Lung scintigraphy may be more reliable than pulmonary CT angiography (CTA) for identifying or excluding pulmonary embolism (PE) in pregnant patients, according to a study published in the November issue of the American Journal of Roentgenology.
Pulmonary embolism is the leading cause of maternal death in pregnancy. CTA is the imaging modality of choice for the diagnosis of pulmonary embolism; however, lung scintigraphy, a form of radionuclide imaging that produces 2D images, has been shown to produce better diagnostic-quality images more often than CTA in pregnant patients.
The study, led by Dr. Carole Ridge from St. Vincent's University in Dublin, Ireland, analyzed 28 CTA studies and 25 lung scintigraphy studies performed on a group of 50 patients. The results showed that lung scintigraphy is more reliable than CTA for the diagnosis of PE.
Only one of 25 lung scintigraphy studies was inadequate for diagnosis, compared with 10 out of 28 CTA examinations that were found to be inadequate. Exams were considered inadequate when poor image quality prohibited a diagnosis.
Lung scintigraphy is more reliable than CTA for diagnosing or excluding PE in pregnant patients, the authors concluded, and it should be considered the imaging technique of choice unless the CTA image technique can be optimized for the pregnant patient.
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![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
