Jing Yuan1, Steven K K Chow, Ann D King, David K W Yeung. 1. Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China. jyuan@cuhk.edu.hk
Abstract
PURPOSE: To present a novel heuristic linear mapping method to individually estimate physiological parameters for Tofts model without T(1) measurement and contrast agent concentration. MATERIALS AND METHODS: A linear relationship was used for k(ep) mapping through a heuristic time intensity curve (TIC) shape factor (TSF). K(trans) maps were subsequently estimated using k(ep) maps and another approximate linear model derived from the Tofts model. Twenty-seven patients with head-and-neck squamous cell carcinoma received dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Physiological parameters maps were obtained using this heuristic linear mapping method and compared to the maps obtained by the normal nonlinear least-square fitting with T(1) measurement. RESULTS: High linearity (R(2) >0.95) between k(ep) and TSF was found in all patients for k(ep) <5/min. This linearity is robust for TSF timepoint selection. The k(ep) maps generated by this linear fitting were highly consistent with those by the normal nonlinear approach (P > 0.05). The K(trans) maps were consistent with the normally derived maps in pattern distribution but the absolute value might be scaled due to the assumption of the reference K(trans) value. CONCLUSION: This novel method generates reliable and consistent physiological parameter maps with significantly lower computation complexity than the multiparameter nonlinear fitting. The DCE-MRI scan time can be greatly shortened without T(1) mapping.
PURPOSE: To present a novel heuristic linear mapping method to individually estimate physiological parameters for Tofts model without T(1) measurement and contrast agent concentration. MATERIALS AND METHODS: A linear relationship was used for k(ep) mapping through a heuristic time intensity curve (TIC) shape factor (TSF). K(trans) maps were subsequently estimated using k(ep) maps and another approximate linear model derived from the Tofts model. Twenty-seven patients with head-and-neck squamous cell carcinoma received dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Physiological parameters maps were obtained using this heuristic linear mapping method and compared to the maps obtained by the normal nonlinear least-square fitting with T(1) measurement. RESULTS: High linearity (R(2) >0.95) between k(ep) and TSF was found in all patients for k(ep) <5/min. This linearity is robust for TSF timepoint selection. The k(ep) maps generated by this linear fitting were highly consistent with those by the normal nonlinear approach (P > 0.05). The K(trans) maps were consistent with the normally derived maps in pattern distribution but the absolute value might be scaled due to the assumption of the reference K(trans) value. CONCLUSION: This novel method generates reliable and consistent physiological parameter maps with significantly lower computation complexity than the multiparameter nonlinear fitting. The DCE-MRI scan time can be greatly shortened without T(1) mapping.
Authors: Jing Yuan; Steven Kwok Keung Chow; Qinwei Zhang; David Ka Wai Yeung; Anil T Ahuja; Ann D King Journal: PLoS One Date: 2013-03-20 Impact factor: 3.240