Brain lesion MRI and co-related MRS spectroscopy datasetMendeley Data

Analysing brain lesions of various aetiologies necessitates imaging data with subsequent diagnostic techniques that may enable concomitant visualization of spatial anatomical entities, and aberrant molecular behaviour. To fulfil this necessity, several image types and modalities should be collected....

Full description

Saved in:
Bibliographic Details
Main Authors: Sura Riyadh Saleh, Suhad A. Yousif, Israa Qader Ahmed
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Data in Brief
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340925000204
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Analysing brain lesions of various aetiologies necessitates imaging data with subsequent diagnostic techniques that may enable concomitant visualization of spatial anatomical entities, and aberrant molecular behaviour. To fulfil this necessity, several image types and modalities should be collected. This dataset includes MRI (Magnetic Resonance Imaging) with three modalities T2-FLAIR, T1-weighted pre- and post-contrast along with Magnetic Resonance Spectroscopy (MRS) scans for 55 patients. All patients were diagnosed with neoplastic and non-neoplastic brain lesions. T2-FLAIR and contrast-enhanced T1 MRI modalities reveal structural differences in lesions, whereas MRS affords metabolite information. In addition to the imaging data, patient metadata such as age, gender, and expert diagnosis- classify brain lesions into two types: neoplastic (low or high grade) and non-neoplastic. The data were collected between 2023 and 2024 at Al-Andalus Oncology Centre in Baghdad, Iraq, and are publicly available. This dataset is essential as it combines conventional (MRI) and metabolic (MRS) imaging with expert diagnosis information. This dataset is significant as it includes MRI and MRS images along with expert diagnoses information, offering high reuse potential in medical imaging and diagnostic research.
ISSN:2352-3409