Abstract
In this paper, Ultra-short Echo Time (UTE) \(T_{2}^{*}\) mapping is proposed to non-invasively evaluate auricular cartilages from volunteers and donated bodies. The mono- and bi-exponential models were used for mono- and bi-component analysis (short component \(T_{2}^{*}\) and long component \(T_{2}^{*}\)) respectively. The external ears were manually segmented from images and then reconstructed into 3D \(T_{2}^{*}\) mappings. In the mono-component analysis, the mean \(T_{2}^{*}\) value for 3 volunteers was 34.987 ± 2.266 ms. As for results from the bi-component analysis, the mean values for 3 volunteers were 8.992 ± 0.466 ms and 53.648 ± 1.961 ms for short component \(T_{2}^{*}\) and long component \(T_{2}^{*}\) respectively, with the ratio of bound water to free water of 0.464 ± 0.020. The bi-exponential fitting model performed better than the mono-exponential fitting model on the curve fitting in volunteers, with \(R^{2}\)[bi] = 0.999 ± 0.131 vs. \(R^{2}\)[mono] = 0.972 ± 0.144. According to the bi-component analysis from donated specimens of auricular cartilage, the ratio of bound water to free water was 0.023 ± 0.018, which was significantly different from that of volunteers (p < 0.01), but the fitting curves of specimens showed similar findings with volunteers, with \(R^{2}\)[bi] = 0.999 ± 0.001 vs. \(R^{2}\)[mono] = 0.903 ± 0.005. Our preliminary results demonstrated that the proposed UTE \(T_{2}^{*}\) mapping is a feasible non-invasive means for evaluating the development of auricular cartilage scaffold with bio-inks in reconstructive surgery using 3D bioprinting technique.
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Acknowledgement
This work is supported by CAMS Innovation Fund for Medical Sciences (CIFMS) (2017-I2M-1-007). The donated specimens of auricular cartilage were provided by Human Tissue Bank, Neuroscience Center, Chinese Academy of Medical Sciences and Peking Union Medical College. Authors would like to thank Chao Ma, Naili Wang from the above center, and Rui Li, Le He, Yandong Zhu from Center for Biomedical Imaging Research Department of Biomedical Engineering School of Medicine, Tsinghua University, for their supports.
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Li, X., Zhao, C., Zhang, W. (2019). Non-invasive Assessment of in Vivo Auricular Cartilage by Ultra-short Echo Time (UTE) \(T_{2}^{*}\) Mapping. In: Shen, D., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science(), vol 11768. Springer, Cham. https://doi.org/10.1007/978-3-030-32254-0_11
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