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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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Sakulsingharoj S, Kadoya N, Tanaka S, Sato K, Nakamura M, Jingu K. Dosimetric impact of deformable image registration using radiophotoluminescent glass dosimeters with a physical geometric phantom. J Appl Clin Med Phys 2023; 24:e13890. [PMID: 36609786 PMCID: PMC10113686 DOI: 10.1002/acm2.13890] [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: 08/09/2022] [Revised: 11/04/2022] [Accepted: 12/15/2022] [Indexed: 01/09/2023] Open
Abstract
PURPOSE To study the dosimetry impact of deformable image registration (DIR) using radiophotoluminescent glass dosimeter (RPLD) and custom developed phantom with various inserts. METHODS The phantom was developed to facilitate simultaneous evaluation of geometric and dosimetric accuracy of DIR. Four computed tomography (CT) images of the phantom were acquired with four different configurations. Four volumetric modulated arc therapy (VMAT) plans were computed for different phantom. Two different patterns were applied to combination of four phantom configurations. RPLD dose measurement was combined between corresponding two phantom configurations. DIR-based dose accumulation was calculated between corresponding two CT images with two commercial DIR software and various DIR parameter settings, and an open source software. Accumulated dose calculated using DIR was then compared with measured dose using RPLD. RESULTS The mean ± standard deviation (SD) of dose difference was 2.71 ± 0.23% (range, 2.22%-3.01%) for tumor-proxy and 3.74 ± 0.79% (range, 1.56%-4.83%) for rectum-proxy. The mean ± SD of target registration error (TRE) was 1.66 ± 1.36 mm (range, 0.03-4.43 mm) for tumor-proxy and 6.87 ± 5.49 mm (range, 0.54-17.47 mm) for rectum-proxy. These results suggested that DIR accuracy had wide range among DIR parameter setting. CONCLUSIONS The dose difference observed in our study was 3% for tumor-proxy and within 5% for rectum-proxy. The custom developed physical phantom with inserts showed potential for accurate evaluation of DIR-based dose accumulation. The prospect of simultaneous evaluation of geometric and dosimetric DIR accuracy in a single phantom may be useful for validation of DIR for clinical use.
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Affiliation(s)
- Siwaporn Sakulsingharoj
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan.,Division of Radiation Oncology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Shohei Tanaka
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Kiyokazu Sato
- Department of Radiation Technology, Tohoku University Hospital, Sendai, Japan
| | - Mitsuhiro Nakamura
- Department of Radiation Oncology and Image-Applied Therapy, Kyoto University, Kyoto, Japan.,Department of Information Technology and Medical Engineering, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
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Katsuta Y, Kadoya N, Kajikawa T, Mouri S, Kimura T, Takeda K, Yamamoto T, Imano N, Tanaka S, Ito K, Kanai T, Nakajima Y, Jingu K. Radiation pneumonitis prediction model with integrating multiple dose-function features on 4DCT ventilation images. Phys Med 2023; 105:102505. [PMID: 36535238 DOI: 10.1016/j.ejmp.2022.11.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 11/18/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022] Open
Abstract
PURPOSE Radiation pneumonitis (RP) is dose-limiting toxicity for non-small-cell cancer (NSCLC). This study developed an RP prediction model by integrating dose-function features from computed four-dimensional computed tomography (4DCT) ventilation using the least absolute shrinkage and selection operator (LASSO). METHODS Between 2013 and 2020, 126 NSCLC patients were included in this study who underwent a 4DCT scan to calculate ventilation images. We computed two sets of candidate dose-function features from (1) the percentage volume receiving > 20 Gy or the mean dose on the functioning zones determined with the lower cutoff percentile ventilation value, (2) the functioning zones determined with lower and upper cutoff percentile ventilation value using 4DCT ventilation images. An RP prediction model was developed by LASSO while simultaneously determining the regression coefficient and feature selection through fivefold cross-validation. RESULTS We found 39.3 % of our patients had a ≥ grade 2 RP. The mean area under the curve (AUC) values for the developed models using clinical, dose-volume, and dose-function features with a lower cutoff were 0.791, and the mean AUC values with lower and upper cutoffs were 0.814. The relative regression coefficient (RRC) on dose-function features with upper and lower cutoffs revealed a relative impact of dose to each functioning zone to RP. RRCs were 0.52 for the mean dose on the functioning zone, with top 20 % of all functioning zone was two times greater than that of 0.19 for these with 60 %-80 % and 0.17 with 40 %-60 % (P < 0.01). CONCLUSIONS The introduction of dose-function features computed from functioning zones with lower and upper cutoffs in a machine learning framework can improve RP prediction. The RRC given by LASSO using dose-function features allows for the quantification of the RP impact of dose on each functioning zones and having the potential to support treatment planning on functional image-guided radiotherapy.
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Affiliation(s)
- Yoshiyuki Katsuta
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan.
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Tomohiro Kajikawa
- Department of Radiology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Shina Mouri
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Tomoki Kimura
- Department of Radiation Oncology, Kochi Medical School, Kochi University, Nangoku, Japan
| | - Kazuya Takeda
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Takaya Yamamoto
- Department of Radiation Oncology, Graduate School of Biomedical Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Nobuki Imano
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Shohei Tanaka
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Kengo Ito
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Takayuki Kanai
- Department of Radiation Oncology, Yamagata University, Yamagata, Japan
| | - Yujiro Nakajima
- Department of Radiological Sciences, Komazawa University, Tokyo, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
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Fujimoto K. [8. Overview of Deformable Image Registration for Clinical Applications]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2023; 79:78-83. [PMID: 36682782 DOI: 10.6009/jjrt.2023-2136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Affiliation(s)
- Koya Fujimoto
- Department of Radiation Oncology, Graduate School of Medicine, Yamaguchi University
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Takahashi H, Kadoya N, Katsuta Y, Tanaka S, Arai K, Yamamoto T, Umezawa R, Jingu K. [Evaluation of Accuracy of Deformable Image Registration with Newly Developed Treatment Planning Support Software for Thoracic Images]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2022; 78:1187-1193. [PMID: 36002256 DOI: 10.6009/jjrt.2022-1308] [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] [Indexed: 06/15/2023]
Abstract
This study evaluated accuracy of deformable image registration (DIR) with twelve parameter settings for thoracic images. We used peak-inhale and peak-exhale images for ten patients provided by DIR-lab. We used a prototype version of iCView software (ITEM Corporation) with DIR to perform intensity, structure, and hybrid-based DIR with the twelve parameter settings. DIR accuracy was evaluated by a target registration error (TRE) using 300 bronchial bifurcations and the Dice similarity coefficient (DSC) of the lungs. For twelve parameter settings, TRE ranged from 2.83 mm to 5.27 mm, whereas DSC ranged from 0.96 to 0.98. These results demonstrated that DIR accuracy differed among parameter settings and show that appropriate parameter settings are required for clinical practice.
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Affiliation(s)
- Haruna Takahashi
- Department of Radiation Oncology, Tohoku University School of Medicine
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University School of Medicine
| | - Yoshiyuki Katsuta
- Department of Radiation Oncology, Tohoku University School of Medicine
| | - Shohei Tanaka
- Department of Radiation Oncology, Tohoku University School of Medicine
| | - Kazuhiro Arai
- Department of Radiation Oncology, Tohoku University School of Medicine
| | - Takaya Yamamoto
- Department of Radiation Oncology, Tohoku University School of Medicine
| | - Rei Umezawa
- Department of Radiation Oncology, Tohoku University School of Medicine
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University School of Medicine
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Hu R, Yan H, Nian F, Mao R, Li T. Unsupervised computed tomography and cone-beam computed tomography image registration using a dual attention network. Quant Imaging Med Surg 2022; 12:3705-3716. [PMID: 35782273 PMCID: PMC9246738 DOI: 10.21037/qims-21-1194] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 04/13/2022] [Indexed: 09/13/2023]
Abstract
BACKGROUND The registration of computed tomography (CT) and cone-beam computed tomography (CBCT) plays a key role in image-guided radiotherapy (IGRT). However, the large intensity variation between CT and CBCT images limits the registration performance and its clinical application in IGRT. In this study, a learning-based unsupervised approach was developed to address this issue and accurately register CT and CBCT images by predicting the deformation field. METHODS A dual attention module was used to handle the large intensity variation between CT and CBCT images. Specifically, a scale-aware position attention block (SP-BLOCK) and a scale-aware channel attention block (SC-BLOCK) were employed to integrate contextual information from the image space and channel dimensions. The SP-BLOCK enhances the correlation of similar features by weighting and aggregating multi-scale features at different positions, while the SC-BLOCK handles the multiple features of all channels to selectively emphasize dependencies between channel maps. RESULTS The proposed method was compared with existing mainstream methods on the 4D-LUNG data set. Compared to other mainstream methods, it achieved the highest structural similarity (SSIM) and dice similarity coefficient (DICE) scores of 86.34% and 89.74%, respectively, and the lowest target registration error (TRE) of 2.07 mm. CONCLUSIONS The proposed method can register CT and CBCT images with high accuracy without the needs of manual labeling. It provides an effective way for high-accuracy patient positioning and target localization in IGRT.
