4D-Precise: Learning-based 3D motion estimation and high temporal resolution 4DCT reconstruction from treatment 2D+t X-ray projections.

BACKGROUND AND OBJECTIVE: In radiotherapy treatment planning, respiration-induced motion introduces uncertainty that, if not appropriately considered, could result in dose delivery problems. 4D cone-beam computed tomography (4D-CBCT) has been developed to provide imaging guidance by reconstructing a pseudo-motion sequence of CBCT volumes through binning projection data into breathing phases. However, it suffers from artefacts and erroneously characterizes the averaged breathing motion. Furthermore, conventional 4D-CBCT can only be generated post-hoc using the full sequence of kV projections after the treatment is complete, limiting its utility. Hence, our purpose is to develop a deep-learning motion model for estimating 3D+t CT images from treatment kV projection series. METHODS: We propose an end-to-end learning-based 3D motion modelling and 4DCT reconstruction model named 4D-Precise, abbreviated from Probabilistic reconstruction of image sequences from CBCT kV projections. The model estimates voxel-wise motion fields and simultaneously reconstructs a 3DCT volume at any arbitrary time point of the input projections by transforming a reference CT volume. Developing a Torch-DRR module, it enables end-to-end training by computing Digitally Reconstructed Radiographs (DRRs) in PyTorch. During training, DRRs with matching projection angles to the input kVs are automatically extracted from reconstructed volumes and their structural dissimilarity to inputs is penalised. We introduced a novel loss function to regulate spatio-temporal motion field variations across the CT scan, leveraging planning 4DCT for prior motion distribution estimation. RESULTS: The model is trained patient-specifically using three kV scan series, each including over 1200 angular/temporal projections, and tested on three other scan series. Imaging data from five patients are analysed here. Also, the model is validated on a simulated paired 4DCT-DRR dataset created using the Surrogate Parametrised Respiratory Motion Modelling (SuPReMo). The results demonstrate that the reconstructed volumes by 4D-Precise closely resemble the ground-truth volumes in terms of Dice, volume similarity, mean contour distance, and Hausdorff distance, whereas 4D-Precise achieves smoother deformations and fewer negative Jacobian determinants compared to SuPReMo. CONCLUSIONS: Unlike conventional 4DCT reconstruction techniques that ignore breath inter-cycle motion variations, the proposed model computes both intra-cycle and inter-cycle motions. It represents motion over an extended timeframe, covering several minutes of kV scan series.

CT respiratory motion synthesis using joint supervised and adversarial learning.

Objective.Four-dimensional computed tomography (4DCT) imaging consists in reconstructing a CT acquisition into multiple phases to track internal organ and tumor motion. It is commonly used in radiotherapy treatment planning to establish planning target volumes. However, 4DCT increases protocol complexity, may not align with patient breathing during treatment, and lead to higher radiation delivery.Approach.In this study, we propose a deep synthesis method to generate pseudo respiratory CT phases from static images for motion-aware treatment planning. The model produces patient-specific deformation vector fields (DVFs) by conditioning synthesis on external patient surface-based estimation, mimicking respiratory monitoring devices. A key methodological contribution is to encourage DVF realism through supervised DVF training while using an adversarial term jointly not only on the warped image but also on the magnitude of the DVF itself. This way, we avoid excessive smoothness typically obtained through deep unsupervised learning, and encourage correlations with the respiratory amplitude.Main results.Performance is evaluated using real 4DCT acquisitions with smaller tumor volumes than previously reported. Results demonstrate for the first time that the generated pseudo-respiratory CT phases can capture organ and tumor motion with similar accuracy to repeated 4DCT scans of the same patient. Mean inter-scans tumor center-of-mass distances and Dice similarity coefficients were 1.97 mm and 0.63, respectively, for real 4DCT phases and 2.35 mm and 0.71 for synthetic phases, and compares favorably to a state-of-the-art technique (RMSim).Significance.This study presents a deep image synthesis method that addresses the limitations of conventional 4DCT by generating pseudo-respiratory CT phases from static images. Although further studies are needed to assess the dosimetric impact of the proposed method, this approach has the potential to reduce radiation exposure in radiotherapy treatment planning while maintaining accurate motion representation. Our training and testing code can be found athttps://github.com/cyiheng/Dynagan.

The impact of motion on onboard MRI-guided pencil beam scanned proton therapy treatments.

