APPA-defined pelvic state and iliac tilt-based estimation of pelvic tilt in a large standing radiographic cohort.

Abstract

BackgroundPelvic tilt (PT) is a key spinopelvic parameter, but direct measurement may be limited on routine lateral radiographs when the femoral heads are obscured. Anterior pelvic plane angle (APPA) and iliac tilt (IT) may serve as alternative descriptors of pelvic orientation, but the optimal IT-derived metric for estimating PT remains unclear.MethodsWe retrospectively reviewed 977 consecutive individuals who underwent standardized standing lateral whole-spine radiography between February 2024 and November 2025. Only radiographs without radiographically evident structural spinal pathology and with directly measurable PT were included. Pelvic state was classified by APPA. Candidate IT measurements, including superior iliac tilt (ITS), inferior iliac tilt (ITI), and mean iliac tilt (ITM), were compared in terms of measurability, reliability, and estimation error. Linear regression models were then developed to estimate PT from ITM and internally validated using 10-fold cross-validation.ResultsOf the 977 individuals, 660 (67.6%) showed pelvic retroversion, 311 (31.8%) anteversion, and 6 (0.6%) a neutral state. APPA-defined retroversion was more frequently observed in older age groups, reaching 85.7% in participants aged ≥70 years. ITM provided the most favorable overall performance, with 94.2% measurability, high reproducibility, the lowest mean absolute error (3.17°), and the narrowest 95% limits of agreement (-8.21° to 8.21°). PT correlated most strongly with ITM (<i>r</i> = 0.87, <i>P</i> < 0.001). The model incorporating ITM, age, and sex showed the best internally validated performance (<i>R</i>² = 0.79, RMSE = 3.91°, MAE = 3.01°).ConclusionsIn this cohort with directly measurable PT, APPA-defined retroversion was more frequent in older age groups. ITM may provide an approximate PT estimate when direct PT measurement is limited, but further validation is needed in PT-nonmeasurable radiographs.