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Affiliation(s)
- Rui Hu
- Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education/School of Artificial Intelligence, Anhui University, Hefei, China
| | - Hui Yan
- 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, China
| | - Fudong Nian
- School of Advanced Manufacturing Engineering, Hefei University, Hefei, China
| | - Ronghu Mao
- Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Teng Li
- Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education/School of Artificial Intelligence, Anhui University, Hefei, China
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Katsuta Y, Kadoya N, Mouri S, Tanaka S, Kanai T, Takeda K, Yamamoto T, Ito K, Kajikawa T, Nakajima Y, Jingu K. Prediction of radiation pneumonitis with machine learning using 4D-CT based dose-function features. JOURNAL OF RADIATION RESEARCH 2022; 63:71-79. [PMID: 34718683 PMCID: PMC8776701 DOI: 10.1093/jrr/rrab097] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 08/20/2021] [Indexed: 06/13/2023]
Abstract
In this article, we highlight the fundamental importance of the simultaneous use of dose-volume histogram (DVH) and dose-function histogram (DFH) features based on functional images calculated from 4-dimensional computed tomography (4D-CT) and deformable image registration (DIR) in developing a multivariate radiation pneumonitis (RP) prediction model. The patient characteristics, DVH features and DFH features were calculated from functional images by Hounsfield unit (HU) and Jacobian metrics, for an RP grade ≥ 2 multivariate prediction models were computed from 85 non-small cell lung cancer patients. The prediction model is developed using machine learning via a kernel-based support vector machine (SVM) machine. In the patient cohort, 21 of the 85 patients (24.7%) presented with RP grade ≥ 2. The median area under curve (AUC) was 0.58 for the generated 50 prediction models with patient clinical features and DVH features. When HU metric and Jacobian metric DFH features were added, the AUC improved to 0.73 and 0.68, respectively. We conclude that predictive RP models that incorporate DFH features were successfully developed via kernel-based SVM. These results demonstrate that effectiveness of the simultaneous use of DVH features and DFH features calculated from 4D-CT and DIR on functional image-guided radiotherapy.
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Affiliation(s)
- Yoshiyuki Katsuta
- Corresponding author. Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan, Tel: +81-22-717-7312, Fax: +81-22-717-7316, E-mail:
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Ishida T, Kadoya N, Tanabe S, Ohashi H, Nemoto H, Dobashi S, Takeda K, Jingu K. Evaluation of performance of pelvic CT-MR deformable image registration using two software programs. JOURNAL OF RADIATION RESEARCH 2021:rrab078. [PMID: 34505155 DOI: 10.1093/jrr/rrab078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 06/19/2021] [Indexed: 06/13/2023]
Abstract
We assessed the accuracy of deformable image registration (DIR) accuracy between CT and MR images using an open-source software (Elastix, from Utrecht Medical Center) and a commercial software (Velocity AI Ver. 3.2.0 from Varian Medical Systems, Palo Alto, CA, USA) software. Five male patients' pelvic regions were studied using publicly available CT, T1-weighted (T1w) MR, and T2-weighted (T2w) MR images. In the cost function of the Elastix, we used six DIR parameter settings with different regularization weights (Elastix0, Elastix0.01, Elastix0.1, Elastix1, Elastix10, and Elastix100). We used MR Corrected Deformable algorithm for Velocity AI. The Dice similarity coefficient (DSC) and mean distance to agreement (MDA) for the prostate, bladder, rectum and left and right femoral heads were used to evaluate DIR accuracy. Except for the bladder, most algorithms produced good DSC and MDA results for all organs. In our study, the mean DSCs for the bladder ranged from 0.75 to 0.88 (CT-T1w) and from 0.72 to 0.76 (CT-T2w). Similarly, the mean MDA ranges were 2.4 to 4.9 mm (CT-T1w), 4.6 to 5.3 mm (CT-T2w). For the Elastix, CT-T1w was outperformed CT-T2w for both DSCs and MDAs at Elastix0, Elastix0.01, and Elastix0.1. In the case of Velocity AI, no significant differences in DSC and MDA of all organs were observed. This implied that the DIR accuracy of CT and MR images might differ depending on the sequence used.
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Affiliation(s)
- Tomoya Ishida
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai 980-8574, Japan
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai 980-8574, Japan
| | - Shunpei Tanabe
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai 980-8574, Japan
| | - Haruna Ohashi
- Department of Radiation Technology, Tohoku University Graduate School of Health Sciences, Sendai 980-8574, Japan
| | - Hikaru Nemoto
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai 980-8574, Japan
- Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo 113-8677, Japan
| | - Suguru Dobashi
- Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Tohoku University, Sendai 980-8574, Japan
| | - Ken Takeda
- Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Tohoku University, Sendai 980-8574, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai 980-8574, Japan
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Saito M, Sano N, Kuriyama K, Komiyama T, Marino K, Aoki S, Maehata Y, Suzuki H, Ueda K, Onishi H. New method for measurement of chest surface motion in lung cancer patients: Quantification using a technique of deformable image registration. Med Dosim 2020; 46:111-116. [PMID: 32972812 DOI: 10.1016/j.meddos.2020.09.001] [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: 04/14/2020] [Revised: 08/27/2020] [Accepted: 09/11/2020] [Indexed: 11/29/2022]
Abstract
The purpose of this study was to measure the motion of the chest surface during breath-holding treatment for lung cancer using deformable image registration (DIR). Forty non-small-cell lung cancer patients treated with breath-holding stereotactic body radiation therapy were retrospectively examined. First, intensity-based DIR between 2 breath-holding computed tomography (CT) images was performed. Subsequently, deformation vector field (DVF) for all dimensions (left-right, anterior-posterior, and superior-inferior) was calculated from the result. For the analysis of chest surface, the DVF value of the only chest surface area was extracted after the chest surface was divided into 12 regions of interest (ROI) based on anatomy. Additionally, for the analysis of the correlation with the internal tumor motion, the median value of DVF for each surface ROI and the motion of the center of gravity of the tumor volume were used. It was possible to calculate the motion of chest surface without any outliers for all patients. For the average of 12 surface ROIs, the motion of 3D chest surface was within 2 mm (30 cases), 3 mm (8 cases), and 4 mm (2 cases). There was no correlation between the motion of the chest surface and that of the tumor for all 12 surface ROIs. We proposed a technique to evaluate the surface motion using DIR between multiple CT images. It could be a useful tool to calculate the motion of chest surface.
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Affiliation(s)
- Masahide Saito
- Department of Radiology, University of Yamanashi, Yamanashi, Japan.
| | - Naoki Sano
- Department of Radiology, University of Yamanashi, Yamanashi, Japan
| | - Kengo Kuriyama
- Department of Radiology, University of Yamanashi, Yamanashi, Japan
| | | | - Kan Marino
- Department of Radiology, University of Yamanashi, Yamanashi, Japan
| | - Shinichi Aoki
- Department of Radiology, University of Yamanashi, Yamanashi, Japan
| | | | - Hidekazu Suzuki
- Department of Radiology, University of Yamanashi, Yamanashi, Japan
| | - Koji Ueda
- Department of Radiology, University of Yamanashi, Yamanashi, Japan
| | - Hiroshi Onishi
- Department of Radiology, University of Yamanashi, Yamanashi, Japan
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Kadoya N, Nemoto H, Kajikawa T, Nakajima Y, Kanai T, Ieko Y, Ikeda R, Sato K, Dobashi S, Takeda K, Jingu K. Evaluation of four-dimensional cone beam computed tomography ventilation images acquired with two different linear accelerators at various gantry speeds using a deformable lung phantom. Phys Med 2020; 77:75-83. [PMID: 32795891 DOI: 10.1016/j.ejmp.2020.07.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 06/24/2020] [Accepted: 07/26/2020] [Indexed: 10/23/2022] Open
Abstract
We evaluated four-dimensional cone beam computed tomography (4D-CBCT) ventilation images (VICBCT) acquired with two different linear accelerator systems at various gantry speeds using a deformable lung phantom. The 4D-CT and 4D-CBCT scans were performed using a computed tomography (CT) scanner, an X-ray volume imaging system (Elekta XVI) mounted in Versa HD, and an On-Board Imager (OBI) system mounted in TrueBeam. Intensity-based deformable image registration (DIR) was performed between peak-exhale and peak-inhale images. VICBCT- and 4D-CT-based ventilation images (VICT) were derived by DIR using two metrics: one based on the Jacobian determinant and one on changes in the Hounsfield unit (HU). Three different DIR regularization values (λ) were used for VICBCT. Correlations between the VICBCT and VICT values were evaluated using voxel-wise Spearman's rank correlation coefficient (r). In case of both metrics, the Jacobian-based VICBCT with a gantry speed of 0.6 deg/sec in Versa HD showed the highest correlation for all the gantry speeds (e.g., λ = 0.05 and r = 0.68). Thus, the r value of the Jacobian-based VICBCT was greater or equal to that of the HU-based VICBCT. In addition, the ventilation accuracy of VICBCT increased at low gantry speeds. Thus, the image quality of VICBCT was affected by the change in gantry speed in both the imaging systems. Additionally, DIR regularization considerably influenced VICBCT in both the imaging systems. Our results have the potential to assist in designing CBCT protocols, incorporating VICBCT imaging into the functional avoidance planning process.
