4D CT image artifacts affect local control in SBRT of lung and liver metastases

Deep learning-based conditional inpainting for restoration of artifact-affected 4D CT images

BACKGROUND

4D CT imaging is an essential component of radiotherapy of thoracic and abdominal tumors. 4D CT images are, however, often affected by artifacts that compromise treatment planning quality and image information reliability.

PURPOSE

In this work, deep learning (DL)-based conditional inpainting is proposed to restore anatomically correct image information of artifact-affected areas.

METHODS

The restoration approach consists of a two-stage process: DL-based detection of common interpolation (INT) and double structure (DS) artifacts, followed by conditional inpainting applied to the artifact areas. In this context, conditional refers to a guidance of the inpainting process by patient-specific image data to ensure anatomically reliable results. The study is based on 65 in-house 4D CT images of lung cancer patients (48 with only slight artifacts, 17 with pronounced artifacts) and two publicly available 4D CT data sets that serve as independent external test sets.

RESULTS

Automated artifact detection revealed a ROC-AUC of 0.99 for INT and of 0.97 for DS artifacts (in-house data). The proposed inpainting method decreased the average root mean squared error (RMSE) by 52 % (INT) and 59 % (DS) for the in-house data. For the external test data sets, the RMSE improvement is similar (50 % and 59 %, respectively). Applied to 4D CT data with pronounced artifacts (not part of the training set), 72 % of the detectable artifacts were removed.

CONCLUSIONS

The results highlight the potential of DL-based inpainting for restoration of artifact-affected 4D CT data. Compared to recent 4D CT inpainting and restoration approaches, the proposed methodology illustrates the advantages of exploiting patient-specific prior image information.

Optimized raw data selection for artifact reduction of breathing controlled four-dimensional sequence scanning

Background and purpose

Even with most breathing-controlled four-dimensional computed tomography (4DCT) algorithms image artifacts caused by single significant longer breathing still occur, resulting in negative consequences for radiotherapy. Our study presents first phantom examinations of a new optimized raw data selection and binning algorithm, aiming to improve image quality and geometric accuracy without additional dose exposure.

Materials and methods

To validate the new approach, phantom measurements were performed to assess geometric accuracy (volume fidelity, root mean square error, Dice coefficient of volume overlap) for one- and three-dimensional tumor motion trajectories with and without considering motion hysteresis effects. Scans without significantly longer breathing cycles served as references.

Results

Median volume deviations between optimized approach and reference of at maximum 1% were obtained considering all movements. In comparison, standard reconstruction yielded median deviations of 9%, 21% and 12% for one-dimensional, three-dimensional, and hysteresis motion, respectively. Measurements in one- and three-dimensional directions reached a median Dice coefficient of 0.970 ± 0.013 and 0.975 ± 0.012, respectively, but only 0.918 ± 0.075 for hysteresis motions averaged over all measurements for the optimized selection. However, for the standard reconstruction median Dice coefficients were 0.845 ± 0.200, 0.868 ± 0.205 and 0.915 ± 0.075 for one- and three-dimensional as well as hysteresis motions, respectively. Median root mean square errors for the optimized algorithm were 30 ± 16 HU2 and 120 ± 90 HU2 for three-dimensional and hysteresis motions, compared to 212 ± 145 HU2 and 130 ± 131 HU2 for the standard reconstruction.

Conclusions

The algorithm was proven to reduce 4DCT-related artifacts due to missing projection data without further dose exposure. An improvement in radiotherapy treatment planning due to better image quality can be expected.

Survey on fan-beam computed tomography for radiotherapy: Current implementation and future perspectives of motion management and surface guidance devices

Background and purpose

This work reports on the results of a survey performed on the use of computed tomography (CT) imaging for motion management, surface guidance devices, and their quality assurance (QA). Additionally, it details the collected user insights regarding professional needs in CT for radiotherapy. The purpose of the survey is to understand current practice, professional needs and future directions in the field of fan-beam CT in radiation therapy (RT).

Materials and methods

An online institutional survey was conducted between 1-Sep-2022 and 10-Oct-2022 among medical physics experts at Belgian and Dutch radiotherapy institutions, to assess the current status, challenges, and future directions of motion management and surface image-guided radiotherapy. The survey consisted of a maximum of 143 questions, with the exact number depending on participants' responses.

Results

The response rate was 66 % (31/47). Respiratory management was reported as standard practice in all but one institution; surface imaging during CT-simulation was reported in ten institutions. QA procedures are applied with varying frequencies and methodologies, primarily with commercial anatomy-like phantoms. Surface guidance users report employing commercial static and dynamic phantoms. Four main subjects are considered clinically important by the respondents: surface guidance, CT protocol optimisation, implementing gated imaging (4DCT, breath-hold), and a tattoo-less workflow.

