Volumetric Classification: Unveiling the True Extent of Rotator Cuff Tears.

Introduction: Rotator cuff injury diagnosis involves comprehensive clinical, physical, and imaging assessments, with MRI being pivotal for detecting and classifying these injuries. However, the absence of a universally accepted classification system necessitates a more precise approach, advocating for the use of three-dimensional (3D) modeling to better understand and categorize rotator cuff tears.

Methodology: This research was conducted as a prospective, single-institution study on 62 patients exhibiting full-thickness rotator cuff tears. Utilizing preoperative 1.5T MRI, the study aimed to create a more detailed classification system based on volumetric and surface area measurements. Advanced 3D modeling software was employed to transform MRI data into precise 3D representations, facilitating a more accurate analysis of the lesions.

Results: The study unveiled a novel classification system rooted in volumetric and surface area assessments, revealing significant discrepancies in the existing two-dimensional classifications. Approximately 45% of the cases demonstrated inconsistencies between traditional classifications and 3D measurements. Notably, medium-sized lesions were often overestimated, while small and large lesions were consistently underestimated in their severity. The volumetric and surface area-based classifications provided a more accurate depiction, highlighting the limitations of relying solely on coronal plane assessments in MRI. Comparative analysis confirmed the improved accuracy of the 3D method.

Conclusion: The integration of 3D imaging and volumetric analysis offers novel advancement in diagnosing and classifying rotator cuff injuries. This study's findings challenge the conventional reliance on 2D MRI, proposing a more detailed and accurate classification system that enhances the precision of surgical planning and potentially improves patient outcomes. The incorporation of comprehensive 3D assessments into the diagnostic process represents a significant step forward in the orthopedic imaging field.