Cinematic rendering improves the AO/OTA classification of distal femur fractures compared to volume rendering: a retrospective single-center study

Front Bioeng Biotechnol. 2024 Jan 8:11:1335759. doi: 10.3389/fbioe.2023.1335759. eCollection 2023.

Abstract

Purpose: Correctly classifying distal femur fractures is essential for surgical treatment planning and patient prognosis. This study assesses the potential of Cinematic Rendering (CR) in classifying these fractures, emphasizing its reported ability to produce more realistic images than Volume Rendering (VR). Methods: Data from 88 consecutive patients with distal femoral fractures collected between July 2013 and July 2020 were included. Two orthopedic surgeons independently evaluated the fractures using CR and VR. The inter-rater and intra-rater agreement was evaluated by using the Cicchetti-Allison weighted Kappa method. Accuracy, precision, recall, and F1 score were also calculated. Diagnostic confidence scores (DCSs) for both imaging methods were compared using chi-square or Fisher's exact tests. Results: CR reconstruction yielded excellent inter-observer (Kappa = 0.989) and intra-observer (Kappa = 0.992) agreement, outperforming VR (Kappa = 0.941 and 0.905, respectively). While metrics like accuracy, precision, recall, and F1 scores were higher for CR, the difference was not statistically significant (p > 0.05). However, DCAs significantly favored CR (p < 0.05). Conclusion: CR offers a superior visualization of distal femur fractures than VR. It enhances fracture classification accuracy and bolsters diagnostic confidence. The high inter- and intra-observer agreement underscores its reliability, suggesting its potential clinical importance.

Keywords: AO/OTA classification; cinematic rendering; diagnostic confidence; distal femur fracture; volume rendering.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Medical and Healthcare Talent Research Initiation Fund Category G (KYQD 2022-30); and the Science and Technology Programme of Quzhou, Zhejiang Province, China (2023K111).