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Suchandrima Banerjee

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4 papers

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YNIMG Journal 2022 Journal Article

A geometric view of signal sensitivity metrics in multi-echo fMRI

Thomas T. Liu
Bochao Li
Brice Fernandez
Suchandrima Banerjee

In multi-echo fMRI (ME-fMRI), two metrics have been widely used to measure the performance of various acquisition and analysis approaches. These are temporal SNR (tSNR) and differential contrast-to-noise ratio (dCNR). A key step in ME-fMRI is the weighted combination of the data from multiple echoes, and prior work has examined the dependence of tSNR and dCNR on the choice of weights. However, most studies have focused on only one of these two metrics, and the relationship between the two metrics has not been examined. In this work, we present a geometric view that offers greater insight into the relation between the two metrics and their weight dependence. We identify three major regimes: (1) a tSNR robust regime in which tSNR is robust to the weight selection with most weight variants achieving close to optimal performance, whereas dCNR shows a pronounced dependence on the weights with most variants achieving suboptimal performance; (2) a dCNR robust regime in which dCNR is robust to the weight selection with most weight variants achieving close to optimal performance, while tSNR exhibits a strong dependence on the weights with most variants achieving significantly lower than optimal performance; and (3) a within-type robust regime in which both tSNR and dCNR achieve nearly optimal performance when the form of the weights are variants of their respective optimal weights and exhibit a moderate decrease in performance for other weight variants. Insight into the behavior observed in the different regimes is gained by considering spherical representations of the weight dependence of the components used to form each metric. For multi-echo acquisitions, dCNR is shown to be more directly related than tSNR to measures of CNR and signal-to-noise ratio (SNR) for task-based and resting-state fMRI scans, respectively.

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YNIMG Journal 2022 Journal Article

Rigid real-time prospective motion-corrected three-dimensional multiparametric mapping of the human brain

Shohei Fujita
Akifumi Hagiwara
Naoyuki Takei
Issei Fukunaga
Yasuhiro Hagiwara
Takashi Ogawa
Taku Hatano
Dan Rettmann

PURPOSE: To develop a rigid real-time prospective motion-corrected multiparametric mapping technique and to test the performance of quantitative estimates. METHODS: Motion tracking and correction were performed by integrating single-shot spiral navigators into a multiparametric imaging technique, three-dimensional quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS). The spiral navigator was optimized, and quantitative measurements were validated using a standard system phantom. The effect of motion correction on whole-brain T1 and T2 mapping under different types of head motion during the scan was evaluated in 10 healthy volunteers. Finally, six patients with Parkinson's disease, which is known to be associated with a high prevalence of motion artifacts, were scanned to evaluate the effectiveness of our method in the real world. RESULTS: The phantom study demonstrated that the proposed motion correction method did not introduce quantitative bias. Improved parametric map quality and repeatability were shown in volunteer experiments with both in-plane and through-plane motions, comparable to the no-motion ground truth. In real-life validation in patients, the approach showed improved parametric map quality compared to images obtained without motion correction. CONCLUSIONS: Real-time prospective motion-corrected multiparametric relaxometry based on 3D-QALAS provided robust and repeatable whole-brain multiparametric mapping.

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YNIMG Journal 2021 Journal Article

Improved resting state functional connectivity sensitivity and reproducibility using a multiband multi-echo acquisition

Alexander D. Cohen
Baolian Yang
Brice Fernandez
Suchandrima Banerjee
Yang Wang

Recent advances in functional MRI techniques include multiband (MB) imaging and multi-echo (ME) imaging. In MB imaging multiple slices are acquired simultaneously leading to significant increases in temporal and spatial resolution. Multi-echo imaging enables multiple echoes to be acquired in one shot, where the ME images can be used to denoise the BOLD time series and increase BOLD sensitivity. In this study, resting state fMRI (rs-fMRI) data were collected using a combined MBME sequence and compared to an MB single echo sequence. In total, 29 subjects were imaged, and 18 of them returned within two weeks for repeat imaging. Participants underwent one MBME scan with three echoes and one MB scan with one echo. Both datasets were processed using standard denoising and advanced denoising. Advanced denoising included multi-echo independent component analysis (ME-ICA) for the MBME data and ICA-AROMA for the MB data. Resting state functional connectivity (RSFC) was evaluated using both selective seed-based and whole grey matter (GM) region-of-interest (ROI) based approaches. The reproducibility of connectivity metrics was also analyzed in the repeat subjects. In addition, functional connectivity density (FCD), a data-driven approach that counts the number of significant connections, both within a local cluster and globally, with each voxel was analyzed. Regardless of the standard or advanced denoising technique, all seed-based RSFC was significantly higher for MBME compared to MB. Much more GM ROI combinations showed significantly higher RSFC for MBME vs. MB. Reproducibility, evaluated using the dice coefficient was significantly higher for MBME relative to MB data. Finally, FCD was also higher for MBME vs. MB data. This study showed higher RSFC for MBME vs. MB data using selected seed-based, whole GM ROI-based, and data-driven approaches. Reproducibility found also higher for MBME data. Taken together, these results indicate that MBME is a promising technique for rs-fMRI.

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YNICL Journal 2015 Journal Article

Clinically feasible NODDI characterization of glioma using multiband EPI at 7 T

Qiuting Wen
Douglas A.C. Kelley
Suchandrima Banerjee
Janine M. Lupo
Susan M. Chang
Duan Xu
Christopher P. Hess
Sarah J. Nelson

Recent technological progress in the multiband echo planer imaging (MB EPI) technique enables accelerated MR diffusion weighted imaging (DWI) and allows whole brain, multi-b-value diffusion imaging to be acquired within a clinically feasible time. However, its applications at 7 T have been limited due to B1 field inhomogeneity and increased susceptibility artifact. It is an ongoing debate whether DWI at 7 T can be performed properly in patients, and a systematic SNR comparison for multiband spin-echo EPI between 3 T and 7 T has not been methodically studied. The goal of this study was to use MB EPI at 7 T in order to obtain 90-directional multi-shell DWI within a clinically feasible acquisition time for patients with glioma. This study included an SNR comparison between 3 T and 7 T, and the application of B1 mapping and distortion correction procedures for reducing the impact of variations in B0 and B1. The optimized multiband sequence was applied in 20 patients with glioma to generate both DTI and NODDI maps for comparison of values in tumor and normal appearing white matter (NAWM). Our SNR analysis showed that MB EPI at 7 T was comparable to that at 3 T, and the data quality acquired in patients was clinically acceptable. NODDI maps provided unique contrast within the T2 lesion that was not seen in anatomical images or DTI maps. Such contrast may reflect the complexity of tissue compositions associated with disease progression and treatment effects. The ability to consistently obtain high quality diffusion data at 7 T will contribute towards the implementation of a comprehensive brain MRI examination at ultra-high field.

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