Spectral Detector CT-Derived Pulmonary Perfusion Maps and Pulmonary Parenchyma Characteristics for the Semiautomated Classification of Pulmonary Hypertension

• Published in: Frontiers in cardiovascular medicine Vol. 9; p. 835732
• Main Authors: Gertz, Roman Johannes, Gerhardt, Felix, Kröger, Jan Robert, Shahzad, Rahil, Caldeira, Liliana, Kottlors, Jonathan, Große Hokamp, Nils, Maintz, David, Rosenkranz, Stephan, Bunck, Alexander Christian
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 28.02.2022
• Subjects: Cardiovascular Medicine; dual energy; pulmonary hypertension; pulmonary perfusion maps; spectral detector CT; virtual non-contrast pulmonary parenchyma characteristics; virtual non-contrast pulmonary parenchyma characteristics; spectral detector CT; pulmonary perfusion maps; pulmonary hypertension; dual energy
• ISSN: 2297-055X; 2297-055X
• DOI: 10.3389/fcvm.2022.835732

To evaluate the usefulness of spectral detector CT (SDCT)-derived pulmonary perfusion maps and pulmonary parenchyma characteristics for the semiautomated classification of pulmonary hypertension (PH). A total of 162 consecutive patients with right heart catheter (RHC)-proven PH of different aetiologies as defined by the current ESC/ERS guidelines who underwent CT pulmonary angiography (CTPA) on SDCT and 20 patients with an invasive rule-out of PH were included in this retrospective study. Semiautomatic lung segmentation into normal and malperfused areas based on iodine density (ID) as well as automatic, virtual non-contrast-based emphysema quantification were performed. Corresponding volumes, histogram features and the ID Skewness -Emphysema-Index (δ-index) accounting for the ratio of ID distribution in malperfused lung areas and the proportion of emphysematous lung parenchyma were computed and compared between groups. Patients with PH showed a significantly greater extent of malperfused lung areas as well as stronger and more homogenous perfusion defects. In group 3 and 4 patients, ID skewness revealed a significantly more homogenous ID distribution in perfusion defects than in all other subgroups. The δ-index allowed for further subclassification of subgroups 3 and 4 ( < 0.001), identifying patients with chronic thromboembolic PH (CTEPH, subgroup 4) with high accuracy (AUC: 0.92, 95%-CI, 0.85-0.99). Abnormal pulmonary perfusion in PH can be detected and quantified by semiautomated SDCT-based pulmonary perfusion maps. ID skewness in malperfused lung areas, and the δ-index allow for a classification of PH subgroups, identifying groups 3 and 4 patients with high accuracy, independent of reader expertise.