Dosimetric comparison of deformable image registration and synthetic CT generation based on CBCT images for organs at risk in cervical cancer radiotherapy

Yankui Chang; Yongguang Liang; Bo Yang; Jie Qiu; Xi Pei; Xie George Xu

doi:10.1186/s13014-022-02191-3

Dosimetric comparison of deformable image registration and synthetic CT generation based on CBCT images for organs at risk in cervical cancer radiotherapy

Radiat Oncol. 2023 Jan 5;18(1):3. doi: 10.1186/s13014-022-02191-3.

Authors

Yankui Chang^#¹, Yongguang Liang^#², Bo Yang², Jie Qiu³, Xi Pei^{1

4}, Xie George Xu^{5

6}

Affiliations

¹ School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, China.
² Department of Radiation Oncology, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China.
³ Department of Radiation Oncology, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China. qj_ww@139.com.
⁴ Technology Development Department, Anhui Wisdom Technology Co., Ltd., Hefei, China.
⁵ School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, China. xgxu@ustc.edu.cn.
⁶ Department of Radiation Oncology, First Affiliated Hospital of University of Science and Technology of China, Hefei, China. xgxu@ustc.edu.cn.

^# Contributed equally.

Abstract

Objective: Anatomical variations existing in cervical cancer radiotherapy treatment can be monitored by cone-beam computed tomography (CBCT) images. Deformable image registration (DIR) from planning CT (pCT) to CBCT images and synthetic CT (sCT) image generation based on CBCT are two methods for improving the quality of CBCT images. This study aims to compare the accuracy of these two approaches geometrically and dosimetrically in cervical cancer radiotherapy.

Methods: In this study, 40 paired pCT-CBCT images were collected to evaluate the accuracy of DIR and sCT generation. The DIR method was based on a 3D multistage registration network that was trained with 150 paired pCT-CBCT images, and the sCT generation method was performed based on a 2D cycle-consistent adversarial network (CycleGAN) with 6000 paired pCT-CBCT slices for training. Then, the doses were recalculated with the CBCT, pCT, deformed pCT (dpCT) and sCT images by a GPU-based Monte Carlo dose code, ArcherQA, to obtain Dose_CBCT, Dose_pCT, Dose_dpCT and Dose_sCT. Organs at risk (OARs) included small intestine, rectum, bladder, spinal cord, femoral heads and bone marrow, CBCT and pCT contours were delineated manually, dpCT contours were propagated through deformation vector fields, sCT contours were auto-segmented and corrected manually.

Results: The global gamma pass rate of Dose_sCT and Dose_dpCT was 99.66% ± 0.34%, while that of Dose_CBCT and Dose_dpCT was 85.92% ± 7.56% at the 1%/1 mm criterion and a low-dose threshold of 10%. Based on Dose_dpCT as uniform dose distribution, there were comparable errors in femoral heads and bone marrow for the dpCT and sCT contours compared with CBCT contours, while sCT contours had lower errors in small intestine, rectum, bladder and spinal cord, especially for those with large volume difference of pCT and CBCT.

Conclusions: For cervical cancer radiotherapy, the DIR method and sCT generation could produce similar precise dose distributions, but sCT contours had higher accuracy when the difference in planning CT and CBCT was large.

Keywords: CBCT; Cervical cancer; Deformable image registration; Dosimetric comparison; sCT generation.

MeSH terms

Cone-Beam Computed Tomography / methods
Female
Humans
Image Processing, Computer-Assisted / methods
Organs at Risk
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted / methods
Spiral Cone-Beam Computed Tomography*
Uterine Cervical Neoplasms* / diagnostic imaging
Uterine Cervical Neoplasms* / radiotherapy