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Hindi Research Article
Efficacy of ADC Histogram Analysis for Differentiating Thymic Cancer from Thymoma
Takafumi Yamada1, Kazuhiro Saito1*, Yoichi Araki, Jinho Park1, Jun Matsubayashi2, Toshitaka Nagao2, Masatoshi Kakihana3, Norihiko Ikeda3 and Koichi Tokuuye11Department of Radiology, Tokyo Medical University, Tokyo, Japan
2Department of Anatomic Pathology, Tokyo Medical University, Tokyo, Japan
3Department of Thoracic Surgery, Tokyo Medical University, Tokyo, Japan
- *Corresponding Author:
- Kazuhiro Saito
Department of Radiology, Tokyo Medical University
6-7-1 Nishishinjuku, Shinjuku-Ku
Tokyo 160-0023, Japan
Tel: +81-3-3342-6111
E-mail: saito-k@tokyo-med.ac.jp
Received date: January 17, 2017; Accepted date: February 04, 2017; Published date: February 10, 2017
Citation: Yamada T, Saito K, Araki Y, Park J, Matsubayashi J, et al. (2017) Efficacy of ADC Histogram Analysis for Differentiating Thymic Cancer from Thymoma. OMICS J Radiol 6:252. doi: 10.4172/2167-7964.1000252
Copyright: © 2017 Yamada T, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Objective: An ADC histogram which was derived from the Region of Interest (ROI) set over the entire tumor may distinguish thymoma from thymic cancer and provide less bias and reproducibility. To evaluate the utility of ADC histogram analysis for differentiating thymic cancer from thymoma in comparison with conventional MRI findings.
Materials and methods: The subjects consisted of 31 patients with 27 thymomas and 4 thymic cancers. Diffusionweighted imaging was performed with b values of 100 and 800 s/mm2. Data acquired from each slice were summed up to derive voxel-by-voxel ADC values for the entire tumor and an ADC histogram was generated. The mean, standard deviation, minimum, maximum, 5th, 25th, 50th, 75th, 90th percentiles, mode, skewness, and kurtosis were derived from the ADC histogram. MRI findings were evaluated in terms of contour, capsulization, septum, hemorrhage, necrosis or cystic change, lymph node swelling, pleural effusion, major vascular invasion, and homogeneity.
Results: Significant differences were observed in the minimum ADC, contour, and major vascular invasion between thymoma and thymic cancer (p=0.010, p=0.03, and p=0.009, respectively). The sensitivities and specificities when the minimum ADC was 70 × 10−6 mm2/s or lower, when the contour was lobular or irregular, and when the presence of vascular invasion was considered to be thymic cancer were 75% and 93%, 100% and 37%, and 25% and 100%, respectively.
Conclusion: Minimum ADC was useful for distinguishing thymic cancer from thymoma, and it had an additional value to the routine MRI sequence.
