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CC BY-NC-ND 4.0 · Thromb Haemost 2022; 122(03): 415-426
DOI: 10.1055/a-1522-4507
Stroke, Systemic or Venous Thromboembolism

An Older Thrombus Delays Reperfusion after Mechanical Thrombectomy for Ischemic Stroke

Takaya Kitano
1   Department of Neurology, Osaka University Graduate School of Medicine, Osaka, Japan
2   Department of Stroke Medicine, Kawasaki Medical School, Okayama, Japan
,
Yumiko Hori
3   Department of Pathology, Osaka University Graduate School of Medicine, Osaka, Japan
,
Shuhei Okazaki
1   Department of Neurology, Osaka University Graduate School of Medicine, Osaka, Japan
,
Yuki Shimada
4   Department of Neurology, Osaka General Medical Center, Osaka, Japan
,
Takanori Iwamoto
2   Department of Stroke Medicine, Kawasaki Medical School, Okayama, Japan
,
Hideaki Kanki
1   Department of Neurology, Osaka University Graduate School of Medicine, Osaka, Japan
,
Shintaro Sugiyama
1   Department of Neurology, Osaka University Graduate School of Medicine, Osaka, Japan
,
Tsutomu Sasaki
1   Department of Neurology, Osaka University Graduate School of Medicine, Osaka, Japan
,
Hajime Nakamura
5   Department of Neurosurgery, Osaka University Graduate School of Medicine, Osaka, Japan
,
Naoki Oyama
2   Department of Stroke Medicine, Kawasaki Medical School, Okayama, Japan
,
Taku Hoshi
4   Department of Neurology, Osaka General Medical Center, Osaka, Japan
,
Goichi Beck
1   Department of Neurology, Osaka University Graduate School of Medicine, Osaka, Japan
,
Hiroki Takai
6   Department of Neurosurgery, Kawasaki Medical School, Okayama, Japan
,
Shunji Matsubara
6   Department of Neurosurgery, Kawasaki Medical School, Okayama, Japan
,
Hiroya Mizuno
7   Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
,
Hirotake Nishimura
8   Department of Pathology, Kawasaki Medical School, Okayama, Japan
,
Ryo Tamaki
9   Department of Neurosurgery, Osaka General Medical Center, Osaka, Japan
,
Junichi Iida
9   Department of Neurosurgery, Osaka General Medical Center, Osaka, Japan
,
Jiro Iba
10   Department of Traumatology and Acute Critical Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
,
Masaaki Uno
6   Department of Neurosurgery, Kawasaki Medical School, Okayama, Japan
,
Haruhiko Kishima
5   Department of Neurosurgery, Osaka University Graduate School of Medicine, Osaka, Japan
,
Hiroaki Fushimi
11   Department of Pathology, Osaka General Medical Center, Osaka, Japan
,
Satoshi Hattori
12   Department of Integrated Medicine, Biomedical Statistics, Osaka University Graduate School of Medicine, Osaka, Japan
13   Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Osaka, Japan
,
Shigeo Murayama
14   Brain Bank for Neurodevelopmental, Neurological and Psychiatric Disorders, United Graduate School of Child Development, Osaka University, Osaka, Japan
15   Department of Neurology and Neuropathology (the Brain Bank for Aging Research), Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan
,
Eiichi Morii
3   Department of Pathology, Osaka University Graduate School of Medicine, Osaka, Japan
,
Manabu Sakaguchi
4   Department of Neurology, Osaka General Medical Center, Osaka, Japan
,
Yoshiki Yagita
2   Department of Stroke Medicine, Kawasaki Medical School, Okayama, Japan
,
Takeshi Shimazu
10   Department of Traumatology and Acute Critical Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
,
Hideki Mochizuki
1   Department of Neurology, Osaka University Graduate School of Medicine, Osaka, Japan
,
Kenichi Todo
1   Department of Neurology, Osaka University Graduate School of Medicine, Osaka, Japan
› Institutsangaben Funding This work was supported by JSPS KAKENHI [grants TK19K20729 and JSPS KAKENHI 21K15696].
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Abstract

Background Thrombosis is a dynamic process, and a thrombus undergoes physical and biochemical changes that may alter its response to reperfusion therapy. This study assessed whether thrombus age influenced reperfusion quality and outcomes after mechanical thrombectomy for cerebral embolism.

Methods We retrospectively evaluated 185 stroke patients and thrombi that were collected during mechanical thrombectomy at three stroke centers. Thrombi were pathologically classified as fresh or older based on their granulocytes' nuclear morphology and organization. Thrombus components were quantified, and the extent of NETosis (the process of neutrophil extracellular trap formation) was assessed using the density of citrullinated histone H3-positive cells. Baseline patient characteristics, thrombus features, endovascular procedures, and functional outcomes were compared according to thrombus age.

