Deep-learning for automated detection of MSU deposits on DECT: evaluating impact on efficiency and reader confidence

IntroductionDual-energy CT (DECT) is a non-invasive way to determine the presence of monosodium urate (MSU) crystals in the workup of gout. Color-coding distinguishes MSU from calcium following material decomposition and post-processing. Manually identifying these foci (most commonly labeled green) is tedious, and an automated detection system could streamline the process. This study aims to evaluate the impact of a deep-learning (DL) algorithm developed for detecting green pixelations on DECT on reader time, accuracy, and confidence.MethodsWe collected a sample of positive and negative DECTs, reviewed twice—once with and once without the DL tool—with a 2-week washout period. An attending musculoskeletal radiologist and a fellow separately reviewed the cases, simulating clinical workflow. Metrics such as time taken, confidence in diagnosis, and the tool's helpfulness were recorded and statistically analyzed.ResultsWe included thirty DECTs from different patients. The DL tool significantly reduced the reading time for the trainee radiologist (p = 0.02), but not for the attending radiologist (p = 0.15). Diagnostic confidence remained unchanged for both (p = 0.45). However, the DL model identified tiny MSU deposits that led to a change in diagnosis in two cases for the in-training radiologist and one case for the attending radiologist. In 3/3 of these cases, the diagnosis was correct when using DL.ConclusionsThe implementation of the developed DL model slightly reduced reading time for our less experienced reader and led to improved diagnostic accuracy. There was no statistically significant difference in diagnostic confidence when studies were interpreted without and with the DL model

Dual-Energy CT for Evaluation of Intra- and Extracapsular Silicone Implant Rupture

Silicone implants are commonly used for both breast augmentation and breast reconstruction. With aging of the implant, the silicone envelope may become weak or may rupture. The technique of choice for evaluation of implant integrity is breast MRI; however this may be contraindicated in some patients or the cost may be prohibitive. Dual-energy CT allows determination of density and atomic number of tissue and can provide material composition information. We present a case of extracapsular implant rupture with MRI and dual-energy CT imaging and surgical correlation

Multiple glomus tumors of the lower leg

Glomus tumors are rare, usually solitary lesions, most commonly presenting as a painful nodule in the subungual location of the digits. Glomus tumors have been reported in multiples and can be found in atypical locations, including the lower leg. We describe sonographic and magnetic resonance imaging (MRI) findings in a patient with multiple glomus tumors of the lower leg

Sonography of active rheumatoid arthritis during pregnancy: a case report and literature review

Disease activity in rheumatoid arthritis usually subsides in pregnancy, however a subset of patients have worsened symptoms with joint pain and swelling. Monitoring and mitigating disease activity in pregnancy is important for preventing deforming structural changes which can affect the ability of the patient to care for themselves and the newborn. Ultrasound is a safe and low-cost imaging modality for detecting active changes from an inflammatory arthritis, which can help guide management. We describe a case of an acute disease flare during pregnancy, readily detected with ultrasound, and present a review of sonographic evaluation of rheumatoid arthritis in pregnancy. Keywords: Rheumatoid arthritis, ultrasound, pregnancy, synoviti