‘ground truth’ distributions of volume and center of mass changes. Results. With a DICE score of 0.86 ± 0.05 and a distance between prostate contours of 1.09 ± 0.93 mm, DAM matches and improves upon previously published PCA-based models, using as few as 8 latent variables. The overlap between distributions further indicates that DAM’s sampled movements match the range and frequency of clinically observed daily changes on repeat CTs. Significance. Conditioned only on planning CT values and organ contours of a new patient without any pre-processing, DAM can accurately deformations seen during following treatment sessions, enabling anatomically robust treatment planning and robustness evaluation against inter-fraction anatomical changes.

Dosimetric Impact of Intrafraction Prostate Motion and Interfraction Anatomical Changes in Dose-Escalated Linac-Based SBRT

The dosimetric impact of intrafraction prostate motion and interfraction anatomical changes and the effect of beam gating and motion correction were investigated in dose-escalated linac-based SBRT. Fifty-six gated fractions were delivered using a novel electromagnetic tracking device with a 2 mm threshold. Real-time prostate motion data were incorporated into the patient's original plan with an isocenter shift method. Delivered dose distributions were obtained by recalculating these motion-encoded plans on deformed CTs reflecting the patient's CBCT daily anatomy. Non-gated treatments were simulated using the prostate motion data assuming that no treatment interruptions have occurred. The mean relative dose differences between delivered and planned treatments were -3.0% [-18.5-2.8] for CTV D99% and -2.6% [-17.8-1.0] for PTV D95%. The median cumulative CTV coverage with 93% of the prescribed dose was satisfactory. Urethra sparing was slightly degraded, with the maximum dose increased by only 1.0% on average, and a mean reduction in the rectum and bladder doses was seen in almost all dose metrics. Intrafraction prostate motion marginally contributed in gated treatments, while in non-gated treatments, further deteriorations in the minimum target coverage and bladder dose metrics would have occurred on average. The implemented motion management strategy and the strict patient preparation regimen, along with other treatment optimization strategies, ensured no significant degradations of dose metrics in delivered treatments.

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

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. 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. 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. 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 D95% from the initial plan was 0.4 ± 0.5% (Mean ± S.D.) for DDR. The calculation time was 8.1 ± 6.4 min. 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. This article is protected by copyright. All rights reserved.

Dosimetric impacts of cone-beam computed tomography (CBCT)-based anatomic changes in intensity-modulated radiotherapy for cervical cancer.

To evaluate the effects of dose to tumors and organs at risk (OARs) on inter-fractional anatomic changes. We evaluated nine patients with cervical cancer treated with intensity-modulated radiotherapy (IMRT) (45 Gy in 25 fractions) using kV cone-beam computed tomography (CBCT) image guidance once or twice a week before treatment. For each patient, the original plan on the computed tomography (CT) image was copied to merged images, and then the fractional doses were calculated. Subsequently, deformable accumulated doses were obtained by summing the fractional absolute doses into a single dose in MIM Maestro software. The volume changes in the target and OARs were compared between the original CT and merged CBCT images, and the differences in the fractional and accumulated doses were also evaluated. Sixty-nine merged CBCT images were obtained and analyzed in this study. For the target areas, the volume changes in the clinical target volume (CTV) and planning target volume (PTV) reached -18.05% and -24.11% at most, respectively. The fractional D2% of the CTV and PTV was generally higher than the original plans, and the accumulated deviations were 2.27%±0.82% (P<0.01) and 2.42%±1.28% (P<0.01), respectively. The fractional D98% of the PTV was underdosed up to 18.28% for 78% of patients, and the accumulated deviations were -2.06% to -17.29% (P<0.05). For the OARs, the bladder volume changes were the most dramatic, reducing up to 93.60%. The fractional Dmean and D2cc of the bladder were generally higher than the original plans, and there were significant differences in their accumulated values (P<0.05). There was no obvious trend of rectal volume change with -69.65% to 74.20%. The rectum Dmean and D2cc of the accumulated were not significantly different from the planned dose (P>0.05). For patients with cervical cancer, the changes in bladder and rectal volume were greater than in the target volume. Although the volume changes in the bladder and rectum had no significant effect on D98% of the CTV and PTV, they had a significant effect on their own D2cc and the D2% of the CTV and PTV. More attention should be paid to the volume changes in the bladder and rectum in clinical work.

