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Zhong H, Pursley JM, Rong Y. Deformable dose accumulation is required for adaptive radiotherapy practice. J Appl Clin Med Phys 2024:e14457. [PMID: 39031438 DOI: 10.1002/acm2.14457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Accepted: 07/08/2024] [Indexed: 07/22/2024] Open
Affiliation(s)
- Hualiang Zhong
- Department of Radiation Oncology, Medical College of Wisconsin, MILWAUKEE, Wisconsin, USA
| | - Jennifer M Pursley
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Yi Rong
- Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA
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Li G, Wang G, Wei W, Li Z, Xiao Q, He H, Luo D, Chen L, Li J, Zhang X, Song Y, Bai S. Cardiorespiratory motion characteristics and their dosimetric impact on cardiac stereotactic body radiotherapy. Med Phys 2024. [PMID: 38994881 DOI: 10.1002/mp.17284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 06/19/2024] [Accepted: 06/20/2024] [Indexed: 07/13/2024] Open
Abstract
BACKGROUND Cardiac stereotactic body radiotherapy (CSBRT) is an emerging and promising noninvasive technique for treating refractory arrhythmias utilizing highly precise, single or limited-fraction high-dose irradiations. This method promises to revolutionize the treatment of cardiac conditions by delivering targeted therapy with minimal exposure to surrounding healthy tissues. However, the dynamic nature of cardiorespiratory motion poses significant challenges to the precise delivery of dose in CSBRT, introducing potential variabilities that can impact treatment efficacy. The complexities of the influence of cardiorespiratory motion on dose distribution are compounded by interplay and blurring effects, introducing additional layers of dose uncertainty. These effects, critical to the understanding and improvement of the accuracy of CSBRT, remain unexplored, presenting a gap in current clinical literature. PURPOSE To investigate the cardiorespiratory motion characteristics in arrhythmia patients and the dosimetric impact of interplay and blurring effects induced by cardiorespiratory motion on CSBRT plan quality. METHODS The position and volume variations in the substrate target and cardiac substructures were evaluated in 12 arrhythmia patients using displacement maximum (DMX) and volume metrics. Moreover, a four-dimensional (4D) dose reconstruction approach was employed to examine the dose uncertainty of the cardiorespiratory motion. RESULTS Cardiac pulsation induced lower DMX than respiratory motion but increased the coefficient of variation and relative range in cardiac substructure volumes. The mean DMX of the substrate target was 0.52 cm (range: 0.26-0.80 cm) for cardiac pulsation and 0.82 cm (range: 0.32-2.05 cm) for respiratory motion. The mean DMX of the cardiac structure ranged from 0.15 to 1.56 cm during cardiac pulsation and from 0.35 to 1.89 cm during respiratory motion. Cardiac pulsation resulted in an average deviation of -0.73% (range: -4.01%-4.47%) in V25 between the 3D and 4D doses. The mean deviations in the homogeneity index (HI) and gradient index (GI) were 1.70% (range: -3.10%-4.36%) and 0.03 (range: -0.14-0.11), respectively. For cardiac substructures, the deviations in D50 due to cardiac pulsation ranged from -1.88% to 1.44%, whereas the deviations in Dmax ranged from -2.96% to 0.88% of the prescription dose. By contrast, the respiratory motion led to a mean deviation of -1.50% (range: -10.73%-4.23%) in V25. The mean deviations in HI and GI due to respiratory motion were 4.43% (range: -3.89%-13.98%) and 0.18 (range: -0.01-0.47) (p < 0.05), respectively. Furthermore, the deviations in D50 and Dmax in cardiac substructures for the respiratory motion ranged from -0.28% to 4.24% and -4.12% to 1.16%, respectively. CONCLUSIONS Cardiorespiratory motion characteristics vary among patients, with the respiratory motion being more significant. The intricate cardiorespiratory motion characteristics and CSBRT plan complexity can induce substantial dose uncertainty. Therefore, assessing individual motion characteristics and 4D dose reconstruction techniques is critical for implementing CSBRT without compromising efficacy and safety.
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Affiliation(s)
- Guangjun Li
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Guangyu Wang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Weige Wei
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhibin Li
- Department of Radiotherapy & Oncology, The First Affiliated Hospital of Soochow University, Institute of Radiotherapy & Oncology, Soochow University, Suzhou, China
| | - Qing Xiao
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Haiping He
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dashuang Luo
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Chen
- Department of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jing Li
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiangyu Zhang
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ying Song
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Sen Bai
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Wei W, Li Z, Xiao Q, Wang G, He H, Luo D, Chen L, Li J, Zhang X, Qin T, Song Y, Li G, Bai S. Quantifying dose uncertainties resulting from cardiorespiratory motion in intensity-modulated proton therapy for cardiac stereotactic body radiotherapy. Front Oncol 2024; 14:1399589. [PMID: 39040445 PMCID: PMC11260676 DOI: 10.3389/fonc.2024.1399589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 06/19/2024] [Indexed: 07/24/2024] Open
Abstract
Background Cardiac stereotactic body radiotherapy (CSBRT) with photons efficaciously and safely treats cardiovascular arrhythmias. Proton therapy, with its unique physical and radiobiological properties, can offer advantages over traditional photon-based therapies in certain clinical scenarios, particularly pediatric tumors and those in anatomically challenging areas. However, dose uncertainties induced by cardiorespiratory motion are unknown. Objective This study investigated the effect of cardiorespiratory motion on intensity-modulated proton therapy (IMPT) and the effectiveness of motion-encompassing methods. Methods We retrospectively included 12 patients with refractory arrhythmia who underwent CSBRT with four-dimensional computed tomography (4DCT) and 4D cardiac CT (4DcCT). Proton plans were simulated using an IBA accelerator based on the 4D average CT. The prescription was 25 Gy in a single fraction, with all plans normalized to ensure that 95% of the target volume received the prescribed dose. 4D dose reconstruction was performed to generate 4D accumulated and dynamic doses. Furthermore, dose uncertainties due to the interplay effect of the substrate target and organs at risk (OARs) were assessed. The differences between internal organs at risk volume (IRV) and OARreal (manually contoured on average CT) were compared. In 4D dynamic dose, meeting prescription requirements entails V25 and D95 reaching 95% and 25 Gy, respectively. Results The 4D dynamic dose significantly differed from the 3D static dose. The mean V25 and D95 were 89.23% and 24.69 Gy, respectively, in 4DCT and 94.35% and 24.99 Gy, respectively, in 4DcCT. Eleven patients in 4DCT and six in 4DcCT failed to meet the prescription requirements. Critical organs showed varying dose increases. All metrics, except for Dmean and D50, significantly changed in 4DCT; in 4DcCT, only D50 remained unchanged with regards to the target dose uncertainties induced by the interplay effect. The interplay effect was only significant for the Dmax values of several OARs. Generally, respiratory motion caused a more pronounced interplay effect than cardiac pulsation. Neither IRV nor OARreal effectively evaluated the dose discrepancies of the OARs. Conclusions Complex cardiorespiratory motion can introduce dose uncertainties during IMPT. Motion-encompassing techniques may mitigate but cannot entirely compensate for the dose discrepancies. Individualized 4D dose assessments are recommended to verify the effectiveness and safety of CSBRT.
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Affiliation(s)
- Weige Wei
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhibin Li
- Department of Radiotherapy & Oncology, The First Affiliated Hospital of Soochow University, Institute of Radiotherapy & Oncology, Soochow University, Suzhou, China
| | - Qing Xiao
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Guangyu Wang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Haiping He
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dashuang Luo
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Chen
- Department of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jing Li
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiangyu Zhang
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Taolin Qin
- Department of Medical Physics, Brown University, Providence, RI, United States
| | - Ying Song
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Guangjun Li
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Sen Bai
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Patrick HM, Kildea J. The use of dose surface maps as a tool to investigate spatial dose delivery accuracy for the rectum during prostate radiotherapy. J Appl Clin Med Phys 2024; 25:e14314. [PMID: 38425148 PMCID: PMC11244681 DOI: 10.1002/acm2.14314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 01/17/2024] [Accepted: 02/07/2024] [Indexed: 03/02/2024] Open
Abstract
PURPOSE This study aims to address the lack of spatial dose comparisons of planned and delivered rectal doses during prostate radiotherapy by using dose-surface maps (DSMs) to analyze dose delivery accuracy and comparing these results to those derived using DVHs. METHODS Two independent cohorts were used in this study: twenty patients treated with 36.25 Gy in five fractions (SBRT) and 20 treated with 60 Gy in 20 fractions (IMRT). Daily delivered rectum doses for each patient were retrospectively calculated using daily CBCT images. For each cohort, planned and average-delivered DVHs were generated and compared, as were planned and accumulated DSMs. Permutation testing was used to identify DVH metrics and DSM regions where significant dose differences occurred. Changes in rectal volume and position between planning and delivery were also evaluated to determine possible correlation to dosimetric changes. RESULTS For both cohorts, DVHs and DSMs reported conflicting findings on how planned and delivered rectum doses differed from each other. DVH analysis determined average-delivered DVHs were on average 7.1% ± 7.6% (p ≤ 0.002) and 5.0 ± 7.4% (p ≤ 0.021) higher than planned for the IMRT and SBRT cohorts, respectively. Meanwhile, DSM analysis found average delivered posterior rectal wall dose was 3.8 ± 0.6 Gy (p = 0.014) lower than planned in the IMRT cohort and no significant dose differences in the SBRT cohort. Observed dose differences were moderately correlated with anterior-posterior rectal wall motion, as well as PTV superior-inferior motion in the IMRT cohort. Evidence of both these relationships were discernable in DSMs. CONCLUSION DSMs enabled spatial investigations of planned and delivered doses can uncover associations with interfraction motion that are otherwise masked in DVHs. Investigations of dose delivery accuracy in radiotherapy may benefit from using DSMs over DVHs for certain organs such as the rectum.
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Affiliation(s)
- Haley M Patrick
- Medical Physics Unit, McGill University, Montreal, Quebec, Canada
| | - John Kildea
- Medical Physics Unit, McGill University, Montreal, Quebec, Canada
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Wong YM, Koh CWY, Lew KS, Chua CGA, Yeap PL, Zhang ET, Ong ALK, Tuan JKL, Ng BF, Lew WS, Lee JCL, Tan HQ. Deformable anthropomorphic pelvis phantom for dose accumulation verification. Phys Med Biol 2024; 69:12NT01. [PMID: 38821109 DOI: 10.1088/1361-6560/ad52e4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 05/31/2024] [Indexed: 06/02/2024]
Abstract
Objective.The validation of deformable image registration (DIR) for contour propagation is often done using contour-based metrics. Meanwhile, dose accumulation requires evaluation of voxel mapping accuracy, which might not be accurately represented by contour-based metrics. By fabricating a deformable anthropomorphic pelvis phantom, we aim to (1) quantify the voxel mapping accuracy for various deformation scenarios, in high- and low-contrast regions, and (2) identify any correlation between dice similarity coefficient (DSC), a commonly used contour-based metric, and the voxel mapping accuracy for each organ.Approach. Four organs, i.e. pelvic bone, prostate, bladder and rectum (PBR), were 3D printed using PLA and a Polyjet digital material, and assembled. The latter three were implanted with glass bead and CT markers within or on their surfaces. Four deformation scenarios were simulated by varying the bladder and rectum volumes. For each scenario, nine DIRs with different parameters were performed on RayStation v10B. The voxel mapping accuracy was quantified by finding the discrepancy between true and mapped marker positions, termed the target registration error (TRE). Pearson correlation test was done between the DSC and mean TRE for each organ.Main results. For the first time, we fabricated a deformable phantom purely from 3D printing, which successfully reproduced realistic anatomical deformations. Overall, the voxel mapping accuracy dropped with increasing deformation magnitude, but improved when more organs were used to guide the DIR or limit the registration region. DSC was found to be a good indicator of voxel mapping accuracy for prostate and rectum, but a comparatively poorer one for bladder. DSC > 0.85/0.90 was established as the threshold of mean TRE ⩽ 0.3 cm for rectum/prostate. For bladder, extra metrics in addition to DSC should be considered.Significance. This work presented a 3D printed phantom, which enabled quantification of voxel mapping accuracy and evaluation of correlation between DSC and voxel mapping accuracy.
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Affiliation(s)
- Yun Ming Wong
- Division of Physics and Applied Physics, Nanyang Technological University, Singapore, Singapore
| | - Calvin Wei Yang Koh
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
- Ai3 Lab, National Cancer Centre Singapore, Singapore, Singapore
| | - Kah Seng Lew
- Division of Physics and Applied Physics, Nanyang Technological University, Singapore, Singapore
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Clifford Ghee Ann Chua
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
- Ai3 Lab, National Cancer Centre Singapore, Singapore, Singapore
| | - Ping Lin Yeap
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
- Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Ee Teng Zhang
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore
- Singapore Centre for 3D Printing, Nanyang Technological University, Singapore, Singapore
| | - Ashley Li Kuan Ong
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
- Ai3 Lab, National Cancer Centre Singapore, Singapore, Singapore
| | - Jeffrey Kit Loong Tuan
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
- Ai3 Lab, National Cancer Centre Singapore, Singapore, Singapore
| | - Bing Feng Ng
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore
| | - Wen Siang Lew
- Division of Physics and Applied Physics, Nanyang Technological University, Singapore, Singapore
| | - James Cheow Lei Lee
- Division of Physics and Applied Physics, Nanyang Technological University, Singapore, Singapore
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Hong Qi Tan
- Division of Physics and Applied Physics, Nanyang Technological University, Singapore, Singapore
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
- Oncology Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore
- Ai3 Lab, National Cancer Centre Singapore, Singapore, Singapore
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Lazzeroni M, Ureba A, Rosenberg V, Schäfer H, Rühle A, Baltas D, Toma-Dasu I, Grosu AL. Evaluating the impact of a rigid and a deformable registration method of pre-treatment images for hypoxia-based dose painting. Phys Med 2024; 122:103376. [PMID: 38772061 DOI: 10.1016/j.ejmp.2024.103376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 04/19/2024] [Accepted: 05/10/2024] [Indexed: 05/23/2024] Open
Abstract
PURPOSE To assess the impact of rigid and deformable image registration methods (RIR, DIR) on the outcome of a hypoxia-based dose painting strategy. MATERIALS AND METHODS Thirty head and neck cancer patients were imaged with [18F]FMISO-PET/CT before radiotherapy. [18F]FMISO-PET/CT images were registered to the planning-CT by RIR or DIR. The [18F]FMISO uptake was converted into oxygen partial pressure (pO2) maps. Hypoxic Target Volumes were contoured on pO2 maps for the deformed (HTVdef) and non-deformed (HTV) cases. A dose escalation strategy by contours, aiming at 95 % tumour control probability (TCP), was applied. HTVs were characterised based on geometry-related metrics, the underlying pO2 distribution, and the dose boost level. A dosimetric and radiobiological evaluation of selected treatment plans made considering RIR and DIR was performed. Moreover, the TCP of the RIR dose distribution was evaluated when considering the deformed [18F]FMISO-PET image as an indicator of the actual target radiosensitivity to determine the potential impact of an unalignment. RESULTS Statistically significant differences were found between HTV and HTVdef for volume-based metrics and underlying pO2 distribution. Eight out of nine treatment plans for HTV and HTVdef showed differences on the level 10 %/3 mm on a gamma analysis. The TCP difference, however, between RIR and the case when the RIR dose distribution was used with the deformed radiosensitivity map was below 2 pp. CONCLUSIONS Although the choice of the CTplan-to-PET registration method pre-treatment impacts the HTV localisation and morphology and the corresponding dose distribution, it negligibly affects the TCP in the proposed dose escalation strategy by contours.
