scholarly journals Simultaneous perfusion and blood-oxygenation-level-dependent measurements using single-shot interleavedz-shim echo-planar imaging

2005 ◽  
Vol 53 (5) ◽  
pp. 1207-1211 ◽  
Author(s):  
Yihong Yang ◽  
Hong Gu ◽  
David A. Silbersweig ◽  
Emily Stern
Keyword(s):  
Blood Oxygenation Level Dependent ◽  
Echo Planar Imaging ◽  
Blood Oxygenation ◽  
Single Shot ◽  
Planar Imaging ◽  
Blood Oxygenation Level ◽  
Oxygenation Level ◽  
Echo Planar

scholarly journals Simultaneous Blood Oxygenation Level-Dependent and Cerebral Blood Flow Functional Magnetic Resonance Imaging during Forepaw Stimulation in the Rat

1999 ◽  
Vol 19 (8) ◽  
pp. 871-879 ◽  
Author(s):  
Afonso C. Silva ◽  
Sang-Pil Lee ◽  
Guang Yang ◽  
Costantino Iadecola ◽  
Seong-Gi Kim
Keyword(s):  
Correlation Coefficient ◽  
Cerebral Blood Volume ◽  
Blood Oxygenation Level Dependent ◽  
Blood Oxygenation ◽  
Single Shot ◽  
Bold Signal ◽  
Doppler Flowmetry ◽  
Blood Oxygenation Level ◽  
Oxygenation Level ◽  
Signal Changes

The blood oxygenation level-dependent (BOLD) contrast mechanism can be modeled as a complex interplay between CBF, cerebral blood volume (CBV), and CMRO2. Positive BOLD signal changes are presumably caused by CBF changes in excess of increases in CMRO2. Because this uncoupling between CBF and CMRO2 may not always be present, the magnitude of BOLD changes may not be a good index of CBF changes. In this study, the relation between BOLD and CBF was investigated further. Continuous arterial spin labeling was combined with a single-shot, multislice echo-planar imaging to enable simultaneous measurements of BOLD and CBF changes in a well-established model of functional brain activation, the electrical forepaw stimulation of a-chloralose-anesthetized rats. The paradigm consisted of two 18- to 30-second stimulation periods separated by a 1-minute resting interval. Stimulation parameters were optimized by laser Doppler flowmetry. For the same cross-correlation threshold, the BOLD and CBF active maps were centered within the size of one pixel (470 µm). However, the BOLD map was significantly larger than the CBF map. Measurements taken from 15 rats at 9.4 T using a 10-millisecond echo-time showed 3.7 ± 1.7% BOLD and 125.67 ± 81.7% CBF increases in the contralateral somatosensory cortex during the first stimulation, and 2.6 ± 1.2% BOLD and 79.3 ± 43.6% CBF increases during the second stimulation. The correlation coefficient between BOLD and CBF changes was 0.89. The overall temporal correlation coefficient between BOLD and CBF time-courses was 0.97. These results show that under the experimental conditions of the current study, the BOLD signal changes follow the changes in CBF.

Quantitative susceptibility mapping using single-shot echo-planar imaging

2014 ◽  
Vol 73 (5) ◽  
pp. 1932-1938 ◽  
Author(s):  
Hongfu Sun ◽  
Alan H. Wilman
Keyword(s):  
Echo Planar Imaging ◽  
Susceptibility Mapping ◽  
Single Shot ◽  
Planar Imaging ◽  
Quantitative Susceptibility Mapping ◽  
Echo Planar

scholarly journals Magnetic Resonance Fingerprinting with Combined Gradient- and Spin-echo Echo-planar Imaging: Simultaneous Estimation of T1, T2 and T2* with integrated-B1 Correction

2019 ◽  
Author(s):  
Mahdi Khajehim ◽  
Thomas Christen ◽  
J. Jean Chen
Keyword(s):  
Magnetic Resonance ◽  
Spin Echo ◽  
Echo Planar Imaging ◽  
Simultaneous Estimation ◽  
Single Shot ◽  
Planar Imaging ◽  
Reconstruction Process ◽  
Data Segment ◽  
T1 And T2 ◽  
Echo Planar

AbstractPurposeTo introduce a novel magnetic-resonance fingerprinting (MRF) framework with single-shot echo-planar imaging (EPI) readout to simultaneously estimate tissue T2, T1 and T2*, and integrate B1 correction.MethodsSpin-echo EPI is combined with gradient-echo EPI to achieve T2 estimation as well as T1 and T2* quantification. In the dictionary matching step, the GE-EPI data segment provides estimates of tissue T1 and T2* with additional B1 information, which are then incorporated into the T2-matching step that uses the SE-EPI data segment. In this way, biases in T2 and T2* estimates do not affect each other.ResultsAn excellent correspondence was found between our T1, T2, and T2* estimates and results obtained from standard approaches in both phantom and human scans. In the phantom scan, a linear relationship with R2>0.96 was found for all parameter estimates. The maximum error in the T2 estimate was found to be below 6%. In the in-vivo scan, similar contrast was noted between MRF and standard approaches, and values found in a small region of interest (ROI) located in the grey matter (GM) were in line with previous measurements (T2MRF=88±7ms vs T2Ref=89±11ms, T1MRF=1153±154ms vs T1Ref=1122±52ms, T2*MRF=56±4ms vs T2*Ref=53±3ms).ConclusionAdding a spin echo data segment to EPI based MRF allows accurate and robust measurements of T2, T1 and T2* relaxation times. This MRF framework is easier to implement than spiral-based MRF. It doesn’t suffer from undersampling artifacts and seems to require a smaller dictionary size that can fasten the reconstruction process.

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