Addressing phase errors in fat‐water imaging using a mixed magnitude/complex fitting method

Citations Over TimeTop 10% of 2011 papers

Abstract

Accurate, noninvasive measurements of liver fat content are needed for the early diagnosis and quantitative staging of nonalcoholic fatty liver disease. Chemical shift-based fat quantification methods acquire images at multiple echo times using a multiecho spoiled gradient echo sequence, and provide fat fraction measurements through postprocessing. However, phase errors, such as those caused by eddy currents, can adversely affect fat quantification. These phase errors are typically most significant at the first echo of the echo train, and introduce bias in complex-based fat quantification techniques. These errors can be overcome using a magnitude-based technique (where the phase of all echoes is discarded), but at the cost of significantly degraded signal-to-noise ratio, particularly for certain choices of echo time combinations. In this work, we develop a reconstruction method that overcomes these phase errors without the signal-to-noise ratio penalty incurred by magnitude fitting. This method discards the phase of the first echo (which is often corrupted) while maintaining the phase of the remaining echoes (where phase is unaltered). We test the proposed method on 104 patient liver datasets (from 52 patients, each scanned twice), where the fat fraction measurements are compared to coregistered spectroscopy measurements. We demonstrate that mixed fitting is able to provide accurate fat fraction measurements with high signal-to-noise ratio and low bias over a wide choice of echo combinations.

Related Papers

• → Comparison of Magnitude Estimates for New Zealand Earthquakes: Moment Magnitude, Local Magnitude, and Teleseismic Body-Wave Magnitude(2009)110 cited
• → Spin-echo versus gradient-echo fMRI with short echo times(2001)57 cited
• 福建省“九五”地震监测台网台站震级校正及单台震级应用研究(2010)
• MSVQ(Multi-Stage Vector Quantization)를 이용한 임베디드 구조의 양자화(2006)
• Studies on Single Station’s Magnitude Biases Correction in Fujian "nine-five" Earthquake Network and Its Applications(2010)