Surface Imaging-Guided Adaptive Radiotherapy (ART): Imaging Protocol and Verification for Inter- and Intra-Fractional Motion Managements

<h3>Purpose/Objective(s)</h3> CBCT-guided adaptive radiotherapy (CT-ART) has proven to account for inter-fractional anatomic changes. However, no commercial solution for intra-fractional respiratory motion management existed in CT-ART. Therefore, we investigated intra-fractional motion-managed treatment strategies in CT-ART (or Image-guided RT: IGRT) using optical surface imaging combined with <i>in-situ</i> CBCTs. <h3>Materials/Methods</h3> Eight of ten cancer patients with mobile lower lung or upper abdominal malignancies have completed CT-ART (or IGRT) using Ethos radiotherapy in an IRB-approved clinical trial (phase I). Four of the eight patients underwent additional MR simulations, including cine MRIs, to estimate the tumor/abdominal skin motion correlation. In CT-ART, a pre-configured gating window (±2 mm in vertical position) on surface imaging was used for manually triggering intra-fractional CBCT and treatment beam irradiation in breath-hold (six patients for exhalation and two patients for inhalation). A donut-shaped imaging-surrogate on patient's abdomen was used to localize Region of Interest (ROI) of the abdomen on CBCTs. Two inter-fractional CBCTs at exhalation and inhalation in each fraction were acquired to verify the tumor/imaging-surrogate motions range. Intra-fractional CBCTs were used to quantify the residual motion of the tumor/imaging-surrogate within the pre-configured gating window. Tumor motion was measured by tracking the position of a tumor centroid. <h3>Results</h3> The pre-configured gating window on surface imaging was confirmed based on the correlation of the tumor and abdominal skin motions using cine MRIs. Thirty-six pairs of inter-fractional CBCTs and 100 intra-fractional CBCTs from 36 fractions were analyzed (13 fractions for IGRT and 23 for ART). In the motion range study from the inter-fractional CBCTs, the values of mean ± std were 17.3 ± 12.0 mm in the SI direction for the tumors and 16.6 ± 7.9 mm in the AP direction for the imaging-surrogate, respectively. The residual motion of the imaging-surrogate from intra-fractional CBCTs was 2.5 ± 2.1 mm for SI, 2.3 ± 2.0 mm for RL, and 2.1 ± 2.3 mm for AP directions. The residual motion of the tumors was 2.4 ± 3.1 mm for SI, 2.3 ± 2.3 mm for RL, and 2.2 ± 2.0 mm for AP directions. Trends in the residual motion during the course of treatment fractions and over time through delivery were stable. Inter-fractional residual motions of the tumors were 2.3 ± 0.8 mm for SI, 2.3 ± 0.6 mm for RL, and 2.2 ± 0.7 mm for AP directions. Intra-fractional residual motions of the tumors were 2.4 ± 0.9 mm for SI, 2.4 ± 0.7 mm for RL, and 3.2 ± 1.3 mm for AP. <h3>Conclusion</h3> We demonstrated the inter- and intra-fractional motion-managed treatment strategies in CBCT-guided ART using surface imaging. Since the residual motion of the tumors was comparable to that of the imaging-surrogate within clinical PTV margins (5 mm) but a bit larger than the pre-configured gating window, additional caution is needed with intra-fractional motion management in CT-ART using the optical surface imaging.

Feasibility and Dosimetric Benefits of Adaptive Planning in Prostate Cancer Radiotherapy Using a Novel Treatment Planning Machine with Integrated Dual kVCT/PET Imaging Systems

