Echo-planar and gradient-echo diffusion MRI of normal brain iron in the globus pallidus

2050 Background: The infiltrating nature of gliomas, particularly into the peritumoral area, is a major barrier to improving clinical outcome as microscopic disease remains even after apparent gross total resection. Conventional T1 post-contrast and T2/FLAIR MRI do not capture full tumor extent. A better imaging biomarker is needed to improve differentiation between tumor, peritumoral area and normal brain. Methods: 4 pre-surgical patients with non-enhancing, FLAIR-hyperintense lesions suspicious for glioma underwent ultra-high gradient diffusion MRI on the Connectome MRI scanner, a unique scanner with maximum gradient strength of 300 mT/m enabling mapping of cellular microstructures on a micron-level scale. The FLAIR area was defined as the tumor region of interest (ROI). Radiographically normal appearing brain up to 1 cm around the FLAIR area was defined as the peritumoral ROI. Using a novel 3 compartment diffusion model (Linear Multiscale Model), the volume fraction of water (VFW) was calculated within restricted (intracellular), hindered (extracellular) and free (CSF) spaces. VFW in the tumor, peritumoral ROI, contralateral normal white matter (WM) and cortex were compared. Results: Within the tumor ROI, the median VFW in the restricted compartment was decreased vs. the peritumoral ROI (↓ 34%), WM (↓ 46%) and cortex (↓ 18%) while median VFW in the hindered compartment was increased vs. the peritumoral ROI (↑ 26%), WM (↑ 54%) and cortex (↑ 25%). Within the peritumoral ROI, median VFW in the hindered compartment was increased compared to WM (↑ 23%). 3 patients had available histopathology revealing isocitrate dehydrogenase-mutant gliomas. Conclusions: Using ultra-high gradient diffusion MRI and a novel diffusion model, we detected distinct diffusion patterns in the tumor and peritumoral area not seen on conventional MRI. Lower VFW in the restricted compartment within the tumor may reflect decreased intracellular water mobility due to enlarged nuclei. Higher VFW in the hindered compartment in the tumor and peritumoral area may reflect higher degree of tissue permeability and edema. MRI-pathology and larger cohort validation studies are underway to elucidate microenvironment changes in response to treatment.

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Comparison of tri-exponential decay vs. bi-exponential decay and full fitting vs. segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI

10.1101/429977 ◽

2018 ◽

Author(s):

Olivier Chevallier ◽

Nan Zhou ◽

Jean-Pierre Cercueil ◽

Jian He ◽

Romaric Loffroy ◽

...

Keyword(s):

Healthy Volunteers ◽

Exponential Decay ◽

Diffusion Mri ◽

Region Of Interest ◽

Exponential Model ◽

Accurate Estimation ◽

Signal Prediction ◽

Diffusion Weighted Images ◽

Echo Planar ◽

Healthy Liver

AbstractPurposeTo determine whether bi- or tri-exponential models, and full or segmented fittings, better fit IVIM imaging signal of healthy livers.Materials and methodsDiffusion-weighted images were acquired with a 3-T scanner using respiratory-triggered echo-planar sequence and 16 b-values (0∼800 s/mm2). Eighteen healthy volunteers had liver scanned twice in the same session, and then once again in another session. Region of interest (ROI)-based measurements were processed with bi-exponential model full fitting and segmented fitting (threshold b-value = 80 s/mm2), as well as tri-exponential model full fitting and segmented fitting (threshold b-value = 200 s/mm2).ResultsWith all scans’ signal averaged, bi-exponential model full fitting showed Dslow=1.14, Dfast=193.6×10-3 mm2/s, and PF=16.9%, and segmented fitting showed Dslow=1.03, Dfast=56.7×10-3 mm2/s, and PF=21.3%. IVIM parameters derived from tri-exponential model were similar for full fitting and segmented fitting, with a slow (D’slow=0.98×10-3 mm2/s; F’slow=76.4 or 76.6%), a fast (D’fast=15.1 or 15.4×10-3 mm2/s; F’fast=11.8 or 11.7%) and a very fast (D’Vfast=445.0 or 448.8×10-3 mm2/s; F’Vfast=11.8 or 11.7 %) diffusion compartments. Tri-exponential model provided an overall better fit than bi-exponential model. For bi-exponential model, full fitting provided better fit at very low and low b-values compared with segmented fitting with the later tended to underestimate Dfast, however, segmented method demonstrated lower error in signal prediction for high b-values. Compared with full fitting, tri-exponential segmented fitting offered better scan-rescan reproducibility.ConclusionFor healthy liver, tri-exponential modelling is preferred than bi-exponential modelling. For bi-exponential model, segmented fitting underestimates Dfast, but offers more accurate estimation of Dslow.

