Dual-energy CT-generated bone marrow edema maps improve reader confidence without changing fracture detection rates in bony pelvis trauma.

Authors

Boniface Yarabe, William R Walter, Shana G Neumann, Hyung G Park, Meghan Jardon

Published in

Skeletal radiology. Aug 28, 2026. Epub Aug 28, 2026.

Abstract

To retrospectively evaluate the diagnostic utility of dual-energy computed tomography (DECT) virtual non-calcium bone marrow edema (BME) maps in the assessment of osseous pelvic trauma compared to conventional CT. In addition to fracture detection rates, we sought to determine the DECT effect on reader diagnostic confidence and follow-up recommendations.
Three radiologists performed independent retrospective reviews of 92 consecutive pelvic CTs for the presence of fractures, without the use of DECT-generated BME maps. Following a washout period of ≥ 4 weeks, the cases were re-reviewed with the addition of DECT BME maps. Comparison of fracture detection rates, frequency of "indeterminate" reads, reader confidence ratings, and follow-up imaging recommendations were performed using McNemar's test and mixed-effects logistic regressions. Mixed-effect models were utilized to assess the effect of DEXA-derived patient bone mineral density, when available, on fracture detection rates.
The use of DECT BME maps resulted in higher pooled reader diagnostic confidence, with a mean 0.19 increase on a 5-point Likert scale (p < 0.001). There was, however, no statistically significant difference in fracture detection rates for readers utilizing DECT versus conventional CT alone, with similar rates of "indeterminate" interpretations between the groups. For patients with recent DEXAs (n = 27), DECT was not associated with change in fracture detection rates among patients with osteoporosis or osteopenia. Readers recommended follow-up imaging more frequently in cases interpreted with DECT, but this effect was not significant (p = 0.266).
When interpreting pelvic CT for trauma, DECT-generated BME maps increased diagnostic confidence without changing detection rates.

PMID:
42665718
Bibliographic data and abstract were imported from PubMed on 29 Aug 2026.

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