The evaluation of bone marrow edema in sacroiliac joint in patients with ankylosing spondylitis using magnetic resonance imaging Dixon sequence.

Background: Bone marrow edema of the sacroiliac joint is the early imaging manifestation, an indicator of inflammatory activity of ankylosing spondylitis (AS) (Yang R, et. al. Medicine (Baltimore) 98:e14620, 2019).

Quantitative measurement of cartilage volume with automatic cartilage segmentation in knee osteoarthritis.

Purpose: To determine the reproducibility of the automatic cartilage segmentation method using a prototype KneeCaP software (version 1.3; Siemens Healthcare, Erlangen, Germany) and to compare the difference in cartilage volume (CV) between the normal knee joint and knee osteoarthritis (KOA) of different degrees by using the above software.

Materials And Methods: The study included 62 subjects with knee OA and 29 healthy control subjects.

Pulmonary invasive fungal disease and bacterial pneumonia: a comparative study with high-resolution CT.

Background: Early diagnosis of invasive fungal disease (IFD) is challenging. High-resolution computed tomography (CT) may improve IFD diagnosis; however, there are no definitive imaging signs for differentiating between bacterial pneumonia and IFD.

Methods: We retrospectively evaluated CT images of 208 patients with IFD (n = 102) or bacterial pneumonia (n = 106).

Association of radiomic imaging features and gene expression profile as prognostic factors in pancreatic ductal adenocarcinoma.

In this study, we investigated whether radiomic features of CT image data can accurately predict HMGA2 and C-MYC gene expression status and identify the patient survival time using a machine learning approach in pancreatic ductal adenocarcinoma (PDAC). A cohort of 111 patients with PDAC was enrolled in our study. Radiomic features were extracted using conventional (shape and texture analysis) and deep learning approaches following to segmentation of preoperative CT data.

Multi-parameter evaluation of lumbar intervertebral disc degeneration using quantitative magnetic resonance imaging techniques.

To quantitatively evaluate lumbar disc degeneration with recently-developed quantitative magnetic resonance imaging (MRI) techniques. A series of MRI parameters, including T2*, T1rho relaxation time, apparent diffusion coefficient and gagCEST, were compared and correlated with the Pfirrmann semi-quantitative classification of lumbar intervertebral disc degeneration; the most accurate and relevant MRI parameters of lumbar disc degeneration were identified. Thirty-seven subjects (age range, 18-74 years) with non-specific low back pain (LBP) for more than 6 months were enrolled.