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Affiliation(s)
- M Lazzeroni
- Department of Physics, Stockholm University, Sweden; Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden.
| | - A Ureba
- Department of Physics, Stockholm University, Sweden; Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden
| | - V Rosenberg
- Royal Institute of Technology (KTH), Stockholm, Sweden
| | - H Schäfer
- Department of Radiation Oncology, Medical Center, Medical Faculty Freiburg, German Cancer Consortium (DKTK) Partner Site Freiburg, Germany
| | - A Rühle
- Department of Radiation Oncology, Medical Center, Medical Faculty Freiburg, German Cancer Consortium (DKTK) Partner Site Freiburg, Germany; University of Leipzig Medical Center, Department of Radiation Oncology, Leipzig, Germany
| | - D Baltas
- Department of Radiation Oncology, Medical Center, Medical Faculty Freiburg, German Cancer Consortium (DKTK) Partner Site Freiburg, Germany
| | - I Toma-Dasu
- Department of Physics, Stockholm University, Sweden; Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden
| | - A L Grosu
- Department of Radiation Oncology, Medical Center, Medical Faculty Freiburg, German Cancer Consortium (DKTK) Partner Site Freiburg, Germany
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Wang H, Ni D, Wang Y. Recursive Deformable Pyramid Network for Unsupervised Medical Image Registration. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2229-2240. [PMID: 38319758 DOI: 10.1109/tmi.2024.3362968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
Complicated deformation problems are frequently encountered in medical image registration tasks. Although various advanced registration models have been proposed, accurate and efficient deformable registration remains challenging, especially for handling the large volumetric deformations. To this end, we propose a novel recursive deformable pyramid (RDP) network for unsupervised non-rigid registration. Our network is a pure convolutional pyramid, which fully utilizes the advantages of the pyramid structure itself, but does not rely on any high-weight attentions or transformers. In particular, our network leverages a step-by-step recursion strategy with the integration of high-level semantics to predict the deformation field from coarse to fine, while ensuring the rationality of the deformation field. Meanwhile, due to the recursive pyramid strategy, our network can effectively attain deformable registration without separate affine pre-alignment. We compare the RDP network with several existing registration methods on three public brain magnetic resonance imaging (MRI) datasets, including LPBA, Mindboggle and IXI. Experimental results demonstrate our network consistently outcompetes state of the art with respect to the metrics of Dice score, average symmetric surface distance, Hausdorff distance, and Jacobian. Even for the data without the affine pre-alignment, our network maintains satisfactory performance on compensating for the large deformation. The code is publicly available at https://github.com/ZAX130/RDP.
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Zhong H, Kainz KK, Paulson ES. Evaluation and mitigation of deformable image registration uncertainties for MRI-guided adaptive radiotherapy. J Appl Clin Med Phys 2024; 25:e14358. [PMID: 38634799 PMCID: PMC11163488 DOI: 10.1002/acm2.14358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 03/03/2024] [Accepted: 03/25/2024] [Indexed: 04/19/2024] Open
Abstract
PURPOSE We evaluate the performance of a deformable image registration (DIR) software package in registering abdominal magnetic resonance images (MRIs) and then develop a mechanical modeling method to mitigate detected DIR uncertainties. MATERIALS AND METHODS Three evaluation metrics, namely mean displacement to agreement (MDA), DICE similarity coefficient (DSC), and standard deviation of Jacobian determinants (STD-JD), are used to assess the multi-modality (MM), contour-consistency (CC), and image-intensity (II)-based DIR algorithms in the MIM software package, as well as an in-house developed, contour matching-based finite element method (CM-FEM). Furthermore, we develop a hybrid FEM registration technique to modify the displacement vector field of each MIM registration. The MIM and FEM registrations were evaluated on MRIs obtained from 10 abdominal cancer patients. One-tailed Wilcoxon-Mann-Whitney (WMW) tests were conducted to compare the MIM registrations with their FEM modifications. RESULTS For the registrations performed with the MIM-CC, MIM-MM, MIM-II, and CM-FEM algorithms, their average MDAs are 0.62 ± 0.27, 2.39 ± 1.30, 3.07 ± 2.42, 1.04 ± 0.72 mm, and average DSCs are 0.94 ± 0.03, 0.80 ± 0.12, 0.77 ± 0.15, 0.90 ± 0.11, respectively. The p-values of the WMW tests between the MIM registrations and their FEM modifications are less than 0.0084 for STD-JDs and greater than 0.87 for MDA and DSC. CONCLUSIONS Among the three MIM DIR algorithms, MIM-CC shows the smallest errors in terms of MDA and DSC but exhibits significant Jacobian uncertainties in the interior regions of abdominal organs. The hybrid FEM technique effectively mitigates the Jacobian uncertainties in these regions.
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Affiliation(s)
- Hualiang Zhong
- Department of Radiation OncologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Kristofer K. Kainz
- Department of Radiation OncologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Eric S. Paulson
- Department of Radiation OncologyMedical College of WisconsinMilwaukeeWisconsinUSA
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Amstutz F, D'Almeida PG, Wu X, Albertini F, Bachtiary B, Weber DC, Unkelbach J, Lomax AJ, Zhang Y. Quantification of deformable image registration uncertainties for dose accumulation on head and neck cancer proton treatments. Phys Med 2024; 122:103386. [PMID: 38805762 DOI: 10.1016/j.ejmp.2024.103386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 03/11/2024] [Accepted: 05/21/2024] [Indexed: 05/30/2024] Open
Abstract
PURPOSE Head and neck cancer (HNC) patients in radiotherapy require adaptive treatment plans due to anatomical changes. Deformable image registration (DIR) is used in adaptive radiotherapy, e.g. for deformable dose accumulation (DDA). However, DIR's ill-posedness necessitates addressing uncertainties, often overlooked in clinical implementations. DIR's further clinical implementation is hindered by missing quantitative commissioning and quality assurance tools. This study evaluates one pathway for more quantitative DDA uncertainties. METHODS For five HNC patients, each with multiple repeated CTs acquired during treatment, a simultaneous-integrated boost (SIB) plan was optimized. Recalculated doses were warped individually using multiple DIRs from repeated to reference CTs, and voxel-by-voxel dose ranges determined an error-bar for DDA. Followed by evaluating, a previously proposed early-stage DDA uncertainty estimation method tested for lung cancer, which combines geometric DIR uncertainties, dose gradients and their directional dependence, in the context of HNC. RESULTS Applying multiple DIRs show dose differences, pronounced in high dose gradient regions. The patient with largest anatomical changes (-13.1 % in ROI body volume), exhibited 33 % maximum uncertainty in contralateral parotid, with 54 % of voxels presenting an uncertainty >5 %. Accumulation over multiple CTs partially mitigated uncertainties. The estimation approach predicted 92.6 % of voxels within ±5 % to the reference dose uncertainty across all patients. CONCLUSIONS DIR variations impact accumulated doses, emphasizing DDA uncertainty quantification's importance for HNC patients. Multiple DIR dose warping aids in quantifying DDA uncertainties. An estimation approach previously described for lung cancer was successfully validated for HNC, for SIB plans, presenting different dose gradients, and for accumulated treatments.
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Affiliation(s)
- Florian Amstutz
- Center for Proton Therapy, Paul Scherrer Institute, Switzerland; Department of Physics, ETH Zurich, Switzerland
| | - Peter G D'Almeida
- Center for Proton Therapy, Paul Scherrer Institute, Switzerland; Department of Information Technology & Electrical Engineering, ETH Zurich, Switzerland
| | - Xin Wu
- Center for Proton Therapy, Paul Scherrer Institute, Switzerland; Department of Information Technology & Electrical Engineering, ETH Zurich, Switzerland
| | | | | | - Damien C Weber
- Center for Proton Therapy, Paul Scherrer Institute, Switzerland; Department of Radiation Oncology, University Hospital Zurich, Switzerland; Department of Radiation Oncology, University Hospital Bern, Switzerland
| | - Jan Unkelbach
- Department of Radiation Oncology, University Hospital Zurich, Switzerland
| | - Antony J Lomax
- Center for Proton Therapy, Paul Scherrer Institute, Switzerland; Department of Physics, ETH Zurich, Switzerland
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, Switzerland.
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Chen ZJ, Li XA, Brenner DJ, Hellebust TP, Hoskin P, Joiner MC, Kirisits C, Nath R, Rivard MJ, Thomadsen BR, Zaider M. AAPM Task Group Report 267: A joint AAPM GEC-ESTRO report on biophysical models and tools for the planning and evaluation of brachytherapy. Med Phys 2024; 51:3850-3923. [PMID: 38721942 DOI: 10.1002/mp.17062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 02/28/2024] [Accepted: 03/08/2024] [Indexed: 06/05/2024] Open
Abstract
Brachytherapy utilizes a multitude of radioactive sources and treatment techniques that often exhibit widely different spatial and temporal dose delivery patterns. Biophysical models, capable of modeling the key interacting effects of dose delivery patterns with the underlying cellular processes of the irradiated tissues, can be a potentially useful tool for elucidating the radiobiological effects of complex brachytherapy dose delivery patterns and for comparing their relative clinical effectiveness. While the biophysical models have been used largely in research settings by experts, it has also been used increasingly by clinical medical physicists over the last two decades. A good understanding of the potentials and limitations of the biophysical models and their intended use is critically important in the widespread use of these models. To facilitate meaningful and consistent use of biophysical models in brachytherapy, Task Group 267 (TG-267) was formed jointly with the American Association of Physics in Medicine (AAPM) and The Groupe Européen de Curiethérapie and the European Society for Radiotherapy & Oncology (GEC-ESTRO) to review the existing biophysical models, model parameters, and their use in selected brachytherapy modalities and to develop practice guidelines for clinical medical physicists regarding the selection, use, and interpretation of biophysical models. The report provides an overview of the clinical background and the rationale for the development of biophysical models in radiation oncology and, particularly, in brachytherapy; a summary of the results of literature review of the existing biophysical models that have been used in brachytherapy; a focused discussion of the applications of relevant biophysical models for five selected brachytherapy modalities; and the task group recommendations on the use, reporting, and implementation of biophysical models for brachytherapy treatment planning and evaluation. The report concludes with discussions on the challenges and opportunities in using biophysical models for brachytherapy and with an outlook for future developments.
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Affiliation(s)
- Zhe Jay Chen
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - X Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - David J Brenner
- Center for Radiological Research, Columbia University Medical Center, New York, New York, USA
| | - Taran P Hellebust
- Department of Oncology, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway
| | - Peter Hoskin
- Mount Vernon Cancer Center, Mount Vernon Hospital, Northwood, UK
- University of Manchester, Manchester, UK
| | - Michael C Joiner
- Department of Radiation Oncology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Christian Kirisits
- Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Ravinder Nath
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Mark J Rivard
- Department of Radiation Oncology, Brown University School of Medicine, Providence, Rhode Island, USA
| | - Bruce R Thomadsen
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Marco Zaider
- Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA
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11
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Lei Y, Matkovic LA, Roper J, Wang T, Zhou J, Ghavidel B, McDonald M, Patel P, Yang X. Diffeomorphic transformer-based abdomen MRI-CT deformable image registration. Med Phys 2024. [PMID: 38820286 DOI: 10.1002/mp.17235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 03/29/2024] [Accepted: 05/17/2024] [Indexed: 06/02/2024] Open
Abstract
BACKGROUND Stereotactic body radiotherapy (SBRT) is a well-established treatment modality for liver metastases in patients unsuitable for surgery. Both CT and MRI are useful during treatment planning for accurate target delineation and to reduce potential organs-at-risk (OAR) toxicity from radiation. MRI-CT deformable image registration (DIR) is required to propagate the contours defined on high-contrast MRI to CT images. An accurate DIR method could lead to more precisely defined treatment volumes and superior OAR sparing on the treatment plan. Therefore, it is beneficial to develop an accurate MRI-CT DIR for liver SBRT. PURPOSE To create a new deep learning model that can estimate the deformation vector field (DVF) for directly registering abdominal MRI-CT images. METHODS The proposed method assumed a diffeomorphic deformation. By using topology-preserved deformation features extracted from the probabilistic diffeomorphic registration model, abdominal motion can be accurately obtained and utilized for DVF estimation. The model integrated Swin transformers, which have demonstrated superior performance in motion tracking, into the convolutional neural network (CNN) for deformation feature extraction. The model was optimized using a cross-modality image similarity loss and a surface matching loss. To compute the image loss, a modality-independent neighborhood descriptor (MIND) was used between the deformed MRI and CT images. The surface matching loss was determined by measuring the distance between the warped coordinates of the surfaces of contoured structures on the MRI and CT images. To evaluate the performance of the model, a retrospective study was carried out on a group of 50 liver cases that underwent rigid registration of MRI and CT scans. The deformed MRI image was assessed against the CT image using the target registration error (TRE), Dice similarity coefficient (DSC), and mean surface distance (MSD) between the deformed contours of the MRI image and manual contours of the CT image. RESULTS When compared to only rigid registration, DIR with the proposed method resulted in an increase of the mean DSC values of the liver and portal vein from 0.850 ± 0.102 and 0.628 ± 0.129 to 0.903 ± 0.044 and 0.763 ± 0.073, a decrease of the mean MSD of the liver from 7.216 ± 4.513 mm to 3.232 ± 1.483 mm, and a decrease of the TRE from 26.238 ± 2.769 mm to 8.492 ± 1.058 mm. CONCLUSION The proposed DIR method based on a diffeomorphic transformer provides an effective and efficient way to generate an accurate DVF from an MRI-CT image pair of the abdomen. It could be utilized in the current treatment planning workflow for liver SBRT.
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Affiliation(s)
- Yang Lei
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Luke A Matkovic
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Justin Roper
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Tonghe Wang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Jun Zhou
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Beth Ghavidel
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Mark McDonald
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Pretesh Patel
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Xiaofeng Yang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
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Finnegan RN, Quinn A, Booth J, Belous G, Hardcastle N, Stewart M, Griffiths B, Carroll S, Thwaites DI. Cardiac substructure delineation in radiation therapy - A state-of-the-art review. J Med Imaging Radiat Oncol 2024. [PMID: 38757728 DOI: 10.1111/1754-9485.13668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 04/29/2024] [Indexed: 05/18/2024]
Abstract
Delineation of cardiac substructures is crucial for a better understanding of radiation-related cardiotoxicities and to facilitate accurate and precise cardiac dose calculation for developing and applying risk models. This review examines recent advancements in cardiac substructure delineation in the radiation therapy (RT) context, aiming to provide a comprehensive overview of the current level of knowledge, challenges and future directions in this evolving field. Imaging used for RT planning presents challenges in reliably visualising cardiac anatomy. Although cardiac atlases and contouring guidelines aid in standardisation and reduction of variability, significant uncertainties remain in defining cardiac anatomy. Coupled with the inherent complexity of the heart, this necessitates auto-contouring for consistent large-scale data analysis and improved efficiency in prospective applications. Auto-contouring models, developed primarily for breast and lung cancer RT, have demonstrated performance comparable to manual contouring, marking a significant milestone in the evolution of cardiac delineation practices. Nevertheless, several key concerns require further investigation. There is an unmet need for expanding cardiac auto-contouring models to encompass a broader range of cancer sites. A shift in focus is needed from ensuring accuracy to enhancing the robustness and accessibility of auto-contouring models. Addressing these challenges is paramount for the integration of cardiac substructure delineation and associated risk models into routine clinical practice, thereby improving the safety of RT for future cancer patients.
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Affiliation(s)
- Robert N Finnegan
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Alexandra Quinn
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Jeremy Booth
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Gregg Belous
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland, Australia
| | - Nicholas Hardcastle
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Maegan Stewart
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Brooke Griffiths
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Susan Carroll
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - David I Thwaites
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Radiotherapy Research Group, Leeds Institute of Medical Research, St James's Hospital and University of Leeds, Leeds, UK
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13
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Paetkau O, Weppler S, Quon HC, Tchistiakova E, Kirkby C. Developing and validating multi-omics prediction models for late patient-reported dysphagia in head and neck radiotherapy. Biomed Phys Eng Express 2024; 10:045014. [PMID: 38697028 DOI: 10.1088/2057-1976/ad4651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 05/02/2024] [Indexed: 05/04/2024]
Abstract
Background and purpose. To investigate models developed using radiomic and dosiomic (multi-omics) features from planning and treatment imaging for late patient-reported dysphagia in head and neck radiotherapy.Materials and methods. Training (n = 64) and testing (n = 23) cohorts of head and neck cancer patients treated with curative intent chemo-radiotherapy with a follow-up time greater than 12 months were retrospectively examined. Patients completed the MD Anderson Dysphagia Inventory and a composite score ≤60 was interpreted as patient-reported dysphagia. A chart review collected baseline dysphagia and clinical factors. Multi-omic features were extracted from planning and last synthetic CT images using the pharyngeal constrictor muscle contours as a region of interest. Late patient-reported dysphagia models were developed using a random forest backbone, with feature selection and up-sampling methods to account for the imbalanced data. Models were developed and validated for multi-omic feature combinations for both timepoints.Results. A clinical and radiomic feature model developed using the planning CT achieved good performance (validation: sensitivity = 80 ± 27% / balanced accuracy = 71 ± 23%, testing: sensitivity = 80 ± 10% / balanced accuracy = 73 ± 11%). The synthetic CT models did not show improvement over the plan CT multi-omics models, with poor reliability of the radiomic features on these images. Dosiomic features extracted from the synthetic CT showed promise in predicting late patient-reported dysphagia.Conclusion. Multi-omics models can predict late patient-reported dysphagia in head and neck radiotherapy patients. Synthetic CT dosiomic features show promise in developing successful models to account for changes in delivered dose distribution. Multi-center or prospective studies are required prior to clinical implementation of these models.
