Detection of Bone Marrow Edema in Patients with Osteoid Osteoma Using Three-Material Decomposition with Dual-Layer Spectral CT.
Florian Tilman GassertJohannes HammelFelix C HofmannJan NeumannClaudio E von SchackyFelix G GassertDaniela PfeifferFranz PfeifferMarcus R MakowskiKlaus WoertlerAlexandra S GersingBenedikt J SchwaigerPublished in: Diagnostics (Basel, Switzerland) (2021)
The aim of this study is to assess whether perifocal bone marrow edema (BME) in patients with osteoid osteoma (OO) can be accurately detected on dual-layer spectral CT (DLCT) with three-material decomposition. To that end, 18 patients with OO (25.33 ± 12.44 years; 7 females) were pairwise-matched with 18 patients (26.72 ± 9.65 years; 9 females) admitted for suspected pathologies other than OO in the same anatomic location but negative imaging findings. All patients were examined with DLCT and MRI. DLCT data was decomposed into hydroxyapatite and water- and fat-equivalent volume fraction maps. Two radiologists assessed DLCT-based volume fraction maps for the presence of perifocal BME, using a Likert scale (1 = no edema; 2 = likely no edema; 3 = likely edema; 4 = edema). Accuracy, sensitivity, and specificity for the detection of BME on DLCT were analyzed using MR findings as standard of reference. For the detection of BME in patients with OO, DLCT showed a sensitivity of 0.92, a specificity of 0.94, and an accuracy of 0.92 for both radiologists. Interreader agreement for the assessment of BME with DLCT was substantial (weighted κ = 0.78; 95% CI, 0.59, 0.94). DLCT with material-specific volume fraction maps allowed accurate detection of BME in patients with OO. This may spare patients additional examinations and facilitate the diagnosis of OO.
Keyphrases
- end stage renal disease
- bone marrow
- newly diagnosed
- chronic kidney disease
- ejection fraction
- computed tomography
- contrast enhanced
- peritoneal dialysis
- prognostic factors
- optical coherence tomography
- real time pcr
- positron emission tomography
- label free
- electronic health record
- big data
- image quality
- fatty acid
- patient reported
- pet ct