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Affiliation(s)
- Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan.
| | - Hikaru Nemoto
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan; Department of Radiotherapy, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan
| | - Tomohiro Kajikawa
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan; Department of Radiology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Yujiro Nakajima
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan; Department of Radiotherapy, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan
| | - Takayuki Kanai
- Department of Radiation Oncology, Yamagata University Faculty of Medicine, Yamagata, Japan
| | - Yoshiro Ieko
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan; Department of Radiation Oncology, Iwate Medical University School of Medicine, Iwate, Japan
| | - Ryutaro Ikeda
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan; Department of Radiology, Japanese Red Cross Ishinomaki Hospital, Ishinomaki, Japan
| | - Kiyokazu Sato
- Radiation Technology, Tohoku University Hospital, Sendai, Japan
| | - Suguru Dobashi
- Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Tohoku University, Sendai, Japan
| | - Ken Takeda
- Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Tohoku University, Sendai, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
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11
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Ieko Y, Kadoya N, Kanai T, Nakajima Y, Arai K, Kato T, Ito K, Miyasaka Y, Takeda K, Iwai T, Nemoto K, Jingu K. The impact of 4DCT-ventilation imaging-guided proton therapy on stereotactic body radiotherapy for lung cancer. Radiol Phys Technol 2020; 13:230-237. [PMID: 32537735 DOI: 10.1007/s12194-020-00572-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 06/05/2020] [Accepted: 06/08/2020] [Indexed: 01/01/2023]
Abstract
Functional lung avoidance during radiotherapy can help reduce pulmonary toxicity. This study assessed the potential impact of four-dimensional computed tomography (4DCT)-ventilation imaging-guided proton radiotherapy (PT) on stereotactic body radiotherapy (SBRT) by comparing it with three-dimensional conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT), which employ photon beams. Thirteen lung cancer patients who received SBRT with 3D-CRT were included in the study. 4DCT ventilation was calculated using the patients' 4DCT data, deformable image registration, and a density-change-based algorithm. Three functional treatment plans sparing the functional lung regions were developed for each patient using 3D-CRT, VMAT, and PT. The prescribed doses and dose constraints were based on the Radiation Therapy Oncology Group 0618 protocol. We evaluated the region of interest (ROI) and functional map-based dose-function metrics for 4DCT ventilation and the irradiated dose. Using 3D-CRT, VMAT, and PT, the percentages of the functional lung regions that received ≥ 5 Gy (fV5) were 26.0%, 21.9%, and 10.7%, respectively; the fV10 were 14.4%, 11.4%, and 9.0%, respectively; and fV20 were 6.5%, 6.4%, and 6.6%, respectively, and the functional mean lung doses (fMLD) were 5.6 Gy, 5.2 Gy, and 3.8 Gy, respectively. These results indicated that PT resulted in a significant reduction in fMLD, fV5, and fV10, but not fV20. The use of PT reduced the radiation to highly functional lung regions compared with those for 3D-CRT and VMAT while meeting all dose constraints.
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Affiliation(s)
- Yoshiro Ieko
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan.,Department of Heavy Particle Medical Science, Yamagata University Graduate School of Medical Science, Yamagata, Japan
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan.
| | - Takayuki Kanai
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan.,Department of Radiation Oncology, Faculty of Medicine, Yamagata University, Yamagata, Japan
| | - Yujiro Nakajima
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan.,Department of Radiation Oncology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan
| | - Kazuhiro Arai
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan.,Department of Radiation Physics and Technology, Southern Tohoku Proton Therapy Center, Koriyama, Japan
| | - Takahiro Kato
- Department of Radiation Physics and Technology, Southern Tohoku Proton Therapy Center, Koriyama, Japan.,Preparing Section for New Facility of Medical Science, Fukushima Medical University, Fukushima, Japan
| | - Kengo Ito
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan
| | - Yuya Miyasaka
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan.,Department of Heavy Particle Medical Science, Yamagata University Graduate School of Medical Science, Yamagata, Japan
| | - Ken Takeda
- Department of Radiological Technology, Graduate School of Health Sciences, Faculty of Medicine, Tohoku University, Sendai, Japan
| | - Takeo Iwai
- Department of Heavy Particle Medical Science, Yamagata University Graduate School of Medical Science, Yamagata, Japan
| | - Kenji Nemoto
- Department of Heavy Particle Medical Science, Yamagata University Graduate School of Medical Science, Yamagata, Japan.,Department of Radiation Oncology, Faculty of Medicine, Yamagata University, Yamagata, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan
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12
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Nakajima Y, Kadoya N, Kimura T, Hioki K, Jingu K, Yamamoto T. Variations Between Dose-Ventilation and Dose-Perfusion Metrics in Radiation Therapy Planning for Lung Cancer. Adv Radiat Oncol 2020; 5:459-465. [PMID: 32529141 PMCID: PMC7280081 DOI: 10.1016/j.adro.2020.03.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 02/20/2020] [Accepted: 03/05/2020] [Indexed: 12/25/2022] Open
Abstract
Purpose Currently, several active clinical trials of functional lung avoidance radiation therapy using different imaging modalities for ventilation or perfusion are underway. Patients with lung cancer often show ventilation-perfusion mismatch, whereas the significance of dose-function metric remains unclear. The aim of the present study was to compare dose-ventilation metrics with dose-perfusion metrics for radiation therapy plan evaluation. Methods and Materials Pretreatment 4-dimensional computed tomography and 99mTc-macroaggregated albumin single-photon emission computed tomography perfusion images of 60 patients with lung cancer treated with radiation therapy were analyzed. Ventilation images were created using the deformable image registration of 4-dimensional computed tomography image sets and image analysis for regional volume changes as a surrogate for ventilation. Ventilation and perfusion images were converted into percentile distribution images. Analyses included Pearson’s correlation coefficient and comparison of agreements between the following dose-ventilation and dose-perfusion metrics: functional mean lung dose and functional percent lung function receiving 5, 10, 20, 30, and 40 Gy (fV5, fV10, fV20, fV30, and fV40, respectively). Results Overall, the dose-ventilation metrics were greater than the dose-perfusion metrics (ie, fV20, 26.3% ± 9.9% vs 23.9% ± 9.8%). Correlations between the dose-ventilation and dose-perfusion metrics were strong (range, r = 0.94-0.97), whereas the agreements widely varied among patients, with differences as large as 6.6 Gy for functional mean lung dose and 11.1% for fV20. Paired t test indicated that the dose-ventilation and dose-perfusion metrics were significantly different. Conclusions Strong correlations were present between the dose-ventilation and dose-perfusion metrics. However, the agreement between the dose-ventilation and dose-perfusion metrics widely varied among patients, suggesting that ventilation-based radiation therapy plan evaluation may not be comparable to that based on perfusion. Future studies should elucidate the correlation of dose-function metrics with clinical pulmonary toxicity metrics.
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Affiliation(s)
- Yujiro Nakajima
- Department of Radiation Oncology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan.,Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Tomoki Kimura
- Department of Radiation Oncology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Kazunari Hioki
- Department of Clinical Support, Hiroshima University Hospital, Hiroshima, Japan.,Graduate School of Health Science, Kumamoto University, Kumamoto, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Tokihiro Yamamoto
- Department of Radiation Oncology, University of California Davis School of Medicine, Sacramento, California
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13
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Evaluation of the effect of user-guided deformable image registration of thoracic images on registration accuracy among users. Med Dosim 2020; 45:206-212. [PMID: 32014379 DOI: 10.1016/j.meddos.2019.12.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 11/22/2019] [Accepted: 12/10/2019] [Indexed: 11/20/2022]
Abstract
User-guided deformable image registration (DIR) has allowed users to actively participate in the DIR process and is expected to improve DIR accuracy. The purpose of this study was to evaluate the time required for and effect of user-guided DIR on registration accuracy for thoracic images among users. In this study, 4-dimensional computed tomographic images of 10 thoracic cancer patients were used. The dataset for these patients was provided by DIR-Lab (www.dir-lab.com) and included a coordinate list of anatomical landmarks (300 bronchial bifurcations). Four medical physicists from different institutions performed DIR between peak-inhale and peak-exhale images with/without the user-guided DIR tool, Reg Refine, implemented in MIM Maestro (MIM software, Cleveland, OH). DIR accuracy was quantified by using target registration errors (TREs) for 300 anatomical landmarks in each patient. The average TREs with user-guided DIR in the 10 images by the 4 medical physicists were 1.48, 1.80, 3.46, and 3.55 mm, respectively, whereas the TREs without user-guided DIR were 3.28, 3.45, 3.56, and 3.28 mm, respectively. The average times taken by the 4 physicists to use the user-guided DIR were 10.0, 6.7, 7.1, and 8.0 min, respectively. This study demonstrated that user-guided DIR can improve DIR accuracy and requires only a moderate amount of time (<10 min). However, 2 of the 4 users did not show much improvement in DIR accuracy, which indicated the necessity of training prior to use of user-guided DIR.
