TY - JOUR
T1 - Quantitative thrombus characteristics on thin-slice computed tomography improve prediction of thrombus histopathology
T2 - results of the MR CLEAN Registry
AU - Hund, Hajo
AU - Boodt, Nikki
AU - Arrarte Terreros, Nerea
AU - Taha, Aladdin
AU - Marquering, Henk A.
AU - van Es, Adriaan C. G. M.
AU - on behalf of the MR CLEAN Registry Investigators
AU - Bokkers, Reinoud P. H.
AU - Lycklama à Nijeholt, Geert J.
AU - Majoie, Charles B. L. M.
AU - Dippel, Diederik W. J.
AU - Lingsma, Hester F.
AU - van Beusekom, Heleen M. M.
AU - van der Lugt, Aad
N1 - Funding Information: The authors of this manuscript declare relationships with the following companies: Erasmus Medical Center received compensation from Stryker, Siemens Healthineers, and GE Healthcare for activities of A.v.d.L. Dr. Dippel and Dr. Van der Lugt report grants from Dutch Heart Foundation, grants from Brain Foundation Netherlands, grants from Health Holland Top Sector Life Sciences & Health, grants from the Netherlands Organisation for Health Research and Development, and unrestricted grants from Stryker European Operations BV; from Penumbra Inc.; from Medtronic; from Thrombolytic Science, LLC; and from Cerenovus outside the submitted work, all paid to institution. H.A.M. is co-founder and shareholder of Nicolab, a company that focuses on the use of artificial intelligence for medical image analysis. C.B.L.M. is a recipient of grants from the CVON/Dutch Heart Foundation, Stryker, European Commission, TWIN Foundation, and Health Evaluation Netherlands and is shareholder of Nicolab. Funding Information: This study was funded and carried out by the Erasmus University Medical Center, the Academic Medical Center Amsterdam, and the Maastricht University Medical Center. The study was additionally funded by the European Union’s Horizon 2020 research and innovation program under grant agreement no. 777072 (IN-SIlico trials for treatment of acute Ischemic STroke; INSIST), which played no role in trial design and patient enrolment, nor in data collection, analysis, or writing of the manuscript. Publisher Copyright: © 2022, The Author(s).
PY - 2022/11
Y1 - 2022/11
N2 - Objectives: Thrombus computed tomography (CT) characteristics might be used to assess histopathologic thrombus composition in patients treated with endovascular thrombectomy (EVT) for acute ischemic stroke (AIS). We aimed to assess the variability in thrombus composition that could be predicted with combined thrombus CT characteristics. Methods: Thrombi of patients enrolled in the MR CLEAN Registry between March 2014 and June 2016 were histologically analyzed with hematoxylin-eosin staining and quantified for percentages of red blood cells (RBCs) and fibrin/platelets. We estimated the association between general qualitative characteristics (hyperdense artery sign [HAS], occlusion location, clot burden score [CBS]) and thrombus composition with linear regression, and quantified RBC variability that could be explained with individual and combined characteristics with R2. For patients with available thin-slice (≤ 2.5 mm) imaging, we performed similar analyses for general and quantitative characteristics (HAS, occlusion location, CBS, [relative] thrombus density, thrombus length, perviousness, distance from ICA-terminus). Results: In 332 included patients, the presence of HAS (aβ 7.8 [95% CI 3.9–11.7]) and shift towards a more proximal occlusion location (aβ 3.9 [95% CI 0.6–7.1]) were independently associated with increased RBC and decreased fibrin/platelet content. With general characteristics, 12% of RBC variability could be explained; HAS was the strongest predictor. In 94 patients with available thin-slice imaging, 30% of RBC variability could be explained; thrombus density and thrombus length were the strongest predictors. Conclusions: Quantitative thrombus CT characteristics on thin-slice admission CT improve prediction of thrombus composition and might be used to further guide clinical decision-making in patients treated with EVT for AIS in the future. Key Points: • With hyperdense artery sign and occlusion location, 12% of variability in thrombus RBC content can be explained. • With hyperdense artery sign, occlusion location, and quantitative thrombus characteristics on thin-slice (≤ 2.5 mm) non-contrast CT and CTA, 30% of variability in thrombus RBC content can be explained. • Absolute thrombus density and thrombus length were the strongest predictors for thrombus composition.
AB - Objectives: Thrombus computed tomography (CT) characteristics might be used to assess histopathologic thrombus composition in patients treated with endovascular thrombectomy (EVT) for acute ischemic stroke (AIS). We aimed to assess the variability in thrombus composition that could be predicted with combined thrombus CT characteristics. Methods: Thrombi of patients enrolled in the MR CLEAN Registry between March 2014 and June 2016 were histologically analyzed with hematoxylin-eosin staining and quantified for percentages of red blood cells (RBCs) and fibrin/platelets. We estimated the association between general qualitative characteristics (hyperdense artery sign [HAS], occlusion location, clot burden score [CBS]) and thrombus composition with linear regression, and quantified RBC variability that could be explained with individual and combined characteristics with R2. For patients with available thin-slice (≤ 2.5 mm) imaging, we performed similar analyses for general and quantitative characteristics (HAS, occlusion location, CBS, [relative] thrombus density, thrombus length, perviousness, distance from ICA-terminus). Results: In 332 included patients, the presence of HAS (aβ 7.8 [95% CI 3.9–11.7]) and shift towards a more proximal occlusion location (aβ 3.9 [95% CI 0.6–7.1]) were independently associated with increased RBC and decreased fibrin/platelet content. With general characteristics, 12% of RBC variability could be explained; HAS was the strongest predictor. In 94 patients with available thin-slice imaging, 30% of RBC variability could be explained; thrombus density and thrombus length were the strongest predictors. Conclusions: Quantitative thrombus CT characteristics on thin-slice admission CT improve prediction of thrombus composition and might be used to further guide clinical decision-making in patients treated with EVT for AIS in the future. Key Points: • With hyperdense artery sign and occlusion location, 12% of variability in thrombus RBC content can be explained. • With hyperdense artery sign, occlusion location, and quantitative thrombus characteristics on thin-slice (≤ 2.5 mm) non-contrast CT and CTA, 30% of variability in thrombus RBC content can be explained. • Absolute thrombus density and thrombus length were the strongest predictors for thrombus composition.
KW - Computed tomography
KW - Histopathology
KW - Ischemic stroke
KW - Thrombectomy
KW - Thrombus
UR - http://www.scopus.com/inward/record.url?scp=85129318396&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s00330-022-08762-y
DO - https://doi.org/10.1007/s00330-022-08762-y
M3 - Article
C2 - 35501573
SN - 0938-7994
VL - 32
SP - 7811
EP - 7823
JO - European Radiology
JF - European Radiology
IS - 11
ER -