Journal
JOURNAL OF ORTHOPAEDIC RESEARCH
Volume 40, Issue 12, Pages 2914-2923Publisher
WILEY
DOI: 10.1002/jor.25303
Keywords
automated magnetic resonance image segmentation; Kambin's triangle; spinal structures; three-dimensional reconstruction
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Funding
- National Natural Science Foundation of China [ZH0406190031PWC, 62001207]
- Zhuhai City Innovation and Innovation Team Project, Guangdong Province, China
- China Postdoctoral Science Foundation [2020M672712]
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This study developed a new method for 3D reconstruction of Kambin's triangle using automated MRI segmentation. The method showed good performance in segmenting lumbar spinal structures and evaluating anatomical performance.
The three-dimensional (3D) anatomy of Kambin's triangle is crucial for surgical planning in minimally invasive spine surgery via the transforaminal approach. Few pieces of research have, however, used image segmentation to explore the 3D reconstruction of Kambin's triangle. This study aimed to develop a new method of 3D reconstruction of Kambin's triangle based on automated magnetic resonance image (MRI) segmentation of the lumbar spinal structures. An experienced (>5 years) ground truth spinal pain physician meticulously segmented and labeled spinal structures (e.g., bones, dura mater, discs, and nerve roots) on MRI. Subsequently, a 3D U-Net algorithm was developed for automatically segmenting lumbar spinal structures for the 3D reconstruction of Kambin's triangle. The Dice similarity coefficient (DSC), precision, recall, and the area of Kambin's triangle were used to assess anatomical performance. The automatic segmentation of all spinal structures at the L4/L5 levels and L5/S1 levels resulted in good performance: DSC = 0.878/0.883, precision = 0.889/0.890, recall = 0.873/0.882. Furthermore, the area measurements of Kambin's triangle revealed no significant difference between ground truth and automatic segmentation (p = 0.333 at the L4/L5 level, p = 0.302 at the L5/S1 level). The 3D U-Net model used in this study performed well in terms of simultaneous segmentation of multi-class spinal structures (including bones, dura mater, discs, and nerve roots) on MRI, allowing for accurate 3D reconstruction of Kambin's triangle.
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