Emergency Breast Imaging, What Radiologists Need To Know

Awareness by the general radiologist of the various emergent conditions of the breast would enable a better management and appropriate referral, rather than postponing management till a breast radiologist is available for consultation. Early referrals are essential to prevent deterioration of complications including severe infection and even sepsis. There has been a lack of consensus in the past regarding appropriate management and delays in treatment have resulted in worse outcomes which could have been avoided.

Radiomics and Machine Learning Can Differentiate Transient Osteoporosis from Avascular Necrosis of the Hip

Differentiation between transient osteoporosis (TOH) and avascular necrosis (AVN) of the hip is a longstanding challenge in musculoskeletal radiology. The purpose of this study was to utilize MRI-based radiomics and machine learning (ML) for accurate differentiation between the two entities. A total of 109 hips with TOH and 104 hips with AVN were retrospectively included. Femoral heads and necks with segmented radiomics features were extracted. Three ML classifiers (XGboost, CatBoost and SVM) using 38 relevant radiomics features were trained on 70% and validated on 30% of the dataset. ML performance was compared to two musculoskeletal radiologists, a general radiologist and two radiology residents. XGboost achieved the best performance with an area under the curve (AUC) of 93.7% (95% CI from 87.7 to 99.8%) among ML models. MSK radiologists achieved an AUC of 90.6% (95% CI from 86.7% to 94.5%) and 88.3% (95% CI from 84% to 92.7%), respectively, similar to residents. The general radiologist achieved an AUC of 84.5% (95% CI from 80% to 89%), significantly lower than of XGboost (p = 0.017). In conclusion, radiomics-based ML achieved a performance similar to MSK radiologists and significantly higher compared to general radiologists in differentiating between TOH and AVN.

Duodenal imaging on the spotlight: from A to Z

Abdominal computed tomography (CT) is frequently performed to evaluate gastrointestinal pathologic conditions. The majority of the gastrointestinal radiology literature has concentrated on the colon, stomach, and distal small bowel. The duodenum is often overlooked on imaging, namely on CT, but its anatomy (intra and retroperitoneal) and location in such close proximity to other viscera results in involvement by a multitude of primary and secondary processes, some of them exclusive to this bowel segment. While some conditions, like duplications, lipomas, and diverticula, are usually asymptomatic and are incidentalomas that have no pathologic significance, others are symptomatic and very relevant and should be recognized by every general radiologist: development conditions such as annular pancreas and gut malrotation; inflammatory processes such as ulcers and secondary involvement from pancreatitis; neoplastic conditions such as adenocarcinoma, lymphoma, or local extension from adjacent malignancies. They all can be reliably diagnosed with CT. In this article, we demonstrate the typical imaging features of various diseases involving the duodenum, such as developmental, traumatic, inflammatory, infectious, neoplastic, and postsurgical pathologic conditions in alphabetical order, focusing mainly on upper gastrointestinal series (UGIS) and CT but also some radiography, ultrasound, and magnetic resonance (MR) imaging.