Cross-Sectional Imaging of Nontraumatic Peritoneal and Mesenteric Emergencies

Multiple nontraumatic peritoneal and mesenteric emergencies are encountered at imaging of patients in the emergency department. Peritoneal and mesenteric emergencies are usually detected in patients in the emergency department during evaluation of nonspecific abdominal pain. A high index of suspicion is required for the establishment of early diagnosis and aversion of life-threatening complications in cases of peritoneal carcinomatosis, nontraumatic hemoperitoneum, and peritonitis. A correct diagnosis of omental infarction, mesenteric adenitis, and mesenteric panniculitis helps patients primarily by avoiding unnecessary surgery. In this review article, we illustrate the cross-sectional imaging appearance of various nontraumatic peritoneal and mesenteric emergencies by emphasizing the role of the emergency radiologist in detecting and managing these entities

Analysis of the correlations between the severity of lung involvement and olfactory psychophysical scores in coronavirus disease 2019 (COVID-19) patients

Interstitial pneumonia is an important complication of COVID-19 and a reliable negative prognostic factor. This study aimed to analyze the correlation between olfactory psychophysical scores and severity of lung involvement detected by chest computed tomography in COVID-19 patients suspected of having interstitial pneumonia. We also evaluated whether severity of respiratory disease predicted recovery of olfactory dysfunction

Can Clinical and Surgical Parameters Be Combined to Predict How Long It Will Take a Tibia Fracture to Heal? A Prospective Multicentre Observational Study: The FRACTING Study

Background. Healing of tibia fractures occurs over a wide time range of months, with a number of risk factors contributing to prolonged healing. In this prospective, multicentre, observational study, we investigated the capability of FRACTING (tibia FRACTure prediction healING days) score, calculated soon after tibia fracture treatment, to predict healing time. Methods. The study included 363 patients. Information on patient health, fracture morphology, and surgical treatment adopted were combined to calculate the FRACTING score. Fractures were considered healed when the patient was able to fully weight-bear without pain. Results. 319 fractures (88%) healed within 12 months from treatment. Forty-four fractures healed after 12 months or underwent a second surgery. FRACTING score positively correlated with days to healing: r = 0.63 (p < 0.0001). Average score value was 7.3 \ub1 2.5; ROC analysis showed strong reliability of the score in separating patients healing before versus after 6 months: AUC = 0.823. Conclusions. This study shows that the FRACTING score can be employed both to predict months needed for fracture healing and to identify immediately after treatment patients at risk of prolonged healing. In patients with high score values, new pharmacological and nonpharmacological treatments to enhance osteogenesis could be tested selectively, which may finally result in reduced disability time and health cost savings

Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction

Coronary computed tomography angiography (CCTA) is a medical imaging technique that produces detailed images of the coronary arteries. Our work focuses on the optimization of the prospectively ECG-triggered scan technique, which delivers the radiation efficiently only during a fraction of the R–R interval, matching the aim of reducing radiation dose in this increasingly used radiological examination. In this work, we analyzed how the median DLP (Dose-Length Product) values for CCTA of our Center decreased significantly in recent times mainly due to a notable change in the technology used. We passed from a median DLP value of 1158 mGy·cm to 221 mGy·cm for the whole exam and from a value of 1140 mGy·cm to 204 mGy·cm if considering CCTA scanning only. The result was obtained through the association of important factors during the dose imaging optimization: technological improvement, acquisition technique, and image reconstruction algorithm intervention. The combination of these three factors allows us to perform a faster and more accurate prospective CCTA with a lower radiation dose. Our future aim is to tune the image quality through a detectability-based study, combining algorithm strength with automatic dose settings