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14
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Palma G, Monti S, Cella L. Voxel-based analysis in radiation oncology: A methodological cookbook. Phys Med 2020; 69:192-204. [PMID: 31923757 DOI: 10.1016/j.ejmp.2019.12.013] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 12/20/2022] Open
Abstract
Recently, 2D or 3D methods for dose distribution analysis have been proposed as evolutions of the Dose Volume Histogram (DVH) approaches. Those methods, collectively referred to as pixel- or voxel-based (VB) methods, evaluate local dose response patterns and go beyond the organ-based philosophy of Normal Tissue Complication Probability (NTCP) modelling. VB methods have been introduced in the context of radiation oncology in the very last years following the virtuous example of neuroimaging experience. In radiation oncology setting, dose mapping is a suitable scheme to compare spatial patterns of local dose distributions between patients who develop toxicity and who do not. In this critical review, we present the methods that include spatial dose distribution information for evaluating different toxicity endpoints after radiation therapy. The review addresses two main topics. First, the critical aspects in dose map building, namely the spatial normalization of the dose distributions from different patients. Then, the issues related to the actual dose map comparison, i.e. the viable options for a robust VB statistical analysis and the potential pitfalls related to the adopted solutions. To elucidate the different theoretical and technical issues, the covered topics are illustrated in relation to practical applications found in the existing literature. We conclude the overview on the VB philosophy in radiation oncology by introducing new phenomenological approaches to NTCP modelling that accounts for inhomogeneous organ radiosensitivity.
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Affiliation(s)
- G Palma
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy.
| | - S Monti
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
| | - L Cella
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
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15
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Atehortúa A, Garreau M, Simon A, Donal E, Lederlin M, Romero E. Fusion of 3D real-time echocardiography and cine MRI using a saliency analysis. Int J Comput Assist Radiol Surg 2019; 15:277-285. [PMID: 31713090 DOI: 10.1007/s11548-019-02087-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 11/04/2019] [Indexed: 10/25/2022]
Abstract
PURPOSE This paper presents a novel 3D multimodal registration strategy to fuse 3D real-time echocardiography images with cardiac cine MRI images. This alignment is performed in a saliency space, which is designed to maximize similarity between the two imaging modalities. This fusion improves the quality of the available information. METHODS The method performs in two steps: temporal and spatial registrations. A temporal alignment is firstly achieved by nonlinearly matching pairs of correspondences between the two modalities using a dynamic time warping. A temporal registration is then carried out by applying nonrigid transformations in a common saliency space where normalized cross correlation between temporal pairs of salient volumes is maximized. RESULTS The alignment performance was evaluated with a set of 18 subjects, 3 with cardiomyopathies and 15 healthy, by computing the Dice score and Hausdorff distance with respect to manual delineations of the left ventricle cavity in both modalities. A Dice score and Hausdorff distance of [Formula: see text] and [Formula: see text], respectively, were obtained. In addition, the deformation field was estimated by quantifying its foldings, obtaining a 98% of regularity in the deformation field. CONCLUSIONS The 3D multimodal registration strategy presented is performed in a saliency space. Unlike state-of-the-art methods, the presented one takes advantage of the temporal information of the heart to construct this common space, ending up with two well-aligned modalities and regular deformation fields. This preliminary study was evaluated on heterogeneous data composed of two different datasets, healthy and pathological cases, showing similar performances in both cases. Future work will focus on testing the presented strategy in a larger dataset with a balanced number of classes.
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Affiliation(s)
- Angélica Atehortúa
- Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, 35000, Rennes, France. .,Universidad Nacional de Colombia, Bogotá, Colombia.
| | - Mireille Garreau
- Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, 35000, Rennes, France
| | - Antoine Simon
- Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, 35000, Rennes, France
| | - Erwan Donal
- Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, 35000, Rennes, France
| | - Mathieu Lederlin
- Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, 35000, Rennes, France
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16
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Guy CL, Weiss E, Jan N, Christensen GE, Hugo GD. Technical Note: A method for quality assurance of landmark sets for use in evaluation of deformable image registration accuracy of lung parenchyma. Med Phys 2018; 46:766-773. [PMID: 30537225 DOI: 10.1002/mp.13336] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Revised: 12/04/2018] [Accepted: 12/04/2018] [Indexed: 11/10/2022] Open
Abstract
PURPOSE To develop a quality control method to improve the accuracy of corresponding landmark sets used for deformable image registration (DIR) evaluation in the lung parenchyma. METHODS An iterative workflow was developed as a method for quality assurance of landmark sets. Starting with the initial landmark set for a given image pair, a landmark-based deformation was applied to one of the images. A difference image and a color overlay were generated using the deformed image and the other image of the pair. Inspection of these generated images at locations of landmarks allowed for the identification of misplaced landmarks. The observer responsible for creating the initial landmark set was tasked with review and revision of points flagged by the quality assurance procedure. Using the updated landmark sets, the process was repeated until all points were acceptable to the reviewer. RESULTS Eighteen landmark sets, containing a mean (SD) of 170 (31) landmarks, were created using CT images from non-small cell lung cancer patients exhibiting large geometric changes and atelectasis resolution, making landmark specification challenging. Following the quality assurance procedure, the final landmark sets contained a mean (SD) of 165 (25) landmarks, as points too difficult to match were removed and points were added to regions deficient in landmarks. For landmark sets in which changes were made, maximum and mean differences in landmark positions before and after quality assurance ranged between 8.7-81.5 mm and 0.3-9.6 mm, respectively. CONCLUSIONS An effective method for improving the accuracy of landmark correspondence was presented. This quality assurance approach enables more accurate evaluation of DIR for lung parenchyma in clinical image pairs in the absence of a ground truth deformation and may be applicable to other feature-rich anatomical sites.
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Affiliation(s)
- Christopher L Guy
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | - Elisabeth Weiss
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | - Nuzhat Jan
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | - Gary E Christensen
- Department of Electrical and Computer Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, 52242, USA
| | - Geoffrey D Hugo
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, 63110, USA
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17
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Wu RY, Liu AY, Wisdom P, Zhu XR, Frank SJ, Fuller CD, Gunn GB, Palmer MB, Wages CA, Gillin MT, Yang J. Characterization of a new physical phantom for testing rigid and deformable image registration. J Appl Clin Med Phys 2018; 20:145-153. [PMID: 30580471 PMCID: PMC6333135 DOI: 10.1002/acm2.12514] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 10/03/2018] [Accepted: 10/21/2018] [Indexed: 11/06/2022] Open
Abstract
The purpose of this study was to describe a new user-friendly, low-cost phantom that was developed to test the accuracy of rigid and deformable image registration (DIR) systems and to demonstrate the functional efficacy of the new phantom. The phantom was constructed out of acrylic and includes a variety of inserts that simulate different tissue shapes and properties. It can simulate deformations and location changes in patient anatomy by changing the rotations of both the phantom and the inserts. CT scans of this phantom were obtained and used to test the rigid and deformable registration accuracy of the Velocity software. Eight rotation and translation scenarios were used to test the rigid registration accuracy, and 11 deformation scenarios were used to test the DIR accuracy. The mean rotation accuracies in the X-Y (axial) and X-Z (coronal) planes were 0.50° and 0.13°, respectively. The mean translation accuracy was 1 mm in both the X and Y direction and was tested in soft tissue and bone. The DIR accuracies for soft tissue and bone were 0.93 (mean Dice similarity coefficient), 8.3 and 4.5 mm (mean Hausdouff distance), 0.95 and 0.79 mm (mean distance), and 1.13 and 1.12 (mean volume ratio) for soft tissue content (DTE oil) and bone, respectively. The new phantom has a simple design and can be constructed at a low cost. This phantom will allow DIR systems to be effectively and efficiently verified to ensure system performance.