Objective.Online magnetic resonance imaging (MRI) guidance could be especially beneficial for pencil beam scanned (PBS) proton therapy of tumours affected by respiratory motion. For the first time to our knowledge, we investigate the dosimetric impact of respiratory motion on MRI-guided proton therapy compared to the scenario without magnetic field.Approach.A previously developed analytical proton dose calculation algorithm accounting for perpendicular magnetic fields was extended to enable 4D dose calculations. For two geometrical phantoms and three liver and two lung patient cases, static treatment plans were optimised with and without magnetic field (0, 0.5 and 1.5 T). Furthermore, plans were optimised using gantry angle corrections (0.5 T +5° and 1.5 T +15°) to reproduce similar beam trajectories compared to the 0 T reference plans. The effect of motion was then considered using 4D dose calculations without any motion mitigation and simulating 8-times volumetric rescanning, with motion for the patient cases provided by 4DCT(MRI) data sets. Each 4D dose calculation was performed for different starting phases and the CTV dose coverageV95%and homogeneityD5%-D95%were analysed.Main results.For the geometrical phantoms with rigid motion perpendicular to the beam and parallel to the magnetic field, a comparable dosimetric effect was observed independent of the magnetic field. Also for the five 4DCT(MRI) cases, the influence of motion was comparable for all magnetic field strengths with and without gantry angle correction. On average, the motion-induced decrease in CTVV95%from the static plan was 17.0% and 18.9% for 1.5 T and 0.5 T, respectively, and 19.9% without magnetic field.Significance.For the first time, this study investigates the combined impact of magnetic fields and respiratory motion on MR-guided proton therapy. The comparable dosimetric effects irrespective of magnetic field strength indicate that the effects of motion for future MR-guided proton therapy may not be worse than for conventional PBS proton therapy.

Comparing interplay effects in scanned proton therapy of lung cancer: Free breathing with various layer and volume rescanning versus respiratory gating with different gate widths.

PURPOSE: We investigated interplay effects and treatment time (TT) in scanned proton therapy for lung cancer patients. We compared free-breathing (FB) approaches with multiple rescanning strategies and respiratory-gating (RG) methods with various gating widths to identify the superior irradiation technique. METHODS: Plans were created with 4/1, 2/2, and 1/4 layered/volume rescans of FB (L4V1, L2V2, and L1V4), and 50%, 30%, and 10% gating widths of the total respiratory curves (G50, G30, and G10) of the RG plans with L4V1. We calculated 4-dimensional dynamic doses assuming a constant sinusoidal curve for six irradiation methods. The reconstructed doses per fraction were compared with planned doses in terms of dose differences in 99% clinical-target-volume (CTV) (ΔD99%), near-maximum dose differences (ΔD2%) at organs-at-risk (OARs), and TT. RESULTS: The mean/minimum CTV ΔD99% values for FB were -1.0%/-4.9%, -0.8%/-4.3%, and -0.1%/-1.0% for L4V1, L2V2, and L1V4, respectively. Those for RG were -0.3%/-1.7%, -0.1%/-1.0%, and 0.0%/-0.5% for G50, G30, and G10, respectively. The CTV ΔD99% of the RGs with less than 50% gate width and the FBs of L1V4 were within the desired tolerance (±3.0%), and the OARs ΔD2% for RG were lower than those for FB. The mean TTs were 90, 326, 824, 158, 203, and 422 s for L4V1, L2V2, L1V4, G50, G30, and G10, respectively. CONCLUSIONS: FB (L4V1) is the most efficient treatment, but not necessarily the optimal choice due to interplay effects. To satisfy both TT extensions and interplay, RG with a gate width as large as possible within safety limits is desirable.

Imaging Characteristics and Interpretation Strategy for Renal Hyperparathyroidism: A Retrospective 4-Dimensional Computed Tomography Study.

OBJECTIVE: Parathyroidectomy treats uncontrolled renal hyperparathyroidism (RHPT), requiring identification of all glands. Three types of enhancement are proposed. Type A lesions have higher arterial phase attenuation than the thyroid, type B lesions lack higher arterial phase attenuation but have lower venous phase attenuation, and type C lesions have neither higher arterial phase attenuation nor lower venous phase attenuation than the thyroid. We aimed to outline the image features of problematic parathyroid glands in RHPT and propose a 4-dimensional computed tomography (4DCT) interpretation algorithm. METHODS: This retrospective study involved data collection from patients with RHPT who underwent preoperative 4DCT for parathyroidectomy between January and November 2022. Pathologically confirmed parathyroid lesions were retrospectively identified on 4DCT according to the location and size described in the surgical notes. The attenuation of parathyroid lesions and the thyroid glands was assessed in 3 phases, and demographic data of the patients were collected. RESULTS: Ninety-seven pathology-proven parathyroid glands from 27 patients were obtained, with 86 retrospectively detected on 4DCT. In the arterial phase, the attenuation of parathyroid lesions in RHPT did not exceed that of the thyroid gland (P < .001). In the venous phase, parathyroid lesions demonstrated lower attenuation than the thyroid gland (P < .001). A total of 81 parathyroid lesions (94.2%) exhibited type B patterns. CONCLUSION: Unlike primary hyperparathyroidism, lesions in RHPT exhibited more type B enhancement, making them less readily identifiable in the arterial phase. Therefore, we propose a distinct imaging interpretation strategy to locate these problematic glands more efficiently.