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Clinical characteristics in normal healthy adults with microbleeds on echo-planar gradient-echo T2*-weighted MRI

Nosotchu ◽

10.3995/jstroke.26.357 ◽

2004 ◽

Vol 26 (2) ◽

pp. 357-363 ◽

Cited By ~ 1

Author(s):

Wakoh Takahashi ◽

Tomohide Ohnuki ◽

Michiru Ide ◽

Shigcharu Takagi ◽

Yukito Shinohara

Keyword(s):

Clinical Characteristics ◽

Healthy Adults ◽

Gradient Echo ◽

Echo Planar

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Evaluation of Imaging Schemes for Pulsed Arterial Spin Labelling of the Human Kidney Cortex

10.20944/preprints201805.0386.v1 ◽

2018 ◽

Author(s):

Charlotte E. Buchanan ◽

Eleanor F. Cox ◽

Susan T. Francis

Keyword(s):

Spin Echo ◽

Human Kidney ◽

Echo Planar Imaging ◽

Arterial Spin Labelling ◽

Kidney Cortex ◽

Gradient Echo ◽

Planar Imaging ◽

Spatial Coverage ◽

Echo Planar ◽

Spin Labelling

Purpose: A number of imaging readout schemes have been proposed for renal arterial spin labelling (ASL) to quantify kidney cortex perfusion, including gradient echo based methods of balanced fast field echo (bFFE) and gradient-echo echo-planar imaging (GE-EPI), or spin echo based schemes of spin-echo echo planar imaging (SE-EPI) and turbo spin-echo (TSE). Here, we compare these imaging schemes to evaluate the optimal imaging scheme for pulsed ASL (PASL) assessment of human kidney cortex perfusion at 3 T. Methods: Ten healthy volunteers with normal renal function were scanned using each 2D multislice imaging scheme, in combination with a respiratory triggered FAIR (flow-sensitive alternating inversion recovery) ASL scheme on a 3 T Philips Achieva scanner. All volunteers returned for a second identical scan session within two weeks of the first scan session. Comparisons were made between the imaging schemes in terms of perfusion weighted image (PWI) signal-to-noise ratio (SNR) and perfusion quantification, temporal SNR (tSNR), spatial coverage, and repeatability. Results: For each imaging scheme, renal cortex perfusion was calculated (bFFE: 276 ± 29 mL/100 g/min, GE-EPI: 222 ± 18 mL/100 g/min, SE-EPI: 201 ± 36 mL/100 g/min, TSE: 200 ± 20 mL/100 g/min). Perfusion was found to be higher for GE based readouts compared to SE based readouts, with significantly higher measured perfusion for the bFFE readout compared to all other schemes (P < 0.05), attributed to the greater vascular signal present. Despite the PWI-SNR being significantly lower for SE-EPI compared to all other schemes (P < 0.05), the SE-EPI readout gave the highest tSNR and was found to be the most reproducible scheme for the assessment of kidney cortex, with a CoV of 17.2%, whilst minimizing variability of the perfusion weighted signal across slices for whole kidney perfusion assessment. Conclusion: For the assessment of kidney cortex perfusion, SE-EPI provides optimal tSNR, minimal variability across slices and repeatable data acquired in a short scan time with low specific absorption rate. 

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