scholarly journals Using synthetic MR images for field map-less distortion correction

2021 ◽  
Author(s):  
David Florentino Montez ◽  
Andrew N. Van ◽  
Ryland L. Miller ◽  
Nicole A. Seider ◽  
Scott Marek ◽  
...  

Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) is highly distorted by magnetic field inhomogeneity. Distortion combined with underlying differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) structural images makes the alignment of functional and anatomical images a challenge. Typically, separately acquired field map data are used to correct fMRI distortions and a flexible cost function insensitive to cross-modal differences in image contrast and intensity is used for aligning fMRI and anatomical images. The quality of alignment achieved with this approach can vary greatly and depends on the availability and quality of field map data. To address this issue, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require separately acquired field map data. Synth combines information from T1w/T2w anatomical images to construct an idealized undistorted synthetic image that has similar contrast and intensity properties to fMRI data. The undistorted synthetic image then serves as an effective reference for individual-specific nonlinear unwarping to correct fMRI distortions. We demonstrate that Synth reliably outperforms other standard registration and distortion correction approaches that utilize field maps in both pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club) data. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.

2014 ◽  
Vol 40 (1) ◽  
pp. 120-126 ◽  
Author(s):  
Andrew B. Rosenkrantz ◽  
Hersh Chandarana ◽  
Josef Pfeuffer ◽  
Michael J. Triolo ◽  
Mohammed Bilal Shaikh ◽  
...  

2017 ◽  
Vol 79 (4) ◽  
pp. 2135-2141 ◽  
Author(s):  
Jack J. Miller ◽  
Angus Z. Lau ◽  
Damian J. Tyler

2019 ◽  
Author(s):  
Hyuntaek Oh ◽  
Jung Hwan Kim ◽  
Jeffrey M. Yau

AbstractTranscranial magnetic stimulation (TMS) can be paired with functional magnetic resonance imaging (fMRI) in simultaneous TMS-fMRI experiments. These multimodal experiments enable causal probing of network architecture in the human brain which can complement alternative network mapping approaches. Critically, merely introducing the TMS coil into the scanner environment can sometimes produce substantial magnetic field inhomogeneities and spatial distortions which limit the utility of simultaneous TMS-fMRI. We assessed the efficacy of point spread function corrected echo planar imaging (PSF-EPI) in correcting for the field inhomogeneities associated with a TMS coil at 3T. In phantom and brain scans, we quantitatively compared the coil-induced distortion artifacts measured in PSF-EPI scans to artifacts measured in conventional echo-planar imaging (EPI) and a simultaneous multi-slice sequence (SMS)-EPI. While we observed substantial coil-related artifacts in the data produced by the conventional EPI and SMS sequences, PSF-EPI produced data that had significantly greater signal-to-noise and less distortions. In phantom scans with the PSF-EPI sequence, we also characterized the temporal profile of dynamic artifacts associated with TMS delivery and found that image quality remained high as long as the TMS pulse preceded the RF excitation pulses by at least 50ms. Lastly, we validated the PSF-EPI sequence in human brain scans involving TMS and motor behavior as well as resting state fMRI scans. Our collective results demonstrate the superiority of PSF-EPI over conventional EPI and SMS sequences for simultaneous TMS-fMRI when coil-related artifacts are a concern. The ability to collect high quality resting state fMRI data in the same session as the simultaneous TMS-fMRI experiment offers a unique opportunity to interrogate network architecture in the human brain.


2020 ◽  
pp. 20200427
Author(s):  
Gabrielle C Baxter ◽  
Andrew J Patterson ◽  
Ramona Woitek ◽  
Iris Allajbeu ◽  
Martin J Graves ◽  
...  

Objective: To compare diffusion-weighted images (DWI) acquired using single-shot echo-planar imaging (ss-EPI) and multiplexed sensitivity encoding (MUSE) in breast cancer. Methods 20 females with pathologically confirmed breast cancer (age 51 ± 12 years) were imaged with ss-EPI-DWI and MUSE-DWI. ADC, normalised ADC (nADC), blur and distortion metrics and qualitative image quality scores were compared. The Crété-Roffet and Mattes mutual information metrics were used to evaluate blurring and distortion, respectively. In a breast phantom, six permutations of MUSE-DWI with varying parallel acceleration factor and number of shots were compared. Differences in ADC and nADC were compared using the coefficient of variation in the phantom and a paired t-test in patients. Differences in blur, distortion and qualitative metrics were analysed using a Wilcoxon signed-rank test. Results: There was a low coefficient of variation (<2%) in ADC between ss-EPI-DWI and all MUSE-DWI permutations acquired using the phantom. 22 malignant and three benign lesions were identified in 20 patients. ADC values measured using MUSE were significantly lower compared to ss-EPI for malignant but not benign lesions (p < 0.001, p = 0.21). nADC values were not significantly different (p = 0.62, p = 0.28). Blurring and distortion improved with number of shots and acceleration factor, and significantly improved with MUSE in patients (p < 0.001, p = 0.002). Qualitatively, image quality improved using MUSE. Conclusion: MUSE improves the image quality of breast DWI compared to ss-EPI. Advances in knowledge: MUSE-DWI has superior image quality and reduced blurring and distortion compared to ss-EPI-DWI in breast cancer.


2009 ◽  
Vol 61 (4) ◽  
pp. 994-1000 ◽  
Author(s):  
Iulius Dragonu ◽  
Baudouin Denis de Senneville ◽  
Bruno Quesson ◽  
Chrit Moonen ◽  
Mario Ries

2008 ◽  
Vol 59 (3) ◽  
pp. 598-606 ◽  
Author(s):  
Joseph W. Stevick ◽  
Sally G. Harding ◽  
Ulrich Paquet ◽  
Richard E. Ansorge ◽  
T. Adrian Carpenter ◽  
...  

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