Comparative Efficacy of Ultra-High-Resolution and Conventional Spiral Computed Tomography in the Diagnosis of Limb Fractures

Objective: To investigate the clinical value of ultra-high-resolution computed tomography (U-HRCT) in diagnosing extremity joint fractures and to compare its performance with that of multi-slice spiral computed tomography (MSCT). Methods: A prospective cohort study was conducted on 135 patients with suspected extremity joint fractures who presented to Nanjing Tongren Hospital between February 2024 and February 2026. All patients underwent sequential imaging using 16-slice MSCT and domestic U-HRCT systems. The gold standard for surgical results or follow-up CT/MRI at 2–4 weeks was used as a reference. We compared the detection rates, miss rates, incremental diagnostic yields, and image quality scores (assessed using a 5-point Likert scale) between the two modalities using subgroup analysis across different anatomical locations. Results: In total, 245 fractures were identified. MSCT identified 169 fractures, yielding a detection rate of 68.98% (169/245) and miss rate of 31.02%. Notably, U-HRCT detected 241 fractures, achieving a significantly higher detection rate of 98.37% (241/245) and a substantially lower miss rate of 1.63% (all P < 0.001). U-HRCT also identified 72 fractures missed by MSCT, including 28 intra-articular fractures (38.89%) and 25 avulsion fractures (34.72%), representing an incremental detection rate of 29.39%. The detection rates of U-HRCT for hand, wrist, elbow, ankle, and foot fractures were all significantly higher than those of MSCT. Image quality scores revealed that U-HRCT provided superior delineation of the cortical bone, trabecular microstructure, and articular surfaces compared with MSCT, with no false-positive cases observed. Conclusion: U-HRCT significantly improved the detection of extremity joint fractures, particularly subtle and occult lesions, effectively resolving the diagnostic uncertainties inherent in conventional MSCT. This provides a reliable imaging basis for precise fracture classification and informed surgical decision making.