<h3>Purpose/Objective(s)</h3> Interfraction anatomical changes during intensity-modulated radiotherapy for prostate cancer may lead to suboptimal patients' treatment. This study assessed the dosimetric effects of anatomical changes on pretreatment kilovoltage computed tomography (kVCT) scans of a novel dual on-board kVCT/positiron emission tomography (PET) imaging radiotherapy system. <h3>Materials/Methods</h3> This retrospective study analyzed daily kVCT scans acquired on days 1, 5, 13, 17, and 22 of a post-prostatectomy patient treated with 44 Gy/22 fractions to the prostate bed and lymph nodes. The prostate bed CTV, pelvic lymph nodes, rectum and bladder were re-contoured on the daily kVCT, and treatment plans were subsequently created. The treatment doses were calculated using the HU density table of kVCT. Delineation and treatment plans created on the daily kVCT scans were compared with those created on the planning CT. Interfraction changes of bladder and rectum were analyzed based on median dose (Dmedian), mean dose (Dmean), maximum dose (Dmax), volume receiving 10 Gy (V10), volume receiving 30 Gy (V30), and overall volume. For bladder and rectum, the correlation coefficient between volume and Dmean was analyzed. <h3>Results</h3> For the kVCT days investigated in this study, mean bladder and rectum volume changes were 10.69 cc ± 10.08 cc and 1.31 cc ± 0.64 cc, respectively. Consequentially, the average changes in Dmedian, Dmean, Dmax for the bladder were 0.51 Gy ±0.32 Gy, 0.30 Gy ±0.22 Gy, and 0.75 Gy ±0.44 Gy, respectively. For the rectum, the average changes in Dmedian, Dmean, Dmax were 0.62 Gy ±0.36 Gy, 0.59 Gy ±0.49 Gy, and 0.76 Gy ±0.57 Gy, respectively. The average changes in V10, and V30 were 0.48 % ±0.56 %, and 1.1 %± 0.66 % for bladder and 1.48 % ±1.27 %, and 1.83 %± 1.34 % for rectum. The correlation coefficient (r2) for bladder-Dmean and Rectum-Dmean were 0.765 and 0.002, respectively. <h3>Conclusion</h3> This study showed that with adaptive planning, the interfraction dose variation was minimal because adaptive plans were optimized based on daily kVCT images (this is one primary benefit of adaptive planning). Even with adaptive planning, there is still a correlation between bladder dose and bladder volume. The high-quality kVCT images produced could potentially be used for target and OAR delineation and consequentially for treatment planning. Treatment delivery could further be improved by kVCT adaptive planning, which will account for possible interfraction variations.

Adaptive Proton Therapy of Pediatric Head and Neck Cases Using MRI-Based Synthetic CTs: Initial Experience of the Prospective KiAPT Study.

Simple SummaryRadiation therapy with protons facilitates highly conformal dose distributions. Thus, normal tissue can be spared effectively, which is a benefit, especially for children. Magnetic resonance imaging (MRI) is ideally suited to assess anatomical changes during the radiation course due to its superior soft tissue contrast and non-existent X-ray exposure. The MRI data have to be transformed to X-ray computed tomography (CT) images, which form the basis of treatment planning. This is conducted by capturing anatomical deformations between MRIs acquired at different times and by warping the planning CT according to these deformations. This procedure was applied in a prospective study enrolling pediatric head and neck cases. The preliminary evaluation of eleven patients with mainly rhabdomyosarcoma diagnosis and at craniofacial and base of skull tumor sites show that neither the deterioration of the target volume coverage nor an increased dose to organs-at-risk over the treatment course is a concern.Background and Purpose: Interfractional anatomical changes might affect the outcome of proton therapy (PT). We aimed to prospectively evaluate the role of Magnetic Resonance Imaging (MRI) based adaptive PT for children with tumors of the head and neck and base of skull. Methods: MRI verification images were acquired at half of the treatment course. A synthetic computed tomography (CT) image was created using this MRI and a deformable image registration (DIR) to the reference MRI. The methodology was verified with in-silico phantoms and validated using a clinical case with a shrinking cystic hygroma on the basis of dosimetric quantities of contoured structures. The dose distributions on the verification X-ray CT and on the synthetic CT were compared with a gamma-index test using global 2 mm/2% criteria. Results: Regarding the clinical validation case, the gamma-index pass rate was 98.3%. Eleven patients were included in the clinical study. The most common diagnosis was rhabdomyosarcoma (73%). Craniofacial tumor site was predominant in 64% of patients, followed by base of skull (18%). For one individual case the synthetic CT showed an increase in the median and dose on the spinal cord from 20.5 GyRBE to 24.8 GyRBE and 14.7 GyRBE to 25.1 GyRBE, respectively. Otherwise, doses received by OARs remained relatively stable. Similarly, the target volume coverage seen by and remained unchanged. Conclusions: The method of transferring anatomical changes from MRIs to a synthetic CTs was successfully implemented and validated with simple, commonly available tools. In the frame of our early results on a small cohort, no clinical relevant deterioration for neither PTV coverage nor an increased dose burden to OARs occurred. However, the study will be continued to identify a pediatric patient cohort, which benefits from adaptive treatment planning.