A model that predicts a real-time tumour surface using intra-treatment skin surface and end-of-expiration and end-of-inhalation planning CT images.

OBJECTIVES: To develop a mapping model between skin surface motion and internal tumour motion and deformation using end-of-exhalation (EOE) and end-of-inhalation (EOI) 3D CT images for tracking lung tumours during respiration. METHODS: Before treatment, skin and tumour surfaces were segmented and reconstructed from the EOE and the EOI 3D CT images. A non-rigid registration algorithm was used to register the EOE skin and tumour surfaces to the EOI, resulting in a displacement vector field that was then used to construct a mapping model. During treatment, the EOE skin surface was registered to the real-time, yielding a real-time skin surface displacement vector field. Using the mapping model generated, the input of a real-time skin surface can be used to calculate the real-time tumour surface. The proposed method was validated with and without simulated noise on 4D CT images from 15 patients at Léon Bérard Cancer Center and the 4D-lung dataset. RESULTS: The average centre position error, dice similarity coefficient (DSC), 95%-Hausdorff distance and mean distance to agreement of the tumour surfaces were 1.29 mm, 0.924, 2.76 mm, and 1.13 mm without simulated noise, respectively. With simulated noise, these values were 1.33 mm, 0.920, 2.79 mm, and 1.15 mm, respectively. CONCLUSIONS: A patient-specific model was proposed and validated that was constructed using only EOE and EOI 3D CT images and real-time skin surface images to predict internal tumour motion and deformation during respiratory motion. ADVANCES IN KNOWLEDGE: The proposed method achieves comparable accuracy to state-of-the-art methods with fewer pre-treatment planning CT images, which holds potential for application in precise image-guided radiation therapy.

Myocardial analysis from routine 4D cardiac-CT to predict reverse remodeling and clinical outcomes after transcatheter aortic valve implantation.

PURPOSE: Our study aimed to determine whether 4D cardiac computed tomography (4DCCT) based quantitative myocardial analysis may improve risk stratification and can predict reverse remodeling (RRM) and mortality after transcatheter aortic valve implantation (TAVI). METHODS: Consecutive patients undergoing clinically indicated 4DCCT prior to TAVI were prospectively enrolled. 4DCCT-derived left- (LV) and right ventricular (RV), and left atrial (LA) dimensions, mass, ejection fraction (EF) and myocardial strain were evaluated to predict RRM and survival. RRM was defined by either relative increase in LVEF by 5% or relative decline in LV end diastolic diameter (LVEDD) by 5% assessed by transthoracic echocardiography prior TAVI, at discharge, and at 12-month follow-up compared to baseline prior to TAVI. RESULTS: Among 608 patients included in this study (55 % males, age 81 ± 6.6 years), RRM was observed in 279 (54 %) of 519 patients at discharge and in 218 (48 %) of 453 patients at 12-month echocardiography. While no CCT based measurements predicted RRM at discharge, CCT based LV mass index and LVEF independently predicted RRM at 12-month (ORadj = 1.012; 95 %CI:1.001-1.024; p = 0.046 and ORadj = 0.969; 95 %CI:0.943-0.996; p = 0.024, respectively). The most pronounced changes in LVEF and LVEDD were observed in patients with impaired LV function at baseline. In multivariable analysis age (HRadj = 1.037; 95 %CI:1.005-1.070; p = 0.022) and CCT-based LVEF (HRadj = 0.972; 95 %CI:0.945-0.999; p = 0.048) and LAEF (HRadj = 0.982; 95 %CI:0.968-0.996; p = 0.011) independently predicted survival. CONCLUSION: Comprehensive myocardial functional information derived from routine 4DCCT in patients with severe aortic stenosis undergoing TAVI could predict reverse remodeling and clinical outcomes at 12-month following TAVI.

Motion compensated cone-beam CT reconstruction using ana priorimotion model from CT simulation: a pilot study.

