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Wang X, Hu R, Wang Y, Yan Q, Wang Y, Kang F, Zhu S. A Data Self-Calibration Method Based on High-Density Parallel Plate Diffuse Optical Tomography for Breast Cancer Imaging. Front Oncol 2021; 11:786289. [PMID: 34993144 PMCID: PMC8724432 DOI: 10.3389/fonc.2021.786289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/03/2021] [Indexed: 11/13/2022] Open
Abstract
When performing the diffuse optical tomography (DOT) of the breast, the mismatch between the forward model and the experimental conditions will significantly hinder the reconstruction accuracy. Therefore, the reference measurement is commonly used to calibrate the measured data before the reconstruction. However, it is complicated to customize corresponding reference phantoms based on the breast shape and background optical parameters of different subjects in clinical trials. Furthermore, although high-density (HD) DOT configuration has been proven to improve imaging quality, a large number of source-detector (SD) pairs also increase the difficulty of multi-channel correction. To enhance the applicability of the breast DOT, a data self-calibration method based on an HD parallel-plate DOT system is proposed in this paper to replace the conventional relative measurement on a reference phantom. The reference predicted data can be constructed directly from the measurement data with the support of the HD-DOT system, which has nearly a hundred sets of measurements at each SD distance. The proposed scheme has been validated by Monte Carlo (MC) simulation, breast-size phantom experiments, and clinical trials, exhibiting the feasibility in ensuring the quality of the DOT reconstruction while effectively reducing the complexity associated with relative measurements on reference phantoms.
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Affiliation(s)
- Xin Wang
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
| | - Rui Hu
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
| | - Yirong Wang
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Qiang Yan
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
| | - Yihan Wang
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
- *Correspondence: Yihan Wang, ; Shouping Zhu,
| | - Fei Kang
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Shouping Zhu
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
- *Correspondence: Yihan Wang, ; Shouping Zhu,
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