Multimodal model predicts screw loosening at user-specified postoperative time points after single-level lumbar interbody fusion.

PURPOSE: To develop a model that predicts screw loosening at user-specified postoperative time points after lumbar fusion. METHODS: We retrospectively enrolled patients who underwent single-level lumbar interbody fusion at five hospitals: three hospitals for training and two for external testing. Preoperative CT images, clinical characteristics, and postoperative follow-up CT images were collected. Many patients had multiple follow-up CT scans, with screw loosening evaluated for each. Multimodal models were developed using preoperative CT images and the day of the follow-up CT scans as inputs and the occurrence of screw loosening on that day as the label. Three types of preoperative CT images were prepared and used for training: original, whole vertebra, and vertebral body. The results were evaluated in testing, and the best model with the highest AUC among the three was selected. Additionally, clinical characteristics were incorporated as an additional input, and the result was also evaluated. RESULTS: A total of 212 patients (mean age, 66.5 ± 11.3, 123 male) with 552 follow-up CT scans were included: 412 follow-ups for training and validation, and 140 follow-ups for testing. The model using vertebral body showed the best performance, with an AUC of 0.823 (95% CI, 0.737-0.895) and a sensitivity of 0.914 (95% CI, 0.769-0.999). When clinical characteristics were added to the input, no improvement was observed, with an AUC of 0.721 (95% CI, 0.621-0.817). CONCLUSION: The model predicted screw loosening at any postoperative time point with high AUC and sensitivity and has the potential to enable more thorough patient management.