Abdominopelvic MR to CT registration using a synthetic CT intermediate

Jin Uk Heo, Feifei Zhou, Robert Jones, Jiamin Zheng, Xin Song, Pengjiang Qian, Atallah Baydoun, Melanie S. Traughber, Jung Wen Kuo, Rose Al Helo, Cheryl Thompson, Norbert Avril, Daniel DeVincent, Harold Hunt, Amit Gupta, Navid Faraji, Michael Z. Kharouta, Arash Kardan, David Bitonte, Christian B. LangmackAaron Nelson, Alexandria Kruzer, Min Yao, Jennifer Dorth, John Nakayama, Steven E. Waggoner, Tithi Biswas, Eleanor Harris, Susan Sandstrom, Bryan J. Traughber, Raymond F. Muzic

Research output: Contribution to journalArticlepeer-review

Abstract

Accurate coregistration of computed tomography (CT) and magnetic resonance (MR) imaging can provide clinically relevant and complementary information and can serve to facilitate multiple clinical tasks including surgical and radiation treatment planning, and generating a virtual Positron Emission Tomography (PET)/MR for the sites that do not have a PET/MR system available. Despite the long-standing interest in multimodality co-registration, a robust, routine clinical solution remains an unmet need. Part of the challenge may be the use of mutual information (MI) maximization and local phase difference (LPD) as similarity metrics, which have limited robustness, efficiency, and are difficult to optimize. Accordingly, we propose registering MR to CT by mapping the MR to a synthetic CT intermediate (sCT) and further using it in a sCT-CT deformable image registration (DIR) that minimizes the sum of squared differences. The resultant deformation field of a sCT-CT DIR is applied to the MRI to register it with the CT. Twenty-five sets of abdominopelvic imaging data are used for evaluation. The proposed method is compared to standard MI- and LPD-based methods, and the multimodality DIR provided by a state of the art, commercially available FDA-cleared clinical software package. The results are compared using global similarity metrics, Modified Hausdorff Distance, and Dice Similarity Index on six structures. Further, four physicians visually assessed and scored registered images for their registration accuracy. As evident from both quantitative and qualitative evaluation, the proposed method achieved registration accuracy superior to LPD- and MI-based methods and can refine the results of the commercial package DIR when using its results as a starting point. Supported by these, this manuscript concludes the proposed registration method is more robust, accurate, and efficient than the MI- and LPD-based methods.

Original languageEnglish (US)
Article numbere13731
JournalJournal of applied clinical medical physics
Volume23
Issue number9
DOIs
StatePublished - Sep 2022

All Science Journal Classification (ASJC) codes

  • Radiation
  • Instrumentation
  • Radiology Nuclear Medicine and imaging

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