Gertz, Roman Johannes;
Gerhardt, Felix;
Kröger, Jan Robert;
Shahzad, Rahil;
Caldeira, Liliana;
Kottlors, Jonathan;
Große Hokamp, Nils;
Maintz, David;
Rosenkranz, Stephan;
Bunck, Alexander Christian
Spectral Detector CT-Derived Pulmonary Perfusion Maps and Pulmonary Parenchyma Characteristics for the Semiautomated Classification of Pulmonary Hypertension
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Medientyp:
E-Artikel
Titel:
Spectral Detector CT-Derived Pulmonary Perfusion Maps and Pulmonary Parenchyma Characteristics for the Semiautomated Classification of Pulmonary Hypertension
Beteiligte:
Gertz, Roman Johannes;
Gerhardt, Felix;
Kröger, Jan Robert;
Shahzad, Rahil;
Caldeira, Liliana;
Kottlors, Jonathan;
Große Hokamp, Nils;
Maintz, David;
Rosenkranz, Stephan;
Bunck, Alexander Christian
Erschienen:
Frontiers Media SA, 2022
Erschienen in:Frontiers in Cardiovascular Medicine
Beschreibung:
<jats:sec><jats:title>Objectives</jats:title><jats:p>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).</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>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<jats:sub>PerfDef</jats:sub>-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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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 (<jats:italic>p</jats:italic> &lt; 0.001), identifying patients with chronic thromboembolic PH (CTEPH, subgroup 4) with high accuracy (AUC: 0.92, 95%-CI, 0.85–0.99).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>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.</jats:p></jats:sec>