Multimodal Brain MRI and Clinical Data in Olfactory Groove Meningioma: A Prospective Data Report

This dataset contains multimodal magnetic resonance imaging (MRI) and clinical data acquired prospectively from patients diagnosed with olfactory groove meningioma (OGM). Data were collected before and after surgical treatment using a standardized imaging and assessment protocol. The dataset is intended to support research in neuroimaging, neuro-oncology, and computational neuroscience, with a particular focus on tumor-related brain alterations, peritumoral edema effects, and postoperative recovery.
The dataset includes high-resolution structural MRI, diffusion MRI, resting-state functional MRI, and associated clinical and neuropsychological assessments.

Participants
* Diagnosis: OGM
* Study design: prospective, single-center
* Imaging time points: preoperative (folders labeled sub-**) and postoperative (folders labeled sub-**fu, when available)

Modalities included:

Structural MRI
* T1-weighted (pre- and post-contrast)
* T2-weighted

Diffusion MRI
* Multi-direction diffusion-weighted imaging (64 directions, b = 1500 s/mm²)
* Multiple b = 0 volumes with opposite phase-encoding directions for distortion correction

Functional MRI
* Resting-state BOLD fMRI (eyes closed)

Data organization

The dataset follows the BIDS standard and includes the following main directories:
* sub-*/anat/ – structural MRI data
* sub-*/dwi/ – raw diffusion MRI data
* sub-*/func/ – resting-state fMRI data
* derivatives/ – processed data outputs

Derivatives
The derivatives/ directory contains processed imaging data, including:
* Preprocessed diffusion MRI data corrected for susceptibility distortions and eddy currents (topup + eddy)
* Diffusion tensor–derived metrics: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and longitudinal/axial diffusivity (LD/AD)
* Tractography files derived from constrained spherical deconvolution (CSD)
* MRIQC output folder with both participant and group-level analyses

Preprocessing summary
* Structural MRI data were visually inspected and defaced for anonymization.
* Diffusion MRI data were corrected for susceptibility-induced distortions, eddy-current effects, and subject motion.
* Diffusion tensor fitting and constrained spherical deconvolution were performed using ExploreDTI.
* Quality control was conducted at multiple stages to ensure adequate data quality for reuse.

Potential reuse
This dataset may be reused for studies of tumor-related brain changes, diffusion MRI methodology tractography analyses in the presence of mass lesions, imaging biomarker development using multimodal MRI data.