Small Bowel Obstruction Rationale and Objectives: Our primary aim was to improve radiology reports by increasing concordance of target lesion measurements with oncology records using radiology preprocessors (RP). Faster notification of incidental actionable findings to referring clinicians and clinical radiologist exam interpretation time savings with RPs quantifying tumor burden were also assessed. Materials and Methods: In this prospective quality improvement initiative, RPs annotated lesions before radiologist interpretation of CT exams. Clinical radiologists then hyperlinked approved measurements into interactive reports during interpretations. RPs evaluated concordance with our tumor measurement radiologist, the determinant of tumor burden. Actionable finding detection and notification times were also deduced. Clinical radiologist interpretation times were calculated from established average CT chest, abdomen, and pelvis interpretation times. Results: RPs assessed 1287 body CT exams with 812 follow-up CT chest, abdomen, and pelvis studies; 95 (11.7%) of which had 241 verified target lesions. There was improved concordance (67.8% vs. 22.5%) of target lesion measurements. RPs detected 93.1% incidental actionable findings with faster clinician notification by a median time of 1 hour (range: 15 minutesÀ16 hours). Radiologist exam interpretation times decreased by 37%. Conclusions: This workflow resulted in threefold improved target lesion measurement concordance with oncology records, earlier detection and faster notification of incidental actionable findings to referring clinicians, and decreased exam interpretation times for clinical radiologists. These findings demonstrate potential roles for automation (such as AI) to improve report value, worklist prioritization, and patient care.

No abstract

• Abdominal imaging plays a crucial role in management of Erdheim-Chester disease. • Significant associations exist between BRAF mutation and several abdominal imaging findings. • Considering several associations, evaluating BRAF mutation status is recommended in ECD patients.

No abstract

Photon-counting computed tomography (CT) is a developing technology that has the potential to address some limitations of CT imaging and bring about improvements and potentially new applications to this field. Photon-counting detectors have a fundamentally different detection mechanism from conventional CT energy-integrating detectors that can improve dose efficiency, spatial resolution, and energy-discrimination capabilities. In the past decade, promising human studies have been reported in the literature that have demonstrated benefits of this relatively new technology for various clinical applications. In this review, we provide a succinct description of the photon-counting detector technology and its detection mechanism in comparison with energy-integrating detectors in a manner understandable for clinicians and radiologists, introduce benefits and some of the existing challenges present in this technology, and provide an overview of the current status and potential clinical applications of this technology in imaging of the thorax by providing example images acquired with an investigational whole-body photon-counting CT scanner.