Weightbearing CT-based predictive surgical planning for joint-sparing reconstruction of progressive collapsing foot deformity.

Abstract

Progressive Collapsing Foot Deformity (PCFD) is a complex multiplanar deformity commonly treated with osteotomy-based reconstruction in flexible cases. Although weightbearing CT (WBCT) has improved assessment of PCFD, WBCT-based predictive planning models remain unexplored. To evaluate the accuracy of a WBCT-based predictive surgical planning model in estimating postoperative alignment following reconstruction for flexible PCFD. Retrospective cohort study METHODS: Thirty-four patients with PCFD who underwent reconstruction with medial displacement calcaneal osteotomy, lateral column lengthening, and/or first-ray plantarflexion osteotomy and had preoperative and 3-month postoperative WBCT were included. The model estimated postoperative hindfoot moment arm (HMA), axial talus-first metatarsal angle (TFMA-A), talonavicular coverage angle (TNCA), and sagittal talus-first metatarsal angle (TFMA-S) using correction magnitudes. Predicted alignment was compared with postoperative WBCT measurements using Bland-Altman analysis, mean absolute error (MAE), root-mean-square error (RMSE), and paired t-tests. Predictive accuracy was highest for HMA, with a mean bias of +2.73 mm (p = 0.005), narrowest limits of agreement (-7.66 mm to +13.12 mm), and lowest MAE and RMSE values (approximately 2.9 mm and 3.7 mm). TFMA-A, TNCA, and TFMA-S demonstrated wider limits of agreement (approximately -17° to +21°) and greater case-level variability, although no significant systematic differences between predicted and postoperative values were observed (p = 0.21-0.90). A WBCT-based predictive surgical planning model estimated postoperative alignment accurately for hindfoot valgus correction, while predictions of midfoot/forefoot abduction and arch collapse demonstrated greater individual variability. Despite this variability, the model accurately reproduced mean multiplanar correction, supporting patient-specific surgical planning in PCFD.