RSNA Lumbar Spine Degenerative Classification AI Challenge (2024)
In collaboration with the American Society of Neuroradiology, the 2024 RSNA Lumbar Spine Degenerative Classification AI Challenge invited researchers to develop models that can detect and classify degenerative spine conditions using lumbar spine MR images. The carefully curated and annotated dataset includes images from more than eight sites across five continents.
The challenge, supported by Vision Radiology, attracted 1,874 teams from around the world—a new record for participation in an RSNA challenge.
Background
AI-driven detection tools have the potential to enhance the efficiency and accuracy of diagnostic radiology. To build these tools, AI researchers need access to substantial volumes of imaging data annotated by expert radiologists. Data challenges such as the RSNA Lumbar Spine Degenerative Classification AI Challenge engage the radiology community to develop such datasets, which provide the standard of truth in training AI systems to perform tasks relevant to diagnostic imaging.
According to the World Health Organization, low back pain is the leading cause of disability worldwide, affecting 619 million people in 2020, a 60% increase over 1990.
Most people experience low back pain at some point in their lives and its prevalence increases with age. Pain and restricted mobility are often symptoms of spondylosis. Spondylosis encompasses a set of degenerative spine conditions, including degeneration of vertebral discs and narrowing of the spinal canal (spinal stenosis), that exert pressure on nerves in the low back.
MRI provides a detailed view of the lumbar spine vertebra, discs and nerves, enabling radiologists to assess the presence and severity of these conditions. Proper diagnosis and grading of these conditions help guide treatment and potential surgery to help alleviate back pain and improve overall health and quality of life for patients.
The challenge focused on classifying and localizing three lumbar spine degenerative conditions: Neural Foraminal Narrowing, Subarticular Stenosis and Spinal Canal Stenosis.
Winning teams and entries
| Team Name | Solution |
|---|---|
| Avengers | Solution |
| IanPan-Kevin-Yuji-Bartley | Solution |
| SonySpine s & tkmm & Moyashii | Solution |
| SPINE CHART | Solution |
| Two people | Solution |
| NVSpine | Solution |
| HLIP | Solution |
| K_mataro | Solution |
| Adam Narai | Solution |
The Educational Merit Award is a distinction to recognize a winner from among the top nine teams whose entry is deemed outstanding in clarity, completeness, organization and efficiency of its submitted code. Two teams were selected for the 2024 Educational Merit Award: SonySpine s & tkmn & Moyashii Avengers.
Results
Access the challenge results on the Kaggle website.
Acknowledgments
RSNA would like to thank all those who made this challenge possible.
Recognition for winning teams
The nine teams who submitted the highest-scoring algorithms shared in $50,000 total prize money. The teams will be recognized at an event during RSNA 2024 (Dec.1–5, 2024).