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Affiliation(s)
- Owen Paetkau
- Department of Physics and Astronomy, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Sarah Weppler
- Tom Baker Cancer Center, 1331 29 St NW, Calgary, AB, T2N 4N2, Canada
| | - Harvey C Quon
- Tom Baker Cancer Center, 1331 29 St NW, Calgary, AB, T2N 4N2, Canada
| | - Ekaterina Tchistiakova
- Department of Physics and Astronomy, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Charles Kirkby
- Department of Physics and Astronomy, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
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14
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Wang X, Chang Y, Pei X, Xu XG. A prior-information-based automatic segmentation method for the clinical target volume in adaptive radiotherapy of cervical cancer. J Appl Clin Med Phys 2024; 25:e14350. [PMID: 38546277 PMCID: PMC11087177 DOI: 10.1002/acm2.14350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/09/2024] [Accepted: 03/18/2024] [Indexed: 05/12/2024] Open
Abstract
OBJECTIVE Adaptive planning to accommodate anatomic changes during treatment often requires repeated segmentation. In this study, prior patient-specific data was integrateda into a registration-guided multi-channel multi-path (Rg-MCMP) segmentation framework to improve the accuracy of repeated clinical target volume (CTV) segmentation. METHODS This study was based on CT image datasets for a total of 90 cervical cancer patients who received two courses of radiotherapy. A total of 15 patients were selected randomly as the test set. In the Rg-MCMP segmentation framework, the first-course CT images (CT1) were registered to second-course CT images (CT2) to yield aligned CT images (aCT1), and the CTV in the first course (CTV1) was propagated to yield aligned CTV contours (aCTV1). Then, aCT1, aCTV1, and CT2 were combined as the inputs for 3D U-Net consisting of a channel-based multi-path feature extraction network. The performance of the Rg-MCMP segmentation framework was evaluated and compared with the single-channel single-path model (SCSP), the standalone registration methods, and the registration-guided multi-channel single-path (Rg-MCSP) model. The Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and average surface distance (ASD) were used as the metrics. RESULTS The average DSC of CTV for the deformable image DIR-MCMP model was found to be 0.892, greater than that of the standalone DIR (0.856), SCSP (0.837), and DIR-MCSP (0.877), which were improvements of 4.2%, 6.6%, and 1.7%, respectively. Similarly, the rigid body DIR-MCMP model yielded an average DSC of 0.875, which exceeded standalone RB (0.787), SCSP (0.837), and registration-guided multi-channel single-path (0.848), which were improvements of 11.2%, 4.5%, and 3.2%, respectively. These improvements in DSC were statistically significant (p < 0.05). CONCLUSION The proposed Rg-MCMP framework achieved excellent accuracy in CTV segmentation as part of the adaptive radiotherapy workflow.
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Affiliation(s)
- Xuanhe Wang
- School of Nuclear Science and TechnologyUniversity of Science and Technology of ChinaHefeiChina
| | - Yankui Chang
- School of Nuclear Science and TechnologyUniversity of Science and Technology of ChinaHefeiChina
| | - Xi Pei
- School of Nuclear Science and TechnologyUniversity of Science and Technology of ChinaHefeiChina
- Anhui Wisdom Technology Company LtmitedHefeiChina
| | - Xie George Xu
- School of Nuclear Science and TechnologyUniversity of Science and Technology of ChinaHefeiChina
- Department of Radiation OncologyThe First Affiliated Hospital of University of Science and Technology of ChinaHefeiChina
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15
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Criscuolo ER, Fu Y, Hao Y, Zhang Z, Yang D. A comprehensive lung CT landmark pair dataset for evaluating deformable image registration algorithms. Med Phys 2024; 51:3806-3817. [PMID: 38478966 DOI: 10.1002/mp.17026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 01/29/2024] [Accepted: 03/03/2024] [Indexed: 05/08/2024] Open
Abstract
PURPOSE Deformable image registration (DIR) is a key enabling technology in many diagnostic and therapeutic tasks, but often does not meet the required robustness and accuracy for supporting clinical tasks. This is in large part due to a lack of high-quality benchmark datasets by which new DIR algorithms can be evaluated. Our team was supported by the National Institute of Biomedical Imaging and Bioengineering to develop DIR benchmark dataset libraries for multiple anatomical sites, comprising of large numbers of highly accurate landmark pairs on matching blood vessel bifurcations. Here we introduce our lung CT DIR benchmark dataset library, which was developed to improve upon the number and distribution of landmark pairs in current public lung CT benchmark datasets. ACQUISITION AND VALIDATION METHODS Thirty CT image pairs were acquired from several publicly available repositories as well as authors' institution with IRB approval. The data processing workflow included multiple steps: (1) The images were denoised. (2) Lungs, airways, and blood vessels were automatically segmented. (3) Bifurcations were directly detected on the skeleton of the segmented vessel tree. (4) Falsely identified bifurcations were filtered out using manually defined rules. (5) A DIR was used to project landmarks detected on the first image onto the second image of the image pair to form landmark pairs. (6) Landmark pairs were manually verified. This workflow resulted in an average of 1262 landmark pairs per image pair. Estimates of the landmark pair target registration error (TRE) using digital phantoms were 0.4 mm ± 0.3 mm. DATA FORMAT AND USAGE NOTES The data is published in Zenodo at https://doi.org/10.5281/zenodo.8200423. Instructions for use can be found at https://github.com/deshanyang/Lung-DIR-QA. POTENTIAL APPLICATIONS The dataset library generated in this work is the largest of its kind to date and will provide researchers with a new and improved set of ground truth benchmarks for quantitatively validating DIR algorithms within the lung.
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Affiliation(s)
- Edward R Criscuolo
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
| | - Yabo Fu
- Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Yao Hao
- Washington University School of Medicine, St. Louis, Missouri, USA
| | - Zhendong Zhang
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
| | - Deshan Yang
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
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Delgadillo R, Deana AM, Ford JC, Studenski MT, Padgett KR, Abramowitz MC, Pra AD, Spieler BO, Dogan N. Increasing the efficiency of cone-beam CT based delta-radiomics using automated contours to predict radiotherapy-related toxicities in prostate cancer. Sci Rep 2024; 14:9563. [PMID: 38671043 PMCID: PMC11053114 DOI: 10.1038/s41598-024-60281-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 04/21/2024] [Indexed: 04/28/2024] Open
Abstract
Extracting longitudinal image quantitative data, known as delta-radiomics, has the potential to capture changes in a patient's anatomy throughout the course of radiation treatment for prostate cancer. Some of the major challenges of delta-radiomics studies are contouring the structures for individual fractions and accruing patients' data in an efficient manner. The manual contouring process is often time consuming and would limit the efficiency of accruing larger sample sizes for future studies. The problem is amplified because the contours are often made by highly trained radiation oncologists with limited time to dedicate to research studies of this nature. This work compares the use of automated prostate contours generated using a deformable image-based algorithm to make predictive models of genitourinary and changes in total international prostate symptom score in comparison to manually contours for a cohort of fifty patients. Area under the curve of manual and automated models were compared using the Delong test. This study demonstrated that the delta-radiomics models were similar for both automated and manual delta-radiomics models.
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Affiliation(s)
- Rodrigo Delgadillo
- Department of Radiation Oncology, University of Miami Miller School of Medicine, 1475 NW 12Th Ave, Miami, FL, 33136, USA
| | - Anthony M Deana
- Department of Radiation Oncology, University of Miami Miller School of Medicine, 1475 NW 12Th Ave, Miami, FL, 33136, USA
- Varian Medical Systems, Advanced Oncology Solutions, Avon, IN, USA
| | - John C Ford
- Department of Radiation Oncology, University of Miami Miller School of Medicine, 1475 NW 12Th Ave, Miami, FL, 33136, USA
| | - Matthew T Studenski
- Department of Radiation Oncology, University of Miami Miller School of Medicine, 1475 NW 12Th Ave, Miami, FL, 33136, USA
| | - Kyle R Padgett
- Department of Radiation Oncology, University of Miami Miller School of Medicine, 1475 NW 12Th Ave, Miami, FL, 33136, USA
| | - Matthew C Abramowitz
- Department of Radiation Oncology, University of Miami Miller School of Medicine, 1475 NW 12Th Ave, Miami, FL, 33136, USA
| | - Alan Dal Pra
- Department of Radiation Oncology, University of Miami Miller School of Medicine, 1475 NW 12Th Ave, Miami, FL, 33136, USA
| | - Benjamin O Spieler
- Department of Radiation Oncology, University of Miami Miller School of Medicine, 1475 NW 12Th Ave, Miami, FL, 33136, USA
| | - Nesrin Dogan
- Department of Radiation Oncology, University of Miami Miller School of Medicine, 1475 NW 12Th Ave, Miami, FL, 33136, USA.
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Zhou Z, Yin P, Liu Y, Hu J, Qian X, Chen G, Hu C, Dai Y. Uncertain prediction of deformable image registration on lung CT using multi-category features and supervised learning. Med Biol Eng Comput 2024:10.1007/s11517-024-03092-1. [PMID: 38658497 DOI: 10.1007/s11517-024-03092-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 04/08/2024] [Indexed: 04/26/2024]
Abstract
The assessment of deformable registration uncertainty is an important task for the safety and reliability of registration methods in clinical applications. However, it is typically done by a manual and time-consuming procedure. We propose a novel automatic method to predict registration uncertainty based on multi-category features and supervised learning. Three types of features, including deformation field statistical features, deformation field physiologically realistic features, and image similarity features, are introduced and calculated to train the random forest regressor for local registration uncertain prediction. Deformation field statistical features represent the numerical stability of registration optimization, which are correlated to the uncertainty of deformation fields; deformation field physiologically realistic features represent the biomechanical properties of organ motions, which mathematically reflect the physiological reality of deformation; image similarity features reflect the similarity between the warped image and fixed image. The multi-category features comprehensively reflect the registration uncertainty. The strategy of spatial adaptive random perturbations is also introduced to accurately simulate spatial distribution of registration uncertainty, which makes deformation field statistical features more discriminative to the uncertainty of deformation fields. Experiments were conducted on three publicly available thoracic CT image datasets. Seventeen randomly selected image pairs are used to train the random forest model, and 9 image pairs are used to evaluate the prediction model. The quantitative experiments on lung CT images show that the proposed method outperforms the baseline method for uncertain prediction of classical iterative optimization-based registration and deep learning-based registration with different registration qualities. The proposed method achieves good performance for registration uncertain prediction, which has great potential in improving the accuracy of registration uncertain prediction.
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Affiliation(s)
- Zhiyong Zhou
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Pengfei Yin
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yuhang Liu
- School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
| | - Jisu Hu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Xusheng Qian
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Guangqiang Chen
- The Second Affiliated Hospital of Soochow University, Suzhou, 215163, China
| | - Chunhong Hu
- The First Affiliated Hospital of Soochow University, Suzhou, 215163, China.
| | - Yakang Dai
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China.
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
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Lorenzo Polo A, Nix M, Thompson C, O'Hara C, Entwisle J, Murray L, Appelt A, Weistrand O, Svensson S. Improving hybrid image and structure-based deformable image registration for large internal deformations. Phys Med Biol 2024; 69:095011. [PMID: 38518382 DOI: 10.1088/1361-6560/ad3723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 03/22/2024] [Indexed: 03/24/2024]
Abstract
Objective.Deformable image registration (DIR) is a widely used technique in radiotherapy. Complex deformations, resulting from large anatomical changes, are a regular challenge. DIR algorithms generally seek a balance between capturing large deformations and preserving a smooth deformation vector field (DVF). We propose a novel structure-based term that can enhance the registration efficacy while ensuring a smooth DVF.Approach.The proposed novel similarity metric for controlling structures was introduced as a new term into a commercially available algorithm. Its performance was compared to the original algorithm using a dataset of 46 patients who received pelvic re-irradiation, many of which exhibited complex deformations.Main results.The mean Dice Similarity Coefficient (DSC) under the improved algorithm was 0.96, 0.94, 0.76, and 0.91 for bladder, rectum, colon, and bone respectively, compared to 0.69, 0.89, 0.62, and 0.88 for the original algorithm. The improvement was more pronounced for complex deformations.Significance.With this work, we have demonstrated that the proposed term is able to improve registration accuracy for complex cases while maintaining realistic deformations.
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Affiliation(s)
| | - M Nix
- Leeds Cancer Centre, Department of Medical Physics, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - C Thompson
- Leeds Cancer Centre, Department of Medical Physics, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - C O'Hara
- Leeds Cancer Centre, Department of Medical Physics, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - J Entwisle
- Leeds Cancer Centre, Department of Medical Physics, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - L Murray
- Leeds Cancer Centre, Department of Clinical Oncology, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
- Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, United Kingdom
| | - A Appelt
- Leeds Cancer Centre, Department of Medical Physics, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
- Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, United Kingdom
| | - O Weistrand
- RaySearch Laboratories, SE-104 30 Stockholm, Sweden
| | - S Svensson
- RaySearch Laboratories, SE-104 30 Stockholm, Sweden
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Nuyts S, Bollen H, Eisbruch A, Strojan P, Mendenhall WM, Ng SP, Ferlito A. Adaptive radiotherapy for head and neck cancer: Pitfalls and possibilities from the radiation oncologist's point of view. Cancer Med 2024; 13:e7192. [PMID: 38650546 PMCID: PMC11036082 DOI: 10.1002/cam4.7192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 03/19/2024] [Accepted: 04/03/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Patients with head and neck cancer (HNC) may experience substantial anatomical changes during the course of radiotherapy treatment. The implementation of adaptive radiotherapy (ART) proves effective in managing the consequent impact on the planned dose distribution. METHODS This narrative literature review comprehensively discusses the diverse strategies of ART in HNC and the documented dosimetric and clinical advantages associated with these approaches, while also addressing the current challenges for integration of ART into clinical practice. RESULTS AND CONCLUSION Although based on mainly non-randomized and retrospective trials, there is accumulating evidence that ART has the potential to reduce toxicity and improve quality of life and tumor control in HNC patients treated with RT. However, several questions remain regarding accurate patient selection, the ideal frequency and timing of replanning, and the appropriate way for image registration and dose calculation. Well-designed randomized prospective trials, with a predetermined protocol for both image registration and dose summation, are urgently needed to further investigate the dosimetric and clinical benefits of ART.
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Affiliation(s)
- Sandra Nuyts
- Laboratory of Experimental Radiotherapy, Department of OncologyKU LeuvenLeuvenBelgium
- Department of Radiation OncologyLeuven Cancer Institute, University Hospitals LeuvenLeuvenBelgium
| | - Heleen Bollen
- Laboratory of Experimental Radiotherapy, Department of OncologyKU LeuvenLeuvenBelgium
- Department of Radiation OncologyLeuven Cancer Institute, University Hospitals LeuvenLeuvenBelgium
| | - Avrahram Eisbruch
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - Primoz Strojan
- Department of Radiation Oncology Institute of OncologyUniversity of LjubljanaLjubljanaSlovenia
| | - William M. Mendenhall
- Department of Radiation OncologyUniversity of Florida College of MedicineGainesvilleFloridaUSA
| | - Sweet Ping Ng
- Department of Radiation OncologyOlivia Newton‐John Cancer and Wellness Centre, Austin HealthMelbourneAustralia
| | - Alfio Ferlito
- Coordinator International Head and Neck Scientific GroupUdineItaly
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Szkitsak J, Karius A, Fernolendt S, Schubert P, Speer S, Fietkau R, Bert C, Hofmann C. Optimized raw data selection for artifact reduction of breathing controlled four-dimensional sequence scanning. Phys Imaging Radiat Oncol 2024; 30:100584. [PMID: 38803466 PMCID: PMC11128500 DOI: 10.1016/j.phro.2024.100584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 04/10/2024] [Accepted: 05/02/2024] [Indexed: 05/29/2024] Open
Abstract
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.
