论文标题

SPARCQ:一种使用不对称的脂肪分数映射的新方法

SPARCQ: A new approach for fat fraction mapping using asymmetries in the phase-cycled bSSFP signal profile

论文作者

Rossi, Giulia MC, Mackowiak, Adele LC, Hilbert, Tom, Acikgoz, Berk C, Pierzchała, Katarzyna, Kober, Tobias, Bastiaansen, Jessica AM

论文摘要

目的:开发SPARCQ(用于快速隔室定量的信号曲线不对称),一种新的方法,是在相循环的BSSFP曲线中使用不对称性来量化脂肪分数的新方法。方法:SPARCQ使用相循环获得BSSFP频率曲线,在某些重复时间在脂肪和水存在下显示不对称。对于每个体素,测得的信号曲线通过多室词典匹配分解为模拟配置文件的加权总和。每个字典条目代表具有特定非谐波频率和放松时间比的单室BSSFP轮廓。使用字典匹配的结果,为每个体素提取了不同离子分量的分数,从而为整个图像体积生成了水和脂肪分数的定量图以及无带段的图像。使用模拟,水脂幻影中的实验和健康志愿者的膝盖对SPARCQ进行了验证。将实验结果与参考质子密度脂肪分数进行比较,该脂肪分数(幻象)和多回波梯度回波MRI(幻影和志愿者)进行了比较。在六个扫描剂量实验中评估了SPARCQ的可重复性。结果:模拟表明,脂肪分数定量对于大于20的信噪比是准确且健壮的。幻影实验表明,SPARCQ和金标准脂肪分数之间良好的一致性。在志愿者中,用SPARCQ和ME-GRE获得的无带艺术的定量图和水脂分离图像显示了脂肪和非脂肪组织之间的预期对比度。 SPARCQ脂肪分数的可重复性系数为0.0512。结论:SPARCQ在BSSFP概况中使用不对称性证明了脂肪定量的潜力,并且可能是传统脂肪分数定量技术的有前途替代方法。

Purpose: To develop SPARCQ (Signal Profile Asymmetries for Rapid Compartment Quantification), a novel approach to quantify fat fraction using asymmetries in the phase-cycled bSSFP profile. Methods: SPARCQ uses phase-cycling to obtain bSSFP frequency profiles, which display asymmetries in the presence of fat and water at certain repetition times. For each voxel, the measured signal profile is decomposed into a weighted sum of simulated profiles via multi-compartment dictionary matching. Each dictionary entry represents a single-compartment bSSFP profile with a specific off-resonance frequency and relaxation time ratio. Using the results of dictionary matching, the fractions of the different off-resonance components are extracted for each voxel, generating quantitative maps of water and fat fraction and banding-artifact-free images for the entire image volume. SPARCQ was validated using simulations, experiments in a water-fat phantom and in knees of healthy volunteers. Experimental results were compared with reference proton density fat fractions obtained with 1H-MRS (phantoms) and with multiecho gradient-echo MRI (phantoms and volunteers). SPARCQ repeatability was evaluated in six scan-rescan experiments. Results: Simulations showed that fat fraction quantification is accurate and robust for signal-to-noise ratios greater than 20. Phantom experiments demonstrated good agreement between SPARCQ and gold standard fat fractions. In volunteers, banding-artifact-free quantitative maps and water-fat-separated images obtained with SPARCQ and ME-GRE demonstrated the expected contrast between fatty and non-fatty tissues. The coefficient of repeatability of SPARCQ fat fraction was 0.0512. Conclusion: SPARCQ demonstrates potential for fat quantification using asymmetries in bSSFP profiles, and may be a promising alternative to conventional fat fraction quantification techniques.

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