论文研究 - 螺旋CT成像技术在kVCT和MVCT之间的直方图匹配算法评估可变形图像的配准和剂量累积.pdf

发布时间：2022-05-30 发布人：admin 分类：说明书资料大小：1.41M 资料格式：pdf 举报版权申诉

weixin_38645133-12455560-16359647386412318097.pdf-第1页.png

第1页 / 共12页

weixin_38645133-12455560-16359647386412318097.pdf-第2页.png

第2页 / 共12页

weixin_38645133-12455560-16359647386412318097.pdf-第3页.png

第3页 / 共12页

weixin_38645133-12455560-16359647386412318097.pdf-第4页.png

第4页 / 共12页

weixin_38645133-12455560-16359647386412318097.pdf-第5页.png

第5页 / 共12页

weixin_38645133-12455560-16359647386412318097.pdf-第6页.png

第6页 / 共12页

weixin_38645133-12455560-16359647386412318097.pdf-第7页.png

第7页 / 共12页

weixin_38645133-12455560-16359647386412318097.pdf-第8页.png

第8页 / 共12页

Evaluation of Deformable Image Registration and Dose Accumulation Using Histogram Matching Algorithm between kVCT and MVCT with Helical Tomotherapy

Abstract

Keywords

1. Introduction

2. Materials and Methods

2.1. Planning kVCT and MVCT Images

2.2. DIR Using Histogram Matching Algorithm

2.3. Dose Accumulation

2.4. Evaluation and Analysis

3. Results

3.1. DIR Using HM Algorithm

3.2. Dose Accumulation

4. Conclusion

Conflicts of Interest

References

Journal of Modern Physics, 2018, 9, 2274-2285 http://www.scirp.org/journal/jmp ISSN Online: 2153-120X ISSN Print: 2153-1196 Evaluation of Deformable Image Registration and Dose Accumulation Using Histogram Matching Algorithm between kVCT and MVCT with Helical Tomotherapy Masahide Saito*, Yuki Shibata, Naoki Sano, Kengo Kuriyama, Takafumi Komiyama, Kan Marino, Shinichi Aoki, Hiroshi Onishi Department of Radiology, University of Yamanashi, Yamanashi, Japan How to cite this paper: Saito, M., Shibata, Y., Sano, N., Kuriyama, K., Komiyama, T., Marino, K., Aoki, S. and Onishi, H. (2018) Evaluation of Deformable Image Registra- tion and Dose Accumulation Using Histo- gram Matching Algorithm between kVCT and MVCT with Helical Tomotherapy. Journal of Modern Physics, 9, 2274-2285. https://doi.org/10.4236/jmp.2018.913143 Received: October 8, 2018 Accepted: October 30, 2018 Published: November 2, 2018 Copyright © 2018 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access Abstract Purpose: To evaluate the accuracy of deformable image registration (DIR) between the planning kVCT (pCT) and the daily MVCT combined with the histogram matching (HM) algorithm, and evaluate the deformable dose ac- cumulation using a suggested method for adaptive radiotherapy with Helical Tomotharapy (HT). Methods: For five prostate cancer patients (76 Gy/38 Fr) treated with HT in our institution, seven MVCT series (a total of 35 series) acquired weekly were investigated. First, to minimize the effect of different HU values between pCT and MVCT, this image-processing method adjusts HU values between pCT and MVCT images by using image cumulative his- tograms of HU values, generating an HM-MVCT. Then, the DIR of the pCT to the HM-MVCT was performed, generating a deformed pCT. Finally, de- formable dose accumulation was performed toward the pCT image. Results: The accuracy of DIR was significantly improved by using the HM algorithm, compared with non-HM method for several structures (p < 0.05). The mean dice similarity coefficient of the non-HM method was 0.75 ± 0.05, 0.83 ± 0.06, and 0.90 ± 0.04 for the CTV, rectum, and bladder, respectively, while that of the HM method was 0.81 ± 0.06, 0.81 ± 0.04, and 0.92 ± 0.06, respectively. For the deformable dose accumulation, some difference was observed be- tween the two methods, particularly for the small calculated regions, such as rectum V60 and V70. Conclusion: Adapting the HM method can improve the accuracy of DIR. Furthermore, dose calculation using the deformed pCT using HM methods can be an effective tool for adaptive radiotherapy. Keywords Radiotherapy, Tomotherapy, MVCT, Histogram-Matching, Deformable Image DOI: 10.4236/jmp.2018.913143 Nov. 2, 2018 2274 Journal of Modern Physics