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Affiliation(s)
- Juliane Szkitsak
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Andre Karius
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | | | - Philipp Schubert
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Stefan Speer
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Rainer Fietkau
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Christoph Bert
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Christian Hofmann
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Siemens Healthcare GmbH, 91301 Forchheim, Germany
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21
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Ferris WS, Smith BR, Hyer DE, St‐Aubin JJ. Technical note: A simple method for patient-specific quality assurance for lateral targets on a 1.5 T MR-Linac. J Appl Clin Med Phys 2024; 25:e14323. [PMID: 38426612 PMCID: PMC11005970 DOI: 10.1002/acm2.14323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 02/01/2024] [Accepted: 02/05/2024] [Indexed: 03/02/2024] Open
Abstract
The Elekta Unity magnetic resonance (MR) linac is limited to longitudinal couch motion and a sagittal-only laser, which restricts the ability to perform patient-specific quality assurance (PSQA) intensity-modulated radiotherapy (IMRT) measurements for very lateral targets. This work introduces a simple method to perform PSQA using the Sun Nuclear ArcCheck-MR phantom at left and right lateral positions without additional equipment or in-house construction. The proposed setup places the center of the phantom 1.3 cm vertical and 12.9 cm lateral to isocenter in either the left or right direction. Computed tomography (CT) scans are used to simulate the setup and create a QA plan template in the Monaco treatment planning system (TPS). The workflow is demonstrated for four patients, with an average axial distance from the center of the bore to the planning target volume (PTV) of 12.4 cm. Gamma pass rates were above 94% for all plans using global 3%/2 mm gamma criterion with a 10% threshold. Setup uncertainties are slightly larger for the proposed lateral setup compared to the centered setup on the Elekta platform (∼1 mm compared to ∼0.5 mm), but acceptable pass rates are achievable without optimizing shifts in the gamma analysis software. In general, adding the left and right lateral positions increases the axial area in the bore encompassed by the cylindrical measurement array by 147%, substantially increasing the flexibility of measurements for offset targets. Based on this work, we propose using the lateral QA setup if the closest distance to the PTV edge from isocenter is larger than the array radius (10.5 cm) or the percent of the PTV encompassed by the diode array would be increased with the lateral setup compared to the centered setup.
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Affiliation(s)
| | - Blake R. Smith
- Department of Radiation OncologyUniversity of IowaIowa CityIowaUSA
| | - Daniel E. Hyer
- Department of Radiation OncologyUniversity of IowaIowa CityIowaUSA
| | - Joel J. St‐Aubin
- Department of Radiation OncologyUniversity of IowaIowa CityIowaUSA
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22
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Hassan SP, de Leon J, Batumalai V, Moutrie Z, Hogan L, Ge Y, Stricker P, Jameson MG. Magnetic resonance guided adaptive post prostatectomy radiotherapy: Accumulated dose comparison of different workflows. J Appl Clin Med Phys 2024; 25:e14253. [PMID: 38394627 PMCID: PMC11005979 DOI: 10.1002/acm2.14253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 09/26/2023] [Accepted: 12/06/2023] [Indexed: 02/25/2024] Open
Abstract
PURPOSE The aim of this study was to assess the use of magnetic resonance guided adaptive radiotherapy (MRgART) in the post-prostatectomy setting; comparing dose accumulation for our initial seven patients treated with fully adaptive workflow on the Unity MR-Linac (MRL) and with non-adaptive plans generated offline. Additionally, we analyzed toxicity in patients receiving treatment. METHODS Seven patients were treated with MRgART. The prescription was 70-72 Gy in 35-36 fractions. Patients were treated with an adapt to shape (ATS) technique. For each clinically delivered plan, a non-adaptive plan based upon the reference plan was generated and compared to the associated clinically delivered plan. A total of 468 plans were analyzed. Concordance Index of target and Organs at Risk (OARs) for each fraction with reference contours was analyzed. Acute toxicity was then assessed at six-months following completion of treatment with Common Terminology for Adverse Events (CTCAE) Toxicity Criteria. RESULTS A total of 246 fractions were clinically delivered to seven patients; 234 fractions were delivered via MRgART and 12 fractions delivered via a traditional linear accelerator due to machine issues. Pre-treatment reference plans met CTV and OAR criteria. PTV coverage satisfaction was higher in the clinically delivered adaptive plans than non-adaptive comparison plans; 42.93% versus 7.27% respectively. Six-month CTCAE genitourinary and gastrointestinal toxicity was absent in most patients, and mild-to-moderate in a minority of patients (Grade 1 GU toxicity in one patient and Grade 2 GI toxicity in one patient). CONCLUSIONS Daily MRgART treatment consistently met planning criteria. Target volume variability in prostate bed treatment can be mitigated by using MRgART and deliver satisfactory coverage of CTV whilst minimizing dose to adjacent OARs and reducing toxicity.
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Affiliation(s)
- Sean P. Hassan
- GenesisCareSt Vincent's HospitalSydneyNew South WalesAustralia
| | | | - Vikneswary Batumalai
- GenesisCareSt Vincent's HospitalSydneyNew South WalesAustralia
- Faculty of MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Zoe Moutrie
- GenesisCareSt Vincent's HospitalSydneyNew South WalesAustralia
- Faculty of MedicineUniversity of New South WalesSydneyNew South WalesAustralia
- South Western Sydney Cancer ServicesNew South Wales HealthSydneyAustralia
- Ingham Institute for Applied Medical ResearchSydneyAustralia
| | - Louise Hogan
- GenesisCareSt Vincent's HospitalSydneyNew South WalesAustralia
- GenesisCareMurdochWestern AustraliaAustralia
| | - Yuanyuan Ge
- GenesisCareSt Vincent's HospitalSydneyNew South WalesAustralia
| | - Phillip Stricker
- Faculty of MedicineUniversity of New South WalesSydneyNew South WalesAustralia
- Western Sydney UniversityPenrithNew South WalesAustralia
- St Vincent's Prostate Cancer Research CentreDarlinghurstNew South WalesAustralia
- Garvan Institute, DarlinghurstSydneyNew South WalesAustralia
- University of SydneyCamperdownNew South WalesAustralia
| | - Michael G. Jameson
- GenesisCareSt Vincent's HospitalSydneyNew South WalesAustralia
- Faculty of MedicineUniversity of New South WalesSydneyNew South WalesAustralia
- Centre for Medical Radiation PhysicsUniversity of WollongongWollongongAustralia
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Samanci Y, Askeroglu MO, Düzkalir AH, Peker S. Assessing the impact of distortion correction on Gamma Knife radiosurgery for multiple metastasis: Volumetric and dosimetric analysis. BRAIN & SPINE 2024; 4:102791. [PMID: 38584868 PMCID: PMC10995810 DOI: 10.1016/j.bas.2024.102791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 03/11/2024] [Accepted: 03/19/2024] [Indexed: 04/09/2024]
Abstract
Introduction Magnetic resonance imaging (MRI) is a robust neuroimaging technique and is the preferred method for stereotactic radiosurgery (SRS) planning. However, MRI data always contain distortions caused by hardware and patient factors. Research question Can these distortions potentially compromise the effectiveness and safety of SRS treatments? Material and methods Twenty-six MR datasets with multiple metastatic brain tumors (METs) used for Gamma Knife radiosurgery (GKRS) were retrospectively evaluated. A commercially available software was used for distortion correction. Geometrical agreement between corrected and uncorrected tumor volumes was evaluated using MacDonald criteria, Euclidian distance, and Dice similarity coefficient (DSC). SRS plans were generated using uncorrected tumor volumes, which were assessed to determine their coverage of the corrected tumor volumes. Results The median target volume was 0.38 cm3 (range,0.01-12.38 cm3). A maximum displacement of METs of up to 2.87 mm and a median displacement of 0.55 mm (range,0.1-2.87 mm) were noted. The median DSC between uncorrected and corrected MRI was 0.92, and the most concerning case had a DSC of 0.46. Although all plans met the optimization criterion of at least 98% of the uncorrected tumor volume (median 99.55%, range 98.1-100%) receiving at least 100% of the prescription dose, the percent of the corrected tumor volume receiving the total prescription dose was a median of 95.45% (range,23.1-99.5%). Discussion and conclusion MRI distortion, though visually subtle, has significant implications for SRS planning. Regular utilization of corrected MRI is recommended for SRS planning as distortion is sometimes enough to cause a volumetric miss of SRS targets.
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Affiliation(s)
- Yavuz Samanci
- Department of Neurosurgery, Koc University School of Medicine, Istanbul, Turkey
- Gamma Knife Center, Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
| | - M. Orbay Askeroglu
- Gamma Knife Center, Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
| | - Ali Haluk Düzkalir
- Gamma Knife Center, Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
- Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
| | - Selcuk Peker
- Department of Neurosurgery, Koc University School of Medicine, Istanbul, Turkey
- Gamma Knife Center, Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
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24
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Song Z, Li T, Zuo L, Song Y, Wei R, Dai J. A grayscale compression method to segment bone structures for 2D-3D registration of setup images in non-coplanar radiotherapy. Biomed Phys Eng Express 2024; 10:035014. [PMID: 38442730 DOI: 10.1088/2057-1976/ad3050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 03/05/2024] [Indexed: 03/07/2024]
Abstract
Purpose. To evaluate the performance of an automated 2D-3D bone registration algorithm incorporating a grayscale compression method for quantifying patient position errors in non-coplanar radiotherapy.Methods. An automated 2D-3D registration incorporating a grayscale compression method to segment bone structures was proposed. Portal images containing only bone structures (Portalbone) and digitally reconstructed radiographs containing only bone structures (DRRbone) were used for registration. First, the portal image was filtered by a high-pass finite impulse response (FIR) filter. Then the grayscale range of the filtered portal image was compressed. Thresholds were determined based on the difference in gray values of bone structures in the filtered and compressed portal image to obtainPortalbone.Another threshold was applied to generateDRRbonewhen the CT image uses the ray-casting algorithm to generate DRR images. The compression performance was assessed by registering theDRRbonewith thePortalboneobtained by compressing the portal image into various grayscale ranges. The proposed registration method was quantitatively and visually validated using (1) a CT image of an anthropomorphic head phantom and its portal images obtained in different poses and (2) CT images and pre-treatment portal images of 20 patients treated with non-coplanar radiotherapy.Results. Mean absolute registration errors for the best compression grayscale range test were 0.642 mm, 0.574 mm, and 0.643 mm, with calculation times of 50.6 min, 42.2 min, and 49.6 min for grayscale ranges of 0-127, 0-63 and 0-31, respectively. For the accuracy validation (1), the mean absolute registration errors for couch angles 0°, 45°, 90°, 270°, and 315° were 0.694 mm, 0.839 mm, 0.726 mm, 0.833 mm, and 0.873 mm, respectively. Among the six transformation parameters, the translation error in the vertical direction contributed the most to the registration errors. Visual inspection of the patient registration results revealed success in every instance.Conclusions. The implemented grayscale compression method successfully enhances and segments bone structures in portal images, allowing for accurate determination of patient setup errors in non-coplanar radiotherapy.
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Affiliation(s)
- Zhiyue Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Tantan Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Lijing Zuo
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Yongli Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Ran Wei
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Jianrong Dai
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
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25
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Rankine LJ, Lu J, Wang Z, Kelsey CR, Marks LB, Das SK, Driehuys B. Quantifying Regional Radiation-Induced Lung Injury in Patients Using Hyperpolarized 129Xe Gas Exchange Magnetic Resonance Imaging. Int J Radiat Oncol Biol Phys 2024:S0360-3016(24)00359-6. [PMID: 38452858 DOI: 10.1016/j.ijrobp.2024.02.049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 02/05/2024] [Accepted: 02/24/2024] [Indexed: 03/09/2024]
Abstract
PURPOSE Radiation-induced lung injury has been shown to alter regional ventilation and perfusion in the lung. However, changes in regional pulmonary gas exchange have not previously been measured. METHODS AND MATERIALS Ten patients receiving conventional radiation therapy (RT) for lung cancer underwent pre-RT and 3-month post-RT magnetic resonance imaging (MRI) using an established hyperpolarized 129Xe gas exchange technique to map lung function. Four patients underwent an additional 8-month post-RT MRI. The MR signal from inhaled xenon was measured in the following 3 pulmonary compartments: the lung airspaces, the alveolar membrane tissue, and the pulmonary capillaries (interacting with red blood cells [RBCs]). Thoracic 1H MRI scans were acquired, and deformable registration was used to transfer 129Xe functional maps to the RT planning computed tomography scan. The RT-associated changes in ventilation, membrane uptake, and RBC transfer were computed as a function of regional lung dose (equivalent dose in 2-Gy fractions). Pearson correlations and t tests were used to determine statistical significance, and weighted sum of squares linear regression subsequently characterized the dose dependence of each functional component. The pulmonary function testing metrics of forced vital capacity and diffusing capacity for carbon monoxide were also acquired at each time point. RESULTS Compared with pre-RT baseline, 3-month post-RT ventilation decreased by an average of -0.24 ± 0.05%/Gy (ρ = -0.88; P < .001), membrane uptake increased by 0.69 ± 0.14%/Gy (ρ = 0.94; P < .001), and RBC transfer decreased by -0.41 ± 0.06%/Gy (ρ = -0.92; P < .001). Membrane uptake maintained a strong positive correlation with regional dose at 8 months post-RT, demonstrating an increase of 0.73 ± 0.11%/Gy (ρ = 0.92; P = .006). Changes in membrane uptake and RBC transfer appeared greater in magnitude (%/Gy) for individuals with low heterogeneity in their baseline lung function. An increase in whole-lung membrane uptake showed moderate correlation with decreases in forced vital capacity (ρ = -0.50; P = .17) and diffusing capacity for carbon monoxide (ρ = -0.44; P = .23), with neither correlation reaching statistical significance. CONCLUSIONS Hyperpolarized 129Xe MRI measured and quantified regional, RT-associated, dose-dependent changes in pulmonary gas exchange. This tool could enable future work to improve our understanding and management of radiation-induced lung injury.
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Affiliation(s)
- Leith J Rankine
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina; Medical Physics Graduate Program.
| | | | - Ziyi Wang
- Department of Biomedical Engineering, Duke University, Durham, North Carolina
| | | | - Lawrence B Marks
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina
| | - Shiva K Das
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina
| | - Bastiaan Driehuys
- Medical Physics Graduate Program; Department of Biomedical Engineering, Duke University, Durham, North Carolina; Radiology, Duke University Medical Center, Durham, North Carolina
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Torchia J, Velec M. Deformable image registration for composite planned doses during adaptive radiation therapy. J Med Imaging Radiat Sci 2024; 55:82-90. [PMID: 38218679 DOI: 10.1016/j.jmir.2023.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/18/2023] [Accepted: 12/21/2023] [Indexed: 01/15/2024]
Abstract
INTRODUCTION Some patients have significant anatomic changes during radiotherapy, necessitating an adaptive repeat CT-simulation and re-planning. This yields two unique planning datasets that introduce uncertainty into total dose records. This study explored the impact of using deformable image registration (DIR) to spatially align repeat CT-simulation images and calculate total planned dose distributions. MATERIALS & METHODS Data from 5 head-and-neck, 5 lung, and 5 sarcoma patients who had unanticipated re-planning during radiotherapy were analyzed in a treatment planning system (RayStation v6.1 RaySearch Laboratories). Total planned doses to normal tissues were calculated using two methods and the previously generated manual contours defined on each CT. The first method, termed 'parameter addition', simply sums the relevant DVH metrics from the initial and re-planned distributions without spatially registering the CTs. The second, termed 'dose accumulation', uses a validated hybrid contour/intensity-based DIR algorithm to deform initial CT and dose distribution onto the repeat CT and re-planning dose distribution. DVH metrics from the summed distribution on the repeat CT are then calculated. Dose differences for organs-at-risk between parameter addition and dose accumulation ≥100 cGy were assumed to be clinically relevant. To elucidate whether relevant differences were due to registration accuracy or contouring variability between CTs, the analysis was repeated using contours on the first CT and the same contours deformed to the repeat CT with DIR. RESULTS For all patients, high overall DIR accuracy was verified visually (qualitatively) and numerically (quantitatively) using image similarity and contour-based metrics. All head-and-neck and lung patients, and one sarcoma patient (11 of 15 total) had dose differences between parameter addition and dose accumulation ≥100 cGy, with absolute mean differences of 160 cGy (range 101-436 cGy) seen in 41 of 205 total DVH criteria. In 22 of these 41 criteria, these differences were attributed to contouring variability between CTs. After correcting for contouring variations using DIR, the mean absolute differences in 7 of these 22 criteria with a relevant result (across 6 patients) was 146 cGy (range 100-502 cGy). In only 4 DVH criteria, the DIR mapped contours had higher variations than the original contours. One lung patient had a DVH criteria exceeding the clinical dose constraint by 125 cGy with parameter addition, and with accurate DIR and dose accumulation, the criteria was actually 97 cGy lower than the constraint. CONCLUSIONS The use of DIR to generate total planned dose records revealed substantial dose differences in most cases compared to commonly used clinical methods (i.e. parameter addition), and altered the planned acceptance criteria in a minority. DIR is recommended to be used for future adaptive re-plans to generate total planned dose records and facilitate accurate re-contouring. More accurate dose records may also improve our understanding of clinical outcomes.
