Dr. Benjamin Roach25 for 25AuntMinnie 2006: How 64-slice CT saved my life: A radiologist's storyBuying a major piece of imaging equipment is always a big moment for a radiologist. So Benjamin Roach, MD, was truly excited when his facility, Our Lady of Bellefonte Hospital in Ashland, KY, decided to purchase a new CT scanner.July 29, 2024CTHow 64-slice CT saved my life: A radiologist's storyBuying a major piece of imaging equipment is always a big moment for a radiologist. So Dr. Benjamin Roach was truly excited when his facility, Our Lady of Bellefonte Hospital in Ashland, KY, decided to purchase a new CT scanner. For the purchase of a cutting-edge, state-of-the-art 64-slice scanner, the excitement was palpable: "Think of the lives we'll save," he thought. Little did he know that one of the first lives saved would be his own.February 6, 2006Page 1 of 1Top StoriesCTDL segmentation of chest muscle volume shows promise for COPD patientsDeep learning (DL)-based muscle volume assessment from routine CT scans could help identify COPD patients with comorbid sarcopenia.CareersHPI: Workforce attrition higher in radiology subspecialtiesAssociationsVideo from ECR: Minerva Becker shares congress highlightsCTECR: 'Black swan events' demand informed imaging infrastructurePractice ManagementECR: Integrating actionable reporting into the imaging workflow
![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&fit=crop&h=400&q=70&w=600)
![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)