Objective. To combat the motion artifacts present in traditional 4D-CBCT reconstruction, an iterative technique known as the motion-compensated simultaneous algebraic reconstruction technique (MC-SART) was previously developed. MC-SART employs a 4D-CBCT reconstruction to obtain an initial model, which suffers from a lack of sufficient projections in each bin. The purpose of this study is to demonstrate the feasibility of introducing a motion model acquired during CT simulation to MC-SART, coined model-based CBCT (MB-CBCT).Approach. For each of 5 patients, we acquired 5DCTs during simulation and pre-treatment CBCTs with a simultaneous breathing surrogate. We cross-calibrated the 5DCT and CBCT breathing waveforms by matching the diaphragms and employed the 5DCT motion model parameters for MC-SART. We introduced the Amplitude Reassignment Motion Modeling technique, which measures the ability of the model to control diaphragm sharpness by reassigning projection amplitudes with varying resolution. We evaluated the sharpness of tumors and compared them between MB-CBCT and 4D-CBCT. We quantified sharpness by fitting an error function across anatomical boundaries. Furthermore, we compared our MB-CBCT approach to the traditional MC-SART approach. We evaluated MB-CBCT's robustness over time by reconstructing multiple fractions for each patient and measuring consistency in tumor centroid locations between 4D-CBCT and MB-CBCT.Main results. We found that the diaphragm sharpness rose consistently with increasing amplitude resolution for 4/5 patients. We observed consistently high image quality across multiple fractions, and observed stable tumor centroids with an average 0.74 ± 0.31 mm difference between the 4D-CBCT and MB-CBCT. Overall, vast improvements over 3D-CBCT and 4D-CBCT were demonstrated by our MB-CBCT technique in terms of both diaphragm sharpness and overall image quality.Significance. This work is an important extension of the MC-SART technique. We demonstrated the ability ofa priori5DCT models to provide motion compensation for CBCT reconstruction. We showed improvements in image quality over both 4D-CBCT and the traditional MC-SART approach.

PNMC: Four-dimensional conebeam CT reconstruction combining prior network and motion compensation.

Four-dimensional conebeam computed tomography (4D CBCT) is an efficient technique to overcome motion artifacts caused by organ motion during breathing. 4D CBCT reconstruction in a single scan usually divides projections into different groups of sparsely sampled data based on the respiratory phases. The reconstructed images within each group present poor image quality due to the limited number of projections. To improve the image quality of 4D CBCT in a single scan, we propose a novel reconstruction scheme that combines prior knowledge with motion compensation. We apply the reconstructed images of the full projections within a single routine as prior knowledge, providing structural information for the network to enhance the restoration structure. The prior network (PN-Net) is proposed to extract features of prior knowledge and fuse them with the sparsely sampled data using an attention mechanism. The prior knowledge guides the reconstruction process to restore the approximate organ structure and alleviates severe streaking artifacts. The deformation vector field (DVF) extracted using deformable image registration among different phases is then applied in the motion-compensated ordered-subset simultaneous algebraic reconstruction algorithm to generate 4D CBCT images. Proposed method has been evaluated using simulated and clinical datasets and has shown promising results by comparative experiment. Compared with previous methods, our approach exhibits significant improvements across various evaluation metrics.

Analysis of respiratory-induced motion trajectories of individual liver segments in patients with hepatocellular carcinoma.

PURPOSE: To analyze the respiratory-induced motion trajectories of each liver segment for hepatocellular carcinoma (HCC) to derive a more accurate internal margin and optimize treatment protocol selection. MATERIALS AND METHODS: Ten-phase-gated four-dimensional computed tomography (4DCT) scans of 14 patients with HCC were analyzed. For each patient, eight representative regions of interest (ROI) were delineated on each liver segment in all 10 phases. The coordinates of the center of gravity of each ROI were obtained for each phase, and then the respiratory motion in the left-right (LR), anteroposterior (AP), and craniocaudal (CC) directions was analyzed. Two sets of motion in each direction were also compared in terms of only two extreme phases and all 10 phases. RESULTS: Motion of less than 5 mm was detected in 12 (86%) and 10 patients (71%) in the LR and AP directions, respectively, while none in the CC direction. Motion was largest in the CC direction with a maximal value of 19.5 mm, with significant differences between liver segment 7 (S7) and other segments: S1 (p < 0.036), S2 (p < 0.041), S3 (p < 0.016), S4 (p < 0.041), and S5 (p < 0.027). Of the 112 segments, hysteresis >1 mm was observed in 4 (4%), 2 (2%), and 15 (13%) in the LR, AP, and CC directions, respectively, with a maximal value of 5.0 mm in the CC direction. CONCLUSION: A significant amount of respiratory motion was detected in the CC direction, especially in S7, and S8. Despite the small effect of hysteresis, it can be observed specifically in the right lobe. Therefore, caution is required when using 4DCT to determine IM using only end-inspiration and end-expiration. Understanding the respiratory motion in individual liver segments can be helpful when selecting an appropriate treatment protocol.

Which Localizing Strategy is the Most Cost-Effective in Reoperative Primary Hyperparathyroidism?