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Affiliation(s)
- Richard Y Wu
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Amy Y Liu
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Paul Wisdom
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xiaorong Ronald Zhu
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Steven J Frank
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Gary Brandon Gunn
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Matthew B Palmer
- Dosimetry Service, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Cody A Wages
- Dosimetry Service, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Michael T Gillin
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jinzhong Yang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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18
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Otsuka M, Monzen H, Matsumoto K, Tamura M, Inada M, Kadoya N, Nishimura Y. Evaluation of lung toxicity risk with computed tomography ventilation image for thoracic cancer patients. PLoS One 2018; 13:e0204721. [PMID: 30281625 PMCID: PMC6169903 DOI: 10.1371/journal.pone.0204721] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 09/13/2018] [Indexed: 11/18/2022] Open
Abstract
Background Four-dimensional computed tomography (4D-CT) ventilation is an emerging imaging modality. Functional avoidance of regions according to 4D-CT ventilation may reduce lung toxicity after radiation therapy. This study evaluated associations between 4D-CT ventilation-based dosimetric parameters and clinical outcomes. Methods Pre-treatment 4D-CT data were used to retrospectively construct ventilation images for 40 thoracic cancer patients retrospectively. Fifteen patients were treated with conventional radiation therapy, 6 patients with hyperfractionated radiation therapy and 19 patients with stereotactic body radiation therapy (SBRT). Ventilation images were calculated from 4D-CT data using a deformable image registration and Jacobian-based algorithm. Each ventilation map was normalized by converting it to percentile images. Ventilation-based dosimetric parameters (Mean Dose, V5 [percent lung volume receiving ≥5 Gy], and V20 [percent lung volume receiving ≥20 Gy]) were calculated for highly and poorly ventilated regions. To test whether the ventilation-based dosimetric parameters could be used predict radiation pneumonitis of ≥Grade 2, the area under the curve (AUC) was determined from the receiver operating characteristic analysis. Results For Mean Dose, poorly ventilated lung regions in the 0–30% range showed the highest AUC value (0.809; 95% confidence interval [CI], 0.663–0.955). For V20, poorly ventilated lung regions in the 0–20% range had the highest AUC value (0.774; 95% [CI], 0.598–0.915), and for V5, poorly ventilated lung regions in the 0–30% range had the highest AUC value (0.843; 95% [CI], 0.732–0.954). The highest AUC values for Mean Dose, V20, and V5 were obtained in poorly ventilated regions. There were significant differences in all dosimetric parameters between radiation pneumonitis of Grade 1 and Grade ≥2. Conclusions Poorly ventilated lung regions identified on 4D-CT had higher AUC values than highly ventilated regions, suggesting that functional planning based on poorly ventilated regions may reduce the risk of lung toxicity in radiation therapy.
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Affiliation(s)
- Masakazu Otsuka
- Department of Medical Physics, Graduate School of Medical Science, Kindai University, Osakasayama, Japan
| | - Hajime Monzen
- Department of Medical Physics, Graduate School of Medical Science, Kindai University, Osakasayama, Japan
- Department of Radiation Oncology, Kindai University Faculty of Medicine, Osakasayama, Japan
- * E-mail:
| | - Kenji Matsumoto
- Department of Medical Physics, Graduate School of Medical Science, Kindai University, Osakasayama, Japan
| | - Mikoto Tamura
- Department of Medical Physics, Graduate School of Medical Science, Kindai University, Osakasayama, Japan
| | - Masahiro Inada
- Department of Radiation Oncology, Kindai University Faculty of Medicine, Osakasayama, Japan
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Yasumasa Nishimura
- Department of Radiation Oncology, Kindai University Faculty of Medicine, Osakasayama, Japan
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19
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Riyahi S, Choi W, Liu CJ, Zhong H, Wu AJ, Mechalakos JG, Lu W. Quantifying local tumor morphological changes with Jacobian map for prediction of pathologic tumor response to chemo-radiotherapy in locally advanced esophageal cancer. Phys Med Biol 2018; 63:145020. [PMID: 29911659 PMCID: PMC6064042 DOI: 10.1088/1361-6560/aacd22] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
We proposed a framework to detect and quantify local tumor morphological changes due to chemo-radiotherapy (CRT) using a Jacobian map and to extract quantitative radiomic features from the Jacobian map to predict the pathologic tumor response in locally advanced esophageal cancer patients. In 20 patients who underwent CRT, a multi-resolution BSpline deformable registration was performed to register the follow-up (post-CRT) CT to the baseline CT image. The Jacobian map (J) was computed as the determinant of the gradient of the deformation vector field. The Jacobian map measured the ratio of local tumor volume change where J < 1 indicated tumor shrinkage and J > 1 denoted expansion. The tumor was manually delineated and corresponding anatomical landmarks were generated on the baseline and follow-up images. Intensity, texture and geometry features were then extracted from the Jacobian map of the tumor to quantify tumor morphological changes. The importance of each Jacobian feature in predicting pathologic tumor response was evaluated by both univariate and multivariate analysis. We constructed a multivariate prediction model by using a support vector machine (SVM) classifier coupled with a least absolute shrinkage and selection operator (LASSO) for feature selection. The SVM-LASSO model was evaluated using ten-times repeated 10-fold cross-validation (10 × 10-fold CV). After registration, the average target registration error was 4.30 ± 1.09 mm (LR:1.63 mm AP:1.59 mm SI:3.05 mm) indicating registration error was within two voxels and close to 4 mm slice thickness. Visually, the Jacobian map showed smoothly-varying local shrinkage and expansion regions in a tumor. Quantitatively, the average median Jacobian was 0.80 ± 0.10 and 1.05 ± 0.15 for responder and non-responder tumors, respectively. These indicated that on average responder tumors had 20% median volume shrinkage while non-responder tumors had 5% median volume expansion. In univariate analysis, the minimum Jacobian (p = 0.009, AUC = 0.98) and median Jacobian (p = 0.004, AUC = 0.95) were the most significant predictors. The SVM-LASSO model achieved the highest accuracy when these two features were selected (sensitivity = 94.4%, specificity = 91.8%, AUC = 0.94). Novel features extracted from the Jacobian map quantified local tumor morphological changes using only baseline tumor contour without post-treatment tumor segmentation. The SVM-LASSO model using the median Jacobian and minimum Jacobian achieved high accuracy in predicting pathologic tumor response. The Jacobian map showed great potential for longitudinal evaluation of tumor response.
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Affiliation(s)
- Sadegh Riyahi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Wookjin Choi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Chia-Ju Liu
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Hualiang Zhong
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, MI 48202, USA
| | - Abraham J. Wu
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - James G. Mechalakos
- 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
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20
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Evaluation of functionally weighted dose-volume parameters for thoracic stereotactic ablative radiotherapy (SABR) using CT ventilation. Phys Med 2018; 49:47-51. [PMID: 29866342 DOI: 10.1016/j.ejmp.2018.05.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 04/27/2018] [Accepted: 05/01/2018] [Indexed: 01/04/2023] Open
Abstract
For the purpose of reducing radiation pneumontisis (RP), four-dimensional CT (4DCT)-based ventilation can be used to reduce functionally weighted lung dose. This study aimed to evaluate the functionally weighted dose-volume parameters and to investigate an optimal weighting method to realize effective planning optimization in thoracic stereotactic ablative radiotherapy (SABR). Forty patients treated with SABR were analyzed. Ventilation images were obtained from 4DCT using deformable registration and Hounsfield unit-based calculation. Functionally-weighted mean lung dose (fMLD) and functional lung fraction receiving at least x Gy (fVx) were calculated by two weighting methods: thresholding and linear weighting. Various ventilation thresholds (5th-95th, every 5th percentile) were tested. The predictive accuracy for CTCAE grade ≧ 2 pneumonitis was evaluated by area under the curve (AUC) of receiver operating characteristic analysis. AUC values varied from 0.459 to 0.570 in accordance with threshold and dose-volume metrics. A combination of 25th percentile threshold and fV30 showed the best result (AUC: 0.570). AUC values with fMLD, fV10, fV20, and fV40 were 0.541, 0.487, 0.548 and 0.563 using a 25th percentile threshold. Although conventional MLD, V10, V20, V30 and V40 showed lower AUC values (0.516, 0.477, 0.534, 0.552 and 0.527), the differences were not statistically significant. fV30 with 25th percentile threshold was the best predictor of RP. Our results suggested that the appropriate weighting should be used for better treatment outcomes in thoracic SABR.
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Guy CL, Weiss E, Christensen GE, Jan N, Hugo GD. CALIPER: A deformable image registration algorithm for large geometric changes during radiotherapy for locally advanced non-small cell lung cancer. Med Phys 2018; 45:2498-2508. [PMID: 29603277 DOI: 10.1002/mp.12891] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 03/06/2018] [Accepted: 03/19/2018] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Locally advanced non-small cell lung cancer (NSCLC) patients may experience dramatic changes in anatomy during radiotherapy and could benefit from adaptive radiotherapy (ART). Deformable image registration (DIR) is necessary to accurately accumulate dose during plan adaptation, but current algorithms perform poorly in the presence of large geometric changes, namely atelectasis resolution. The goal of this work was to develop a DIR framework, named Consistent Anatomy in Lung Parametric imagE Registration (CALIPER), to handle large geometric changes in the thorax. METHODS Registrations were performed on pairs of baseline and mid-treatment CT datasets of NSCLC patients presenting with atelectasis at the start of treatment. Pairs were classified based on atelectasis volume change as either full, partial, or no resolution. The evaluated registration algorithms consisted of several combinations of a hybrid intensity- and feature-based similarity cost function to investigate the ability to simultaneously match healthy lung parenchyma and adjacent atelectasis. These components of the cost function included a mass-preserving intensity cost in the lung parenchyma, use of filters to enhance vascular structures in the lung parenchyma, manually delineated lung lobes as labels, and several intensity cost functions to model atelectasis change. Registration error was quantified with landmark-based target registration error and post-registration alignment of atelectatic lobes. RESULTS The registrations using both lobe labels and vasculature enhancement in addition to intensity of the CT images were found to have the highest accuracy. Of these registrations, the mean (SD) of mean landmark error across patients was 2.50 (1.16) mm, 2.80 (0.70) mm, and 2.04 (0.13) mm for no change, partial resolution, and full atelectasis resolution, respectively. The mean (SD) atelectatic lobe Dice similarity coefficient was 0.91 (0.08), 0.90 (0.08), and 0.89 (0.04), respectively, for the same groups. Registration accuracy was comparable to healthy lung registrations of current state-of-the-art algorithms reported in literature. CONCLUSIONS The CALIPER algorithm developed in this work achieves accurate image registration for challenging cases involving large geometric and topological changes in NSCLC patients, a requirement for enabling ART in this patient group.
