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Iima M, Nobashi T, Imai H, Koyasu S, Saga T, Nakamoto Y, Kataoka M, Yamamoto A, Matsuda T, Togashi K. Effects of diffusion time on non-Gaussian diffusion and intravoxel incoherent motion (IVIM) MRI parameters in breast cancer and hepatocellular carcinoma xenograft models. Acta Radiol Open 2018; 7:2058460117751565. [PMID: 29372076 PMCID: PMC5774737 DOI: 10.1177/2058460117751565] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Accepted: 12/10/2017] [Indexed: 12/30/2022] Open
Abstract
Background Perfusion-related intravoxel incoherent motion (IVIM) and non-Gaussian diffusion magnetic resonance (MR) parameters are becoming important biomarkers for differentiating malignant from benign tumors without contrast agents. However, diffusion-time dependence has rarely been investigated in tumors. Purpose To investigate the relationship between diffusion time and diffusion parameters in breast cancer and hepatocellular carcinoma xenograft mouse models. Material and Methods Diffusion-weighted MR images (DWI) were obtained on a 7-T magnetic resonance imaging (MRI) scanner at two different diffusion times (9.6 ms and 27.6 ms) in human breast cancer (MDA-MB-231) and hepatocellular carcinoma (HepG2 and PLC/PRF/5) xenograft mouse models. Perfusion-related IVIM (fIVIM and D*) and non-Gaussian diffusion (ADC0 and K) parameters were estimated. Parametric maps of diffusion changes with the diffusion times were generated using a synthetic apparent diffusion coefficient (sADC) obtained from b = 438 and 2584 s/mm2. Results ADC0 values significantly decreased when diffusion times were changed from 9.6 ms to 27.6 ms in MDA-MB-231, HepG2, and PLC/PRF/5 groups (P = 0.0163, 0.0351, and 0.0170, respectively). K values significantly increased in MDA-MB-231 and HepG2 groups (P < 0.0003 and = 0.0007, respectively); however, no significant difference was detected in the PLC/PRF/5 group. fIVIM values increased, although not significantly (P = 0.164–0.748). The maps of sADC changes showed that diffusion changes with the diffusion time were not homogeneous across tumor tissues. Conclusion Diffusion MR parameters in both breast cancer and HCC xenograft models were found to be diffusion time-dependent. Our results show that diffusion time is an important parameter to consider when interpreting DWI data.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,The Hakubi Center for Advanced Research, Kyoto University, Kyoto, Japan
| | - Tomomi Nobashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Hirohiko Imai
- Division of Systems Informatics, Department of Systems Science, Kyoto University Graduate School of Informatics, Kyoto, Japan
| | - Sho Koyasu
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Laboratory of Cancer Cell Biology, Department of Genome Dynamics, Radiation Biology Center, Kyoto University, Kyoto, Japan.,Research Center for Advanced Science and Technology, Tokyo University, Tokyo, Japan
| | - Tsuneo Saga
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Akira Yamamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Tetsuya Matsuda
- Division of Systems Informatics, Department of Systems Science, Kyoto University Graduate School of Informatics, Kyoto, Japan
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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Yan R, Haopeng P, Xiaoyuan F, Jinsong W, Jiawen Z, Chengjun Y, Tianming Q, Ji X, Mao S, Yueyue D, Yong Z, Jianfeng L, Zhenwei Y. Non-Gaussian diffusion MR imaging of glioma: comparisons of multiple diffusion parameters and correlation with histologic grade and MIB-1 (Ki-67 labeling) index. Neuroradiology 2015; 58:121-32. [PMID: 26494463 DOI: 10.1007/s00234-015-1606-5] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2015] [Accepted: 10/02/2015] [Indexed: 12/12/2022]
Abstract
INTRODUCTION This study was conducted to compare the association of Gaussian and non-Gaussian magnetic resonance imaging (MRI)-derived parameters with histologic grade and MIB-1 (Ki-67 labeling) index (MI) in brain glioma. METHODS Sixty-five patients with pathologically confirmed glioma, who underwent diffusion-weighted MRI with 2 b values (0, 1000 s/mm(2)) and 22 b values (≤5000 s/mm(2)), respectively, were divided into three groups of grade II (n = 35), grade III (n = 8), and grade IV (n = 22). Comparisons by two groups were made for apparent diffusion coefficient (ADC), slow diffusion coefficient (Dslow), distributed diffusion coefficient (DDC), and heterogeneity index α. Analyses of receiver operating characteristic (ROC) curve were performed to maximize the area under the curve (AUC) for differentiating grade III + IV (high-grade glioma, HGG) from grade II (low-grade glioma, LGG) and grade IV (glioblastoma multiforme, GBM) from grade II + III (other grade glioma, OGG). Correlations with MI were analyzed for the MRI parameters. RESULTS On tumor regions, the values of ADC, Dslow, DDC, and α were significantly higher in grade II [(1.37 ± 0.29, 0.70 ± 0.11, 1.39 ± 0.34) (×10(-3) mm(2)/s) and 0.88 ± 0.05, respectively] than in grade III [(0.99 ± 0.13, 0.55 ± 0.07, 1.04 ± 0.20) (×10(-3) mm(2)/s) and 0.80 ± 0.03, respectively] and grade IV [(1.03 ± 0.14, 0.50 ± 0.05, 1.02 ± 0.16) (×10(-3) mm(2)/s) and 0.76 ± 0.04, respectively] (all P < 0.001). The parameter α showed the highest AUCs of 0.950 and 0.922 in discriminating HGG from LGG and GBM from OGG, respectively. Significant correlations with histologic grade and MI were observed for the MRI parameters. CONCLUSION The non-Gaussian MRI-derived parameters α and Dslow are superior to ADC in glioma grading, which are comparable with ADC as reliable biomarkers in noninvasively predicting the proliferation level of glioma malignancy.
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Affiliation(s)
- Ren Yan
- Department of Radiology, Huashan Hospital, Fudan University, Mid Wulumuqi Road, Shanghai, 200040, PR China
| | - Pang Haopeng
- Department of Radiology, Huashan Hospital, Fudan University, Mid Wulumuqi Road, Shanghai, 200040, PR China
| | - Feng Xiaoyuan
- Department of Radiology, Huashan Hospital, Fudan University, Mid Wulumuqi Road, Shanghai, 200040, PR China.
| | - Wu Jinsong
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, PR China
| | - Zhang Jiawen
- Department of Radiology, Huashan Hospital, Fudan University, Mid Wulumuqi Road, Shanghai, 200040, PR China
| | - Yao Chengjun
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, PR China
| | - Qiu Tianming
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, PR China
| | - Xiong Ji
- Department of Neuropathology, Huashan Hospital, Fudan University, Shanghai, PR China
| | - Sheng Mao
- Department of Imaging, Suzhou Children's Hospital, Suzhou, Jiangsu, PR China
| | - Ding Yueyue
- Department of Imaging, Suzhou Children's Hospital, Suzhou, Jiangsu, PR China
| | - Zhang Yong
- MR Research, GE Healthcare, Shanghai, PR China
| | - Luo Jianfeng
- Department of Biostatistics, Public Health School, Fudan University, Shanghai, PR China
| | - Yao Zhenwei
- Department of Radiology, Huashan Hospital, Fudan University, Mid Wulumuqi Road, Shanghai, 200040, PR China
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