Results Fresh thrombi were acquired from 43 patients, and older thrombi were acquired from 142 patients. Older thrombi had a lower erythrocyte content (p < 0.001) and higher extent of NETosis (p = 0.006). Restricted mean survival time analysis revealed that older thrombi were associated with longer puncture-to-reperfusion times (difference: 15.6 minutes longer for older thrombi, p = 0.002). This association remained significant even after adjustment for erythrocyte content and the extent of NETosis (adjusted difference: 10.8 minutes, 95% confidence interval [CI]: 0.6–21.1 minutes, p = 0.039). Compared with fresh thrombi, older thrombi required more device passes before reperfusion (p < 0.001) and were associated with poorer functional outcomes (adjusted common odds ratio: 0.49; 95% CI: 0.24–0.99).

Conclusion An older thrombus delays reperfusion after mechanical thrombectomy for ischemic stroke. Adding therapies targeting thrombus maturation may improve the efficacy of mechanical thrombectomy.

Keywords

thrombolysis - embolism - pathology - stroke - macrophage

Supplementary Material



Publikationsverlauf

Eingereicht: 02. März 2021

Angenommen: 22. Mai 2021

Accepted Manuscript online:
02. Juni 2021

Artikel online veröffentlicht:
06. Juli 2021

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Kamel H, Healey JS. Cardioembolic stroke. Circ Res 2017; 120 (03) 514-526
    CrossrefPubMedGoogle Scholar
  • 2 Furie B, Furie BC. Mechanisms of thrombus formation. N Engl J Med 2008; 359 (09) 938-949
    CrossrefPubMedGoogle Scholar
  • 3 January CT, Wann LS, Calkins H. et al. 2019 AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society in Collaboration With the Society of Thoracic Surgeons. Circulation 2019; 140 (02) e125-e151
    CrossrefPubMedGoogle Scholar
  • 4 Nicklas JM, Gordon AE, Henke PK. Resolution of deep venous thrombosis: proposed immune paradigms. Int J Mol Sci 2020; 21 (06) 2080
    CrossrefPubMedGoogle Scholar
  • 5 Saha P, Humphries J, Modarai B. et al. Leukocytes and the natural history of deep vein thrombosis: current concepts and future directions. Arterioscler Thromb Vasc Biol 2011; 31 (03) 506-512
    CrossrefPubMedGoogle Scholar
  • 6 Nosaka M, Ishida Y, Kimura A, Kondo T. Time-dependent organic changes of intravenous thrombi in stasis-induced deep vein thrombosis model and its application to thrombus age determination. Forensic Sci Int 2010; 195 (1–3): 143-147
    CrossrefPubMedGoogle Scholar
  • 7 Helms CC, Ariëns RA, Uitte de Willige S, Standeven KF, Guthold M. α-α Cross-links increase fibrin fiber elasticity and stiffness. Biophys J 2012; 102 (01) 168-175
    CrossrefPubMedGoogle Scholar
  • 8 Collet J-P, Moen JL, Veklich YI. et al. The alphaC domains of fibrinogen affect the structure of the fibrin clot, its physical properties, and its susceptibility to fibrinolysis. Blood 2005; 106 (12) 3824-3830
    CrossrefPubMedGoogle Scholar
  • 9 Czaplicki C, Albadawi H, Partovi S. et al. Can thrombus age guide thrombolytic therapy?. Cardiovasc Diagn Ther 2017; 7 (Suppl. 03) S186-S196
    CrossrefPubMedGoogle Scholar
  • 10 Goyal M, Menon BK, van Zwam WH. et al; HERMES collaborators. Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials. Lancet 2016; 387 (10029): 1723-1731
    CrossrefPubMedGoogle Scholar
  • 11 Jansen IGH, Mulder MJHL, Goldhoorn RB. MR CLEAN Registry investigators. Endovascular treatment for acute ischaemic stroke in routine clinical practice: prospective, observational cohort study (MR CLEAN Registry). BMJ 2018; 360: k949
    CrossrefPubMedGoogle Scholar
  • 12 van den Berg LA, Dijkgraaf MG, Berkhemer OA. et al; MR CLEAN Investigators. Two-year outcome after endovascular treatment for acute ischemic stroke. N Engl J Med 2017; 376 (14) 1341-1349
    CrossrefPubMedGoogle Scholar
  • 13 Khatri P, Yeatts SD, Mazighi M. et al; IMS III Trialists. Time to angiographic reperfusion and clinical outcome after acute ischaemic stroke: an analysis of data from the Interventional Management of Stroke (IMS III) phase 3 trial. Lancet Neurol 2014; 13 (06) 567-574