Conclusions

The survey highlights the scattered pattern of QA procedures for respiratory motion management, indicating the need for well-defined, unambiguous, and practicable guidelines. Surface guidance is considered one of the most important techniques that should be implemented in the clinical radiotherapy simulation workflow.

Dose reduction in sequence scanning 4D CT imaging through respiratory signal-guided tube current modulation: A feasibility study

BACKGROUND

Respiratory signal-guided 4D CT sequence scanning such as the recently introduced Intelligent 4D CT (i4DCT) approach reduces image artifacts compared to conventional 4D CT, especially for irregular breathing. i4DCT selects beam-on periods during scanning such that data sufficiency conditions are fulfilled for each couch position. However, covering entire breathing cycles during beam-on periods leads to redundant projection data and unnecessary dose to the patient during long exhalation phases.

PURPOSE

We propose and evaluate the feasibility of respiratory signal-guided dose modulation (i.e., temporary reduction of the CT tube current) to reduce the i4DCT imaging dose while maintaining high projection data coverage for image reconstruction.

METHODS

The study is designed as an in-silico feasibility study. Dose down- and up-regulation criteria were defined based on the patients' breathing signals and their representative breathing cycle learned before and during scanning. The evaluation (including an analysis of the impact of the dose modulation criteria parameters) was based on 510 clinical 4D CT breathing curves. Dose reduction was determined as the fraction of the downregulated dose delivery time to the overall beam-on time. Furthermore, under the assumption of a 10-phase 4D CT and amplitude-based reconstruction, beam-on periods were considered negatively affected by dose modulation if the downregulation period covered an entire phase-specific amplitude range for a specific breathing phase (i.e., no appropriate reconstruction of the phase image possible for this specific beam-on period). Corresponding phase-specific amplitude bins are subsequently denoted as compromised bins.

RESULTS

Dose modulation resulted in a median dose reduction of 10.4% (lower quartile: 7.4%, upper quartile: 13.8%, maximum: 28.6%; all values corresponding to a default parameterization of the dose modulation criteria). Compromised bins were observed in 1.0% of the beam-on periods (72 / 7370 periods) and affected 10.6% of the curves (54/510 curves). The extent of possible dose modulation depends strongly on the individual breathing patterns and is weakly correlated with the median breathing cycle length (Spearman correlation coefficient 0.22, p < 0.001). Moreover, the fraction of beam-on periods with compromised bins is weakly anti-correlated with the patient's median breathing cycle length (Spearman correlation coefficient -0.24; p < 0.001). Among the curves with the 17% longest average breathing cycles, no negatively affected beam-on periods were observed.

CONCLUSION

Respiratory signal-guided dose modulation for i4DCT imaging is feasible and promises to significantly reduce the imaging dose with little impact on projection data coverage. However, the impact on image quality remains to be investigated in a follow-up study.

Deep learning-based lung image registration: A review

Lung image registration can effectively describe the relative motion of lung tissues, thereby helping to solve series problems in clinical applications. Since the lungs are soft and fairly passive organs, they are influenced by respiration and heartbeat, resulting in discontinuity of lung motion and large deformation of anatomic features. This poses great challenges for accurate registration of lung image and its applications. The recent application of deep learning (DL) methods in the field of medical image registration has brought promising results. However, a versatile registration framework has not yet emerged due to diverse challenges of registration for different regions of interest (ROI). DL-based image registration methods used for other ROI cannot achieve satisfactory results in lungs. In addition, there are few review articles available on DL-based lung image registration. In this review, the development of conventional methods for lung image registration is briefly described and a more comprehensive survey of DL-based methods for lung image registration is illustrated. The DL-based methods are classified according to different supervision types, including fully-supervised, weakly-supervised and unsupervised. The contributions of researchers in addressing various challenges are described, as well as the limitations of these approaches. This review also presents a comprehensive statistical analysis of the cited papers in terms of evaluation metrics and loss functions. In addition, publicly available datasets for lung image registration are also summarized. Finally, the remaining challenges and potential trends in DL-based lung image registration are discussed.

Results of a multicenter 4D computed tomography quality assurance audit: Evaluating image accuracy and consistency

Background and purpose

4D Computed Tomography (4DCT) technology captures the location and movement of tumors and nearby organs at risk over time. In this study, a multi-institutional multi-vendor 4DCT audit was initiated to assess the accuracy of current imaging protocols.