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Affiliation(s)
- Christopher L Guy
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | - Elisabeth Weiss
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | - Gary E Christensen
- Department of Electrical and Computer Engineering and Department of Radiation Oncology, University of Iowa, Iowa City, IA, 52242, USA
| | - Nuzhat Jan
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | - Geoffrey D Hugo
- Department of Radiation Oncology, Washington University, St. Louis, MO, 63110, USA
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Monti S, Pacelli R, Cella L, Palma G. Inter-patient image registration algorithms to disentangle regional dose bioeffects. Sci Rep 2018; 8:4915. [PMID: 29559687 PMCID: PMC5861107 DOI: 10.1038/s41598-018-23327-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Accepted: 03/06/2018] [Indexed: 12/25/2022] Open
Abstract
Radiation therapy (RT) technological advances call for a comprehensive reconsideration of the definition of dose features leading to radiation induced morbidity (RIM). In this context, the voxel-based approach (VBA) to dose distribution analysis in RT offers a radically new philosophy to evaluate local dose response patterns, as an alternative to dose-volume-histograms for identifying dose sensitive regions of normal tissue. The VBA relies on mapping patient dose distributions into a single reference case anatomy which serves as anchor for local dosimetric evaluations. The inter-patient elastic image registrations (EIRs) of the planning CTs provide the deformation fields necessary for the actual warp of dose distributions. In this study we assessed the impact of EIR on the VBA results in thoracic patients by identifying two state-of-the-art EIR algorithms (Demons and B-Spline). Our analysis demonstrated that both the EIR algorithms may be successfully used to highlight subregions with dose differences associated with RIM that substantially overlap. Furthermore, the inclusion for the first time of covariates within a dosimetric statistical model that faces the multiple comparison problem expands the potential of VBA, thus paving the way to a reliable voxel-based analysis of RIM in datasets with strong correlation of the outcome with non-dosimetric variables.
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Affiliation(s)
| | - Roberto Pacelli
- Department of Advanced Biomedical Sciences, "Federico II" University School of Medicine, Napoli, Italy
| | - Laura Cella
- Institute of Biostructures and Bioimaging, National Research Council, Napoli, Italy.
| | - Giuseppe Palma
- Institute of Biostructures and Bioimaging, National Research Council, Napoli, Italy
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Direct dose correlation of MRI morphologic alterations of healthy liver tissue after robotic liver SBRT. Strahlenther Onkol 2018; 194:414-424. [PMID: 29404626 DOI: 10.1007/s00066-018-1271-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Accepted: 01/16/2018] [Indexed: 12/23/2022]
Abstract
PURPOSE For assessing healthy liver reactions after robotic SBRT (stereotactic body radiotherapy), we investigated early morphologic alterations on MRI (magnetic resonance imaging) with respect to patient and treatment plan parameters. PATIENTS AND METHODS MRI data at 6-17 weeks post-treatment from 22 patients with 42 liver metastases were analyzed retrospectively. Median prescription dose was 40 Gy delivered in 3-5 fractions. T2- and T1-weighted MRI were registered to the treatment plan. Absolute doses were converted to EQD2 (Equivalent dose in 2Gy fractions) with α/β-ratios of 2 and 3 Gy for healthy, and 8 Gy for modelling pre-damaged liver tissue. RESULTS Sharply defined, centroid-shaped morphologic alterations were observed outside the high-dose volume surrounding the GTV. On T2-w MRI, hyperintensity at EQD2 isodoses of 113.3 ± 66.1 Gy2, 97.5 ± 54.7 Gy3, and 66.5 ± 32.0 Gy8 significantly depended on PTV dimension (p = 0.02) and healthy liver EQD2 (p = 0.05). On T1-w non-contrast MRI, hypointensity at EQD2 isodoses of 113.3 ± 49.3 Gy2, 97.4 ± 41.0 Gy3, and 65.7 ± 24.2 Gy8 significantly depended on prior chemotherapy (p = 0.01) and total liver volume (p = 0.05). On T1-w gadolinium-contrast delayed MRI, hypointensity at EQD2 isodoses of 90.6 ± 42.5 Gy2, 79.3 ± 35.3 Gy3, and 56.6 ± 20.9 Gy8 significantly depended on total (p = 0.04) and healthy (p = 0.01) liver EQD2. CONCLUSIONS Early post-treatment changes in healthy liver tissue after robotic SBRT could spatially be correlated to respective isodoses. Median nominal doses of 10.1-11.3 Gy per fraction (EQD2 79-97 Gy3) induce characteristic morphologic alterations surrounding the lesions, potentially allowing for dosimetric in-vivo accuracy assessments. Comparison to other techniques and investigations of the short- and long-term clinical impact require further research.
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Miura H, Ozawa S, Nakao M, Furukawa K, Doi Y, Kawabata H, Kenjou M, Nagata Y. Impact of deformable image registration accuracy on thoracic images with different regularization weight parameter settings. Phys Med 2017; 42:108-111. [DOI: 10.1016/j.ejmp.2017.09.122] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 07/20/2017] [Accepted: 09/09/2017] [Indexed: 10/18/2022] Open
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Shao J, Hu P. Quantification of regional deformation of the lungs by non-rigid registration of three-dimensional contrast-enhanced magnetic resonance imaging. Quant Imaging Med Surg 2017; 7:177-186. [PMID: 28516043 PMCID: PMC5418144 DOI: 10.21037/qims.2017.01.01] [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: 10/30/2016] [Accepted: 12/02/2016] [Indexed: 11/06/2022]
Abstract
BACKGROUND Assessment of lung function is vital for the diagnosis of a variety of pathological conditions. Research has been proposed to study pulmonary mechanics and kinematics using two-dimensional (2D) magnetic resonance imaging (MRI). This allows estimation of regional lung tissue mechanics but is limited to 2D information. An approach based on three-dimensional (3D) contrast-enhanced MR angiogram of pulmonary blood vessels and a non-rigid image registration technique is proposed for quantification of lung regional deformations, which can potentially be used for assessment of pulmonary parenchymal mechanics and regional ventilation for disease diagnosis without ionizing radiation. METHODS On three volunteers, an end-expiration scan and end-inspiration scan was acquired successively for each volunteer using a 3D breath-hold contrast-enhanced MRI sequence several minutes after gadolinium injection. Subsequently, a rectangle box lung mask is manually selected for each end-expiration scan, applying non-rigid registration algorithms using cubic B-splines as transformations to align each pair of images. This incorporates the Normalized Correlation Coefficient similarity with the bending energy term as cost function with a multi-resolution multi-grid approach. Finally, the lung regional 3D deformations were obtained using the transformations obtained by registration. The alignment accuracy after non-rigid registration was estimated by using a set of branch points of pulmonary blood vessels as anatomical landmarks for each pair of images. RESULTS With contrast enhancement, the pulmonary blood vessel signal was enhanced, which greatly facilitated the non-rigid registration in the lung parenchyma. The average landmarks distances in three pairs of datasets are reduced from 17.9, 20.3 and 16.3 mm, to 1.0, 1.6 and 1.2 mm, respectively, by non-rigid registration. After registration, the average distances error of each pair of datasets was less than 0.6 mm in the right-to-left (RL) direction, less than 0.9 mm in the inferior-to-superior (IS) direction, and less than 1.2 mm in the anterior-to-posterior (AP) direction. CONCLUSIONS Results demonstrated that the proposed method can accurately register lungs with large deformations to evaluate lung regional deformation. It may be used for quantitative assessment of 3D lung regional ventilation avoiding ionizing radiation.
