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. 2025 Jul;94(1):15-27.
doi: 10.1002/mrm.30447. Epub 2025 Mar 17.

Dynamic glucose enhanced imaging using direct water saturation

Affiliations

Dynamic glucose enhanced imaging using direct water saturation

Linda Knutsson et al. Magn Reson Med. 2025 Jul.

Abstract

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.

Keywords: CEST; Z‐spectra; direct saturation (DS); dynamic glucose enhanced (DGE) MRI; glucoCEST.

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Conflict of interest statement

Under a license agreement between Philips and the Johns Hopkins University, L.K.'s spouse, P.C.M.v.Z., and the University are entitled to fees related to an imaging device used in the study discussed in this publication. P.C.M.v.Z. is also a paid lecturer for Philips. This arrangement has been reviewed and approved by the Johns Hopkins University in accordance with its conflict of interest policies.

Figures

FIGURE 1
FIGURE 1
Normoglycemic (Cpa=6.15mM) and hyperglycemic (Cpa=19.8mM ) simulated Z‐spectra for tissue compartments (left) and total tissue (right). The lower row shows a zoomed‐in view comparing the Z‐spectral intensities around half‐maximum for normoglycemia and hyperglycemia. Only Z‐spectra with a sufficiently large change are visualized for tissue compartments (lower left). Saturation parameters: B 1peak = 0.5 μT, 10 consecutive 50‐ms sinc‐Gauss pulses for tsat=0.5s (TR = 1.2 s).
FIGURE 2
FIGURE 2
Patient with recurrent IDH‐wildtype glioblastoma showing thin Gd‐enhancement around the resection cavity. (Left) ΔLW maps during the scan (averaged over a period of 76 s corresponding to two ΔLW images). (Right top) Anatomical images (Gd‐T1w, FLAIR), together with parametric maps from DCE MRI (K trans, V e), DSC MRI (corr. CBV, K2) and DS‐DGE MRI (AUC grayscale and color‐coded). (Right bottom) Graph of linewidth change versus time obtained from regions of interest (ROIs) placed in the DS‐DGE peri‐cavity infiltrative tumor region, located anterior to the cavity, and ventricle (purple diamonds and blue squares, respectively). The ROIs are overlayed on the DS‐DGE MRI AUC map located in the graph as purple and blue areas, respectively. To visualize the trend in glucose uptake, ΔLW(t) curves were temporally smoothed with a 3‐point moving average (purple and blue lines). ΔLW, glucose‐infusion‐induced LW change; AUC, area‐under‐curve; corr. CBV, corrected cerebral blood volume; DCE, dynamic contrast enhanced; DSC, dynamic susceptibility contrast; DS‐DGE, direct water saturation‐dynamic glucose enhanced; FLAIR, fluid‐attenuated inversion recovery; Gd, gadolinium; K2, leakage; K trans, volume transfer constant; LW, linewidth, T1w, T 1 weighted; V e, interstitial volume.
FIGURE 3
FIGURE 3
(Left) Normoglycemic and hyperglycemic experimental Z‐spectra from the glioblastoma patient in Figure 2 and the corresponding DL Lorentzian fits. (Right) A zoomed‐in view demonstrating the linewidth difference between normoglycemic and hyperglycemic experimental Z‐spectra. ROI locations are displayed in the Gd‐T1w image and DS‐DGE AUC map. AUC, area‐under‐curve; DS‐DGE, direct water saturation‐dynamic glucose enhanced; Gd, gadolinium; hcgl, hyperglycemic; ngl, normoglycemic; T1w, T 1 weighted.
FIGURE 4
FIGURE 4
Patient with grade 2 IDH‐mutated astrocytoma. Anatomical images (Gd‐T1w, FLAIR) together with corr. CBV, K2, K trans, V e, and DS‐DGE MRI maps (AUC in both grayscale and color‐coded). Color‐coded AUC calculated from the infusion block only is also shown. A DS‐DGE AUC map overlayed on fused Gd‐T1w/FLAIR is shown for reference. Graph of linewidth change versus time obtained from region of interest (ROI) placed in the DS‐DGE contrast‐enhanced area (purple overlayed on DS‐DGE AUC map). To visualize the trend in glucose uptake, ΔLW(t) curves (purple dots) were temporally smoothed with a 3‐point moving average (purple line). ΔLW, glucose‐infusion‐induced LW change; AUC, area‐under‐curve; corr. CBV, corrected cerebral blood volume; DS‐DGE, direct water saturation‐dynamic glucose enhanced; FLAIR, fluid‐attenuated inversion recovery; Gd, gadolinium; K2, leakage; K trans, volume transfer constant; LW, linewidth; T1w, T 1 weighted; V e, interstitial volume.
FIGURE 5
FIGURE 5
Patient with a grade 2 IDH‐mutated astrocytoma. Anatomical images (Gd‐T1w, FLAIR) together with parametric maps from DCE MRI (K trans, V e), DSC MRI (uncorr. CBV, corr. CBV, K2) and DS‐DGE MRI (color‐coded AUC) from four slices. AUC, area‐under‐curve; corr. CBV, corrected cerebral blood volume; DCE, dynamic contrast enhanced; DSC, dynamic susceptibility contrast; DS‐DGE, direct water saturation‐dynamic glucose enhanced; FLAIR, fluid‐attenuated inversion recovery; Gd, gadolinium; K2, leakage; K trans, volume transfer constant; T1w, T 1 weighted; uncorr. CBV, uncorrected cerebral blood volume; V e, interstitial volume.
FIGURE 6
FIGURE 6
Patient with brain metastasis from anaplastic lymphoma kinase‐mutated non–small‐cell lung cancer. Anatomical images (Gd‐T1w, FLAIR) together with K trans, V e, uncorr. CBV, corr. CBV, and DS‐DGE MRI maps (LW map from third dynamic, AUC maps in both grayscale and color‐coded). A color‐coded AUC calculated from the infusion block only is also shown. A graph of linewidth change versus time obtained from ROIs placed in the DS‐DGE contrast‐enhanced area and contralateral frontal WM is shown to the right (purple dots and orange diamonds, respectively). Regions of interest (ROIs) are overlayed on the DS‐DGE MRI AUC map in the graph as purple and orange areas, respectively. To visualize the trend in glucose uptake, ΔLW(t) curves were temporally smoothed with a three‐point moving average (purple and orange lines). ΔLW, glucose‐infusion‐induced LW change; AUC, area‐under‐curve; corr. CBV, corrected cerebral blood volume; DS‐DGE, direct water saturation‐dynamic glucose enhanced; FLAIR, fluid‐attenuated inversion recovery; Gd, gadolinium; K trans, volume transfer constant; LW, linewidth; uncorr. CBV, uncorrected cerebral blood volume; T1w, T 1 weighted; V e, interstitial volume.

Update of

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