INTRODUCTION: 2%-10% of patients with primary hyperparathyroidism (PHPT) who undergo parathyroidectomy develop persistent/recurrent disease. The aim of this study was to determine which preoperative localization method is most cost-effective in reoperative PHPT. METHODS: Clinical decision analytic models comparing cost-effectiveness of localizing studies in reoperative PHPT were constructed using TreeAge Pro. Cost and probability assumptions were varied via Probabilistic Sensitivity Analysis (PSA) to test the robustness of the base case models. RESULTS: Base case analysis of model 1 revealed ultrasound (US)-guided fine-needle aspiration with PTH assay as most cost-effective after localizing US. This was confirmed on PSA of model 1. Model 2 showed four-dimensional computed tomography (4D-CT) as most cost-effective after negative US. If not localized by US, on PSA, 4D-CT was the next most cost-effective test. CONCLUSIONS: US-guided FNA with PTH is the most cost-effective confirmatory test after US localization. 4D-CT should be considered as the next best test after negative US.

Four-Dimensional Computed Tomography for Parathyroid Adenoma Localization: A Pre-Operative Imaging Protocol.

OBJECTIVE: Primary hyperparathyroidism (PHPT) affects approximately 0.86% of the population, with surgical resection as the treatment of choice. A 4D computed tomography (CT) is a highly effective tool in localizing parathyroid adenomas; however, there is currently no defined role for 4D CT when stratified against ultrasonography (USG) and nuclear medicine Technetium Sestamibi SPECT/CT (SES) imaging. STUDY DESIGN: Retrospective Study. SETTING: University Hospital. METHODS: All patients who underwent parathyroidectomy for PHPT between 2014 and 2019 at a single institution were reviewed. Patients who had a 4D CT were included. We compared outcomes of 4D CT as a second line imaging modality to those of USG and SES as first line modalities. An imaging algorithm was proposed based on these findings. RESULTS: There were 84 patients identified who had a 4D CT after unsuccessful first line imaging. A 4D CT localized parathyroid adenoma to the correct quadrant in 64% of cases, and to the correct laterality in 75% of cases. Obese patients had significantly lower rates of adenoma localization with USG (33.4%), compared to non-obese patients (67.5%; P = .006). In determining multigland disease the sensitivity of 4D CT was 86%, while the specificity was 87%. CONCLUSIONS: A 4D CT has impressive rates of accurate localization of parathyroid adenomas; however due to the radiation exposure involved, it should remain a second line imaging modality. PHPT patients should first be evaluated with USG, with 4D CT used if this is unsuccessful and patients are greater than 40 years old, have a high BMI, or are having revision surgery.

Real-time estimation of lung deformation from body surface using a general CoordConv CNN.

BACKGROUND AND OBJECTIVE: Estimating the three-dimensional (3D) deformation of the lung is important for accurate dose delivery in radiotherapy and precise surgical guidance in lung surgery navigation. Additional 4D-CT information is often required to eliminate the effect of individual variations and obtain a more accurate estimation of lung deformation. However, this results in increased radiation dose. Therefore, we propose a novel method that estimates lung tissue deformation from depth maps and two CT phases per patient. METHODS: The method models the 3D motion of each voxel as a linear displacement along a direction vector, with a variable amplitude and phase that depend on the voxel location. The direction vector and amplitude are derived from the registration of the CT images at the end-of-exhale (EOE) and the end-of-inhale (EOI) phases. The voxel phase is estimated by a neural network. Coordinate convolution (CoordConv) is used to fuse multimodal data and embed absolute position information. The network takes the front and side views as well as the previous phase views as inputs to enhance accuracy. RESULTS: We evaluate the proposed method on two datasets: DIR-Lab and 4D-Lung, and obtain average errors of 2.11 mm and 1.36 mm, respectively. The method achieves real-time performance of less than 7 ms per frame on a NVIDIA GeForce 2080Ti GPU. CONCLUSION: Compared with previous methods, our method achieves comparable or even better accuracy with less CT phases.

Technical note: Towards more realistic 4DCT(MRI) numerical lung phantoms.