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Affiliation(s)
- Jiaxin Shao
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Peng Hu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Biomedical Physics Interdepartmental Graduate Program, University of California, Los Angeles, CA, USA
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Pusterla O, Bauman G, Bieri O. Three-dimensional oxygen-enhanced MRI of the human lung at 1.5T with ultra-fast balanced steady-state free precession. Magn Reson Med 2017; 79:246-255. [PMID: 28337782 DOI: 10.1002/mrm.26665] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Revised: 02/11/2017] [Accepted: 02/13/2017] [Indexed: 11/12/2022]
Abstract
PURPOSE To assess the feasibility of 3D oxygen-enhanced (OE) MRI of the lung at 1.5T using multi-volumetric ultra-fast balanced steady-state free precession (ufSSFP) acquisitions. METHODS Isotropic imaging of the lung for OE-MRI was performed with an adapted 3D ufSSFP sequence using five breath-hold acquisitions ranging from functional residual capacity to tidal inspiration under both normoxic (room air) and hyperoxic (100% O2 ) gas conditions. For each O2 concentration, a sponge model (which captures the parenchymal signal intensity variation as a function of the lung volume) was fitted to the acquired multi-volumetric datasets after semiautomatic lung segmentation and deformable image registration. From the retrieved model parameters, 3D oxygen-enhancement maps were calculated. RESULTS For OE ufSSFP imaging, the maximum parenchymal signal is observed for flip angles around 23° under both normoxic and hyperoxic conditions. It is found that the sponge model accurately describes parenchymal signal at different breathing positions, thereby mitigating the confounding bias in the estimated oxygen enhancement from residual density modulations. From the model, an average lung oxygen enhancement of 7.0% ± 0.3% was found in the healthy volunteers, and the oxygen-enhancement maps indicate a ventral to dorsal gravitation-related gradient. CONCLUSION The study demonstrates the feasibility of whole-lung OE-MRI from multi-volumetric ufSSFP in healthy volunteers. Magn Reson Med 79:246-255, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Orso Pusterla
- Division of Radiological Physics, Department of Radiology, University of Basel Hospital, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Grzegorz Bauman
- Division of Radiological Physics, Department of Radiology, University of Basel Hospital, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University of Basel Hospital, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
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Stützer K, Haase R, Lohaus F, Barczyk S, Exner F, Löck S, Rühaak J, Lassen-Schmidt B, Corr D, Richter C. Evaluation of a deformable registration algorithm for subsequent lung computed tomography imaging during radiochemotherapy. Med Phys 2017; 43:5028. [PMID: 27587033 DOI: 10.1118/1.4960366] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Rating both a lung segmentation algorithm and a deformable image registration (DIR) algorithm for subsequent lung computed tomography (CT) images by different evaluation techniques. Furthermore, investigating the relative performance and the correlation of the different evaluation techniques to address their potential value in a clinical setting. METHODS Two to seven subsequent CT images (69 in total) of 15 lung cancer patients were acquired prior, during, and after radiochemotherapy. Automated lung segmentations were compared to manually adapted contours. DIR between the first and all following CT images was performed with a fast algorithm specialized for lung tissue registration, requiring the lung segmentation as input. DIR results were evaluated based on landmark distances, lung contour metrics, and vector field inconsistencies in different subvolumes defined by eroding the lung contour. Correlations between the results from the three methods were evaluated. RESULTS Automated lung contour segmentation was satisfactory in 18 cases (26%), failed in 6 cases (9%), and required manual correction in 45 cases (66%). Initial and corrected contours had large overlap but showed strong local deviations. Landmark-based DIR evaluation revealed high accuracy compared to CT resolution with an average error of 2.9 mm. Contour metrics of deformed contours were largely satisfactory. The median vector length of inconsistency vector fields was 0.9 mm in the lung volume and slightly smaller for the eroded volumes. There was no clear correlation between the three evaluation approaches. CONCLUSIONS Automatic lung segmentation remains challenging but can assist the manual delineation process. Proven by three techniques, the inspected DIR algorithm delivers reliable results for the lung CT data sets acquired at different time points. Clinical application of DIR demands a fast DIR evaluation to identify unacceptable results, for instance, by combining different automated DIR evaluation methods.
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Affiliation(s)
- Kristin Stützer
- OncoRay-National Center for Radiation Research in Oncology, Medical Faculty and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Fetscherstr. 74, PF 41, Dresden 01307, Germany
| | - Robert Haase
- OncoRay-National Center for Radiation Research in Oncology, Medical Faculty and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Fetscherstr. 74, PF 41, Dresden 01307, Germany
| | - Fabian Lohaus
- OncoRay-National Center for Radiation Research in Oncology, Medical Faculty and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Fetscherstr. 74, PF 41, Dresden 01307, Germany; Department of Radiation Oncology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden 01307, Germany; German Cancer Consortium (DKTK), Dresden 01307, Germany; and German Cancer Research Center (DKFZ), Heidelberg 69121, Germany
| | - Steffen Barczyk
- OncoRay-National Center for Radiation Research in Oncology, Medical Faculty and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Fetscherstr. 74, PF 41, Dresden 01307, Germany and Department of Radiation Oncology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden 01307, Germany
| | - Florian Exner
- OncoRay-National Center for Radiation Research in Oncology, Medical Faculty and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Fetscherstr. 74, PF 41, Dresden 01307, Germany
| | - Steffen Löck
- OncoRay-National Center for Radiation Research in Oncology, Medical Faculty and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Fetscherstr. 74, PF 41, Dresden 01307, Germany; Department of Radiation Oncology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden 01307, Germany; German Cancer Consortium (DKTK), Dresden 01307, Germany; German Cancer Research Center (DKFZ), Heidelberg 69121, Germany; and Institute of Radiooncology, Helmholtz-Zentrum Dresden-Rossendorf, Dresden 01328, Germany
| | - Jan Rühaak
- Fraunhofer MEVIS, Institute for Medical Image Computing, Maria-Goeppert-Straße 3, Lübeck 23562, Germany
| | - Bianca Lassen-Schmidt
- Fraunhofer MEVIS, Institute for Medical Image Computing, Universitätsallee 29, Bremen 28359, Germany
| | - Dörte Corr
- Fraunhofer MEVIS, Institute for Medical Image Computing, Universitätsallee 29, Bremen 28359, Germany
| | - Christian Richter
- OncoRay-National Center for Radiation Research in Oncology, Medical Faculty and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Fetscherstr. 74, PF 41, Dresden 01307, Germany; Department of Radiation Oncology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden 01307, Germany; German Cancer Consortium (DKTK), Dresden 01307, Germany; German Cancer Research Center (DKFZ), Heidelberg 69121, Germany; and Institute of Radiooncology, Helmholtz-Zentrum Dresden-Rossendorf, Dresden 01328, Germany
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Castillo E, Castillo R, Vinogradskiy Y, Guerrero T. The numerical stability of transformation-based CT ventilation. Int J Comput Assist Radiol Surg 2017; 12:569-580. [PMID: 28058533 PMCID: PMC5362676 DOI: 10.1007/s11548-016-1509-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Accepted: 12/03/2016] [Indexed: 12/31/2022]
Abstract
Abstract Computed tomography (CT)-derived ventilation imaging utilizes deformable image registration (DIR) to recover respiratory-induced tissue volume changes from inhale/exhale 4DCT phases. While current strategies for validating CT ventilation rely on analyzing its correlation with existing functional imaging modalities, the numerical stability of the CT ventilation calculation has not been characterized. Purpose The purpose of this study is to examine how small changes in the DIR displacement field can affect the calculation of transformation-based CT ventilation. Methods First, we derive a mathematical theorem, which states that the change in ventilation metric induced by a perturbation to single displacement vector is bounded by the perturbation magnitude. Second, we introduce a novel Jacobian constrained optimization method for computing user-defined CT ventilation images. Results Using the Jacobian constrained method, we demonstrate that for the same inhale/exhale CT pair, it is possible to compute two DIR transformations that have similar spatial accuracies, but generate ventilation images with significantly different physical characteristics. In particular, we compute a CT ventilation image that perfectly correlates with a single-photon emission CT perfusion scan. Conclusion The analysis and experiments indicate that while transformation-based CT ventilation is a promising modality, small changes in the DIR displacement field can result in large relative changes in the ventilation image. As such, approaches for improving the reproducibility of CT ventilation are still needed.
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Affiliation(s)
- Edward Castillo
- Department of Radiation Oncology, Beaumont Health Systems, Royal Oak, MI, USA.
- Department of Computational and Applied Mathematics, Rice University, Houston, TX, USA.
| | - Richard Castillo
- Department of Radiation Oncology, University of Texas Medical Branch, Galveston, TX, USA
| | | | - Thomas Guerrero
- Department of Radiation Oncology, Beaumont Health Systems, Royal Oak, MI, USA
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MRI morphologic alterations after liver SBRT : Direct dose correlation with intermodal matching. Strahlenther Onkol 2016; 192:641-8. [PMID: 27393400 DOI: 10.1007/s00066-016-1013-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2015] [Accepted: 06/15/2016] [Indexed: 12/12/2022]
Abstract
AIM CT morphologic and histopathologic alterations have been reported after SBRT. We analyzed the correlation of MRI morphologic alterations with radiation doses to assess the potential for MRI-based dose-effect correlation in healthy liver tissue. PATIENTS AND METHODS MRI data of 24 patients with liver metastases 7±3 weeks after image-guided SBRT in deep-inspiration breath-hold were retrospectively analyzed. MRI images were intermodally matched to the planning CT and corresponding dose distribution. Absolute doses were converted to EQD2,α/β =x with α/β values of 2, 3 for healthy liver tissue, 8 Gy for modelled predamaged liver tissue and 10 Gy for tumor tissue. RESULTS A central nonenhancing area was observed within the isodose lines of nominally 48.2 ± 15.2 Gy, EQD2Gy/α/β =10 92.5 ± 27.7 Gy. Contrast-enhancement around the central nonenhancing area was observed within the isodose lines of nominally 46.9 ± 15.3 Gy, EQD2Gy/α/β =10 90.5 ± 28.3 Gy. Outside the high-dose volume, in the beam path, characteristic sharply defined, nonblurred MRI morphologic alterations were observed that corresponded with the following isodose lines: T1-intensity changes occurred at isodose lines of nominally 21.9 ± 6.7 Gy (EQD2,α/β =2 42.5 ± 8.7 Gy, EQD2,α/β =3 38.5 ± 7.6 Gy, EQD2,α/β =8 30.2 ±6.3 Gy). T2-hyper/hypointensity was observed within isodose lines of nominally 22.4 ± 6.6 Gy (EQD2,α/β=2 42.7 ± 8.1 Gy, EQD2,α/β=3 38.7 ± 7 Gy; EQD2,α/β=8 30.5 ± 5.9 Gy). CONCLUSIONS Using deformable matching, direct spatial/dosimetric correlation of SBRT-induced changes in liver tissue was possible. In the PTV high-dose region, a central nonenhancing area and peripheral contrast medium accumulation was observed. Beam path doses of 38-42 Gy (EQD2,α/β =2-3) induce characteristic MRI morphologic alterations.