Materials and methods

Twelve centers, including thirteen scanners performed a 4DCT acquisition of a dynamic thorax phantom using the institution's own protocol with the in-house breathing monitoring system. Five regular and three irregular breathing patterns were used. Image acquisition and reconstruction were followed by automated image analysis with our in-house developed 4DCT QA program (QAMotion). CT number accuracy, volume deviation, amplitude deviation, and spatial integrity were assessed per pattern using both the segmented volumes and line profiles.

Results

Regular breathing curves showed relatively accurate results across all institutions, with mean volume and CT number deviations and median amplitude deviation below 2%, 5 HU and 2 mm, respectively. Results obtained for irregular patterns showed more variation across the institutions. Volume and CT number deviations co-occurred with a blurring of the sphere, interpolation, or double-structure artifacts that were confirmed through the line profiles. For some of the irregular patterns, amplitude deviations up to 6 mm were observed. Maximum Intensity Projection (MaxIP) correctly captured the applied motion amplitude with deviations across all institutions within 2 mm except for double amplitude pattern.

Conclusions

All centers invited to participate in the audit responded positively, highlighting the need for a comprehensive yet easy-to-execute 4DCT quality assurance program. The largest variances between the results from one institution to another confirmed that a standardized 4DCT audit is warranted.

Accelerated respiratory-resolved 4D-MRI with separable spatio-temporal neural networks

BACKGROUND

Respiratory-resolved four-dimensional magnetic resonance imaging (4D-MRI) provides essential motion information for accurate radiation treatments of mobile tumors. However, obtaining high-quality 4D-MRI suffers from long acquisition and reconstruction times.

PURPOSE

To develop a deep learning architecture to quickly acquire and reconstruct high-quality 4D-MRI, enabling accurate motion quantification for MRI-guided radiotherapy (MRIgRT).

METHODS

A small convolutional neural network called MODEST is proposed to reconstruct 4D-MRI by performing a spatial and temporal decomposition, omitting the need for 4D convolutions to use all the spatio-temporal information present in 4D-MRI. This network is trained on undersampled 4D-MRI after respiratory binning to reconstruct high-quality 4D-MRI obtained by compressed sensing reconstruction. The network is trained, validated, and tested on 4D-MRI of 28 lung cancer patients acquired with a T1-weighted golden-angle radial stack-of-stars (GA-SOS) sequence. The 4D-MRI of 18, 5, and 5 patients were used for training, validation, and testing. Network performances are evaluated on image quality measured by the structural similarity index (SSIM) and motion consistency by comparing the position of the lung-liver interface on undersampled 4D-MRI before and after respiratory binning. The network is compared to conventional architectures such as a U-Net, which has 30 times more trainable parameters.

RESULTS

MODEST can reconstruct high-quality 4D-MRI with higher image quality than a U-Net, despite a thirty-fold reduction in trainable parameters. High-quality 4D-MRI can be obtained using MODEST in approximately 2.5 min, including acquisition, processing, and reconstruction.

CONCLUSION

High-quality accelerated 4D-MRI can be obtained using MODEST, which is particularly interesting for MRIgRT.

A comprehensive quality assurance program for four-dimensional computed tomography in radiotherapy

This study aimed to develop and validate a comprehensive, reproducible and automatic 4DCT Quality Assurance (QA) workflow (QAMotion) that evaluates image accuracy across various regular and irregular breathing patterns. Volume and amplitude deviations, CT number accuracy, and spatial integrity were used as evaluation metrics. For repeatability tests, tolerances were respected with a mean CT number deviation < 10 HU, volume deviation < 2% and diameter and amplitude deviation < 2 mm except for irregular amplitude curves for which an amplitude deviation up to 6 mm was measured. QAMotion was able to flag image artefacts for our clinical 4DCT system.

The Role of Stereotactic Body Radiation Therapy in the Management of Liver Metastases

The liver is a common site for metastatic spread for various primary tumor histologies. Stereotactic body radiation therapy (SBRT) is a non-invasive treatment technique with broad patient candidacy for the ablation of tumors in the liver and other organs. SBRT involves focused, high-dose radiation therapy delivered in one to several treatments, resulting in high rates of local control. Use of SBRT for ablation of oligometastatic disease has increased in recent years and emerging prospective data have demonstrated improvements in progression free and overall survival in some settings. When delivering SBRT to liver metastases, clinicians must balance the priorities of delivering ablative tumor dosing while respecting dose constraints to surrounding organs at risk (OARs). Motion management techniques are crucial for meeting dose constraints, ensuring low rates of toxicity, maintaining quality of life, and can allow for dose escalation. Advanced radiotherapy delivery approaches including proton therapy, robotic radiotherapy, and real-time MR-guided radiotherapy may further improve the accuracy of liver SBRT. In this article, we review the rationale for oligometastases ablation, the clinical outcomes with liver SBRT, tumor dose and OAR considerations, and evolving strategies to improve liver SBRT delivery.

