Abstract
To evaluate prospectively the performance of noncalcium images reconstructed from dual-energy (DE) computed tomography (CT) for the diagnosis of bone marrow lesions in patients with acute ankle joint trauma in comparison with magnetic resonance (MR) images. The study had local ethics board approval, and written informed consent was obtained. Thirty consecutive patients (15 women; mean age, 34 years±11.8 [standard deviation]) underwent dual-source DE CT (80 kVp and 140 kVp with tin filter) and MR imaging within 1 day following acute ankle trauma. DE CT data were postprocessed by using a three-material decomposition algorithm for generating noncalcium images. MR and noncalcium images were graded by two blinded, independent readers using a four-point system (1=distinct bone marrow lesion, 4=no lesion); CT numbers in noncalcium images were calculated by a third reader. MR imaging interpretations served as the reference standard. Interreader agreement for qualitative grading of DE CT images was substantial (κ=0.66). The respective sensitivity, specificity, positive predictive value, and negative predictive value of DE CT for depicting distinct bone marrow lesions for both readers were 90.0% each, 80.5% and 81.6%, 25.4% and 26.5%, and 99.1% each. In regions without abnormality, CT numbers in noncalcium images gradually increased from proximal to distal location (P<.001). Significant differences in CT numbers were found in regions positive for bone marrow lesions compared with those that were negative (P<.001). CT numbers for the diagnosis of distinct bone marrow lesions according to MR imaging revealed areas under the receiver operating characteristic curve of 0.973, 0.813, and 0.758 for ankle mortise, talar dome, and talar body/head, respectively. Compared with MR images, distinct traumatic bone marrow lesions of the ankle joint can be diagnosed on noncalcium images reconstructed from DE CT with high sensitivity and excellent negative predictive value, but with moderate specificity and low positive predictive value.
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