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Kanai T, Kadoya N, Ito K, Kishi K, Dobashi S, Yamamoto T, Umezawa R, Matsushita H, Takeda K, Jingu K. Evaluation of four-dimensional computed tomography (4D-CT)-based pulmonary ventilation: The high correlation between 4D-CT ventilation and 81mKr-planar images was found. Radiother Oncol 2016; 119:444-8. [DOI: 10.1016/j.radonc.2016.04.030] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Revised: 04/19/2016] [Accepted: 04/21/2016] [Indexed: 11/25/2022]
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Kadoya N, Cho SY, Kanai T, Onozato Y, Ito K, Dobashi S, Yamamoto T, Umezawa R, Matsushita H, Takeda K, Jingu K. Dosimetric impact of 4-dimensional computed tomography ventilation imaging-based functional treatment planning for stereotactic body radiation therapy with 3-dimensional conformal radiation therapy. Pract Radiat Oncol 2015; 5:e505-e512. [PMID: 25899221 DOI: 10.1016/j.prro.2015.03.001] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2014] [Revised: 01/10/2015] [Accepted: 03/02/2015] [Indexed: 11/30/2022]
Abstract
PURPOSE The purpose of this study was to clarify the dosimetric impact of 4-dimensional computed tomography (4D-CT)-derived, ventilation-guided functional avoidance for stereotactic body radiation therapy (SBRT) with 3-dimensional conformal radiation therapy. METHODS AND MATERIALS Eleven lung cancer patients with peripheral tumors no greater than 5 cm in size were studied (average planning target volume, 42.4 ± 32.5 cm(3)). Four-dimensional-CT ventilation imaging was performed using deformable image registration for spatial mapping of the peak-exhale 4D-CT image to the peak-inhale 4D-CT image and computation of the Jacobian-based ventilation metric. For each patient, anatomical and functional plans were created using 7 to 9 noncoplanar beams for SBRT (40-56 Gy/4-8 fractions). The anatomical plan was generated without incorporating ventilation information. In the functional plan, functional dose-volume constraints were applied in planning to spare the high-functional lung that was defined as the 90th percentile functional volume. The beam directions of the 2 plans were automatically determined by beam angle optimization. RESULTS The percentage of volume receiving a dose of ≥5 Gy (V5), V10, V20, and mean dose to the high-functional lung were 20.5%, 15.6%, 7.8%, and 4.6 Gy, respectively, for the anatomical plan, whereas they were 12.3%, 8.2%, 4.6%, and 3.2 Gy, respectively, for the functional plan. No significant differences in minimum dose, maximum dose, and conformity index of the planning target volume and in all dosimetric parameters for normal tissues between the anatomical and functional plans were seen. CONCLUSIONS We compared anatomical and functional plans for SBRT with 3-dimensional conformal radiation therapy for the first time. Our results demonstrated that a functional plan for SBRT reduced the dose in the high-functional regions without a significant change in the total lung or planning target volume even if the radiation technique cannot modulate beam intensity. Thus, this technique can be safely used in functional planning for SBRT.
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Affiliation(s)
- Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University School of Medicine, Sendai, Japan.
| | - Sang Yong Cho
- Department of Radiation Oncology, Tohoku University School of Medicine, Sendai, Japan
| | - Takayuki Kanai
- Department of Radiation Oncology, Tohoku University School of Medicine, Sendai, Japan
| | - Yusuke Onozato
- Department of Radiation Oncology, Tohoku University School of Medicine, Sendai, Japan
| | - Kengo Ito
- Department of Radiation Oncology, Tohoku University School of Medicine, Sendai, Japan
| | - Suguru Dobashi
- Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Tohoku University, Sendai, Japan
| | - Takaya Yamamoto
- Department of Radiation Oncology, Tohoku University School of Medicine, Sendai, Japan
| | - Rei Umezawa
- Department of Radiation Oncology, Tohoku University School of Medicine, Sendai, Japan
| | - Haruo Matsushita
- Department of Radiation Oncology, Tohoku University School of Medicine, Sendai, Japan
| | - Ken Takeda
- Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Tohoku University, Sendai, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University School of Medicine, Sendai, Japan
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Kerner GS, Fischer A, Koole MJ, Pruim J, Groen HJ. Evaluation of elastix-based propagated align algorithm for VOI- and voxel-based analysis of longitudinal (18)F-FDG PET/CT data from patients with non-small cell lung cancer (NSCLC). EJNMMI Res 2015; 5:15. [PMID: 25853021 PMCID: PMC4385310 DOI: 10.1186/s13550-015-0089-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2014] [Accepted: 02/20/2015] [Indexed: 12/02/2022] Open
Abstract
Background Deformable image registration allows volume of interest (VOI)- and voxel-based analysis of longitudinal changes in fluorodeoxyglucose (FDG) tumor uptake in patients with non-small cell lung cancer (NSCLC). This study evaluates the performance of the elastix toolbox deformable image registration algorithm for VOI and voxel-wise assessment of longitudinal variations in FDG tumor uptake in NSCLC patients. Methods Evaluation of the elastix toolbox was performed using 18F-FDG PET/CT at baseline and after 2 cycles of therapy (follow-up) data in advanced NSCLC patients. The elastix toolbox, an integrated part of the IMALYTICS workstation, was used to apply a CT-based non-linear image registration of follow-up PET/CT data using the baseline PET/CT data as reference. Lesion statistics were compared to assess the impact on therapy response assessment. Next, CT-based deformable image registration was performed anew on the deformed follow-up PET/CT data using the original follow-up PET/CT data as reference, yielding a realigned follow-up PET dataset. Performance was evaluated by determining the correlation coefficient between original and realigned follow-up PET datasets. The intra- and extra-thoracic tumors were automatically delineated on the original PET using a 41% of maximum standardized uptake value (SUVmax) adaptive threshold. Equivalence between reference and realigned images was tested (determining 95% range of the difference) and estimating the percentage of voxel values that fell within that range. Results Thirty-nine patients with 191 tumor lesions were included. In 37/39 and 12/39 patients, respectively, thoracic and non-thoracic lesions were evaluable for response assessment. Using the EORTC/SUVmax-based criteria, 5/37 patients had a discordant response of thoracic, and 2/12 a discordant response of non-thoracic lesions between the reference and the realigned image. FDG uptake values of corresponding tumor voxels in the original and realigned reference PET correlated well (R2=0.98). Using equivalence testing, 94% of all the voxel values fell within the 95% range of the difference between original and realigned reference PET. Conclusions The elastix toolbox impacts lesion statistics and therefore therapy response assessment in a clinically significant way. The elastix toolbox is therefore not applicable in its current form and/or standard settings for PET response evaluation. Further optimization and validation of this technique is necessary prior to clinical implementation. Electronic supplementary material The online version of this article (doi:10.1186/s13550-015-0089-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gerald Sma Kerner
- University of Groningen and Department of Pulmonary Diseases, University Medical Center Groningen, Hanzeplein 1, P.O. Box 30.001, , 9700 RB Groningen, The Netherlands
| | - Alexander Fischer
- Philips Technologie GmbH Innovative Technologies, Postfach 40, Philipstr. 8, Aachen, 52068 Germany
| | - Michel Jb Koole
- University of Groningen and Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Hanzeplein 1, P.O. Box 30.001, , 9700 RB Groningen, The Netherlands
| | - Jan Pruim
- University of Groningen and Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Hanzeplein 1, P.O. Box 30.001, , 9700 RB Groningen, The Netherlands ; Department of Nuclear Medicine, Faculty of Medicine & Health Sciences, Tygerberg Hospital, Stellenbosch University, Francie van Zijl drive, Cape Town, 7505 South-Africa
| | - Harry Jm Groen
- University of Groningen and Department of Pulmonary Diseases, University Medical Center Groningen, Hanzeplein 1, P.O. Box 30.001, , 9700 RB Groningen, The Netherlands
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Kida S. [Toward physiologically-adaptive radiotherapy with lung functional imaging based on 4D CT]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2014; 70:1353-1359. [PMID: 25410344 DOI: 10.6009/jjrt.2014_jsrt_70.11.1353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
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