Cardiac motion and its dosimetric impact during radioablation for refractory ventricular tachycardia

INTRODUCTION

Cardiac radioablation (CR) is a noninvasive treatment option for patients with refractory ventricular tachycardia (VT) during which high doses of radiation, typically 25 Gy, are delivered to myocardial scar. In this study, we investigate motion from cardiac cycle and evaluate the dosimetric impact in a cohort of patients treated with CR.

METHODS

This retrospective study included eight patients treated at our institution who had respiratory-correlated and ECG-gated 4DCT scans acquired within 2 weeks of CR. Deformable image registration was applied between maximum systole (SYS) and diastole (DIAS) CTs to assess cardiac motion. The average respiratory-correlated CT (AVG_resp ) was deformably registered to the average cardiac (AVG_cardiac ), SYS, and DIAS CTs, and contours were propagated using the deformation vector fields (DVFs). Finally, the original treatment plan was recalculated on the deformed AVG_resp CT for dosimetric assessment.

RESULTS

Motion magnitudes were measured as the mean (SD) value over the DVFs within each structure. Displacement during the cardiac cycle for all chambers was 1.4 (0.9) mm medially/laterally (ML), 1.6 (1.0) mm anteriorly/posteriorly (AP), and 3.0 (2.8) mm superiorly/inferiorly (SI). Displacement for the 12 distinct clinical target volumes (CTVs) was 1.7 (1.5) mm ML, 2.4 (1.1) mm AP, and 2.1 (1.5) SI. Displacements between the AVG_resp and AVG_cardiac scans were 4.2 (2.0) mm SI and 5.8 (1.4) mm total. Dose recalculations showed that cardiac motion may impact dosimetry, with dose to 95% of the CTV dropping from 27.0 (1.3) Gy on the AVG_resp to 20.5 (7.1) Gy as estimated on the AVG_cardiac .

CONCLUSIONS

Cardiac CTV motion in this patient cohort is on average below 3 mm, location-dependent, and when not accounted for in treatment planning may impact target coverage. Further study is needed to assess the impact of cardiac motion on clinical outcomes.

4D lung MRI with high-isotropic-resolution using half-spoke (UTE) and full-spoke 3D radial acquisition and temporal compressed sensing reconstruction

Objective. To develop a respiratory motion-resolved four-dimensional (4D) magnetic resonance imaging (MRI) technique with high-isotropic-resolution (1.1 mm) using 3D radial sampling, camera-based respiratory motion sensing, and temporal compressed sensing reconstruction for lung cancer imaging.Approach. Free-breathing half- and full-spoke 3D golden-angle radial acquisitions were performed on eight healthy volunteers and eight patients with lung tumors of varying size. A back-and-forth k-space ordering between consecutive interleaves of the 3D radial acquisition was performed to minimize eddy current-related artifacts. Data were sorted into respiratory motion states using camera-based motion navigation and 4D images were reconstructed using temporal compressed sensing to reduce scan time. Normalized sharpness indices of the diaphragm, apparent signal-to-noise ratio (aSNR) and contrast-to-noise ratio (CNR) of the lung tumor (patients only), liver, and aortic arch were compared between half- and full-spoke 4D MRI images to evaluate the impact of respiratory motion and image contrast on 4D MRI image quality. Respiration-induced changes in lung volumes and center of mass shifts were compared between half- and full-spoke 4D MRI measurements. In addition, the motion measurements from 4D MRI and the same-day 4D CT were presented in one of the lung tumor patients.Main results. Half-spoke 4D MRI provides better visualization of the lung parenchyma, while full-spoke 4D MRI presents sharper diaphragm images and higher aSNR and CNR in the lung tumor, liver, and aortic arch. Lung volume changes and center of mass shifts measured by half- and full-spoke 4D MRI were not statistically different. For the patient with 4D MRI and same-day 4D CT, lung volume changes and center of mass shifts were generally comparable.Significance. This work demonstrates the feasibility of a motion-resolved 4D MRI technique with high-isotropic-resolution using 3D radial acquisition, camera-based respiratory motion sensing, and temporal compressed sensing reconstruction for treatment planning and motion monitoring in radiotherapy of lung cancer.