BACKGROUND: Numerical 4D phantoms, together with associated ground truth motion, offer a flexible and comprehensive data set for realistic simulations in radiotherapy and radiology in target sites affected by respiratory motion. PURPOSE: We present an openly available upgrade to previously reported methods for generating realistic 4DCT lung numerical phantoms, which now incorporate respiratory ribcage motion and improved lung density representation throughout the breathing cycle. METHODS: Density information of reference CTs, toget her with motion from multiple breathing cycle 4DMRIs have been combined to generate synthetic 4DCTs (4DCT(MRI)s). Inter-subject correspondence between the CT and MRI anatomy was first established via deformable image registration (DIR) of binary masks of the lungs and ribcage. Ribcage and lung motions were extracted independently from the 4DMRIs using DIR and applied to the corresponding locations in the CT after post-processing to preserve sliding organ motion. In addition, based on the Jacobian determinant of the resulting deformation vector fields, lung densities were scaled on a voxel-wise basis to more accurately represent changes in local lung density. For validating this process, synthetic 4DCTs, referred to as 4DCT(CT)s, were compared to the originating 4DCTs using motion extracted from the latter, and the dosimetric impact of the new features of ribcage motion and density correction were analyzed using pencil beam scanned proton 4D dose calculations. RESULTS: Lung density scaling led to a reduction of maximum mean lung Hounsfield units (HU) differences from 45 to 12 HU when comparing simulated 4DCT(CT)s to their originating 4DCTs. Comparing 4D dose distributions calculated on the enhanced 4DCT(CT)s to those on the original 4DCTs yielded 2%/2 mm gamma pass rates above 97% with an average improvement of 1.4% compared to previously reported phantoms. CONCLUSIONS: A previously reported 4DCT(MRI) workflow has been successfully improved and the resulting numerical phantoms exhibit more accurate lung density representations and realistic ribcage motion.

Surrogate-driven respiratory motion model for projection-resolved motion estimation and motion compensated cone-beam CT reconstruction from unsorted projection data.

Objective.As the most common solution to motion artefact for cone-beam CT (CBCT) in radiotherapy, 4DCBCT suffers from long acquisition time and phase sorting error. This issue could be addressed if the motion at each projection could be known, which is a severely ill-posed problem. This study aims to obtain the motion at each time point and motion-free image simultaneously from unsorted projection data of a standard 3DCBCT scan.Approach.Respiration surrogate signals were extracted by the Intensity Analysis method. A general framework was then deployed to fit a surrogate-driven motion model that characterized the relation between the motion and surrogate signals at each time point. Motion model fitting and motion compensated reconstruction were alternatively and iteratively performed. Stochastic subset gradient based method was used to significantly reduce the computation time. The performance of our method was comprehensively evaluated through digital phantom simulation and also validated on clinical scans from six patients.Results.For digital phantom experiments, motion models fitted with ground-truth or extracted surrogate signals both achieved a much lower motion estimation error and higher image quality, compared with non motion-compensated results.For the public SPARE Challenge datasets, more clear lung tissues and less blurry diaphragm could be seen in the motion compensated reconstruction, comparable to the benchmark 4DCBCT images but with a higher temporal resolution. Similar results were observed for two real clinical 3DCBCT scans.Significance.The motion compensated reconstructions and motion models produced by our method will have direct clinical benefit by providing more accurate estimates of the delivered dose and ultimately facilitating more accurate radiotherapy treatments for lung cancer patients.

Comparative evaluation of a surface-based respiratory monitoring system against a pressure sensor for 4DCT image reconstruction in phantoms.

Four-dimensional computed tomography (4DCT), which relies on breathing-induced motion, requires realistic surrogate information of breathing variations to reconstruct the tumor trajectory and motion variability of normal tissues accurately. Therefore, the SimRT surface-guided respiratory monitoring system has been installed on a Siemens CT scanner. This work evaluated the temporal and spatial accuracy of SimRT versus our commonly used pressure sensor, AZ-733 V. A dynamic thorax phantom was used to reproduce regular and irregular breathing patterns acquired by SimRT and Anzai. Various parameters of the recorded breathing patterns, including mean absolute deviations (MAD), Pearson correlations (PC), and tagging precision, were investigated and compared to ground-truth. Furthermore, 4DCT reconstructions were analyzed to assess the volume discrepancy, shape deformation and tumor trajectory. Compared to the ground-truth, SimRT more precisely reproduced the breathing patterns with a MAD range of 0.37 ± 0.27 and 0.92 ± 1.02 mm versus Anzai with 1.75 ± 1.54 and 5.85 ± 3.61 mm for regular and irregular breathing patterns, respectively. Additionally, SimRT provided a more robust PC of 0.994 ± 0.009 and 0.936 ± 0.062 for all investigated breathing patterns. Further, the peak and valley recognition were found to be more accurate and stable using SimRT. The comparison of tumor trajectories revealed discrepancies up to 7.2 and 2.3 mm for Anzai and SimRT, respectively. Moreover, volume discrepancies up to 1.71 ± 1.62% and 1.24 ± 2.02% were found for both Anzai and SimRT, respectively. SimRT was validated across various breathing patterns and showed a more precise and stable breathing tracking, (i) independent of the amplitude and period, (ii) and without placing any physical devices on the patient's body. These findings resulted in a more accurate temporal and spatial accuracy, thus leading to a more realistic 4DCT reconstruction and breathing-adapted treatment planning.