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Affiliation(s)
- Joshua Torchia
- Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Michael Velec
- Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada.
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Hoshida K, Ohishi A, Mizoguchi A, Ohkura S, Kawata H. The effects of mega-voltage CT scan parameters on offline adaptive radiation therapy. Radiol Phys Technol 2024; 17:248-257. [PMID: 38334889 DOI: 10.1007/s12194-023-00773-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 12/20/2023] [Accepted: 12/27/2023] [Indexed: 02/10/2024]
Abstract
TomoTherapy involves image-guided radiation therapy (IGRT) using Mega-voltage CT (MVCT) for each treatment session. The acquired MVCT images can be utilized for the retrospective assessment of dose distribution. The TomoTherapy provides 18 distinct imaging conditions that can be selected based on a combination of algorithms, acquisition pitch, and slice interval. We investigated the accuracy of dose calculation and deformable image registration (DIR) depending on MVCT scan parameters and their effects on adaptive radiation therapy (ART). We acquired image values for density calibration tables (IVDTs) under 18 different MVCT conditions and compared them. The planning CT (pCT) was performed using a thoracic phantom, and an esophageal intensity-modulated radiation therapy (IMRT) plan was created. MVCT images of the thoracic phantom were acquired under each of the 18 conditions, and dose recalculation was performed. DIR was performed on the MVCT images acquired under each condition. The accuracy of DIR, depending on the MVCT scan parameters, was compared using the mean distance to agreement (MDA) and Dice similarity coefficient (DSC). The dose distribution calculated on the MVCT images was deformed using deformed vector fields (DVF). No significant differences were observed in the results of the 18 IVDTs. The esophageal IMRT plan also showed a small dose difference. Regarding verifying the DIR accuracy, the MDA increased, and the DSC decreased as the acquisition pitch and slice interval increased. The difference between the dose distributions after dose mapping was comparable to that before DIR. The MVCT scan parameters had little effect on ART.
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Affiliation(s)
- Kento Hoshida
- Department of Radiology, Kurume University Hospital, 67 Asahimachi, Kurume, Fukuoka, 830-0011, Japan.
| | - Ayumu Ohishi
- Department of Radiology, Kurume University Hospital, 67 Asahimachi, Kurume, Fukuoka, 830-0011, Japan
| | - Asumi Mizoguchi
- Department of Radiology, Kurume University Hospital, 67 Asahimachi, Kurume, Fukuoka, 830-0011, Japan
| | - Sunao Ohkura
- Department of Radiology, Kurume University Hospital, 67 Asahimachi, Kurume, Fukuoka, 830-0011, Japan
| | - Hidemichi Kawata
- Department of Radiology, Kurume University Hospital, 67 Asahimachi, Kurume, Fukuoka, 830-0011, Japan
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Podobnik G, Ibragimov B, Peterlin P, Strojan P, Vrtovec T. vOARiability: Interobserver and intermodality variability analysis in OAR contouring from head and neck CT and MR images. Med Phys 2024; 51:2175-2186. [PMID: 38230752 DOI: 10.1002/mp.16924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 10/31/2023] [Accepted: 12/13/2023] [Indexed: 01/18/2024] Open
Abstract
BACKGROUND Accurate and consistent contouring of organs-at-risk (OARs) from medical images is a key step of radiotherapy (RT) cancer treatment planning. Most contouring approaches rely on computed tomography (CT) images, but the integration of complementary magnetic resonance (MR) modality is highly recommended, especially from the perspective of OAR contouring, synthetic CT and MR image generation for MR-only RT, and MR-guided RT. Although MR has been recognized as valuable for contouring OARs in the head and neck (HaN) region, the accuracy and consistency of the resulting contours have not been yet objectively evaluated. PURPOSE To analyze the interobserver and intermodality variability in contouring OARs in the HaN region, performed by observers with different level of experience from CT and MR images of the same patients. METHODS In the final cohort of 27 CT and MR images of the same patients, contours of up to 31 OARs were obtained by a radiation oncology resident (junior observer, JO) and a board-certified radiation oncologist (senior observer, SO). The resulting contours were then evaluated in terms of interobserver variability, characterized as the agreement among different observers (JO and SO) when contouring OARs in a selected modality (CT or MR), and intermodality variability, characterized as the agreement among different modalities (CT and MR) when OARs were contoured by a selected observer (JO or SO), both by the Dice coefficient (DC) and 95-percentile Hausdorff distance (HD95 $_{95}$ ). RESULTS The mean (±standard deviation) interobserver variability was 69.0 ± 20.2% and 5.1 ± 4.1 mm, while the mean intermodality variability was 61.6 ± 19.0% and 6.1 ± 4.3 mm in terms of DC and HD95 $_{95}$ , respectively, across all OARs. Statistically significant differences were only found for specific OARs. The performed MR to CT image registration resulted in a mean target registration error of 1.7 ± 0.5 mm, which was considered as valid for the analysis of intermodality variability. CONCLUSIONS The contouring variability was, in general, similar for both image modalities, and experience did not considerably affect the contouring performance. However, the results indicate that an OAR is difficult to contour regardless of whether it is contoured in the CT or MR image, and that observer experience may be an important factor for OARs that are deemed difficult to contour. Several of the differences in the resulting variability can be also attributed to adherence to guidelines, especially for OARs with poor visibility or without distinctive boundaries in either CT or MR images. Although considerable contouring differences were observed for specific OARs, it can be concluded that almost all OARs can be contoured with a similar degree of variability in either the CT or MR modality, which works in favor of MR images from the perspective of MR-only and MR-guided RT.
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Affiliation(s)
- Gašper Podobnik
- Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia
| | - Bulat Ibragimov
- Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Tomaž Vrtovec
- Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia
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Jóhannesson V, Gunnlaugsson A, Nilsson P, Brynolfsson P, Kjellén E, Wieslander E. Dose-volume relationships of planned versus estimated delivered radiation doses to pelvic organs at risk and side effects in patients treated with salvage radiotherapy for recurrent prostate cancer. Tech Innov Patient Support Radiat Oncol 2024; 29:100231. [PMID: 38192583 PMCID: PMC10772375 DOI: 10.1016/j.tipsro.2023.100231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 11/26/2023] [Accepted: 12/11/2023] [Indexed: 01/10/2024] Open
Abstract
Purpose To investigate estimated delivered dose distributions using weekly cone-beam computed tomography (CBCT) scans for pelvic organs at risk (OARs) in salvage radiotherapy (SRT) after radical prostatectomy. Furthermore, to compare them with the originally planned dose distributions and analyse associations with gastrointestinal (GI) and genitourinary (GU) side effects. Methods This study is part of a phase II trial involving SRT for recurrent prostate cancer. Treatment was personalised based on PSA response during SRT, classifying patients as PSA responders or non-responders. Estimated radiation dose distributions were obtained using deformable image registration from weekly CBCT scans. GI and GU toxicities were assessed using the RTOG toxicity scale, while patient-reported symptoms were monitored through self-assessment questionnaires. Results The study included 100 patients, with similar treatment-related side effects observed in both responders and non-responders. Differences in dose-volume metrics between the planned and estimated delivered doses for the examined OARs were mostly modest, although generally statistically significant. We identified statistically significant associations between QUANTEC-recommended dose-volume constraints and acute bowel toxicity, as well as late urinary patient-reported symptoms, for both the estimated delivered and planned dose distributions. Conclusion We found small but statistically significant differences between estimated delivered and planned doses to OARs. These differences showed trends toward improved associations for estimated delivered dose distributions with side effects. Enhanced registration methods and imaging techniques could potentially further enhance the assessment of truly delivered doses and yield more reliable dose-volume constraints for future therapies.
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Affiliation(s)
- Vilberg Jóhannesson
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Oncology and Pathology, Lund, Sweden
| | - Adalsteinn Gunnlaugsson
- Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Oncology and Pathology, Lund, Sweden
| | - Per Nilsson
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Radiation Physics, Lund, Sweden
| | - Patrik Brynolfsson
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Sweden
| | - Elisabeth Kjellén
- Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Oncology and Pathology, Lund, Sweden
| | - Elinore Wieslander
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Sweden
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George SC, Tolakanahalli R, Aguirre S, Kim TP, Samuel EJJ, Mishra V. A single-institution experience with 177Lu RPT workflow improvements and qualifying the SPECT/CT imaging for dosimetry. Front Oncol 2024; 14:1331266. [PMID: 38469241 PMCID: PMC10925616 DOI: 10.3389/fonc.2024.1331266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 01/22/2024] [Indexed: 03/13/2024] Open
Abstract
Background and purpose Implementing any radiopharmaceutical therapy (RPT) program requires a comprehensive review of system readiness, appropriate workflows, and training to ensure safe and efficient treatment delivery. A quantitative assessment of the dose delivered to targets and organs at risk (OAR) using RPT is possible by correlating the absorbed doses with the delivered radioactivity. Integrating dosimetry into an established RPT program demands a thorough analysis of the necessary components and system fine-tuning. This study aims to report an optimized workflow for molecular radiation therapy using 177Lu with a primary focus on integrating patient-specific dosimetry into an established radiopharmaceutical program in a radiation oncology setting. Materials and methods We comprehensively reviewed using the Plan-Do-Check-Act (PDCA) cycle, including efficacy and accuracy of delivery and all aspects of radiation safety of the RPT program. The GE Discovery SPECT/CT 670DR™ system was calibrated per MIM protocol for dose calculation on MIM SurePlan™ MRT software. Jaszcak Phantom with 15-20 mCi of 177Lu DOTATATE with 2.5 µM EDTA solution was used, with the main energy window defined as 208 keV ±10% (187.6 to 229.2 keV); the upper scatter energy window was set to 240 keV ±5% (228 to 252 keV), while the lower scatter energy window was 177.8 keV ±5% (168.9 to 186.7 keV). Volumetric quality control tests and adjustments were performed to ensure the correct alignment of the table, NM, and CT gantry on SPECT/CT. A comprehensive end-to-end (E2E) test was performed to ensure workflow, functionality, and quantitative dose accuracy. Results Workflow improvements and checklists are presented after systematically analyzing over 400 administrations of 177Lu-based RPT. Injected activity to each sphere in the NEMA Phantom scan was quantified, and the MIM Sureplan MRT reconstruction images calculated activities within ±12% of the injected activity. Image alignment tests on the SPECT/CT showed a discrepancy of more than the maximum tolerance of 2.2 mm on any individual axis. As a result of servicing the machine and updating the VQC and COR corrections, the hybrid imaging system was adjusted to achieve an accuracy of <1 mm in all directions. Conclusion Workflows and checklists, after analysis of system readiness and adequate training for staff and patients, are presented. Hardware and software components for patient-specific dosimetry are presented with a focus on hybrid image registration and correcting any errors that affect dosimetric quantification calculation. Moreover, this manuscript briefly overviews the necessary quality assurance requirements for converting diagnostic images into dosimetry measurement tools and integrating dosimetry for RPT based on 177Lu.
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Affiliation(s)
- Siju C. George
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health, Miami, FL, United States
- Department of Physics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, India
| | - Ranjini Tolakanahalli
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health, Miami, FL, United States
| | - Santiago Aguirre
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health, Miami, FL, United States
| | - Taehyung Peter Kim
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health, Miami, FL, United States
| | | | - Vivek Mishra
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health, Miami, FL, United States
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Lin YM, Paolucci I, Albuquerque Marques Silva J, O'Connor CS, Hong J, Shah KY, Abdelsalam ME, Habibollahi P, Jones KA, Brock KK, Odisio BC. Ablative margin quantification using deformable versus rigid image registration in colorectal liver metastasis thermal ablation: a retrospective single-center study. Eur Radiol 2024:10.1007/s00330-024-10632-8. [PMID: 38334762 DOI: 10.1007/s00330-024-10632-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Revised: 01/11/2024] [Accepted: 01/19/2024] [Indexed: 02/10/2024]
Abstract
PURPOSE To investigate the correlation of minimal ablative margin (MAM) quantification using biomechanical deformable (DIR) versus intensity-based rigid image registration (RIR) with local outcomes following colorectal liver metastasis (CLM) thermal ablation. METHODS This retrospective single-institution study included consecutive patients undergoing thermal ablation between May 2016 and October 2021. Patients who did not have intraprocedural pre- and post-ablation contrast-enhanced CT images for MAM quantification or follow-up period less than 1 year without residual tumor or local tumor progression (LTP) were excluded. DIR and RIR methods were used to quantify the MAM. The registration accuracy was compared using Dice similarity coefficient (DSC). Area under the receiver operating characteristic curve (AUC) was used to test MAM in predicting local tumor outcomes. RESULTS A total of 72 patients (mean age 57; 44 men) with 139 tumors (mean diameter 1.5 cm ± 0.8 (SD)) were included. During a median follow-up of 29.4 months, there was one residual unablated tumor and the LTP rate was 17% (24/138). The ranges of DSC were 0.96-0.98 and 0.67-0.98 for DIR and RIR, respectively (p < 0.001). When using DIR, 27 (19%) tumors were partially or totally registered outside the liver, compared to 46 (33%) with RIR. Using DIR versus RIR, the corresponding median MAM was 4.7 mm versus 4.0 mm, respectively (p = 0.5). The AUC in predicting residual tumor and 1-year LTP for DIR versus RIR was 0.89 versus 0.72, respectively (p < 0.001). CONCLUSION Ablative margin quantified on intra-procedural CT imaging using DIR method outperformed RIR for predicting local outcomes of CLM thermal ablation. CLINICAL RELEVANCE STATEMENT The study supports the role of biomechanical deformable image registration as the preferred image registration method over rigid image registration for quantifying minimal ablative margins using intraprocedural contrast-enhanced CT images. KEY POINTS • Accurate and reproducible image registration is a prerequisite for clinical application of image-based ablation confirmation methods. • When compared to intensity-based rigid image registration, biomechanical deformable image registration for minimal ablative margin quantification was more accurate for liver registration using intraprocedural contrast-enhanced CT images. • Biomechanical deformable image registration outperformed intensity-based rigid image registration for predicting local tumor outcomes following colorectal liver metastasis thermal ablation.
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Affiliation(s)
- Yuan-Mao Lin
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Iwan Paolucci
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Jessica Albuquerque Marques Silva
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Caleb S O'Connor
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Jun Hong
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Ketan Y Shah
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Mohamed E Abdelsalam
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Peiman Habibollahi
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Kyle A Jones
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Kristy K Brock
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Bruno C Odisio
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
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Tegtmeier RC, Kutyreff CJ, Smetanick JL, Hobbis D, Laughlin BS, Toesca DAS, Clouser EL, Rong Y. Custom-Trained Deep Learning-Based Auto-Segmentation for Male Pelvic Iterative CBCT on C-Arm Linear Accelerators. Pract Radiat Oncol 2024:S1879-8500(24)00035-3. [PMID: 38325548 DOI: 10.1016/j.prro.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/21/2023] [Accepted: 01/11/2024] [Indexed: 02/09/2024]
Abstract
PURPOSE The purpose of this investigation was to evaluate the clinical applicability of a commercial artificial intelligence-driven deep learning auto-segmentation (DLAS) tool on enhanced iterative cone beam computed tomography (iCBCT) acquisitions for intact prostate and prostate bed treatments. METHODS AND MATERIALS DLAS models were trained using 116 iCBCT data sets with manually delineated organs at risk (bladder, femoral heads, and rectum) and target volumes (intact prostate and prostate bed) adhering to institution-specific contouring guidelines. An additional 25 intact prostate and prostate bed iCBCT data sets were used for model testing. Segmentation accuracy relative to a reference structure set was quantified using various geometric comparison metrics and qualitatively evaluated by trained physicists and physicians. These results were compared with those obtained for an additional DLAS-based model trained on planning computed tomography (pCT) data sets and for a deformable image registration (DIR)-based automatic contour propagation method. RESULTS In most instances, statistically significant differences in the Dice similarity coefficient (DSC), 95% directed Hausdorff distance, and mean surface distance metrics were observed between the models, as the iCBCT-trained DLAS model outperformed the pCT-trained DLAS model and DIR-based method for all organs at risk and the intact prostate target volume. Mean DSC values for the proposed method were ≥0.90 for these volumes of interest. The iCBCT-trained DLAS model demonstrated a relatively suboptimal performance for the prostate bed segmentation, as the mean DSC value was <0.75 for this target contour. Overall, 90% of bladder, 93% of femoral head, 67% of rectum, and 92% of intact prostate contours generated by the proposed method were deemed clinically acceptable based on qualitative scoring, and approximately 63% of prostate bed contours required moderate or major manual editing to adhere to institutional contouring guidelines. CONCLUSIONS The proposed method presents the potential for improved segmentation accuracy and efficiency compared with the DIR-based automatic contour propagation method as commonly applied in CBCT-based dose evaluation and calculation studies.
