Andrea Wolf[email protected]Practice ManagementHow can radiology practice managers overcome today's challenges?Burnout remains a persistent challenge for radiology practices. In a new column, Andrea Wolf of Uppermost Strategies offers some suggestions for how to address burnout among radiologists.March 16, 2023BreastHow on-demand culture is transforming radiologyCrises spur innovation. This concept is playing out once again in the field of medical education, where healthcare providers are seeking out new forms of education. Andrea Wolf of the Brem Foundation explains.March 9, 2022BreastLanguage matters when screening women with dense breastsUntil we change how we talk about dense breast screenings, we will not make headway in providing access to this essential test to all women with dense tissue. That's according to Andrea Wolf of the Brem Foundation to Defeat Breast Cancer.September 22, 2020Page 1 of 1Top StoriesMRIUnstable brain networks may drive multiple sclerosis fatigueFatigue affects between 36.5% and 78% of people with multiple sclerosis and can dramatically impair their daily lives.Womens ImagingAI-calculated BAC on mammograms predicts cardiovascular disease in womenCardiac ImagingECR: Cardiac imaging is at the 'heart' of precision medicineUltrasoundUltrasound MinnieCast, Episode 3: Focused ultrasound brings hope to patientsWomens ImagingECR: LLMs help patients understand breast imaging reports
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)
