Clinical decision-support (CDS) tools could positively influence the diagnostic workup of patients with suspected pulmonary embolism (PE) and affect the use of pulmonary CT angiography (CTA) for evaluating them, according to a web exclusive article in the March issue of the American Journal of Roentgenology.
Co-authors Dr. William Sherk and Dr. Jadranka Stojanovska, both from the University of Michigan Health System, developed clinical decision rules to determine which patients with suspected pulmonary embolism would benefit from further diagnostic workup, such as pulmonary CTA. They found that overall, CTA is overused for screening as opposed to diagnostic examination, which leads to increased financial costs and patient exposure to radiation and contrast media (AJR, March 2017, Vol. 208:3, pp. W60-W70).
Clinical decision support could help, they concluded.
"The qualities of pulmonary CTA make it desirable to clinicians as a test for suspected PE," they wrote. "As with other diagnostic tests, however, the post-test probability of pulmonary CTA hinges on pretest clinical assessment. Validated clinical decision rules and integrated CDS systems can influence the appropriate use of pulmonary CTA, but further investigation is required to define the most successful means of integration into clinical practice."


















![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=112&q=70&w=112)