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Affiliation(s)
- Riley C Tegtmeier
- Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona
| | | | | | - Dean Hobbis
- Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona; Department of Radiation Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Brady S Laughlin
- Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona
| | | | - Edward L Clouser
- Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona
| | - Yi Rong
- Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
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Meyer S, Alam S, Kuo L, Hu YC, Liu Y, Lu W, Yorke E, Li A, Cervino L, Zhang P. Creating patient-specific digital phantoms with a longitudinal atlas for evaluating deformable CT-CBCT registration in adaptive lung radiotherapy. Med Phys 2024; 51:1405-1414. [PMID: 37449537 PMCID: PMC10787815 DOI: 10.1002/mp.16606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 05/26/2023] [Accepted: 06/22/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Quality assurance of deformable image registration (DIR) is challenging because the ground truth is often unavailable. In addition, current approaches that rely on artificial transformations do not adequately resemble clinical scenarios encountered in adaptive radiotherapy. PURPOSE We developed an atlas-based method to create a variety of patient-specific serial digital phantoms with CBCT-like image quality to assess the DIR performance for longitudinal CBCT imaging data in adaptive lung radiotherapy. METHODS A library of deformations was created by extracting the longitudinal changes observed between a planning CT and weekly CBCT from an atlas of lung radiotherapy patients. The planning CT of an inquiry patient was first deformed by mapping the deformation pattern from a matched atlas patient, and subsequently appended with CBCT artifacts to imitate a weekly CBCT. Finally, a group of digital phantoms around an inquiry patient was produced to simulate a series of possible evolutions of tumor and adjacent normal structures. We validated the generated deformation vector fields (DVFs) to ensure numerically and physiologically realistic transformations. The proposed framework was applied to evaluate the performance of the DIR algorithm implemented in the commercial Eclipse treatment planning system in a retrospective study of eight inquiry patients. RESULTS The generated DVFs were inverse consistent within less than 3 mm and did not exhibit unrealistic folding. The deformation patterns adequately mimicked the observed longitudinal anatomical changes of the matched atlas patients. Worse Eclipse DVF accuracy was observed in regions of low image contrast or artifacts. The structure volumes exhibiting a DVF error magnitude of equal or more than 2 mm ranged from 24.5% (spinal cord) to 69.2% (heart) and the maximum DVF error exceeded 5 mm for all structures except the spinal cord. Contour-based evaluations showed a high degree of alignment with dice similarity coefficients above 0.8 in all cases, which underestimated the overall DVF accuracy within the structures. CONCLUSIONS It is feasible to create and augment digital phantoms based on a particular patient of interest using multiple series of deformation patterns from matched patients in an atlas. This can provide a semi-automated procedure to complement the quality assurance of CT-CBCT DIR and facilitate the clinical implementation of image-guided and adaptive radiotherapy that involve longitudinal CBCT imaging studies.
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Affiliation(s)
- Sebastian Meyer
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Sadegh Alam
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - LiCheng Kuo
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Yu-Chi Hu
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Yilin Liu
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Wei Lu
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Ellen Yorke
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Anyi Li
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Laura Cervino
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Pengpeng Zhang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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Xu Y, Jin W, Butkus M, De Ornelas M, Cyriac J, Studenski MT, Padgett K, Simpson G, Samuels S, Samuels M, Dogan N. Cone beam CT-based adaptive intensity modulated proton therapy assessment using automated planning for head-and-neck cancer. Radiat Oncol 2024; 19:13. [PMID: 38263237 PMCID: PMC10804468 DOI: 10.1186/s13014-024-02406-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 01/15/2024] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND To assess the feasibility of CBCT-based adaptive intensity modulated proton therapy (IMPT) using automated planning for treatment of head and neck (HN) cancers. METHODS Twenty HN cancer patients who received radiotherapy and had pretreatment CBCTs were included in this study. Initial IMPT plans were created using automated planning software for all patients. Synthetic CTs (sCT) were then created by deforming the planning CT (pCT) to the pretreatment CBCTs. To assess dose calculation accuracy on sCTs, repeat CTs (rCTs) were deformed to the pretreatment CBCT obtained on the same day to create deformed rCT (rCTdef), serving as gold standard. The dose recalculated on sCT and on rCTdef were compared by using Gamma analysis. The accuracy of DIR generated contours was also assessed. To explore the potential benefits of adaptive IMPT, two sets of plans were created for each patient, a non-adapted IMPT plan and an adapted IMPT plan calculated on weekly sCT images. The weekly doses for non-adaptive and adaptive IMPT plans were accumulated on the pCT, and the accumulated dosimetric parameters of two sets were compared. RESULTS Gamma analysis of the dose recalculated on sCT and rCTdef resulted in a passing rate of 97.9% ± 1.7% using 3 mm/3% criteria. With the physician-corrected contours on the sCT, the dose deviation range of using sCT to estimate mean dose for the most organ at risk (OARs) can be reduced to (- 2.37%, 2.19%) as compared to rCTdef, while for V95 of primary or secondary CTVs, the deviation can be controlled within (- 1.09%, 0.29%). Comparison of the accumulated doses from the adaptive planning against the non-adaptive plans reduced mean dose to constrictors (- 1.42 Gy ± 2.79 Gy) and larynx (- 2.58 Gy ± 3.09 Gy). The reductions result in statistically significant reductions in the normal tissue complication probability (NTCP) of larynx edema by 7.52% ± 13.59%. 4.5% of primary CTVs, 4.1% of secondary CTVs, and 26.8% tertiary CTVs didn't meet the V95 > 95% constraint on non-adapted IMPT plans. All adaptive plans were able to meet the coverage constraint. CONCLUSION sCTs can be a useful tool for accurate proton dose calculation. Adaptive IMPT resulted in better CTV coverage, OAR sparing and lower NTCP for some OARs as compared with non-adaptive IMPT.
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Affiliation(s)
- Yihang Xu
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
- Department of Biomedical Engineering, College of Engineering, University of Miami, Coral Gables, FL, USA
| | - William Jin
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael Butkus
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Mariluz De Ornelas
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jonathan Cyriac
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Matthew T Studenski
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kyle Padgett
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Garrett Simpson
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Stuart Samuels
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael Samuels
- Department of Radiation Oncology, Banner MD Anderson Cancer Center, Gilbert, AZ, USA
| | - Nesrin Dogan
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA.
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Barten DLJ, van Kesteren Z, Laan JJ, Dassen MG, Westerveld GH, Pieters BR, de Jonge CS, Stoker J, Bel A. Precision assessment of bowel motion quantification using 3D cine-MRI for radiotherapy. Phys Med Biol 2024; 69:04NT01. [PMID: 38232395 DOI: 10.1088/1361-6560/ad1f89] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 01/17/2024] [Indexed: 01/19/2024]
Abstract
Objective. The bowel is an important organ at risk for toxicity during pelvic and abdominal radiotherapy. Identifying regions of high and low bowel motion with MRI during radiotherapy may help to understand the development of bowel toxicity, but the acquisition time of MRI is rather long. The aim of this study is to retrospectively evaluate the precision of bowel motion quantification and to estimate the minimum MRI acquisition time.Approach. We included 22 gynaecologic cancer patients receiving definitive radiotherapy with curative intent. The 10 min pre-treatment 3D cine-MRI scan consisted of 160 dynamics with an acquisition time of 3.7 s per volume. Deformable registration of consecutive images generated 159 deformation vector fields (DVFs). We defined two motion metrics, the 50th percentile vector lengths (VL50) of the complete set of DVFs was used to measure median bowel motion. The 95th percentile vector lengths (VL95) was used to quantify high motion of the bowel. The precision of these metrics was assessed by calculating their variation (interquartile range) in three different time frames, defined as subsets of 40, 80, and 120 consecutive images, corresponding to acquisition times of 2.5, 5.0, and 7.5 min, respectively.Main results. For the full 10 min scan, the minimum motion per frame of 50% of the bowel volume (M50%) ranged from 0.6-3.5 mm for the VL50 motion metric and 2.3-9.0 mm for the VL95 motion metric, across all patients. At 7.5 min scan time, the variation in M50% was less than 0.5 mm in 100% (VL50) and 95% (VL95) of the subsets. A scan time of 5.0 and 2.5 min achieved a variation within 0.5 mm in 95.2%/81% and 85.7%/57.1% of the subsets, respectively.Significance. Our 3D cine-MRI technique quantifies bowel loop motion with 95%-100% confidence with a precision of 0.5 mm variation or less, using a 7.5 min scan time.
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Affiliation(s)
- D L J Barten
- Amsterdam UMC location University of Amsterdam, Department of Radiation Oncology, Meibergdreef 9, 1105 AZAmsterdam, The Netherlands
| | - Z van Kesteren
- Amsterdam UMC location University of Amsterdam, Department of Radiation Oncology, Meibergdreef 9, 1105 AZAmsterdam, The Netherlands
| | - J J Laan
- Amsterdam UMC location University of Amsterdam, Department of Radiation Oncology, Meibergdreef 9, 1105 AZAmsterdam, The Netherlands
| | - M G Dassen
- Amsterdam UMC location University of Amsterdam, Department of Radiation Oncology, Meibergdreef 9, 1105 AZAmsterdam, The Netherlands
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - G H Westerveld
- Amsterdam UMC location University of Amsterdam, Department of Radiation Oncology, Meibergdreef 9, 1105 AZAmsterdam, The Netherlands
- Erasmus MC Cancer Institute, Erasmus University Medical Center, Department of Radiation Oncology, Rotterdam, The Netherlands
| | - B R Pieters
- Amsterdam UMC location University of Amsterdam, Department of Radiation Oncology, Meibergdreef 9, 1105 AZAmsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | - C S de Jonge
- Amsterdam UMC location University of Amsterdam, Department of Radiology and Nuclear Medicine, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, The Netherlands
| | - J Stoker
- Amsterdam UMC location University of Amsterdam, Department of Radiology and Nuclear Medicine, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, The Netherlands
| | - A Bel
- Amsterdam UMC location University of Amsterdam, Department of Radiation Oncology, Meibergdreef 9, 1105 AZAmsterdam, The Netherlands
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Wang E, Yen A, Hrycushko B, Wang S, Lin J, Zhong X, Dohopolski M, Nwachukwu C, Iqbal Z, Albuquerque K. The accuracy of artificial intelligence deformed nodal structures in cervical online cone-beam-based adaptive radiotherapy. Phys Imaging Radiat Oncol 2024; 29:100546. [PMID: 38369990 PMCID: PMC10869256 DOI: 10.1016/j.phro.2024.100546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 01/31/2024] [Accepted: 02/01/2024] [Indexed: 02/20/2024] Open
Abstract
Background and Purpose Online cone-beam-based adaptive radiotherapy (ART) adjusts for anatomical changes during external beam radiotherapy. However, limited cone-beam image quality complicates nodal contouring. Despite this challenge, artificial-intelligence guided deformation (AID) can auto-generate nodal contours. Our study investigated the optimal use of such contours in cervical online cone-beam-based ART. Materials and Methods From 136 adaptive fractions across 21 cervical cancer patients with nodal disease, we extracted 649 clinically-delivered and AID clinical target volume (CTV) lymph node boost structures. We assessed geometric alignment between AID and clinical CTVs via dice similarity coefficient, and 95% Hausdorff distance, and geometric coverage of clinical CTVs by AID planning target volumes by false positive dice. Coverage of clinical CTVs by AID contour-based plans was evaluated using D100, D95, V100%, and V95%. Results Between AID and clinical CTVs, the median dice similarity coefficient was 0.66 and the median 95 % Hausdorff distance was 4.0 mm. The median false positive dice of clinical CTV coverage by AID planning target volumes was 0. The median D100 was 1.00, the median D95 was 1.01, the median V100% was 1.00, and the median V95% was 1.00. Increased nodal volume, fraction number, and daily adaptation were associated with reduced clinical CTV coverage by AID-based plans. Conclusion In one of the first reports on pelvic nodal ART, AID-based plans could adequately cover nodal targets. However, physician review is required due to performance variation. Greater attention is needed for larger, daily-adapted nodes further into treatment.
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Affiliation(s)
- Ethan Wang
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
| | - Allen Yen
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
| | - Brian Hrycushko
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
| | - Siqiu Wang
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
| | - Jingyin Lin
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
| | - Xinran Zhong
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
| | - Michael Dohopolski
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
| | - Chika Nwachukwu
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
| | - Zohaib Iqbal
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
| | - Kevin Albuquerque
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, Dallas, TX, United States
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Xiong Y, Rabe M, Rippke C, Kawula M, Nierer L, Klüter S, Belka C, Niyazi M, Hörner-Rieber J, Corradini S, Landry G, Kurz C. Impact of daily plan adaptation on accumulated doses in ultra-hypofractionated magnetic resonance-guided radiation therapy of prostate cancer. Phys Imaging Radiat Oncol 2024; 29:100562. [PMID: 38463219 PMCID: PMC10924058 DOI: 10.1016/j.phro.2024.100562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 01/18/2024] [Accepted: 02/19/2024] [Indexed: 03/12/2024] Open
Abstract
Background and purpose Ultra-hypofractionated online adaptive magnetic resonance-guided radiotherapy (MRgRT) is promising for prostate cancer. However, the impact of online adaptation on target coverage and organ-at-risk (OAR) sparing at the level of accumulated dose has not yet been reported. Using deformable image registration (DIR)-based accumulation, we compared the delivered adapted dose with the simulated non-adapted dose. Materials and methods Twenty-three prostate cancer patients treated at two clinics with 0.35 T magnetic resonance-guided linear accelerator (MR-linac) following the same treatment protocol (5 × 7.5 Gy with urethral sparing and daily adaptation) were included. The fraction MR images were deformably registered to the planning MR image. Both non-adapted and adapted fraction doses were accumulated with the corresponding vector fields. Two DIR approaches were implemented. PTV* (planning target volume minus urethra+2mm) D95%, CTV* (clinical target volume minus urethra) D98%, and OARs (urethra+2mm, bladder, and rectum) D0.2cc, were evaluated. Statistical significance was inferred from a two-tailed Wilcoxon signed-rank test (p < 0.05). Results Normalized to the baseline, the accumulated PTV* D95% increased significantly by 2.7 % ([1.5, 4.3]%) through adaptation, and the CTV* D98% by 1.2 % ([0.1, 1.7]%). For the OARs after adaptation, accumulated bladder D0.2cc decreased by 0.4 % ([-1.2, 0.4]%), urethra+2mmD0.2cc by 0.8 % ([-1.6, -0.1]%), while rectum D0.2cc increased by 2.6 % ([1.2, 4.9]%). For all patients, rectum D0.2cc was still below the clinical constraint. Results of both DIR approaches differed on average by less than 0.2 %. Conclusions Online adaptation in MRgRT improved target coverage and OARs sparing at the level of accumulated dose.
