Build or Buy? Managing the New Technology Decision Tree.

Technology plays a role in nearly every aspect of healthcare delivery. Health systems must continually invest in new and existing technology and analytics platforms to scale initiatives, enable innovation, and achieve interoperability to meet the needs and expectations of patients and clinicians while remaining focused on the organization's mission and strategic priorities. In this process, decision-makers must determine how to allocate technological resources to platforms that meet clinical and administrative needs while reducing the need for frequent replacement or reconfiguration.

Abbreviated Breast MRI for Supplemental Screening in Patients With Dense Breasts: Comparison of Baseline Versus Subsequent-Round Examinations.

Abbreviated breast MRI (AB-MRI) achieves a higher cancer detection rate (CDR) than digital breast tomosynthesis when applied for baseline (i.e., first-round) supplemental screening of individuals with dense breasts.

Implementation of a Clinical Vessel Wall MR Imaging Program at an Academic Medical Center.

Background And Purpose: The slow adoption of new advanced imaging techniques into clinical practice has been a long-standing challenge. Principles of implementation science and the reach, effectiveness, adoption, implementation, maintenance (RE-AIM) framework were used to build a clinical vessel wall imaging program at an academic medical center.

Materials And Methods: Six phases for implementing a clinical vessel wall MR imaging program were contextualized to the RE-AIM framework.

Clinical correlates of CT imaging-derived phenotypes among lean and overweight patients with hepatic steatosis.

The objective of this study is to define CT imaging derived phenotypes for patients with hepatic steatosis, a common metabolic liver condition, and determine its association with patient data from a medical biobank. There is a need to further characterize hepatic steatosis in lean patients, as its epidemiology may differ from that in overweight patients. A deep learning method determined the spleen-hepatic attenuation difference (SHAD) in Hounsfield Units (HU) on abdominal CT scans as a quantitative measure of hepatic steatosis.