Advancing frontiers in rheumatic and musculoskeletal imaging

Abstract

Tabotta et al. reported the improved diagnostic performance of SPECT/CT (87% sensitivity, 92% specificity) compared with that of bone scintigraphy in detecting prostate cancer bone metastases in 26 patients, thus highlighting the added value of the former to distinguish neoplastic locations from osteoarthritic changes [22]. [...]Wang et al. have nicely discussed about the attractive application of dual-energy CT to detect monosodium urate deposition in a rare pathologic condition of the spine, namely axial gout [9]. Harkey et al. used a semi-automated program to assess cumulative damage (tibio-femoral cartilage and bone marrow lesion) and disease activity (effusion-synovitis) of knee osteoarthritis using MRI [25]. [...]Aoki and Colleagues developed a fully automatic software to obtain a three-dimensional quantification of cartilage thickness/volume and meniscal extrusion reporting a relationship between medial tibial cartilage measurements and medial meniscus extrusion [27]. In keeping with artificial intelligence applications, the paper by Ishimoto et al. reported the potential application of a machine-learning automated system to accurately classify central lumbar spine stenosis using axial views of 4855 intervertebral levels taken from 971 lumbar spine MRI examinations [23].