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Affiliation(s)
- Yuqing Xiong
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Moritz Rabe
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Carolin Rippke
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maria Kawula
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Lukas Nierer
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Sebastian Klüter
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology, National Center for Radiation Oncology, Heidelberg, Germany
| | - Claus Belka
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner site Munich, a Partnership between DKFZ and LMU University Hospital Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Maximilian Niyazi
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Juliane Hörner-Rieber
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology, National Center for Radiation Oncology, Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center, Heidelberg, Germany
- National Center for Tumor Diseases, Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Stefanie Corradini
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Christopher Kurz
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
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Rosu-Bubulac M, Trankle CR, Mankad P, Grizzard JD, Ellenbogen KA, Jordan JH, Weiss E. Institutional experience report on the target contouring workflow in the radiotherapy department for stereotactic arrhythmia radioablation delivered on conventional linear accelerators. Strahlenther Onkol 2024; 200:83-96. [PMID: 37872398 DOI: 10.1007/s00066-023-02159-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 09/17/2023] [Indexed: 10/25/2023]
Abstract
PURPOSE In stereotactic arrhythmia radioablation (STAR), the target is defined using multiple imaging studies and a multidisciplinary team consisting of electrophysiologist, cardiologist, cardiac radiologist, and radiation oncologist collaborate to identify the target and delineate it on the imaging studies of interest. This report describes the workflow employed in our radiotherapy department to transfer the target identified based on electrophysiology and cardiology imaging to the treatment planning image set. METHODS The radiotherapy team was presented with an initial target in cardiac axes orientation, contoured on a wideband late gadolinium-enhanced (WB-LGE) cardiac magnetic resonance (CMR) study, which was subsequently transferred to the computed tomography (CT) scan used for treatment planning-i.e., the average intensity projection (AIP) image set derived from a 4D CT-via an axial CMR image set, using rigid image registration focused on the target area. The cardiac and the respiratory motion of the target were resolved using ciné-CMR and 4D CT imaging studies, respectively. RESULTS The workflow was carried out for 6 patients and resulted in an internal target defined in standard anatomical orientation that encompassed the cardiac and the respiratory motion of the initial target. CONCLUSION An image registration-based workflow was implemented to render the STAR target on the planning image set in a consistent manner, using commercial software traditionally available for radiation therapy.
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Affiliation(s)
- Mihaela Rosu-Bubulac
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, USA.
| | - Cory R Trankle
- Department of Internal Medicine, Division of Cardiology, Virginia Commonwealth University, Richmond, VA, USA
- Pauley Heart Center, Virginia Commonwealth University, Richmond, VA, USA
| | - Pranav Mankad
- Department of Internal Medicine, Division of Cardiology, Virginia Commonwealth University, Richmond, VA, USA
- Pauley Heart Center, Virginia Commonwealth University, Richmond, VA, USA
| | - John D Grizzard
- Department of Radiology, Virginia Commonwealth University, Richmond, VA, USA
| | - Kenneth A Ellenbogen
- Department of Internal Medicine, Division of Cardiology, Virginia Commonwealth University, Richmond, VA, USA
- Pauley Heart Center, Virginia Commonwealth University, Richmond, VA, USA
| | - Jennifer H Jordan
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA, USA
- Pauley Heart Center, Virginia Commonwealth University, Richmond, VA, USA
| | - Elisabeth Weiss
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, USA
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Karius A, Strnad V, Lotter M, Kreppner S, Fietkau R, Bert C. Investigating the impact of breast positioning control on physical treatment parameters in multi-catheter breast brachytherapy. Strahlenther Onkol 2024; 200:49-59. [PMID: 37676482 PMCID: PMC10784386 DOI: 10.1007/s00066-023-02127-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 07/16/2023] [Indexed: 09/08/2023]
Abstract
PURPOSE To assess the effects of a workflow for reproducible patient and breast positioning on implant stability during high-dose-rate multi-catheter breast brachytherapy. METHODS Thirty patients were treated with our new positioning control workflow. Implant stability was evaluated based on a comparison of planning-CTs to control-CTs acquired halfway through the treatment. To assess geometric stability, button-button distance variations as well as Euclidean dwell position deviations were evaluated. The latter were also quantified within various separated regions within the breast to investigate the location-dependency of implant alterations. Furthermore, dosimetric variations to target volume and organs at risk (ribs, skin) as well as isodose volume changes were analyzed. Results were compared to a previously treated cohort of 100 patients. RESULTS With the introduced workflow, the patient fraction affected by button-button distance variations > 5 mm and by dwell position deviations > 7 mm were reduced from 37% to 10% and from 30% to 6.6%, respectively. Implant stability improved the most in the lateral to medial breast regions. Only small stability enhancements were observed regarding target volume dosimetry, but the stability of organ at risk exposure became substantially higher. D0.2ccm skin dose variations > 12.4% and D0.1ccm rib dose variations > 6.7% were reduced from 11% to 0% and from 16% to 3.3% of all patients, respectively. CONCLUSION Breast positioning control improved geometric and dosimetric implant stability for individual patients, and thus enhanced physical plan validity in these cases.
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Affiliation(s)
- Andre Karius
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsstr. 27, 91054, Erlangen, Germany.
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany.
| | - Vratislav Strnad
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsstr. 27, 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Michael Lotter
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsstr. 27, 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Stephan Kreppner
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsstr. 27, 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Rainer Fietkau
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsstr. 27, 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Christoph Bert
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsstr. 27, 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
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He Y, Cazoulat G, Wu C, Svensson S, Almodovar-Abreu L, Rigaud B, McCollum E, Peterson C, Wooten Z, Rhee DJ, Balter P, Pollard-Larkin J, Cardenas C, Court L, Liao Z, Mohan R, Brock K. Quantifying the Effect of 4-Dimensional Computed Tomography-Based Deformable Dose Accumulation on Representing Radiation Damage for Patients with Locally Advanced Non-Small Cell Lung Cancer Treated with Standard-Fractionated Intensity-Modulated Radiation Therapy. Int J Radiat Oncol Biol Phys 2024; 118:231-241. [PMID: 37552151 DOI: 10.1016/j.ijrobp.2023.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/04/2023] [Accepted: 07/14/2023] [Indexed: 08/09/2023]
Abstract
PURPOSE The aim of this study was to investigate the dosimetric and clinical effects of 4-dimensional computed tomography (4DCT)-based longitudinal dose accumulation in patients with locally advanced non-small cell lung cancer treated with standard-fractionated intensity-modulated radiation therapy (IMRT). METHODS AND MATERIALS Sixty-seven patients were retrospectively selected from a randomized clinical trial. Their original IMRT plan, planning and verification 4DCTs, and ∼4-month posttreatment follow-up CTs were imported into a commercial treatment planning system. Two deformable image registration algorithms were implemented for dose accumulation, and their accuracies were assessed. The planned and accumulated doses computed using average-intensity images or phase images were compared. At the organ level, mean lung dose and normal-tissue complication probability (NTCP) for grade ≥2 radiation pneumonitis were compared. At the region level, mean dose in lung subsections and the volumetric overlap between isodose intervals were compared. At the voxel level, the accuracy in estimating the delivered dose was compared by evaluating the fit of a dose versus radiographic image density change (IDC) model. The dose-IDC model fit was also compared for subcohorts based on the magnitude of NTCP difference (|ΔNTCP|) between planned and accumulated doses. RESULTS Deformable image registration accuracy was quantified, and the uncertainty was considered for the voxel-level analysis. Compared with planned doses, accumulated doses on average resulted in <1-Gy lung dose increase and <2% NTCP increase (up to 8.2 Gy and 18.8% for a patient, respectively). Volumetric overlap of isodose intervals between the planned and accumulated dose distributions ranged from 0.01 to 0.93. Voxel-level dose-IDC models demonstrated a fit improvement from planned dose to accumulated dose (pseudo-R2 increased 0.0023) and a further improvement for patients with ≥2% |ΔNTCP| versus for patients with <2% |ΔNTCP|. CONCLUSIONS With a relatively large cohort, robust image registrations, multilevel metric comparisons, and radiographic image-based evidence, we demonstrated that dose accumulation more accurately represents the delivered dose and can be especially beneficial for patients with greater longitudinal response.
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Affiliation(s)
- Yulun He
- Graduate School of Biomedical Sciences, University of Texas MD Anderson Cancer Center UTHealth Houston, Houston, Texas; Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas.
| | - Guillaume Cazoulat
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Carol Wu
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | | | | | - Bastien Rigaud
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Emma McCollum
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Christine Peterson
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Zachary Wooten
- Department of Statistics, Rice University, Houston, Texas
| | - Dong Joo Rhee
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peter Balter
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Julianne Pollard-Larkin
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Carlos Cardenas
- Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Laurence Court
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Zhongxing Liao
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Radhe Mohan
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kristy Brock
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
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Hughes N, Salzillo TC, Vedam S, Lim TY, Wang X, Wang H, Mohammedsaid M, Fuller CD, Wang J, Yang J. A look-up-table development to facilitate CT simulation of MR-Linac treatment. Phys Imaging Radiat Oncol 2024; 29:100524. [PMID: 38192414 PMCID: PMC10772372 DOI: 10.1016/j.phro.2023.100524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 12/09/2023] [Accepted: 12/11/2023] [Indexed: 01/10/2024] Open
Abstract
While current MR-Linac (MRL) treatment workflows utilize a large table overlay during CT simulation to convert indexing between the two machines, we developed a look-up-table (LUT) as an alternative approach. After populating the LUT, index conversion factors were verified at three separate table locations. The resultant root-mean-square isocenter shifts on the MRL were 0.04/0.08 cm, 0.08/0.07 cm, and 0.09/0.08 cm with/without using the table overlay during simulation in the lateral, longitudinal, and vertical directions, respectively, which is within registration tolerance. Clinical implementation of the LUT has resulted in a more efficient MRL treatment workflow while maintaining accurate patient setup.
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Affiliation(s)
- Neil Hughes
- Radiation Therapy Program, MD Anderson Cancer Center School of Health Professions, Houston, TX, United States
| | - Travis C. Salzillo
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, United States
| | - Sastry Vedam
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, United States
| | - Tze Yee Lim
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, United States
| | - Xin Wang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, United States
| | - He Wang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, United States
| | - Mustefa Mohammedsaid
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, United States
| | - Clifton D. Fuller
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, United States
| | - Jihong Wang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, United States
| | - Jinzhong Yang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, United States
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Archawametheekul K, Puttanawarut C, Suphaphong S, Jiarpinitnun C, Sakulsingharoj S, Stansook N, Khachonkham S. The Investigating Image Registration Accuracy and Contour Propagation for Adaptive Radiotherapy Purposes in Line with the Task Group No. 132 Recommendation. J Med Phys 2024; 49:64-72. [PMID: 38828076 PMCID: PMC11141753 DOI: 10.4103/jmp.jmp_168_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/12/2024] [Accepted: 02/12/2024] [Indexed: 06/05/2024] Open
Abstract
Purpose Image registration is a crucial component of the adaptive radiotherapy workflow. This study investigates the accuracy of the deformable image registration (DIR) and contour propagation features of SmartAdapt, an application in the Eclipse treatment planning system (TPS) version 16.1. Materials and Methods The registration accuracy was validated using the Task Group No. 132 (TG-132) virtual phantom, which features contour evaluation and landmark analysis based on the quantitative criteria recommended in the American Association of Physicists in Medicine TG-132 report. The target registration error, Dice similarity coefficient (DSC), and center of mass displacement were used as quantitative validation metrics. The performance of the contour propagation feature was evaluated using clinical datasets (head and neck, pelvis, and chest) and an additional four-dimensional computed tomography (CT) dataset from TG-132. The primary planning and the second CT images were appropriately registered and deformed. The DSC was used to find the volume overlapping between the deformed contours and the radiation oncologist (RO)-drawn contour. The clinical value of the DIR-generated structure was reviewed and scored by an experienced RO to make a qualitative assessment. Results The registration accuracy fell within the specified tolerances. SmartAdapt exhibited a reasonably propagated contour for the chest and head-and-neck regions, with DSC values of 0.80 for organs at risk. Misregistration is frequently observed in the pelvic region, which is specified as a low-contrast region. However, 78% of structures required no modification or minor modification, demonstrating good agreement between contour comparison and the qualitative analysis. Conclusions SmartAdapt has adequate efficiency for image registration and contour propagation for adaptive purposes in various anatomical sites. However, there should be concern about its performance in regions with low contrast and small volumes.
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Affiliation(s)
- Kamonchanok Archawametheekul
- Division of Radiation Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Chanon Puttanawarut
- Chakri Naruebodindra Medical Institute, Mahidol University, Samut Prakan, Thailand
- Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Sithiphong Suphaphong
- Division of Radiation Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Chuleeporn Jiarpinitnun
- Division of Radiation Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Siwaporn Sakulsingharoj
- Division of Radiation Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Nauljun Stansook
- Division of Radiation Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Suphalak Khachonkham
- Division of Radiation Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
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Putz F, Bock M, Schmitt D, Bert C, Blanck O, Ruge MI, Hattingen E, Karger CP, Fietkau R, Grigo J, Schmidt MA, Bäuerle T, Wittig A. Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce "Imaging in Stereotactic Radiotherapy". Strahlenther Onkol 2024; 200:1-18. [PMID: 38163834 PMCID: PMC10784363 DOI: 10.1007/s00066-023-02183-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 11/06/2023] [Indexed: 01/03/2024]
Abstract
Accurate Magnetic Resonance Imaging (MRI) simulation is fundamental for high-precision stereotactic radiosurgery and fractionated stereotactic radiotherapy, collectively referred to as stereotactic radiotherapy (SRT), to deliver doses of high biological effectiveness to well-defined cranial targets. Multiple MRI hardware related factors as well as scanner configuration and sequence protocol parameters can affect the imaging accuracy and need to be optimized for the special purpose of radiotherapy treatment planning. MRI simulation for SRT is possible for different organizational environments including patient referral for imaging as well as dedicated MRI simulation in the radiotherapy department but require radiotherapy-optimized MRI protocols and defined quality standards to ensure geometrically accurate images that form an impeccable foundation for treatment planning. For this guideline, an interdisciplinary panel including experts from the working group for radiosurgery and stereotactic radiotherapy of the German Society for Radiation Oncology (DEGRO), the working group for physics and technology in stereotactic radiotherapy of the German Society for Medical Physics (DGMP), the German Society of Neurosurgery (DGNC), the German Society of Neuroradiology (DGNR) and the German Chapter of the International Society for Magnetic Resonance in Medicine (DS-ISMRM) have defined minimum MRI quality requirements as well as advanced MRI simulation options for cranial SRT.
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Affiliation(s)
- Florian Putz
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
| | - Michael Bock
- Klinik für Radiologie-Medizinphysik, Universitätsklinikum Freiburg, Freiburg, Germany
| | - Daniela Schmitt
- Klinik für Strahlentherapie und Radioonkologie, Universitätsmedizin Göttingen, Göttingen, Germany
| | - Christoph Bert
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Oliver Blanck
- Klinik für Strahlentherapie, Universitätsklinikum Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Maximilian I Ruge
- Klinik für Stereotaxie und funktionelle Neurochirurgie, Zentrum für Neurochirurgie, Universitätsklinikum Köln, Cologne, Germany
| | - Elke Hattingen
- Institut für Neuroradiologie, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
| | - Christian P Karger
- Abteilung Medizinische Physik in der Strahlentherapie, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
- Nationales Zentrum für Strahlenforschung in der Onkologie (NCRO), Heidelberger Institut für Radioonkologie (HIRO), Heidelberg, Germany
| | - Rainer Fietkau
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Johanna Grigo
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel A Schmidt
- Neuroradiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Tobias Bäuerle
- Radiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Andrea Wittig
- Klinik und Poliklinik für Strahlentherapie und Radioonkologie, Universitätsklinikum Würzburg, Würzburg, Germany
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Liu HYH, Hardcastle N, Bailey M, Siva S, Seeley A, Barry T, Booth J, Lao L, Roach M, Buxton S, Thwaites D, Foote M. Guidelines for safe practice of stereotactic body (ablative) radiation therapy: RANZCR 2023 update. J Med Imaging Radiat Oncol 2023. [PMID: 38160448 DOI: 10.1111/1754-9485.13618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 12/17/2023] [Indexed: 01/03/2024]
Affiliation(s)
- Howard Yu-Hao Liu
- Department of Cancer Services, Princess Alexandra Hospital, Brisbane, Queensland, Australia
- ICON Cancer Centre, Greenslopes Private Hospital, Brisbane, Queensland, Australia
| | | | - Michael Bailey
- Illawarra Cancer Care Centre, Wollongong, New South Wales, Australia
| | - Shankar Siva
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Anna Seeley
- North West Cancer Centre, Burnie, Tasmania, Australia
| | - Tamara Barry
- Department of Cancer Services, Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Jeremy Booth
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Louis Lao
- Auckland City Hospital, Auckland, New Zealand
- Auckland Radiation Oncology, Auckland, New Zealand
| | - Michelle Roach
- Liverpool Cancer Therapy Centre, Sydney, New South Wales, Australia
| | - Stacey Buxton
- Liverpool Cancer Therapy Centre, Sydney, New South Wales, Australia
| | - David Thwaites
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, New South Wales, Australia
| | - Matthew Foote
- Department of Cancer Services, Princess Alexandra Hospital, Brisbane, Queensland, Australia
- ICON Cancer Centre, Greenslopes Private Hospital, Brisbane, Queensland, Australia
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45
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Han Y, Geng C, Altieri S, Bortolussi S, Liu Y, Wahl N, Tang X. Combined BNCT-CIRT treatment planning for glioblastoma using the effect-based optimization. Phys Med Biol 2023; 69:015024. [PMID: 38048635 DOI: 10.1088/1361-6560/ad120f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 12/04/2023] [Indexed: 12/06/2023]
Abstract
Objective. Boron neutron capture therapy (BNCT) and carbon ion radiotherapy (CIRT) are emerging treatment modalities for glioblastoma. In this study, we investigated the methodology and feasibility to combine BNCT and CIRT treatments. The combined treatment plan illustrated how the synergistic utilization of BNCT's biological targeting and CIRT's intensity modulation capabilities could lead to optimized treatment outcomes.Approach. The Monte Carlo toolkit, TOPAS, was employed to calculate the dose distribution for BNCT, while matRad was utilized for the optimization of CIRT. The biological effect-based approach, instead of the dose-based approach, was adopted to develop the combined BNCT-CIRT treatment plans for six patients diagnosed with glioblastoma, considering the different radiosensitivity and fraction. Five optional combined treatment plans with specific BNCT effect proportions for each patient were evaluated to identify the optimal treatment that minimizes damage on normal tissue.Main results. Individual BNCT exhibits a significant effect gradient along with the beam direction in the large tumor, while combined BNCT-CIRT treatments can achieve uniform effect delivery within the clinical target volume (CTV) through the effect filling with reversed gradient by the CIRT part. In addition, the increasing BNCT effect proportion in combined treatments can reduce damage in the normal brain tissue near the CTV. Besides, the combined treatments effectively minimize damage to the skin compared to individual BNCT treatments.Significance. The initial endeavor to combine BNCT and CIRT treatment plans is achieved by the effect-based optimization. The observed advantages of the combined treatment suggest its potential applicability for tumors characterized by pleomorphic, infiltrative, radioresistant and voluminous features.