CArdiac and REspiratory adaptive Computed Tomography (CARE-CT): a proof-of-concept digital phantom study

Current respiratory 4DCT imaging for high-dose rate thoracic radiotherapy treatments are negatively affected by the complex interaction of cardiac and respiratory motion. We propose an imaging method to reduce artifacts caused by thoracic motion, CArdiac and REspiratory adaptive CT (CARE-CT), that monitors respiratory motion and ECG signals in real-time, triggering CT acquisition during combined cardiac and respiratory bins. Using a digital phantom, conventional 4DCT and CARE-CT acquisitions for nineteen patient-measured physiological traces were simulated. Ten respiratory bins were acquired for conventional 4DCT scans and ten respiratory bins during cardiac diastole were acquired for CARE-CT scans. Image artifacts were quantified for 10 common thoracic organs at risk (OAR) substructures using the differential normalized cross correlation between axial slices (ΔNCC), mean squared error (MSE) and sensitivity. For all images, on average, CARE-CT improved the ΔNCC for 18/19 and the MSE and sensitivity for all patient traces. The ΔNCC was reduced for all cardiac OARs (mean reduction 21%). The MSE was reduced for all OARs (mean reduction 36%). In the digital phantom study, the average scan time was increased from 1.8 ± 0.4 min to 7.5 ± 2.2 min with a reduction in average beam on time from 98 ± 28 s to 45 s using CARE-CT compared to conventional 4DCT. The proof-of-concept study indicates the potential for CARE-CT to image the thorax in real-time during the cardiac and respiratory cycle simultaneously, to reduce image artifacts for common thoracic OARs.

A comprehensive quality assurance procedure for 4D CT commissioning and periodic QA

PURPOSE

The 4D computed tomography (CT) simulation is an essential procedure for tumors exhibiting breathing-induced motion. However, to date there are no established guidelines to assess the characteristics of existing systems and to describe meaningful performance. We propose a commissioning quality assurance (QA) protocol consisting of measurements and acquisitions that assess the mechanical and computational operation for 4D CT with both phase and amplitude-based reconstructions, for regular and irregular respiratory patterns.

METHODS

The 4D CT scans of a QUASAR motion phantom were acquired for both regular and irregular breathing patterns. The hardware consisted of the Canon Aquilion Exceed LB CT scanner used in conjunction with the Anzai laser motion monitoring system. The nominal machine performance and reconstruction were demonstrated with measurements using regular breathing patterns. For irregular breathing patterns the performance was quantified through the analysis of the target motion in the superior and inferior directions, and the volume of the internal target volume (ITV). Acquisitions were performed using multiple pitches and the reconstructions were performed using both phase and amplitude-based binning.

RESULTS

The target was accurately captured during regular breathing. For the irregular breathing, the measured ITV exceeded the nominal ITV parameters in all scenarios, but all deviations were less than the reconstructed slice thickness. The mismatch between the nominal pitch and the actual breathing rate did not affect markedly the size of the ITV. Phase and normalized amplitude binning performed similarly.

CONCLUSIONS

We demonstrated a framework for measuring and quantifying the initial performance of 4D CT simulation scans that can also be applied during periodic QAs. The regular breathing provided confidence that the hardware and the software between the systems performs adequately. The irregular breathing data suggest that the system may be expected to capture in excess the target motion and geometry, but the deviation is expected to be within the slice thickness.

Quality assurance of a breathing controlled four-dimensional computed tomography algorithm

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Initial quality assurance of a novel breathing-controlled four-dimensional computed tomography algorithm.

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Assessment of geometry, motion representation and image quality for regular and irregular breathing.

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No clinically relevant differences in results for regular and irregular breathing.

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Only minor differences in tumor geometry representation and image quality compared to static three-dimensional computed tomography.

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Table flexion has no clinically relevant impact on geometry representation.

Background & purpose

Material & methods

Results

Conclusions

Towards mid-position based Stereotactic Body Radiation Therapy on the MR-linac for central lung tumours

Background and purpose: Central lung tumours can be treated by magnetic resonance (MR)-guided radiotherapy. Complications might be reduced by decreasing the Planning Target Volume (PTV) using mid-position (midP)-based planning instead of Internal Target Volume (ITV)-based planning. In this study, we aimed to verify a method to automatically derive patient-specific PTV margins for midP-based planning, and show dosimetric robustness of midP-based planning for a 1.5T MR-linac.

