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OpenNeuro dataset - The Impact and Reliability of Tissue Segmentation on In Vivo Magnetic Resonance Spectroscopy Metabolite Quantification

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# The Impact and Reliability of Tissue Segmentation on In Vivo Magnetic Resonance Spectroscopy Metabolite Quantification

Contact: [mam4041@med.cornell.edu](mailto:mam4041@med.cornell.edu)

## Overview

These data were collected as part of a study to assess the test-retest reliability of multi-metabolite edited MRS editing schemes and the [sLASER](https://doi.org/10.1002/mrm.21302) localization approach.
The resulting dataset was also used to evaluate the impact of anatomical segmentation on estimated metabolite concentrations.

Data types included are defaced *T*<sub>1</sub>-weighted 3D structural MRI images and sLASER data.

## Methods

### Subjects

Sixteen healthy adults (10 females, 6 males, mean age = 38.4 years).

### MR protocol

MR data were acquired using a 3T GE Discovery MR750 MRI scanner using a <sup>1</sup>H 32-channel RF phased-array head coil for receive and a body coil for transmit.

#### MRI

*T*<sub>1</sub>-weighted FSPGR BRAVO structural MRI acquisition parameters:

- Voxel resolution = 0.9 × 0.9 × 1.5 mm<sup>3</sup>
- TE/TR/TI (ms) = 5.2/12.2/725
- Flip angle = 7°
- Slices = 124
- FOV = 256 × 256 mm<sup>2</sup>
- Matrix size = 256 × 256
- Parallel acquisition technique: GRAPPA
- Parallel acquisition factor: 2

#### MRS

General MRS acquisition parameters:

- Volume of interest = medial parietal lobe
- Voxel resolution = 30 × 30 × 30 mm<sup>3</sup>
- Spectral width = 5000 Hz
- Number of points = 4096

##### sLASER

- TE/TR = 35/2000 ms
- Number of transients = 64

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OpenNeuro dataset - The Impact and Reliability of Tissue Segmentation on In Vivo Magnetic Resonance Spectroscopy Metabolite Quantification

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