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Affiliation(s)
- Yang Han
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
- Department of Physics, University of Pavia, Pavia, Italy
| | - Changran Geng
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
| | - Saverio Altieri
- Department of Physics, University of Pavia, Pavia, Italy
- National Institute of Nuclear Physics, Unit of Pavia, Pavia, Italy
| | - Silva Bortolussi
- Department of Physics, University of Pavia, Pavia, Italy
- National Institute of Nuclear Physics, Unit of Pavia, Pavia, Italy
| | - Yuanhao Liu
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
- Neuboron Medtech. Ltd, Nanjing, People's Republic of China
| | - Niklas Wahl
- Division of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Institute for Radiation Oncology (HIRO) and National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany
| | - Xiaobin Tang
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
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46
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Nenoff L, Amstutz F, Murr M, Archibald-Heeren B, Fusella M, Hussein M, Lechner W, Zhang Y, Sharp G, Vasquez Osorio E. Review and recommendations on deformable image registration uncertainties for radiotherapy applications. Phys Med Biol 2023; 68:24TR01. [PMID: 37972540 PMCID: PMC10725576 DOI: 10.1088/1361-6560/ad0d8a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 10/30/2023] [Accepted: 11/15/2023] [Indexed: 11/19/2023]
Abstract
Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.
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Affiliation(s)
- Lena Nenoff
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
- OncoRay—National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden—Rossendorf, Dresden Germany
- Helmholtz-Zentrum Dresden—Rossendorf, Institute of Radiooncology—OncoRay, Dresden, Germany
| | - Florian Amstutz
- Department of Physics, ETH Zurich, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Bern, Switzerland
| | - Martina Murr
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany
| | | | - Marco Fusella
- Department of Radiation Oncology, Abano Terme Hospital, Italy
| | - Mohammad Hussein
- Metrology for Medical Physics, National Physical Laboratory, Teddington, United Kingdom
| | - Wolfgang Lechner
- Department of Radiation Oncology, Medical University of Vienna, Austria
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Greg Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Eliana Vasquez Osorio
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
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47
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Smolders A, Lomax A, Weber DC, Albertini F. Deep learning based uncertainty prediction of deformable image registration for contour propagation and dose accumulation in online adaptive radiotherapy. Phys Med Biol 2023; 68:245027. [PMID: 37820691 DOI: 10.1088/1361-6560/ad0282] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 10/11/2023] [Indexed: 10/13/2023]
Abstract
Objective.Online adaptive radiotherapy aims to fully leverage the advantages of highly conformal therapy by reducing anatomical and set-up uncertainty, thereby alleviating the need for robust treatments. This requires extensive automation, among which is the use of deformable image registration (DIR) for contour propagation and dose accumulation. However, inconsistencies in DIR solutions between different algorithms have caused distrust, hampering its direct clinical use. This work aims to enable the clinical use of DIR by developing deep learning methods to predict DIR uncertainty and propagating it into clinically usable metrics.Approach.Supervised and unsupervised neural networks were trained to predict the Gaussian uncertainty of a given deformable vector field (DVF). Since both methods rely on different assumptions, their predictions differ and were further merged into a combined model. The resulting normally distributed DVFs can be directly sampled to propagate the uncertainty into contour and accumulated dose uncertainty.Main results.The unsupervised and combined models can accurately predict the uncertainty in the manually annotated landmarks on the DIRLAB dataset. Furthermore, for 5 patients with lung cancer, the propagation of the predicted DVF uncertainty into contour uncertainty yielded for both methods anexpected calibration errorof less than 3%. Additionally, theprobabilisticly accumulated dose volume histograms(DVH) encompass well the accumulated proton therapy doses using 5 different DIR algorithms. It was additionally shown that the unsupervised model can be used for different DIR algorithms without the need for retraining.Significance.Our work presents first-of-a-kind deep learning methods to predict the uncertainty of the DIR process. The methods are fast, yield high-quality uncertainty estimates and are useable for different algorithms and applications. This allows clinics to use DIR uncertainty in their workflows without the need to change their DIR implementation.
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Affiliation(s)
- A Smolders
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - A Lomax
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - D C Weber
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Radiation Oncology, University Hospital Zurich, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - F Albertini
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
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48
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Bugeja JM, Mehawed G, Roberts MJ, Rukin N, Dowling J, Murray R. Prostate volume analysis in image registration for prostate cancer care: a verification study. Phys Eng Sci Med 2023; 46:1791-1802. [PMID: 37819450 DOI: 10.1007/s13246-023-01342-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 09/26/2023] [Indexed: 10/13/2023]
Abstract
Combined magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) may enhance diagnosis, aid surgical planning and intra-operative orientation for prostate biopsy and radical prostatectomy. Although PET-MRI may provide these benefits, PET-MRI machines are not widely available. Image fusion of Prostate specific membrane antigen PET/CT and MRI acquired separately may be a suitable clinical alternative. This study compares CT-MR registration algorithms for urological prostate cancer care. Paired whole-pelvis MR and CT scan data were used (n = 20). A manual prostate CTV contour was performed independently on each patients MR and CT image. A semi-automated rigid-, automated rigid- and automated non-rigid registration technique was applied to align the MR and CT data. Dice Similarity Index (DSI), 95% Hausdorff distance (95%HD) and average surface distance (ASD) measures were used to assess the closeness of the manual and registered contours. The automated non-rigid approach had a significantly improved performance compared to the automated rigid- and semi-automated rigid-registration, having better average scores and decreased spread for the DSI, 95%HD and ASD (all p < 0.001). Additionally, the automated rigid approach had similar significantly improved performance compared to the semi-automated rigid registration across all accuracy metrics observed (all p < 0.001). Overall, all registration techniques studied here demonstrated sufficient accuracy for exploring their clinical use. While the fully automated non-rigid registration algorithm in the present study provided the most accurate registration, the semi-automated rigid registration is a quick, feasible, and accessible method to perform image registration for prostate cancer care by urologists and radiation oncologists now.
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Affiliation(s)
- Jessica M Bugeja
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Health and Biosecurity, Herston, Australia.
| | - Georges Mehawed
- Herston Biofabrication Institute, Urology Program, Herston, Australia
- Urology Department, Redcliffe Hospital, Redcliffe, Australia
- School of Medicine, The University of Queensland, Brisbane, Australia
- Australian Institute of Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Australia
| | - Matthew J Roberts
- Herston Biofabrication Institute, Urology Program, Herston, Australia
- Urology Department, Redcliffe Hospital, Redcliffe, Australia
- School of Medicine, The University of Queensland, Brisbane, Australia
- Urology Department, Royal Brisbane and Women's Hospital, Herston, Australia
- University of Queensland, University of Queensland Centre for Clinical Research, Herston, Australia
| | - Nicholas Rukin
- Herston Biofabrication Institute, Urology Program, Herston, Australia
- Urology Department, Redcliffe Hospital, Redcliffe, Australia
- School of Medicine, The University of Queensland, Brisbane, Australia
| | - Jason Dowling
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Health and Biosecurity, Herston, Australia
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Rebecca Murray
- Herston Biofabrication Institute, Urology Program, Herston, Australia
- Urology Department, Redcliffe Hospital, Redcliffe, Australia
- Australian Institute of Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Australia
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Paolucci I, Albuquerque Marques Silva J, Lin YM, Fellman BM, Jones KA, Tatsui CE, Weinberg JS, Ruiz J, Tan J, Brock KK, Bale R, Odisio BC. Study Protocol STEREOLAB: Stereotactic Liver Ablation Assisted with Intra-Arterial CT Hepatic Arteriography and Ablation Confirmation Software Assessment. Cardiovasc Intervent Radiol 2023; 46:1748-1754. [PMID: 37563313 DOI: 10.1007/s00270-023-03524-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 07/22/2023] [Indexed: 08/12/2023]
Abstract
PURPOSE This study aims to evaluate the technical efficacy and local tumor progression-free survival (LTPFS) of a standardized workflow for thermal ablation of colorectal liver metastases (CRLM) consisting of CT during hepatic arteriography (CTHA)-based imaging analysis, stereotactic thermal ablation, and computer-based software assessment of ablation margins. MATERIALS AND METHODS This investigator initiated, single-center, single-arm prospective trial will enroll up to 50 patients (≤ 5 CRLM, Measuring ≤ 5 cm). Procedures will be performed in an angio-CT suite under general anesthesia. The primary objective is to estimate LTPFS with a follow-up of up to 2 years and secondary objectives are analysis of the impact of minimal ablative margins on LTPFS, adverse events, contrast media utilization and radiation exposure, overall oncological outcomes, and anesthesia/procedural time. Adverse events (AE) will be recorded by CTCAE (Common Toxicity Criteria for Adverse Events), and Bayesian optimal phase-2 design will be applied for major intraprocedural AE stop boundaries. The institutional CRLM ablation registry will be used as benchmark for comparative analysis with the historical cohort. DISCUSSION The STEREOLAB trial will introduce a high-precision and standardized thermal ablation workflow for CRLM consisting of CT during hepatic arteriography imaging, stereotactic guidance, and ablation confirmation. Trial Registration ClinicalTrials.gov identifier: (NCT05361551).
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Affiliation(s)
- Iwan Paolucci
- Department of Interventional Radiology, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Unit 1471, Houston, TX, USA
| | - Jessica Albuquerque Marques Silva
- Department of Interventional Radiology, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Unit 1471, Houston, TX, USA
| | - Yuan-Mao Lin
- Department of Interventional Radiology, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Unit 1471, Houston, TX, USA
| | - Bryan M Fellman
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kyle A Jones
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Claudio E Tatsui
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jeffrey S Weinberg
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Joseph Ruiz
- Department of Anesthesiology and Perioperative Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jens Tan
- Department of Anesthesiology and Perioperative Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kristy K Brock
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Reto Bale
- Interventionelle Onkologie-Mikroinvasive Therapie (SIP), Medizinische Universität Innsbruck, Innsbruck, Austria
| | - Bruno C Odisio
- Department of Interventional Radiology, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Unit 1471, Houston, TX, USA.
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50
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Heinzerling JH, Pen OV, Robinson M, Foster R, Kelly B, Mileham KF, Moeller B, Prabhu RS, Corso C, Ward MW, Sullivan CM, Burri S, Simone CB. Full Dose SBRT in Combination With Mediastinal Chemoradiation for Locally Advanced, Non-Small Cell Lung Cancer: A Practical Guide for Planning, Dosimetric Results From a Phase 2 Study, and a Treatment Planning Guide for the Phase 3 NRG Oncology LU-008 Trial. Pract Radiat Oncol 2023; 13:531-539. [PMID: 37406774 DOI: 10.1016/j.prro.2023.04.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 04/21/2023] [Accepted: 04/25/2023] [Indexed: 07/07/2023]
Abstract
PURPOSE Stereotactic body radiation therapy (SBRT) has been used with high effectiveness in early-stage non-small cell lung cancer (NSCLC) but has not been studied extensively in locally advanced NSCLC. We conducted a phase 2 study delivering SBRT to the primary tumor followed by conventionally fractionated chemoradiation to the involved lymph nodes for patients with node-positive locally advanced NSCLC. This manuscript serves as both a guide to planning techniques used on this trial and the subsequent phase 3 study, NRG Oncology LU-008, and to report patient dosimetry and toxicity results. METHODS AND MATERIALS We initiated a phase 2 multicenter single arm study evaluating SBRT to the primary tumor (50-54 Gy in 3-5 fractions) followed by conventionally fractionated chemoradiation to 60 Gy in 2 Gy fractions with doublet chemotherapy to the involved lymph nodes for patients with stage III or unresectable stage II NSCLC. Patients eligible for adjuvant immunotherapy received up to 12 months of durvalumab. We report a detailed guide for the entire treatment process from computed tomography simulation through treatment planning and delivery. The dosimetric outcomes from the 60 patients who completed therapy on study are reported both for target coverage and normal structure doses. We also report correlation between radiation-related toxicities and dosimetric parameters. RESULTS Sixty patients were enrolled between 2017 and 2022. Planning techniques used were primarily volumetric modulated arc therapy for SBRT to the primary tumor and conventionally fractionated radiation to the involved nodes, with a minority of cases using dynamic conformal arc technique or static dynamic multileaf collimator intensity modulated radiation therapy. Grade 2 or higher pneumonitis was associated with lung dose V5 Gy > 70% and grade 2 or higher pulmonary toxicity was associated with lung dose V10 Gy > 50%. Only 3 patients (5%) experienced grade 3 or higher pneumonitis. Grade 2 or higher esophagitis was associated with esophageal doses, including mean dose > 20 Gy, V60 Gy > 7%, and D1cc > 55 Gy. Only 1 patient (1.7%) experienced grade 3 esophagitis. CONCLUSIONS SBRT to the primary tumor followed by conventionally fractionated chemoradiation to the involved lymph nodes is feasible with planning techniques as described. Radiation-related toxicity on this phase 2 study was low. This manuscript serves as a guideline for the recently activated NRG Oncology LU-008 phase 3 trial evaluating this experimental regimen.
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Affiliation(s)
- John H Heinzerling
- Levine Cancer Institute, Atrium Health, Southeast Radiation Oncology, Charlotte, North Carolina.
| | - Olga V Pen
- Levine Cancer Institute, Atrium Health, Charlotte, North Carolina
| | - Myra Robinson
- Levine Cancer Institute, Atrium Health, Charlotte, North Carolina
| | - Ryan Foster
- Levine Cancer Institute, Atrium Health, Charlotte, North Carolina
| | - Brian Kelly
- Levine Cancer Institute, Atrium Health, Charlotte, North Carolina
| | | | - Benjamin Moeller
- Levine Cancer Institute, Atrium Health, Southeast Radiation Oncology, Charlotte, North Carolina
| | - Roshan S Prabhu
- Levine Cancer Institute, Atrium Health, Southeast Radiation Oncology, Charlotte, North Carolina
| | - Christopher Corso
- Levine Cancer Institute, Atrium Health, Southeast Radiation Oncology, Charlotte, North Carolina
| | - Matt W Ward
- Levine Cancer Institute, Atrium Health, Southeast Radiation Oncology, Charlotte, North Carolina
| | - Cara M Sullivan
- Levine Cancer Institute, Atrium Health, Charlotte, North Carolina
| | - Stuart Burri
- Levine Cancer Institute, Atrium Health, Southeast Radiation Oncology, Charlotte, North Carolina
| | - Charles B Simone
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York; New York Proton Center, New York, New York
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