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Dual-energy computed tomography for the detection of sacroiliac joints bone marrow oedema in patients with axial spondyloarthritis


1, 2, 3, 4, 5, 6, 7, 8

 

  1. Radiology Clinic, Dipartimento di Scienze Cliniche Specialistiche e Odontostomatologiche, Università Politecnica delle Marche, Ancona, Italy.
  2. Medical Clinic, Dipartimento Scienze Cliniche e Molecolari, Università Politecnica delle Marche, Ancona, Italy.
  3. Rheumatology Clinic, Dipartimento di Scienze Cliniche e Molecolari, Università Politecnica delle Marche, Ancona, Italy. dica.marco@yahoo.it
  4. Rheumatology Clinic, Dipartimento di Scienze Cliniche e Molecolari, Università Politecnica delle Marche, Ancona, Italy.
  5. Medical Clinic, Dipartimento Scienze Cliniche e Molecolari, Università Politecnica delle Marche, Ancona, Italy.
  6. Radiology Clinic, Dipartimento di Scienze Cliniche Specialistiche e Odontostomatologiche, Università Politecnica delle Marche, Ancona, Italy.
  7. Radiology Clinic, Dipartimento di Scienze Cliniche Specialistiche e Odontostomatologiche, Università Politecnica delle Marche, Ancona, Italy.
  8. Rheumatology Clinic, Dipartimento di Scienze Cliniche e Molecolari, Università Politecnica delle Marche, Ancona, Italy.

CER13670
2021 Vol.39, N°6
PI 1316, PF 1323
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PMID: 33427625 [PubMed]

Received: 07/06/2020
Accepted : 27/10/2020
In Press: 07/01/2021
Published: 25/11/2021

Abstract

OBJECTIVES:
To investigate the diagnostic performance of dual-energy computed tomography (DECT) in detection bone marrow oedema (BME) in patients with sacroiliitis associated with axial spondyloarthritis (axial SpA).
METHODS:
Patients with axial SpA according to the ASAS criteria underwent DECT and 1.5-T magnetic resonance imaging (MRI). DECT was post-processed for generating virtual non-calcium (VNCa) images. The presence of abnormal bone marrow attenuation was scored on DECT VNCa images and MRI using a four-point classification system: 0-1 = absent or non-significant oedema, 2 = oedema present in a third of the articular surface, 3 = oedema present in 2/3 of the articular surface, 4 = diffuse oedema throughout the articular surface. Diagnostic accuracy values for BME were calculated for DECT images (quantitative assessment) by using receiver operating characteristic (ROC) curves analysis, applying MRI as gold standard.
RESULTS:
Eighty sacroiliac joints from 40 axial SpA patients were included for study analysis, and 36 sacroiliac joints (45%) were classified as having BME at MRI and compared to DECT. Sensitivity, specificity, and positive likelihood ratio (LR+) in the identification of BME at DECT were 90.0%, 92.8%, and 12.6 respectively. Negative LR was 0.11, positive predictive value 93.1%, and negative predictive value 89.7%. The area under the curve (AUC) was 0.953 in the differentiation of the presence of BME. A cut-off value of -1.6 HU (Youden’s index = 0.828) yielded a sensitivity of 90.0% and specificity of 92.8%, with an LR+ of 12.6, in the detection of BME in the sacroiliac joints.
CONCLUSIONS:
DECT VNCa images had good diagnostic performance in the evaluation of the extent of BME in patients with sacroiliitis associated with axial SpA.

Rheumatology Article