Linda Knutsson, Nirbhay N. Yadav, Sajad Mohammed Ali, David Olayinka Kamson, Eleni Demetriou, Anina Seidemo, Lindsay Blair, Doris D. Lin, John Laterra, Peter C. M. van Zijl
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To overcome this, we propose to utilize exchange-based linewidth <i>(LW)</i> broadening of the direct water saturation (DS) curve of the water saturation spectrum (Z-spectrum) during and after glucose infusion (DS-DGE MRI).</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>To estimate the glucose-infusion-induced <i>LW</i> changes <i>(</i>Δ<i>LW)</i>, Bloch-McConnell simulations were performed for normoglycemia and hyperglycemia in blood, gray matter (GM), white matter (WM), CSF, and malignant tumor tissue. Whole-brain DS-DGE imaging was implemented at 3 T using dynamic Z-spectral acquisitions (1.2 s per offset frequency, 38 s per spectrum) and assessed on four brain tumor patients using infusion of 35 g of D-glucose. To assess Δ<i>LW</i>, a deep learning-based Lorentzian fitting approach was used on voxel-based DS spectra acquired before, during, and post-infusion. Area-under-the-curve <i>(AUC)</i> images, obtained from the dynamic Δ<i>LW</i> time curves, were compared qualitatively to perfusion-weighted imaging parametric maps.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>In simulations, Δ<i>LW</i> was 1.3%, 0.30%, 0.29/0.34%, 7.5%, and 13% in arterial blood, venous blood, GM/WM, malignant tumor tissue, and CSF, respectively. In vivo, Δ<i>LW</i> was approximately 1% in GM/WM, 5% to 20% for different tumor types, and 40% in CSF. The resulting DS-DGE <i>AUC</i> maps clearly outlined lesion areas.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>DS-DGE MRI is highly promising for assessing D-glucose uptake. 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引用次数: 0
摘要
目的:动态葡萄糖增强(DGE) MRI研究采用CEST或自旋锁(CESL)研究葡萄糖摄取。目前,这些方法受到低效应大小和对运动的敏感性的阻碍。为了克服这一问题,我们建议利用基于交换的线宽(LW)拓宽葡萄糖输注期间和之后水饱和度谱(z谱)的直接水饱和度(DS)曲线(DS- dge MRI)。方法:为了估计葡萄糖输注诱导的LW变化(ΔLW),对血液、灰质(GM)、白质(WM)、脑脊液和恶性肿瘤组织中的正常血糖和高血糖进行Bloch-McConnell模拟。采用动态z谱采集(每个偏移频率1.2秒,每个频谱38秒)在3t下进行全脑DS-DGE成像,并通过输注35 g d -葡萄糖对4名脑肿瘤患者进行评估。为了评估ΔLW,对注射前、注射中和注射后获得的基于体素的DS谱使用了基于深度学习的Lorentzian拟合方法。从动态ΔLW时间曲线获得的曲线下面积(AUC)图像与灌注加权成像参数图进行定性比较。结果:在模拟实验中,ΔLW在动脉血、静脉血、GM/WM、恶性肿瘤组织和脑脊液中分别为1.3%、0.30%、0.29/0.34%、7.5%和13%。在体内,ΔLW在GM/WM中约为1%,在不同肿瘤类型中为5%至20%,在脑脊液中为40%。由此产生的DS-DGE AUC清晰地勾勒出病变区域。结论:DS-DGE MRI在评估d -葡萄糖摄取方面非常有前景。脑肿瘤患者的初步结果显示葡萄糖诱导的线拓宽和基于dge的病变增强的高质量AUC图与灌注加权成像相似和/或互补。
Dynamic glucose enhanced imaging using direct water saturation
Purpose
Dynamic glucose enhanced (DGE) MRI studies employ CEST or spin lock (CESL) to study glucose uptake. Currently, these methods are hampered by low effect size and sensitivity to motion. To overcome this, we propose to utilize exchange-based linewidth (LW) broadening of the direct water saturation (DS) curve of the water saturation spectrum (Z-spectrum) during and after glucose infusion (DS-DGE MRI).
Methods
To estimate the glucose-infusion-induced LW changes (ΔLW), Bloch-McConnell simulations were performed for normoglycemia and hyperglycemia in blood, gray matter (GM), white matter (WM), CSF, and malignant tumor tissue. Whole-brain DS-DGE imaging was implemented at 3 T using dynamic Z-spectral acquisitions (1.2 s per offset frequency, 38 s per spectrum) and assessed on four brain tumor patients using infusion of 35 g of D-glucose. To assess ΔLW, a deep learning-based Lorentzian fitting approach was used on voxel-based DS spectra acquired before, during, and post-infusion. Area-under-the-curve (AUC) images, obtained from the dynamic ΔLW time curves, were compared qualitatively to perfusion-weighted imaging parametric maps.
Results
In simulations, ΔLW was 1.3%, 0.30%, 0.29/0.34%, 7.5%, and 13% in arterial blood, venous blood, GM/WM, malignant tumor tissue, and CSF, respectively. In vivo, ΔLW was approximately 1% in GM/WM, 5% to 20% for different tumor types, and 40% in CSF. The resulting DS-DGE AUC maps clearly outlined lesion areas.
Conclusions
DS-DGE MRI is highly promising for assessing D-glucose uptake. Initial results in brain tumor patients show high-quality AUC maps of glucose-induced line broadening and DGE-based lesion enhancement similar and/or complementary to perfusion-weighted imaging.
期刊介绍:
Magnetic Resonance in Medicine (Magn Reson Med) is an international journal devoted to the publication of original investigations concerned with all aspects of the development and use of nuclear magnetic resonance and electron paramagnetic resonance techniques for medical applications. Reports of original investigations in the areas of mathematics, computing, engineering, physics, biophysics, chemistry, biochemistry, and physiology directly relevant to magnetic resonance will be accepted, as well as methodology-oriented clinical studies.