M. Saito et al. Registration 1. Introduction Intensity modulated radiotherapy (IMRT) using helical tomotherapy (HT) (Ac- curay, Sunnyvale, CA) reduces the radiation dose to organs at risks (OAR) while maintaining conformity of the tumor [1]. Meanwhile, image-guided radiothera- py using HT uses mega-voltage computed tomography (MVCT) images [2], which have been used routinely for patient setup in HT treatments. Under- standing daily anatomical changes and calculating the radiation dose are imper- ative. Therefore, some studies on adaptive radiotherapy using the daily MVCT and deformable image registration (DIR) have been published [3] [4] [5] [6]. Recently, Branchini et al. suggested a method of planning CT (pCT) for daily MVCT deformation and evaluated its accuracy [7]. They suggested that the me- thod might be sufficiently fast and reliable for daily delivered dose evaluations in clinical strategies for adaptive radiotherapy using HT. However, the use of the daily MVCT is generally limited due to significant photoelectric interaction components and the presence of noise resulting from low detector quantum effi- ciency of megavoltage x-rays. The poor image quality of MVCT might decrease the accuracy of DIR and dose calculation. Although several authors introduced denoising methods [3], further evaluation for more accurate ART methods using MVCT is needed. Some authors have investigated the improvement of image quality using Hounsfield unit (HU) modification methods, such as histogram matching (HM) method [8] [9] [10]. Although previous studies investigated kV-CBCT, no re- ports on improving the quality of MVCT images have been published. Further- more, the deformable dose accumulation using this method was not investigated sufficiently. Therefore, the purpose of this study was to evaluate the accuracy of DIR between the pCT and the daily MVCT combined with the HM algorithm. In addition, we evaluated the deformable dose accumulation using a suggested method for adaptive radiotherapy with HT. 2. Materials and Methods 2.1. Planning kVCT and MVCT Images For five prostate cancer patients (76 Gy/38 Fr) treated with HT in our institu- tion, seven MVCT series (a total of 35 series) acquired weekly were investigated. These images were used for routine patient setup and acquired with the pitch of 4 mm and reconstruction thickness of 2 mm. For the pCT, the settings for image acquisition were 120 kV, 250 mA, 0.50 s, and a 2.0 mm slice thickness. For the pCT image and each MVCT image, anatomical contours of the CTV (prostate + seminal vesicle), rectum, and bladder were described by an experi- mental oncologist and medical physicist. However, the scan range of each MVCT 2275 Journal of Modern Physics DOI: 10.4236/jmp.2018.913143

M. Saito et al. was insufficient to describe the whole anatomical volume of the rectum and bladder in some patients. 2.2. DIR Using Histogram Matching Algorithm In this study, the scan range of the daily MVCT was smaller than the pCT as mentioned previously. To perform DIR between pCT and MVCT normally, we generated a merged MVCT, as shown in Figure 1. First, the rigid image registra- tion was performed between pCT and each MVCT image. Then, the image re- gion outside the MVCT was replaced with pCT, resulting in the merged MVCT. The algorithm between the pCT and the fractional MVCT was applied to im- prove the accuracy of pCT to MVCT deformation. Figure 2(a) shows the pro- cedure of the HM method. To minimize the effect of different HU values be- tween pCT and MVCT, this image-processing method adjusts HU values be- tween pCT and MVCT images by using image cumulative histograms of HU values, generating an HM-MVCT. The HM method was performed by a script generated using MATLAB 2016a (Mathworks Inc., Natick, MA). Then, the DIR of the pCT to the HM-MVCT was performed, generating a de- formed pCT, as shown as Figure 2(b). In this study, this method was also ap- plied to the original MVCT and the result was compared with that of the HM method. All DIRs were performed using the MIM Maestro ver.6.6.8 (MIM Soft- ware, Inc., Cleveland, OH) with intensity-based free form deforamtion algo- rithm. 2.3. Dose Accumulation Figure 3 demonstrates the workflow of the deformable dose accumulation in Figure 1. Concept of a merged MVCT. First, the rigid image registration was performed between the pCT and each fractional MVCT image. Then, the image region outside the MVCT was replaced with that of the pCT. 2276 Journal of Modern Physics DOI: 10.4236/jmp.2018.913143

