Jing-Lei Li1, Wei-Tao Ye2, Zai-Yi Liu2, Li-Fen Yan2, Wei Luo2, Xi-Ming Cao2, Changhong Liang3. 1. Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou 510080, PR China. Electronic address: lijinglei80@126.com. 2. Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou 510080, PR China. 3. Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou 510080, PR China. Electronic address: cjr.lchh@vip.163.com.
Abstract
OBJECT: To explore microcirculation features with intravoxel incoherent motion (IVIM) and to compare IVIM with CT perfusion imaging (CTPI) and microvessel density (MVD). MATERIALS AND METHODS: Hepatic CTPI and IVIM were performed in 16 rabbit liver VX2 tumor models. Hepatic arterial perfusion (HAP), hepatic arterial perfusion index (HPI), Blood flow (BF), and blood volume (BV) from CTPI were measured. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion fraction (f), and pseudo-diffusion coefficient (D*) from IVIM were measured. MVD was counted with CD34 stain. The microcirculation features with IVIM were compared with CTPI parameters and MVD. RESULTS: Strong linear correlations were found between D value (0.89±0.21×10-3mm2/s) and HAP (15.83±6.97ml/min/100mg) (r=0.755, P=0.001) and between f value (12.64±6.66%) and BV (9.74±5.04ml/100mg) (r=0.693, P=0.004). Moderate linear correlations were observed between ADC (1.07±0.32×10-3mm2/s) and HAP (r=0.538, P=0.039), respectively; and between D value and MVD (9.31±2.57 vessels at 400×magnification) (r=0.509, P=0.044). No correlations were found between D* (119.90±37.67×10-3mm2/s) and HAP, HPI (68.34±12.91%), BF (4.95±2.16ml/min/100mg), BV. CONCLUSION: IVIM parameters can characterize microcirculation to certain extent and separate it from pure water molecular diffusion. There is fair correlation between D or ADC value and CTPI parameters or MVD, but no correlation between D* or f value and CTPI parameters or MVD except f value and BV, which is still unclear and need further clinical studies to validate.
OBJECT: To explore microcirculation features with intravoxel incoherent motion (IVIM) and to compare IVIM with CT perfusion imaging (CTPI) and microvessel density (MVD). MATERIALS AND METHODS: Hepatic CTPI and IVIM were performed in 16 rabbit liver VX2 tumor models. Hepatic arterial perfusion (HAP), hepatic arterial perfusion index (HPI), Blood flow (BF), and blood volume (BV) from CTPI were measured. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion fraction (f), and pseudo-diffusion coefficient (D*) from IVIM were measured. MVD was counted with CD34 stain. The microcirculation features with IVIM were compared with CTPI parameters and MVD. RESULTS: Strong linear correlations were found between D value (0.89±0.21×10-3mm2/s) and HAP (15.83±6.97ml/min/100mg) (r=0.755, P=0.001) and between f value (12.64±6.66%) and BV (9.74±5.04ml/100mg) (r=0.693, P=0.004). Moderate linear correlations were observed between ADC (1.07±0.32×10-3mm2/s) and HAP (r=0.538, P=0.039), respectively; and between D value and MVD (9.31±2.57 vessels at 400×magnification) (r=0.509, P=0.044). No correlations were found between D* (119.90±37.67×10-3mm2/s) and HAP, HPI (68.34±12.91%), BF (4.95±2.16ml/min/100mg), BV. CONCLUSION: IVIM parameters can characterize microcirculation to certain extent and separate it from pure water molecular diffusion. There is fair correlation between D or ADC value and CTPI parameters or MVD, but no correlation between D* or f value and CTPI parameters or MVD except f value and BV, which is still unclear and need further clinical studies to validate.