Robust Deformable Image Registration Using Cycle-Consistent Implicit Representations.

Recent works in medical image registration have proposed the use of Implicit Neural Representations, demonstrating performance that rivals state-of-the-art learning-based methods. However, these implicit representations need to be optimized for each new image pair, which is a stochastic process that may fail to converge to a global minimum. To improve robustness, we propose a deformable registration method using pairs of cycle-consistent Implicit Neural Representations: each implicit representation is linked to a second implicit representation that estimates the opposite transformation, causing each network to act as a regularizer for its paired opposite. During inference, we generate multiple deformation estimates by numerically inverting the paired backward transformation and evaluating the consensus of the optimized pair. This consensus improves registration accuracy over using a single representation and results in a robust uncertainty metric that can be used for automatic quality control. We evaluate our method with a 4D lung CT dataset. The proposed cycle-consistent optimization method reduces the optimization failure rate from 2.4% to 0.0% compared to the current state-of-the-art. The proposed inference method improves landmark accuracy by 4.5% and the proposed uncertainty metric detects all instances where the registration method fails to converge to a correct solution. We verify the generalizability of these results to other data using a centerline propagation task in abdominal 4D MRI, where our method achieves a 46% improvement in propagation consistency compared with single-INR registration and demonstrates a strong correlation between the proposed uncertainty metric and registration accuracy.

Experimental validation of a 4D dynamic dose calculation model for proton pencil beam scanning without spot time stamp considering free-breathing motion.

PURPOSE: We developed a 4-dimensional dynamic dose (4DDD) calculation model for proton pencil beam scanning (PBS). This model incorporates the spill start time for all energies and uses the remaining irradiated spot time model instead of irradiated spot time logs. This study aimed to validate the calculation accuracy of a log file-based 4DDD model by comparing it with dose measurements performed under free-breathing conditions, thereby serving as an alternative approach to the conventional log file-based system. METHODS: Three cubic verification plans were created using a heterogeneous block phantom; these plans were created using 10 phase 4D-CT datasets of the phantom. The CIRS dynamic platform was used to simulate motion with amplitudes of 2.5, 3.75, and 5.0 mm. These plans consisted of eight- and two-layered rescanning techniques. The lateral profiles were measured using a 2D ionization chamber array (2D-array) and EBT3 Gafchromic films at four starting phases, including three sinusoidal curves (periods of 3, 4, and 6 s) and a representative patient curve during actual treatment. 4DDDs were calculated using in-house scripting that assigned a time stamp to each spot and performed dose accumulation using deformable image registration. Furthermore, to evaluate the impact of parameter selection on our 4DDD model calculations, simulations were performed assuming a ±10% change in irradiation time stamp (0.8 ± 0.08 s) and spot scan speed. We evaluated the 2D gamma index and the absolute point doses between the calculated values and the measurements. RESULTS: The 2D-array measurements revealed that the gamma scores for the static plans (no motion) and 4DDD plans exceeded 97.5% and 93.9% at 3%/3 mm, respectively. The average gamma score of the 4DDD plans was at least 96.1%. When using EBT3 films, the gamma scores of the 4DDD model exceeded 92.4% and 98.7% at 2%/2 mm and 3%/3 mm, respectively. Regarding the 4DDD point dose differences, more than 95% of the dose regions exhibited discrepancies within ±5.0% for 97.7% of the total points across all plans. The spot time assignment accuracy of our 4DDD model was acceptable even with ±10% sensitivity. However, the accuracy of the scan speed, when varied within ±10% sensitivity, was not acceptable (minimum gamma scores of 82.6% and maximum dose difference of 12.9%). CONCLUSIONS: Our 4DDD calculations under free-breathing conditions using amplitudes of less than 5.0 mm were in good agreement with the measurements regardless of the starting phases, breathing curve patterns (between 3 and 6 s periods), and varying numbers of layered rescanning. The proposed system allows us to evaluate actual irradiated doses in various breathing periods, amplitudes, and starting phases, even on PBS machines without the ability to record spot logs.

Faster and lower dose imaging: evaluating adaptive, constant gantry velocity and angular separation in fast low-dose 4D cone beam CT imaging.