M. Saito et al. Figure 2. The procedure of deformable image registration combined with the HM me- thod. First, to minimize the effect of different HU values between pCT and MVCT, this image-processing method adjusts HU values between pCT and MVCT images by using image cumulative histograms of HU values, generating an HM-MVCT (a). Then, the DIR of the pCT to the HM-MVCT was performed, generating a deformed pCT (b). Figure 3. The workflow of the deformable dose accumulation in this study. First, each fractional deformed pCT was generated by using HM-MVCT (or non HM-MVCT). Then, the dose of the weekly deformed pCT was calculated. Finally, the deformable dose accumulation was performed toward the pCT image. 2277 Journal of Modern Physics DOI: 10.4236/jmp.2018.913143

M. Saito et al. this study. First, each fractional deformed pCT was generated by using HM-MVCT (or non HM-MVCT). Then, the dose of the weekly deformed pCT was calculated as following condition. The target prescribed dose that was calcu- lated by using each weekly MVCT image was scaled to 10.86 Gy, which was di- vided by the total dose (76 Gy) by 7 weeks. Finally, the deformable dose accu- mulation was performed toward the pCT image using MIM software. The dose calculation of the reference pCT image was performed using Tomotherapy plan- ning station ver. 5.1.0.2, and each fractional dose of the deformed pCT was cal- culated via Tomotherapy DQA station ver. 5.1.0.4 with the fine condition of dose grid size. 2.4. Evaluation and Analysis To evaluate the accuracy of the DIR, dice similarity coefficients (DSC) between deformed contours described in deformed pCT and manual contours described in original MVCT were calculated for CTV, rectum, and bladder, respectively. The DSC results of the HM method were compared with that of the non-HM method. In addition, the accumulated dose using the HM method was compared with that of non-HM method and the reference planned dose for each organ (CTV: mean dose, maximum dose, and D50; rectum: V20, V60, and V70; bladder: V60 and V70). All statistical analyses were performed using JMP ver.11.2.1 (SAS In- stitute, Cary, North Carolina). 3. Results 3.1. DIR Using HM Algorithm First, the DIR of pCT to HM-MVCT (or non-HM-MVCT) was performed. Fig- ure 4 shows a typical case of improving the accuracy of deformation using HM method for CTV. The accuracy of DIR was evaluated using DSC between pCT Figure 4. A typical case of improving the accuracy of deformation using HM method for CTV. 2278 Journal of Modern Physics DOI: 10.4236/jmp.2018.913143

M. Saito et al. and MVCT, comparing with the results of the non-HM method, as shown in Figure 5. The mean DSC of the non-HM method was 0.75 ± 0.05, 0.83 ± 0.06, and 0.90 ± 0.04 for the CTV, rectum, and bladder, respectively, while that of the HM method was 0.81 ± 0.06, 0.81 ± 0.04, and 0.92 ± 0.06, respectively. The ac- curacy for CTV and bladder was significantly improved compared with non-HM MVCT (p < 0.05). 3.2. Dose Accumulation The dose calculation was performed for each fractional deformed pCT. Figure 6 shows the fractional scaled dose changes of patient 1, showing (a) CTV, (b) rec- tum, and (c) bladder for non-HM method (solid line) and HM methods (dash line). For all five patients, the maximum dose deviations of a same fraction be- tween non-HM and HM methods were 0.16 Gy (CTV mean dose), −0.19 Gy (CTV maximum dose), −0.16 Gy (CTV D50), −2.20 Gy (rectum V20), −1.62 Gy (rectum V60), −1.23 Gy (rectum V70), 1.9 Gy (bladder V60), and 1.23 Gy Figure 5. Patient individual dice similarity coefficient (DSC) between manual contours on the each fractional MVCT and deformed contours on the deformed pCT for (a) CTV, (b) rectum, and (c) bladder, and the average DSCs of all patients are shown in (d). Aste- risk symbols (＊) indicates a significant difference between two methods (p<0.05). The mean DSC of the non-HM method was 0.75 ± 0.05, 0.83 ± 0.06, and 0.90 ± 0.04 for the CTV, rectum, and bladder, respectively, while that of the HM method was 0.81 ± 0.06, 0.81 ± 0.04, and 0.92 ± 0.06, respectively. 2279 Journal of Modern Physics DOI: 10.4236/jmp.2018.913143