Materials and methods: Central(n = 12) and peripheral(n = 4) central lung tumour cases who received 8x7.5 Gy were included. A midP-image was reconstructed from ten phases of the 4D-Computed Tomography using deformable image registration. The Gross Tumor Volume (GTV) was delineated on the midP-image and the PTV margin was automatically calculated based on van Herk’s margin recipe, treating the standard deviation of all Deformation Vector Fields, within the GTV, as random error component. Dosimetric robustness of midP-based planning for MR-linac using automatically derived margins was verified by 4D dose-accumulation. MidP-based plans were compared to ITV-based plans. Automatically derived margins were verified with manually derived margins.

Results: The mean D95% target coverage in GTV + 2 mm was 59.9 Gy and 62.0 Gy for midP- and ITV-based central lung plans, respectively. The mean lung dose was significantly lower for midP-based treatment plans (difference:-0.3 Gy; p<0.042). Automatically derived margins agreed within one millimeter with manually derived margins.

Conclusions: This retrospective study indicates that mid-position-based treatment plans for central lung Stereotactic Body Radiation Therapy yield lower OAR doses compared to ITV-based treatment plans on the MR-linac. Patient-specific GTV-to-PTV margins can be derived automatically and result in clinically acceptable target coverage.

First clinical evaluation of breathing controlled four-dimensional computed tomography imaging

Background and Purpose

Four-dimensional computed tomography (4DCT) has become an essential part of radiotherapy planning but is often affected by artifacts. A new breathing controlled 4DCT (i4DCT) algorithm has been introduced. This study aims to present the first clinical data and to evaluate the achieved image quality, projection data coverage and beam-on time.

Material & Methods

The analysis included i4DCT data for 129 scans of patients with thoracic tumors. Projection data coverage and beam-on time were evaluated. Additionally, image quality was exemplarily discussed and rated by ten clinical experts with a 5-score-scale for 30 patients with large variations in their breathing pattern (‘challenging subgroup’). Rated images were reconstructed amplitude- and phase-based.

Results

Expert scoring revealed that 78% (amplitude-based) and 63% (phase-based) of the challenging subgroup were artifact-free (rating ≥4). For the entire cohort, average beam-on time per couch position was 4.9 ± 1.6 s. For the challenging subgroup, time increased slightly but not significantly compared to the remaining patients (5.1 s vs. 4.9 s; p = 0.64). Median projection data coverage was 93% and 94% for inhalation and exhalation, respectively, for the entire cohort. The comparison for the subgroup and the remaining patients revealed a small but significant decrease of the median coverage values for the challenging cases (inhalation: 90% vs. 94%, p = 0.02; exhalation: 93% vs. 94%, p = 0.02).

Conclusions

This first clinical evaluation of i4DCT shows very promising results in terms of image quality and projection data coverage. The results agree with and support the results of previous i4DCT phantom studies.

Comparative Evaluation of 4-Dimensional Computed Tomography and 4-Dimensional Magnetic Resonance Imaging to Delineate the Target of Primary Liver Cancer

Purpose: To evaluate the feasibility of 4-dimensional magnetic resonance imaging (4DMRI) in establishing the target of primary liver cancer in comparison with 4-dimensional computed tomography (4DCT). Methods and Materials: A total of 23 patients with primary liver cancer who received radiotherapy were selected, and 4DCT and T2w-4DMRI simulations were conducted to obtain 4DCT and T2w-4DMRI simulation images. The 4DCT and T2w-4DMRI data were sorted into 10 and 8 respiratory phase bins, respectively. The liver and gross tumor volumes (GTVs) were delineated in all images using programmed clinical workflows under tumor delineation guidelines. The internal organs at risk volumes (IRVs) and internal target volumes (ITVs) were the unions of all the phase livers and GTVs, respectively. Then, the artifacts, liver volume, GTV, and motion range in 4DCT and T2w-4DMRI were compared. Results: The mean GTV volume based on 4DMRI was 136.42 ± 231.27 cm³, which was 25.04 cm³ (15.5%) less than that of 4DCT (161.46 ± 280.29 cm³). The average volume of ITV determined by 4DMRI was 166.12 ± 270.43 cm³, which was 22.44 cm³ (11.9%) less than that determined by 4DCT (188.56 ± 307.57 cm³). Liver volume and IRV in 4DMRI increased by 4.0% and 6.6%, respectively, compared with 4DCT. The difference in tumor motion by T2w-4DMRI based on the centroid was greater than that of 4DCT in the L/R, A/P, and S/I directions, and the average displacement differences were 2.6, 2.8, and 6.9 mm, respectively. The severe artifacts in 4DCT were 47.8% (11/23) greater than in 4DMRI 17.4% (4/23). Conclusions: Compared with 4DCT, T2-weighted and navigator-triggered 4DMRI produces fewer artifacts and larger motion differences in hepatic intrafraction tumors, which is a feasible technique for primary liver cancer treatment planning.