    CrossrefPubMedGoogle Scholar
  • 14 Alawieh A, Vargas J, Fargen KM. et al. Impact of procedure time on outcomes of thrombectomy for stroke. J Am Coll Cardiol 2019; 73 (08) 879-890
    CrossrefPubMedGoogle Scholar
  • 15 Hofmeister J, Bernava G, Rosi A. et al. Clot-based radiomics predict a mechanical thrombectomy strategy for successful recanalization in acute ischemic stroke. Stroke 2020; 51 (08) 2488-2494
    CrossrefPubMedGoogle Scholar
  • 16 Bacigaluppi M, Semerano A, Gullotta GS, Strambo D. Insights from thrombi retrieved in stroke due to large vessel occlusion. J Cereb Blood Flow Metab 2019; 39 (08) 1433-1451
    CrossrefPubMedGoogle Scholar
  • 17 Heo JH, Nam HS, Kim YD. et al. Pathophysiologic and therapeutic perspectives based on thrombus histology in stroke. J Stroke 2020; 22 (01) 64-75
    CrossrefPubMedGoogle Scholar
  • 18 van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke 1988; 19 (05) 604-607
    CrossrefPubMedGoogle Scholar
  • 19 Adams Jr HP, Bendixen BH, Kappelle LJ. et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke 1993; 24 (01) 35-41
    CrossrefPubMedGoogle Scholar
  • 20 Barber PA, Demchuk AM, Zhang J, Buchan AM. Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. ASPECTS Study Group. Alberta Stroke Programme Early CT Score. Lancet 2000; 355 (9216): 1670-1674
    CrossrefPubMedGoogle Scholar
  • 21 Launes J, Ketonen L. Dense middle cerebral artery sign: an indicator of poor outcome in middle cerebral artery area infarction. J Neurol Neurosurg Psychiatry 1987; 50 (11) 1550-1552
    CrossrefPubMedGoogle Scholar
  • 22 Schellinger PD, Chalela JA, Kang DW, Latour LL, Warach S. Diagnostic and prognostic value of early MR imaging vessel signs in hyperacute stroke patients imaged <3 hours and treated with recombinant tissue plasminogen activator. AJNR Am J Neuroradiol 2005; 26 (03) 618-624
    PubMedGoogle Scholar
  • 23 Liebeskind DS, Bracard S, Guillemin F. et al; HERMES Collaborators. eTICI reperfusion: defining success in endovascular stroke therapy. J Neurointerv Surg 2019; 11 (05) 433-438
    CrossrefPubMedGoogle Scholar
  • 24 Schindelin J, Arganda-Carreras I, Frise E. et al. Fiji: an open-source platform for biological-image analysis. Nat Methods 2012; 9 (07) 676-682
    CrossrefPubMedGoogle Scholar
  • 25 Fuchs TA, Abed U, Goosmann C. et al. Novel cell death program leads to neutrophil extracellular traps. J Cell Biol 2007; 176 (02) 231-241
    CrossrefPubMedGoogle Scholar
  • 26 Neeli I, Khan SN, Radic M. Histone deimination as a response to inflammatory stimuli in neutrophils. J Immunol 2008; 180 (03) 1895-1902
    CrossrefPubMedGoogle Scholar
  • 27 Rittersma SZ, van der Wal AC, Koch KT. et al. Plaque instability frequently occurs days or weeks before occlusive coronary thrombosis: a pathological thrombectomy study in primary percutaneous coronary intervention. Circulation 2005; 111 (09) 1160-1165
    CrossrefPubMedGoogle Scholar
  • 28 Lau SK, Chu PG, Weiss LM. CD163: a specific marker of macrophages in paraffin-embedded tissue samples. Am J Clin Pathol 2004; 122 (05) 794-801
    CrossrefPubMedGoogle Scholar
  • 29 Fabriek BO, Dijkstra CD, van den Berg TK. The macrophage scavenger receptor CD163. Immunobiology 2005; 210 (2–4): 153-160
    CrossrefPubMedGoogle Scholar
  • 30 Furukoji E, Gi T, Yamashita A. et al. CD163 macrophage and erythrocyte contents in aspirated deep vein thrombus are associated with the time after onset: a pilot study. Thromb J 2016; 14: 46
    CrossrefPubMedGoogle Scholar
  • 31 Gi T, Kuroiwa Y, Yamashita A. et al. High signal intensity on diffusion-weighted images reflects acute phase of deep vein thrombus. Thromb Haemost 2020; 120 (10) 1463-1473
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 32 Nosaka M, Ishida Y, Kimura A, Kondo T. Time-dependent appearance of intrathrombus neutrophils and macrophages in a stasis-induced deep vein thrombosis model and its application to thrombus age determination. Int J Legal Med 2009; 123 (03) 235-240
    CrossrefPubMedGoogle Scholar
