The RSNA Lumbar Degenerative Imaging Spine Classification (LumbarDISC) Dataset.

Area of Science:

• Radiology and Medical Imaging
• Orthopedics
• Data Science

Background:

• Degenerative spine disease is a significant cause of morbidity in adults.
• Access to large, diverse datasets is crucial for advancing diagnostic and therapeutic strategies.
• Existing public datasets for lumbar spine MRI in degenerative disease are limited.

Purpose of the Study:

• To introduce and describe the RSNA Lumbar Degenerative Imaging Spine Classification dataset.
• To provide a comprehensive resource for research into adult lumbar spine degenerative disease.
• To facilitate the development and validation of AI algorithms for spine imaging analysis.

Main Methods:

• Compilation of multisequence, multiplanar MRI scans from adult patients.
• Inclusion of data from 2,697 patients.
• Data sourced from 8 institutions across 6 countries and 5 continents.

Main Results:

• The dataset represents the largest publicly available collection of adult lumbar spine MRIs for degenerative disease.
• It offers diverse imaging sequences and planes.
• The dataset's global distribution ensures representation of varied patient populations.

Conclusions:

• The RSNA Lumbar Degenerative Imaging Spine Classification dataset is a valuable, large-scale resource for the scientific community.
• It is expected to accelerate research in lumbar spine degenerative diseases.
• The dataset will support advancements in medical imaging analysis and clinical decision-making.