Technical Note: Volumetric computed tomography for radiotherapy simulation and treatment planning

Purpose

For lung and liver tumors requiring radiotherapy, motion artifacts are common in 4D‐CT images due to the small axial field‐of‐view (aFOV) of conventional CT scanners. This may negatively impact contouring and dose calculation accuracy and could lead to a geographic miss during treatment. Recent advancements in volumetric CT (vCT) enable an aFOV up to 160 mm in a single rotation, which may reduce motion artifacts. However, the impact of large aFOV on CT number required for dose calculation needs to be evaluated before clinical implementation. The objective of this study was to determine the utility of a 256‐slice vCT scanner for 4D‐CT simulation by evaluating image quality and generating relative electron density (RED) curves.

Methods

Images were acquired on a 256‐slice GE Revolution CT scanner with 40 mm, 80 mm, 120 mm, 140 mm, and 160 mm aFOV. Image quality was assessed by evaluating CT number linearity, uniformity, noise, and low‐contrast resolution. The relationship between each quality metric and aFOV was assessed.

Results

CT number linearity, uniformity, noise, and low‐contrast resolution were within the expected range for each image set, except CT number in Teflon and Delrin, which were underestimated. Spearman correlation coefficient (ρ) showed that the CT number for Teflon (ρ = 1.0, p = 0.02), Delrin (ρ = 1.0, p = 0.02), and air (ρ = 1.0, p = 0.02) was significantly related to aFOV, while all other measurements were not. The measured deviations from expected values were not clinically significant.

Conclusion

These results suggest that vCT can be used for CT simulation for radiation treatment planning.

Geodesic density regression for correcting 4DCT pulmonary respiratory motion artifacts

Pulmonary respiratory motion artifacts are common in four-dimensional computed tomography (4DCT) of lungs and are caused by missing, duplicated, and misaligned image data. This paper presents a geodesic density regression (GDR) algorithm to correct motion artifacts in 4DCT by correcting artifacts in one breathing phase with artifact-free data from corresponding regions of other breathing phases. The GDR algorithm estimates an artifact-free lung template image and a smooth, dense, 4D (space plus time) vector field that deforms the template image to each breathing phase to produce an artifact-free 4DCT scan. Correspondences are estimated by accounting for the local tissue density change associated with air entering and leaving the lungs, and using binary artifact masks to exclude regions with artifacts from image regression. The artifact-free lung template image is generated by mapping the artifact-free regions of each phase volume to a common reference coordinate system using the estimated correspondences and then averaging. This procedure generates a fixed view of the lung with an improved signal-to-noise ratio. The GDR algorithm was evaluated and compared to a state-of-the-art geodesic intensity regression (GIR) algorithm using simulated CT time-series and 4DCT scans with clinically observed motion artifacts. The simulation shows that the GDR algorithm has achieved significantly more accurate Jacobian images and sharper template images, and is less sensitive to data dropout than the GIR algorithm. We also demonstrate that the GDR algorithm is more effective than the GIR algorithm for removing clinically observed motion artifacts in treatment planning 4DCT scans. Our code is freely available at https://github.com/Wei-Shao-Reg/GDR.

Liver SBRT with active motion-compensation results in excellent local control for liver oligometastases: An outcome analysis of a pooled multi-platform patient cohort

BACKGROUND

Local treatment of metastases in combination with systemic therapy can prolong survival of oligo-metastasized patients. To fully exploit this potential, safe and effective treatments are needed to ensure long-term metastases control. Stereotactic body radiotherapy (SBRT) is one means, however, for moving liver tumors correct delivery of high doses is challenging. After validating equal in-vivo treatment accuracy, we analyzed a pooled multi-platform liver-SBRT-database for clinical outcome.

METHODS

Local control (LC), progression-free interval (PFI), overall survival (OS), predictive factors and toxicity was evaluated in 135 patients with 227 metastases treated by gantry-based SBRT (deep-inspiratory breath-hold-gating; n = 71) and robotic-based SBRT (fiducial-tracking, n = 156) with mean gross tumor volume biological effective dose (GTV-BED_α/β=10Gy) of 146.6 Gy₁₀.

