TY - JOUR
T1 - Quantification of clot spatial heterogeneity and its impact on thrombectomy
AU - Liu, Yang
AU - Brinjikji, Waleed
AU - Abbasi, Mehdi
AU - Dai, Daying
AU - Arturo Larco, Jorge L.
AU - Madhani, Sarosh Irfan
AU - Shahid, Adnan H.
AU - Mereuta, Oana Madalina
AU - Nogueira, Raul G.
AU - Kvamme, Peter
AU - Layton, Kennith F.
AU - Delgado Almandoz, Josser E.
AU - Hanel, Ricardo A.
AU - Mendes Pereira, Vitor
AU - Almekhlafi, Mohammed A.
AU - Yoo, Albert J.
AU - Jahromi, Babak S.
AU - Gounis, Matthew J.
AU - Patel, Biraj
AU - Fitzgerald, Seán
AU - Doyle, Karen
AU - Haussen, Diogo C.
AU - Al-Bayati, Alhamza R.
AU - Mohammaden, Mahmoud
AU - Pisani, Leonardo
AU - Rodrigues, Gabriel Martins
AU - Thacker, Ike C.
AU - Kayan, Yasha
AU - Copelan, Alexander
AU - Aghaebrahim, Amin
AU - Sauvageau, Eric
AU - Demchuk, Andrew M.
AU - Bhuva, Parita
AU - Soomro, Jazba
AU - Nazari, Pouya
AU - Cantrell, Donald Robert
AU - Puri, Ajit S.
AU - Entwistle, John
AU - Kadirvel, Ramanathan
AU - Cloft, Harry J.
AU - Kallmes, David F.
AU - Savastano, Luis
N1 - Publisher Copyright:
© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - BACKGROUND: Compositional and structural features of retrieved clots by thrombectomy can provide insight into improving the endovascular treatment of ischemic stroke. Currently, histological analysis is limited to quantification of compositions and qualitative description of the clot structure. We hypothesized that heterogeneous clots would be prone to poorer recanalization rates and performed a quantitative analysis to test this hypothesis. METHODS: We collected and did histology on clots retrieved by mechanical thrombectomy from 157 stroke cases (107 achieved first-pass effect (FPE) and 50 did not). Using an in-house algorithm, the scanned images were divided into grids (with sizes of 0.2, 0.3, 0.4, 0.5, and 0.6 mm) and the extent of non-uniformity of RBC distribution was computed using the proposed spatial heterogeneity index (SHI). Finally, we validated the clinical significance of clot heterogeneity using the Mann-Whitney test and an artificial neural network (ANN) model. RESULTS: For cases with FPE, SHI values were smaller (0.033 vs 0.039 for grid size of 0.4 mm, P=0.028) compared with those without. In comparison, the clot composition was not statistically different between those two groups. From the ANN model, clot heterogeneity was the most important factor, followed by fibrin content, thrombectomy techniques, red blood cell content, clot area, platelet content, etiology, and admission of intravenous tissue plasminogen activator (IV-tPA). No statistical difference of clot heterogeneity was found for different etiologies, thrombectomy techniques, and IV-tPA administration. CONCLUSIONS: Clot heterogeneity can affect the clot response to thrombectomy devices and is associated with lower FPE. SHI can be a useful metric to quantify clot heterogeneity.
AB - BACKGROUND: Compositional and structural features of retrieved clots by thrombectomy can provide insight into improving the endovascular treatment of ischemic stroke. Currently, histological analysis is limited to quantification of compositions and qualitative description of the clot structure. We hypothesized that heterogeneous clots would be prone to poorer recanalization rates and performed a quantitative analysis to test this hypothesis. METHODS: We collected and did histology on clots retrieved by mechanical thrombectomy from 157 stroke cases (107 achieved first-pass effect (FPE) and 50 did not). Using an in-house algorithm, the scanned images were divided into grids (with sizes of 0.2, 0.3, 0.4, 0.5, and 0.6 mm) and the extent of non-uniformity of RBC distribution was computed using the proposed spatial heterogeneity index (SHI). Finally, we validated the clinical significance of clot heterogeneity using the Mann-Whitney test and an artificial neural network (ANN) model. RESULTS: For cases with FPE, SHI values were smaller (0.033 vs 0.039 for grid size of 0.4 mm, P=0.028) compared with those without. In comparison, the clot composition was not statistically different between those two groups. From the ANN model, clot heterogeneity was the most important factor, followed by fibrin content, thrombectomy techniques, red blood cell content, clot area, platelet content, etiology, and admission of intravenous tissue plasminogen activator (IV-tPA). No statistical difference of clot heterogeneity was found for different etiologies, thrombectomy techniques, and IV-tPA administration. CONCLUSIONS: Clot heterogeneity can affect the clot response to thrombectomy devices and is associated with lower FPE. SHI can be a useful metric to quantify clot heterogeneity.
KW - intervention
KW - stroke
KW - technology
KW - thrombectomy
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U2 - 10.1136/neurintsurg-2021-018183
DO - 10.1136/neurintsurg-2021-018183
M3 - Article
C2 - 34911736
AN - SCOPUS:85127010854
SN - 1759-8478
VL - 14
SP - 1248
EP - 1252
JO - Journal of NeuroInterventional Surgery
JF - Journal of NeuroInterventional Surgery
IS - 12
ER -