Spinal Apophyses Localization in Discretized Models of Human Backs by Shape Index Analysis

• Published in: IEEE transactions on biomedical engineering 2024-11, Vol.71 (11), p.3252-3262
• Main Authors: Angelo, Luca Di, Stefano, Paolo Di, Guardiani, Emanuele, Morabito, Anna
• Format: Article
• Language: English
• Subjects: Adult; Algorithms; Anatomic Landmarks - diagnostic imaging; Back; Back - anatomy & histology; Back - diagnostic imaging; Back - physiology; Female; Humans; Imaging, Three-Dimensional - methods; Indexes; Male; Models, Anatomic; optical methods in medicine; Posture - physiology; Shape; shape index; Spinal apophyses recognition; Spine - anatomy & histology; Spine - diagnostic imaging; Spine - physiology; spine line; Surface morphology; Surface topography; Surface treatment; symmetry line; Three-dimensional displays; Young Adult
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2024.3414674

Objective: The paper proposes a non-invasive original methodology to directly and automatically identify the spine line from the external position of vertebral apophyses, which are key anatomical landmarks. Methods: Apophyses are detected directly on discrete high-density geometric models of human backs acquired by a 3D scanner. The methodology is inspired by the posturologist's approach that detects the spine line through the identification, by manual palpation, of the spinal apophyses. For this purpose, an appropriate shape index is used to identify vertebral positions. The shape index estimates the local differential geometric properties of the back surface. This index is very discriminating in locating both pronounced and blurred apophyses. To validate the method, the research involved the analysis of 21 healthy human backs acquired in both standing and asymmetric postures. For each of them, a skilled operator detected the spinal apophyses by tactile investigation and located them through cutaneous marking. Markers have been used as the reference for spinal apophyses' positions. Results: A comparison of the proposed approach with state-of-the-art methods has been conducted. This study evidences the high accuracy of the methodology proposed here and the capability to recognize also blurred apophyses. Conclusion: The method automatically performs the spine line identification and accurately locates apophyses along both vertical and coronal directions. Significance: The proposed inexpensive and easy-to-use approach significantly advances over other non-invasive methods. Its ability to detect the apophyses' location potentially offers new capabilities in detecting, diagnosing, and monitoring spinal disorders.