Abstract
An image reconstruction regularization approach for magnetic resonance imaging-guided near-infrared spectral tomography has been developed to improve quantification of total hemoglobin (HbT) and water. By combining prior information from dynamic contrast enhanced (DCE) and diffusion weighted (DW) MR images, the absolute bias errors of HbT and water in the tumor were reduced by 22% and 18%, 21% and 6%, and 10% and 11%, compared to that in the no-prior, DCE- or DW-guided reconstructed images in three-dimensional simulations, respectively. In addition, the apparent contrast values of HbT and water were increased in patient image reconstruction from 1.4 and 1.4 (DCE) or 1.8 and 1.4 (DW) to 4.6 and 1.6.
Highlights
An image reconstruction regularization approach for magnetic resonance imaging-guided near-infrared spectral tomography has been developed to improve quantification of total hemoglobin (HbT) and water
T1-weighted (T1W), T2-weighted (T2W), T1weighted dynamic contrast enhanced (DCE), and diffusion weighted (DW) images are often acquired in standard clinical breast MRI
A reconstruction algorithm is presented to directly encode the spatial information derived from DCE and DW MRI into multiple regularization matrices for recovering Near-infrared spectral tomography (NIRST) HbT and water contents
Summary
An image reconstruction regularization approach for magnetic resonance imaging-guided near-infrared spectral tomography has been developed to improve quantification of total hemoglobin (HbT) and water. A reconstruction algorithm is presented to directly encode the spatial information derived from DCE and DW MRI into multiple regularization matrices for recovering NIRST HbT and water contents.
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