Pearls and Pitfalls of Contrast-Enhanced Mammography

Contrast-enhanced mammography (CEM) is a promising new imaging modality that uses a dual-energy acquisition to provide both morphologic and vascular assessment of breast lesions. Although no official BI-RADS lexicon exists, interpretation entails using the mammographic BI-RADS lexicon in combination with that for breast MRI. CEM has comparable performance to breast MRI, with sensitivity of 93–100% and specificity of 80–94%. Currently FDA approved for diagnostic imaging, this technology can be helpful in determining disease extent in patients with newly diagnosed breast malignancy, monitoring response to neoadjuvant therapy, identifying mammographically occult malignancies, and diagnostic problem-solving. Studies are ongoing about its role in screening, especially in women with dense breasts or at elevated risk. There are some challenges to successful implementation into practice, but overall, patients tolerate the study well, and exam times are less than the full breast MRI protocol.

Design of a computer-based learning environment to support diagnostic problem solving towards expertise development

Learning through problem solving is a pedagogical approach that situates learning in problem-solving contexts. As a form of constructivist learning, problem solving has received increased attention in complex and ill-structured domains such as scientific inquiry and medical education. However, effective learning in problem-solving contexts is difficult to realize because problem-solving tasks often involve complex processes that are inaccessible to learners. It is important to make such complex processes visible for observation and practice, and provide learners with necessary help during the learning process. This study explored the design of a computer-based learning environment that helps medical students to externalize the sophisticated process of diagnostic problem-solving and provides them with adaptive feedback when they work with a number of simulated clinical cases. The proposed approach attempted to utilize expert knowledge to transform open-ended problem-solving experience into systematic and deliberate effort towards expertise development.

Diagnostic Problem Solving in Male Collegiate Athletic Trainers

Context: Knowledge and experience may be important factors for understanding expertise based upon a clinician's ability to select and execute an appropriate response as a clinician during injury evaluation. Objective: To describe how collegiate male certified athletic trainers represent injury-evaluation domain knowledge during a situational interview using a think-aloud protocol. Design: Qualitative. Setting: National Collegiate Athletic Association Division I and II colleges in National Athletic Trainers' Association District 3. Patients or Other Participants: A total of 20 male certified athletic trainers (n = 10 with less than 2 years of experience in the college setting and n = 10 with at least 10 years of experience in the college setting) participated in the study. Data Collection and Analysis: We collected data using a situational interview and questionnaire. Data were transcribed, reduced to meaningful units, and analyzed using verbal analysis procedures. Member checks, triangulation of data, field journaling, and peer-debriefing techniques were used to ensure trustworthiness of the data. Knowledge concepts were enumerated to describe differences between experts and novices. Results: Compared with novices, experts had more knowledge concepts of patient history and predictions and fewer concepts of situation appraisal. Conclusions: Expertise in athletic training shares traits with other areas in health care. Athletic training education and professional development may benefit from our understanding which cognitive processes differentiate expert practice. Future investigators should attempt to describe other settings and study diagnostic problem solving in a natural environment.