M. Saito et al. Figure 6. Fractional scaled dose changes of patient 1, showing (a) CTV, (b) rectum, and (c) bladder for non-HM method (solid line) and HM methods (dash line). (bladder V70). Meanwhile, the dose accumulation for all fractional MVCT was performed using the HM method. Table 1 shows the comparison of the reference calculated dose on pCT with the cumulative dose using two deformed pCT datasets. Some difference was observed between the two methods, particularly for the small calculated regions, such as rectum V60 and V70. The DIR between two CT images is an effective tool to perform a more accurate 2280 Journal of Modern Physics DOI: 10.4236/jmp.2018.913143

Table 1. Comparison of the reference calculated dose on pCT with the cumulative dose using two deformed pCT datasets. All p-values were calculated with Wilcoxon test. M. Saito et al. calculated accumulate dose (Gy, mean ± s.d.) pCT 76.5 ± 0.1 79.7 ± 0.7 76.6 ± 0.1 41.1 ± 8.7 11.3 ± 5.4 5.0 ± 3.8 40.4 ± 14.0 15.2 ± 3.1 deformed pCT (non-HM-method) p-value 0.71 0.08 1.00 0.26 0.01 0.01 0.17 0.01 76.4 ± 0.8 79.1 ± 0.8 76.6 ± 0.8 40.1 ± 8.1 7.1 ± 4.5 2.1 ± 3.2 38.5 ± 14.1 11.7 ± 3.3 deformed pCT (HM-method) p-value 0.77 76.6 ± 0.9 0.37 79.3 ± 0.9 76.7 ± 0.9 0.70 0.08 43.1 ± 8.4 0.77 11.1 ± 5.0 0.34 4.3 ± 3.4 40.4 ± 15.7 0.99 0.47 15.7 ± 3.5 rectum CTV Dmean Dmax D50 V20 V60 V70 V40 V70 bladder adaptive radiotherapy. It is usually applied to two kV CT images (two pCT im- ages or pCT image-daily CBCT image). Several authors evaluated their accuracy by using DSC and target registration error (TRE) [11] [12] [13] [14] [15]. Al- though various DIR algorithms were used for these validations, the accuracy of DIR usually depends on the parameter setting of each software. In this study, we used the intensity-based DIR implemented in MIM software. Kadoya et al. in- vestigated the algorithm and found that the 3D registration error was 2.17 mm to 3.61 mm in 10 theoretical images [14]. Although their results were not fo- cused on the pelvic images, the accuracy of the deformation using MIM software was comparable with that of the other commercial DIR software. The MVCT is usually used for daily patient setup for image-guided HT treat- ment instead of kV-CBCT implemented in a conventional linac. Some authors investigated the use of daily MVCT to adaptive radiotherapy, for example, the dose calculation and the deformation between kVCT to MVCT [5] [6]. Howev- er, kVCT and MVCT have some differences, namely, imaging noise, contrast resolution, and field of view, worsening the accuracy for intensity-based defor- mation compared with kV-kV registration. Therefore, to improve the accuracy of DIR, we applied HM algorithm between pCT and MVCT. The HM algorithm is a method used to adjust HU values between pCT and CBCT images by using image cumulative histograms. Van Zijtveld et al. showed that the percentage of points with a gamma value < 1 (2%/2 mm) between pCT and modified CBCT was 98% using the HM algorithm in five patients [10]. However, these reports focused on kV-CBCT, and reports on MVCT combined with the HM algorithm have not been evaluated. Our results indicating that the HM algorithm was effective in improving the accuracy of DIR between pCT and MVCT for almost all anatomical structures are similar to that of the previous kV-CBCT studies [8] [9] [13]. However, some cases had rectal gas and volume change of the bladder, resulting in more variations in the accuracy of DIR. In addition, one of the limitations of this study was the use of the merged MVCT 2281 Journal of Modern Physics DOI: 10.4236/jmp.2018.913143

分享到：

赞收藏

资料库

论文研究 - 螺旋CT成像技术在kVCT和MVCT之间的直方图匹配算法评估可变形图像的配准和剂量累积.pdf

相关推荐

开发技术

热门标签

最新资料