RESULTS

One-, and five-year LC was 90% and 68.7%, respectively. On multivariate analysis, LC was significantly predicted by colorectal histology (p = 0.006). Median OS was 20 months with one- and two-year OS of 67% and 37%. On multivariate analysis, ECOG-status (p = 0.003), simultaneous chemotherapy (p = 0.003), time from metastasis detection to SBRT-treatment (≥2months; p = 0.021) and LC of the treated metastases (≥12 months, p < 0.009) were significant predictors for OS. One- and two-year PFI were 30.5% and 14%. Acute toxicity was mild and rare (14.4% grade I, 2.3% grade II, 0.6% grade III). Chronic °III/IV toxicities occurred in 1.1%.

CONCLUSIONS

Patient selection, time to treatment and sufficient doses are essential to achieve optimal outcome for SBRT with active motion compensation. Local control appears favorable compared to historical control. Long-term LC of the treated lesions was associated with longer overall survival.

Technical Note: Investigating interplay effects in pencil beam scanning proton therapy with a 4D XCAT phantom within the RayStation treatment planning system

PURPOSE

Pencil beam scanning (PBS) for moving targets is known to be impacted by interplay effects. Four-dimensional computed tomography (4DCT)-based motion evaluation is crucial for understanding interplay and developing mitigation strategies. Availability of high-quality 4DCTs with variable breathing traces is limited. Purpose of this work is the development of a framework for interplay analysis using 4D-XCAT phantoms in conjunction with time-resolved irradiation patterns in a commercial treatment planning system (TPS). Four-dimensional dynamically accumulated dose distributions (4DDDs) are simulated in an in-silico study for a PBS liver treatment.

METHODS

An XCAT phantom with 50 phases, varying linearly in amplitude each by 1 mm, was combined with the RayStation TPS (7.99.10). Deformable registration was used with time-resolved dose calculation, mapping XCAT phases to motion signals. To illustrate the applicability of the method a two-field liver irradiation plan was used. A variety sin⁴ type motion signals, varying in amplitude (1-20 mm), period (1.6-5.2 s) and phase (0-2π) were applied. Either single variable variations or random combinations were selected. The interplay effect within a clinical target (5 cm diameter) was characterized in terms of homogeneity index (HI5), with and without five paintings. In total 2092 scenarios were analyzed within RayStation.

RESULTS

A framework is presented for interplay research, allowing for flexibility in determining motion management techniques, increasing reproducibility, and enabling comparisons of different methods. A case study showed the interplay effect was correlated with amplitude and strongly affected by the starting phase, leading to large variance. The average of all scenarios (single fraction) resulted in HI5 of 0.31 (±0.11), while introduction of five times layered repainting reduced this to 0.11(±0.03).

CONCLUSION

The developed framework, which uses the XCAT phantom and RayStation, allows detailed analysis of motion in context of PBS with comparable results to clinical cases. Flexibility in defining motion patterns for detailed anatomies in combination with time-resolved dose calculation, facilitates investigation of optimal treatment and motion mitigation strategies.

Comparison of intelligent 4D CT sequence scanning and conventional spiral 4D CT: a first comprehensive phantom study

4D CT imaging is a cornerstone of 4D radiotherapy treatment. Clinical 4D CT data are, however, often affected by severe artifacts. The artifacts are mainly caused by breathing irregularity and retrospective correlation of breathing phase information and acquired projection data, which leads to insufficient projection data coverage to allow for proper reconstruction of 4D CT phase images. The recently introduced 4D CT approach i4DCT (intelligent 4D CT sequence scanning) aims to overcome this problem by breathing signal-driven tube control. The present motion phantom study describes the first in-depth evaluation of i4DCT in a real-world scenario. Twenty-eight 4D CT breathing curves of lung and liver tumor patients with pronounced breathing irregularity were selected to program the motion phantom. For every motion pattern, 4D CT imaging was performed with i4DCT and a conventional spiral 4D CT mode. For qualitative evaluation, the reconstructed 4D CT images were presented to clinical experts, who scored image quality. Further quantitative evaluation was based on established image intensity-based artifact metrics to measure (dis)similarity of neighboring image slices. In addition, beam-on and scan times of the scan modes were analyzed. The expert rating revealed a significantly higher image quality for the i4DCT data. The quantitative evaluation further supported the qualitative: While 20% of the slices of the conventional spiral 4D CT images were found to be artifact-affected, the corresponding fraction was only 4% for i4DCT. The beam-on time (surrogate of imaging dose) did not significantly differ between i4DCT and spiral 4D CT. Overall i4DCT scan times (time between first beam-on and last beam-on event, including scan breaks to compensate for breathing irregularity) were, on average, 53% longer compared to spiral CT. Thus, the results underline that i4DCT significantly improves 4D CT image quality compared to standard spiral CT scanning in the case of breathing irregularity during scanning.