The Course of Nasolabial Angle Loss After Rhinoplasty and Prediction of Late Outcome Using Machine Learning: A Proof-of-Concept Study

Background/Objectives: The primary objective of this study was to predict the absolute nasolabial angle (NLA) at postoperative month 12 using early postoperative measurements. Secondary objectives were to characterize longitudinal NLA changes through month 12 and quantify residual angle loss.

Methods

This single-center retrospective cohort study included 78 patients who underwent primary open rhinoplasty and had complete standardized lateral photographs from the preoperative assessment and postoperative months 1, 3, 6, and 12. The absolute NLA at month 12 was designated as the primary outcome and prediction target. Longitudinal NLA changes and residual loss from months 1, 3, and 6 to month 12 were secondary outcomes. NLA was measured using a Python (version 3.12.13)/OpenCV-based semi-automatic image-analysis system. Intraobserver and interobserver reliability were evaluated in a stratified random sample of 40 images measured twice by two physicians using intraclass correlation coefficients and Bland–Altman analysis. Linear and machine-learning models were evaluated using repeated nested cross-validation. Three simple benchmarks were also assessed using identical patient-level outer splits: the training-fold mean, persistence (NLA12 = NLA6), and linear regression using NLA6 alone.