Indicators for Hospitalization in Acute Pulmonary Embolism: Uncover the Association Between D-dimer Levels, Thrombus Volume and Radiomics

Jennifer Gotta; Leon D Gruenewald; Tobias Geyer; Katrin Eichler; Simon S Martin; Scherwin Mahmoudi; Christian Booz; Teodora Biciusca; Philipp Reschke; Lisa-Joy Juergens; Christof M Sommer; Tommaso D'Angelo; Haidara Almansour; Melis Onay; Eva Herrmann; Thomas J Vogl; Vitali Koch

doi:10.1016/j.acra.2023.12.045

Indicators for Hospitalization in Acute Pulmonary Embolism: Uncover the Association Between D-dimer Levels, Thrombus Volume and Radiomics

Acad Radiol. 2024 Jan 18:S1076-6332(23)00724-9. doi: 10.1016/j.acra.2023.12.045. Online ahead of print.

Authors

Jennifer Gotta¹, Leon D Gruenewald², Tobias Geyer², Katrin Eichler², Simon S Martin², Scherwin Mahmoudi², Christian Booz², Teodora Biciusca², Philipp Reschke², Lisa-Joy Juergens², Christof M Sommer³, Tommaso D'Angelo⁴, Haidara Almansour⁵, Melis Onay⁶, Eva Herrmann⁷, Thomas J Vogl², Vitali Koch²

Affiliations

¹ Goethe University Hospital Frankfurt, Theodor-Stern-Kai 7, Frankfurt am Main, 60590, Germany (J.G., L.D.G., T.G., K.E., S.S.M., S.M., C.B., T.B., P.R., J.J., T.J.V., V.K.). Electronic address: jennifergotta@aol.com.
² Goethe University Hospital Frankfurt, Theodor-Stern-Kai 7, Frankfurt am Main, 60590, Germany (J.G., L.D.G., T.G., K.E., S.S.M., S.M., C.B., T.B., P.R., J.J., T.J.V., V.K.).
³ Clinic of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany (C.M.S.).
⁴ Department of Biomedical Sciences and Morphological and Functional Imaging, University of Messina, Messina, Italy (T.D.).
⁵ Department of Diagnostic and Interventional Radiology, Tuebingen University Hospital, Tuebingen, Germany (H.A.).
⁶ Department of Internal Medicine I, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany (M.O.).
⁷ Institute for Biostatistics and Mathematic Modelling, Goethe University Frankfurt, 60590, Frankfurt, Germany (E.H.).

PMID: 38242733
DOI: 10.1016/j.acra.2023.12.045

Abstract

Background: The advent of advanced computed tomography (CT) technology and the field of radiomics has opened up new avenues in diagnostic assessments. Increasingly, there is substantial evidence advocating for the incorporation of quantitative imaging biomarkers in the clinical decision-making process. This study aimed to examine the correlation between D-dimer levels and thrombus size in acute pulmonary embolism (PE) combining dual-energy CT (DECT) and radiomics and to investigate the diagnostic utility of a machine learning classifier based on dual-energy computed tomography (DECT) radiomics for identifying patients with a complicated course, defined as at least hospitalization at IMC.

Methods: The study was conducted including 136 participants who underwent pulmonary artery CT angiography from January 2015 to March 2022. Based on DECT imaging, 107 radiomic features were extracted for each patient using standardized image processing. After dividing the dataset into training and test sets, stepwise feature reduction based on reproducibility, variable importance and correlation analyses were performed to select the most relevant features; these were used to train and validate the gradient-boosted tree models.Receiver operating characteristics (ROC) analysis was utilized to evaluate the association between volumetric, laboratory data and adverse outcomes.

Results: In the central PE group, we observed a significant correlation between thrombus volumetrics and D-dimer levels (p = 0.0037), as well as between thrombus volumetrics and hospitalization at the Intermediate Care Unit (IMC) (p = 0.0001). In contrast, no statistically significant differences were identified in thrombus sizes between patients who experienced complications and those who had a favorable course (p = 0.3162). The trained machine learning classifier achieved an accuracy of 61% and 55% in identifying patients with a complicated course, as indicated by an area under the ROC curve of 0.63 and 0.58.

Conclusion: In conclusion, our findings indicate a positive correlation between D-dimer levels and central PE's pulmonary embolic burden. Thrombus volumetrics may serve as an indicator for complications and outcomes in acute PE patients. Thus, thrombus volumetrics, as opposed to D-dimers, could be an additional marker for evaluating embolic disease severity. Moreover, DECT-derived radiomic feature models show promise in identifying patients with a complicated course, such as hospitalization at IMC.

Keywords: D-dimer; Dual-energy computed tomography; Prediction; Pulmonary embolism; Venous thromboembolism.