BACKGROUND: The adoption of four-dimensional cone beam computed tomography (4DCBCT) for image-guided lung cancer radiotherapy is increasing, especially for hypofractionated treatments. However, the drawbacks of 4DCBCT include long scan times (∼240 s), inconsistent image quality, higher imaging dose than necessary, and streaking artifacts. With the emergence of linear accelerators that can acquire 4DCBCT scans in a short period of time (9.2 s) there is a need to examine the impact that these very fast gantry rotations have on 4DCBCT image quality. PURPOSE: This study investigates the impact of gantry velocity and angular separation between x-ray projections on image quality and its implication for fast low-dose 4DCBCT with emerging systems, such as the Varian Halcyon that provide fast gantry rotation and imaging. Large and uneven angular separation between x-ray projections is known to reduce 4DCBCT image quality through increased streaking artifacts. However, it is not known when angular separation starts degrading image quality. The study assesses the impact of constant and adaptive gantry velocity and determines the level when angular gaps impair image quality using state-of-the-art reconstruction methods. METHODS: This study considers fast low-dose 4DCBCT acquisitions (60-80 s, 200-projection scans). To assess the impact of adaptive gantry rotations, the angular position of x-ray projections from adaptive 4DCBCT acquisitions from a 30-patient clinical trial were analyzed (referred to as patient angular gaps). To assess the impact of angular gaps, variable and static angular gaps (20°, 30°, 40°) were introduced into evenly separated 200 projections (ideal angular separation). To simulate fast gantry rotations, which are on emerging linacs, constant gantry velocity acquisitions (9.2 s, 60 s, 120 s, 240 s) were simulated by sampling x-ray projections at constant intervals using the patient breathing traces from the ADAPT clinical trial (ACTRN12618001440213). The 4D Extended Cardiac-Torso (XCAT) digital phantom was used to simulate projections to remove patient-specific image quality variables. Image reconstruction was performed using Feldkamp-Davis-Kress (FDK), McKinnon-Bates (MKB), and Motion-Compensated-MKB (MCMKB) algorithms. Image quality was assessed using Structural Similarity-Index-Measure (SSIM), Contrast-to-Noise-Ratio (CNR), Signal-to-Noise-Ratio (SNR), Tissue-Interface-Width-Diaphragm (TIW-D), and Tissue-Interface-Width-Tumor (TIW-T). RESULTS: Patient angular gaps and variable angular gap reconstructions produced similar results to ideal angular separation reconstructions, while static angular gap reconstructions produced lower image quality metrics. For MCMKB-reconstructions, average patient angular gaps produced SSIM-0.98, CNR-13.6, SNR-34.8, TIW-D-1.5 mm, and TIW-T-2.0 mm, static angular gap 40° produced SSIM-0.92, CNR-6.8, SNR-6.7, TIW-D-5.7 mm, and TIW-T-5.9 mm and ideal produced SSIM-1.00, CNR-13.6, SNR-34.8, TIW-D-1.5 mm, and TIW-T-2.0 mm. All constant gantry velocity reconstructions produced lower image quality metrics than ideal angular separation reconstructions regardless of the acquisition time. Motion compensated reconstruction (MCMKB) produced the highest contrast images with low streaking artifacts. CONCLUSION: Very fast 4DCBCT scans can be acquired provided that the entire scan range is adaptively sampled, and motion-compensated reconstruction is performed. Importantly, the angular separation between x-ray projections within each individual respiratory bin had minimal effect on the image quality of fast low-dose 4DCBCT imaging. The results will assist the development of future 4DCBCT acquisition protocols that can now be achieved in very short time frames with emerging linear accelerators.

An investigation into the impact of volumetric rescanning and fractionation treatment on dose homogeneity in liver cancer proton therapy.

The Pencil Beam Scanning (PBS) technique in modern particle therapy offers a highly conformal dose distribution but poses challenges due to the interplay effect, an interaction between respiration-induced organ movement and PBS. This study evaluates the effectiveness of different volumetric rescanning strategies in mitigating this effect in liver cancer proton therapy. We used a Geant4-based Monte Carlo simulation toolkit, 'TOPAS,' and an image registration toolbox, 'Elastix,' to calculate 4D dose distributions from 5 patients' four-dimensional computed tomography (4DCT). We analyzed the homogeneity index (HI) value of the Clinical Tumor Volume (CTV) at different rescan numbers and treatment times. Our results indicate that dose homogeneity stabilizes at a low point after a week of treatment, implying that both rescanning and fractionation treatments help mitigate the interplay effect. Notably, an increase in the number of rescans doesn't significantly reduce the mean dose to normal tissue but effectively prevents high localized doses to tissue adjacent to the CTV. Rescanning techniques, based on statistical averaging, require no extra equipment or patient cooperation, making them widely accessible. However, the number of rescans, tumor location, diaphragm movement, and treatment fractionation significantly influence their effectiveness. Therefore, deciding the number of rescans should involve considering the number of beams, treatment fraction size, and total delivery time to avoid unnecessary treatment extension without significant clinical benefits. The results showed that 2-3 rescans are more clinically suitable for liver cancer patients undergoing proton therapy.