JOURNAL ARTICLE

Distinguishing Untreated Osteoblastic Metastases From Enostoses Using CT Attenuation Measurements

Adam Ulano, Miriam A Bredella, Patrick Burke, Ivan Chebib, F Joseph Simeone, Ambrose J Huang, Martin Torriani, Connie Y Chang
AJR. American Journal of Roentgenology 2016, 207 (2): 362-8
27101076

OBJECTIVE: The purpose of this study was to determine whether CT attenuation thresholds can be used to distinguish untreated osteoblastic metastases from enostoses.

MATERIALS AND METHODS: The study group comprised 62 patients with 279 sclerotic bone lesions found at CT (126 enostoses in 37 patients and 153 metastases in 25 patients). The cause of sclerotic lesions was assessed histologically or by clinical and imaging follow-up. None of the patients had undergone prior treatment for the metastases. The mean and maximum attenuation were measured in Hounsfield units. ROC analysis was performed to determine sensitivity, specificity, AUC, 95% CIs, and cutoff values of CT attenuation to differentiate metastases from enostoses. Interreader reproducibility was assessed using an intraclass correlation coefficient with 95% CI.

RESULTS: The mean and maximum CT attenuation values of enostoses were 1190 ± 239 HU and 1323 ± 234 HU, respectively, and those of osteoblastic metastases were 654 ± 176 HU and 787 ± 194 HU, respectively. Using a cutoff of 885 HU for mean attenuation, the AUC was 0.982, sensitivity was 95%, and specificity was 96%. Using a cutoff of 1060 HU for maximum CT attenuation, the AUC was 0.976, sensitivity was 95%, and specificity was 96%. The mean attenuation intraclass correlation coefficient was 0.987 for enostoses and 0.81 for metastases. The maximum attenuation intraclass correlation coefficient was 0.814 for enostoses and 0.980 for metastases.

CONCLUSION: CT attenuation measurements can be used to distinguish untreated osteoblastic metastases from enostoses. A mean attenuation of 885 HU and a maximum attenuation of 1060 HU provide reliable thresholds below which a metastatic lesion is the favored diagnosis.

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