  • 33 McCaw ZR, Yin G, Wei L-J. Using the restricted mean survival time difference as an alternative to the hazard ratio for analyzing clinical cardiovascular studies. Circulation 2019; 140 (17) 1366-1368
    CrossrefPubMedGoogle Scholar
  • 34 Royston P, Parmar MKB. The use of restricted mean survival time to estimate the treatment effect in randomized clinical trials when the proportional hazards assumption is in doubt. Stat Med 2011; 30 (19) 2409-2421
    CrossrefPubMedGoogle Scholar
  • 35 Maekawa K, Shibata M, Nakajima H. et al. Erythrocyte-rich thrombus is associated with reduced number of maneuvers and procedure time in patients with acute ischemic stroke undergoing mechanical thrombectomy. Cerebrovasc Dis Extra 2018; 8 (01) 39-49
    CrossrefPubMedGoogle Scholar
  • 36 Sporns PB, Hanning U, Schwindt W. et al. Ischemic stroke: histological thrombus composition and pre-interventional CT attenuation are associated with intervention time and rate of secondary embolism. Cerebrovasc Dis 2017; 44 (5–6): 344-350
    CrossrefPubMedGoogle Scholar
  • 37 Yuki I, Kan I, Vinters HV. et al. The impact of thromboemboli histology on the performance of a mechanical thrombectomy device. AJNR Am J Neuroradiol 2012; 33 (04) 643-648
    CrossrefPubMedGoogle Scholar
  • 38 Novotny J, Oberdieck P, Titova A. et al. Thrombus NET content is associated with clinical outcome in stroke and myocardial infarction. Neurology 2020; 94 (22) e2346-e2360
    CrossrefPubMedGoogle Scholar
  • 39 Longstaff C, Varjú I, Sótonyi P. et al. Mechanical stability and fibrinolytic resistance of clots containing fibrin, DNA, and histones. J Biol Chem 2013; 288 (10) 6946-6956
    CrossrefPubMedGoogle Scholar
  • 40 Ducroux C, Di Meglio L, Loyau S. et al. Thrombus neutrophil extracellular traps content impair tPA-induced thrombolysis in acute ischemic stroke. Stroke 2018; 49 (03) 754-757
    CrossrefPubMedGoogle Scholar
  • 41 Laridan E, Denorme F, Desender L. et al. Neutrophil extracellular traps in ischemic stroke thrombi. Ann Neurol 2017; 82 (02) 223-232
    CrossrefPubMedGoogle Scholar
  • 42 Xie H, Kim K, Aglyamov SR. et al. Correspondence of ultrasound elasticity imaging to direct mechanical measurement in aging DVT in rats. Ultrasound Med Biol 2005; 31 (10) 1351-1359
    CrossrefPubMedGoogle Scholar
  • 43 Lee YU, Lee AY, Humphrey JD, Rausch MK. Histological and biomechanical changes in a mouse model of venous thrombus remodeling. Biorheology 2015; 52 (03) 235-245
    CrossrefPubMedGoogle Scholar
  • 44 Wong SL, Demers M, Martinod K. et al. Diabetes primes neutrophils to undergo NETosis, which impairs wound healing. Nat Med 2015; 21 (07) 815-819
    CrossrefPubMedGoogle Scholar
  • 45 Porrello A, Leslie PL, Harrison EB. et al. Factor XIIIA-expressing inflammatory monocytes promote lung squamous cancer through fibrin cross-linking. Nat Commun 2018; 9 (01) 1988
    CrossrefPubMedGoogle Scholar
  • 46 Niesten JM, van der Schaaf IC, van Dam L. et al. Histopathologic composition of cerebral thrombi of acute stroke patients is correlated with stroke subtype and thrombus attenuation. PLoS One 2014; 9 (02) e88882
    CrossrefPubMedGoogle Scholar
  • 47 Broussalis E, Trinka E, Hitzl W, Wallner A, Chroust V, Killer-Oberpfalzer M. Comparison of stent-retriever devices versus the Merci retriever for endovascular treatment of acute stroke. AJNR Am J Neuroradiol 2013; 34 (02) 366-372
    CrossrefPubMedGoogle Scholar
  • 48 Kim BJ, Kim JS. Ischemic stroke subtype classification: an Asian viewpoint. J Stroke 2014; 16 (01) 8-17
    CrossrefPubMedGoogle Scholar
  • 49 Jeong YH, Kevin B, Ahn JH. et al. Viscoelastic properties of clot formation and their clinical impact in East Asian versus Caucasian patients with stable coronary artery disease: a COMPARE-RACE analysis. J Thromb Thrombolysis 2021; 51 (02) 454-465
    CrossrefPubMedGoogle Scholar
  • 50 Qazi EM, Sohn SI, Mishra S. et al. Thrombus characteristics are related to collaterals and angioarchitecture in acute stroke. Can J Neurol Sci 2015; 42 (06) 381-388
    CrossrefPubMedGoogle Scholar