To develop a semi-automated method to quantify inflammation in sacroiliac (SI) joints by measuring bone marrow edema (BME) on MRI. The SCAISS was designed as an image-processing software. Validation followed: (1) three readers evaluated SI images of 23 patients with axial SpA and various levels of BME severity with the SCAISS, and two non-automated methods, SPARCC and Berlin; (2) 20 readers evaluated 12 patients images, also with the three methods; (3) 203 readers evaluated 12 patient images with the Berlin and the SCAISS. Convergent validity, reliability and feasibility were estimated in the first two steps and reliability was confirmed with the third. The interobserver reliability (ICC and 95% CI) in the three observers' study was similar across methods: SCAISS = 0.770 (0.580-0.889); Berlin = 0.725 (0.537-0.860); and SPARCC = 0.824 (0.671-0.916). In the 20 observers' study, ICC was: SCAISS = 0.801 (0.653-0.927); Berlin = 0.702 (0.518-0.882); and SPARCC = 0.790 (0.623-0.923). In the 203 observers' study, ICC were: SCAISS = 0.810 (0.675-0.930), and Berlin = 0.636 (0.458-0.843). SCAISS showed good convergent validity (r with SPARCC = 0.760). Median time (interquartile range) employed in the reading procedure was 28 (27) seconds for the SCAISS, 14 (9) for the Berlin score, and 94 (68) for the SPARCC. The SCAISS permits a valid, reliable, and fast calculation of overall BME lesion at the SI joint on MRI images not dependent on readers' experience.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s00296-018-4104-3 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Automated classification of coronary LEsions fRom coronary computed Tomography angiography scans with an updated deep learning model: ALERT study.
Eur Radiol
January 2025
Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
Objectives: The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagnostic performance of a recently updated deep learning model (CorEx-2.0) for quantifying coronary stenosis, compared separately with two expert CCTA readers as references.
View Article and Find Full Text PDFDiagnostic Performance of O-RADS US (Version 2019 and Version 2022) Incorporating Acoustic Shadowing by Junior Radiologists: Analyzing 1061 Adnexal Masses.
J Ultrasound Med
January 2025
Department of Ultrasonic Medicine, Fetal Medical Centre, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Introduction: Acoustic shadowing is an important benign ultrasound (US) feature for adnexal masses (AMs). To validate the diagnostic performance and interobserver agreement of the 2019 version and 2022 version of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) and ascertain whether adding acoustic shadowing to O-RADS US v2019 as a benign ultrasound feature can enhance its diagnostic efficacy among junior radiologist.
Methods: This retrospective study included consecutive women with suspected adnexal masses who underwent ultrasound examinations between September 2022 and January 2024.
Quantitative fluorescent nanoparticle tracking analysis and nano-flow cytometry enable advanced characterization of single extracellular vesicles.
J Extracell Biol
January 2025
RoseBio Milano Italy.
Current state-of-the-art tools for analysing extracellular vesicles (EVs) offer either highly sensitive but unidimensional bulk measurements of EV components, or high-resolution multiparametric single-particle analyses which lack standardization and appropriate reference materials. This limits the accuracy of the assessment of marker abundance and overall marker distribution amongst individual EVs, and finally, the understanding of true EV heterogeneity. In this study, we aimed to define the standardized operating procedures and reference material for fluorescent characterization of EVs with two commonly used EV analytical platforms-nanoparticle tracking analysis (NTA) and nano-flow cytometry (nFCM).
View Article and Find Full Text PDFDeep learning model for automatic detection of different types of microaneurysms in diabetic retinopathy.
Eye (Lond)
January 2025
Department of Surgical Sciences, University of Turin, Turin, Italy.
Purpose: This study aims to develop a deep-learning-based software capable of detecting and differentiating microaneurysms (MAs) as hyporeflective or hyperreflective on structural optical coherence tomography (OCT) images in patients with non-proliferative diabetic retinopathy (NPDR).
Methods: A retrospective cohort of 249 patients (498 eyes) diagnosed with NPDR was analysed. Structural OCT scans were obtained using the Heidelberg Spectralis HRA + OCT device.
The application of radiomics in cancer imaging with a focus on lung cancer, renal cell carcinoma, gastrointestinal cancer, and head and neck cancer: A systematic review.
Phys Med
January 2025
Division of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale, IRCCS di Napoli, 80131 Naples, Italy.
Purpose: To study the application of radiomics in cancer imaging with a focus on lung cancer, renal cell carcinoma, gastrointestinal cancer, and head and neck cancer.
Methods: Different electronic databases were considered. Articles published in the last five years were analyzed (January 2019 and December 2023).
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!