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Clinical Neuroradiology

02.01.2024 | Original Article

How Topographic Diffusion-Weighted Imaging Patterns can Predict the Potential Embolic Source

verfasst von: Y Yamamoto, Y Nagakane, E Tanaka, T Yamada, J Fujinami, T Ohara

Erschienen in: Clinical Neuroradiology

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Abstract

Purpose

To develop an imaging prediction model for patients with embolic stroke of undetermined source (ESUS), we investigated the association of topographic diffusion-weighted imaging (DWI) patterns with potential embolic sources (PES) identified by transesophageal echocardiography.

Methods

From a total of 992 consecutive patients with embolic stroke, 366 patients with the ESUS group were selected. ESUS was defined as no atrial fibrillation (Af) within 24h from admission and no PES after general examination. Clinical variables include age (> 80years, 70–80 years), sex, vascular risk factors and left atrial diameter > 4 cm. Age, sex and vascular risk factors adjusted odds ratio of each DWI for the different PESs were calculated. DWI was determined based on the arterial territories. Middle cerebral arteries were divided into 4 segments, i.e., M1–M4. Moreover, M2 segments were subdivided into superior and inferior branches.

Results

The 366 patients consisted of 168 with paroxysmal Af (pAf), 77 with paradoxical embolism, 71 with aortic embolism and 50 with undetermined embolism after transesophageal echocardiography. The variables adjusted odds ratio (OR) of internal carotid artery (OR: 12.1, p = 0.037), M1 (4.2, p = 0.001), inferior M2 (7.5, p = 0.0041) and multiple cortical branches (12.6, p < 0.0001) were significantly higher in patients with pAf. Striatocapsular infarction (12.5, p < 0.0001) and posterior inferior cerebellar artery infarcts (3.6, p = 0.018) were significantly associated with paradoxical embolism. Clinical variables adjusted OR of multiple small scattered infarcts (8.3, p < 0.0001) were significantly higher in patients with aortic embolism.

Conclusion

The associations of DWI with different PES have their distinctive characteristics and DWI along with clinical variables may help predict PES in patients with ESUS.
Literatur
1.
Hart RG, Diener HC, Coutts SB, Easton JD, Granger CB, O’Donnell MJ, et al. Cryptogenic Stroke/ESUS International Working Group. Embolic strokes of undetermined source: the case for a new clinical construct. Lancet Neurol. 2014;13:429–38.CrossRefPubMed
2.
Ntaios G, Papavasileiou V, Milionis H, Makaritsis K, Manios E, Spengos K, et al. Embolic strokes of undetermined source in the Athens stroke registry: a descriptive analysis. Stroke. 2015;46:176–81.CrossRefPubMed
3.
Hart RG, Catanese L, Perera KS, Makaritsis K, Manios E, Spengos K, et al. Embolic Stroke of Undetermined Source: A Systematic Review and Clinical Update. Stroke. 2017;48:867–72.CrossRefPubMed
4.
Saliba W, Gronich N, Barnett-Griness O, Rennert G. Usefulness of CHADS2 and CHA2DS2-VASc Scores in the Prediction of New-Onset Atrial Fibrillation: A Population-Based Study. Am J Med. 2016;129:843–9.CrossRefPubMed
5.
Alonso A, Roetker NS, Soliman EZ, Chen LY, Greenland P, Heckbert SR. Prediction of Atrial Fibrillation in a Racially Diverse Cohort: The Multi-Ethnic Study of Atherosclerosis (MESA). J Am Heart Assoc. 2016;5:e3077.CrossRefPubMedPubMedCentral
6.
Hulme OL, Khurshid S, Weng LC, Anderson CD, Wang EY, Ashburner JM, et al. Development and Validation of a Prediction Model for Atrial Fibrillation Using Electronic Health Records. JACC Clin Electrophysiol. 2019;5:1331–41.CrossRefPubMedPubMedCentral
7.
Sharobeam A, Churilov L, Parsons M, Donnan GA, Davis SM, Yan B. Patterns of Infarction on MRI in Patients with acute ischemic stroke and cardio-embolism: A Systematic Review and Meta-Analysis. Front Neurol. 2020;11:606521.CrossRefPubMedPubMedCentral
8.
Ryoo S, Chung J, Lee MI, Kim SJ, Lee JS, Kim GM, et al. An approach to working up cases of embolic stroke of undetermined source. J Am Heart Assoc. 2016;5:e2975.CrossRefPubMedPubMedCentral
9.
Chen CH, Lee M, Weng HH, Lee JD, Yang JT, Tsai YH, et al. Identification of magnetic resonance imaging features for the prediction of unrecognized atrial fibrillation in acute ischemic stroke. Front Neurol. 2022;13:952462.CrossRefPubMedPubMedCentral
10.
Adams HP Jr, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, 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;24:35–41.CrossRefPubMed
11.
Diener HC, Easton JD, Granger CB, Cronin L, Duffy C, Cotton D, RE-SPECT ESUS Investigators. Design of Randomized. Evaluation in secondary Stroke Prevention comparing the EfficaCy and safety of the oral Thrombin inhibitor dabigatran etexilate vs. acetylsalicylic acid in patients with Embolic Stroke of Undetermined Source (RE-SPECT ESUS). Int J Stroke. 2015;10:1309–12.CrossRefPubMed
12.
Mahagne MH, Lachaud S, Suissa L. Letter by Mahagne et al regarding article, “Embolic strokes of undetermined source in the Athens stroke registry: a descriptive analysis”. Stroke. 2015;46:e69.CrossRefPubMed
13.
Tateishi Y, Ueno Y, Tsujino A, Kuriki A, Kamiya Y, Shimizu T, et al. Cardiac and Echocardiographic Markers in Cryptogenic Stroke with Incidental Patent Foramen Ovale. J Stroke Cerebrovasc Dis. 2021;30:105892.CrossRefPubMed
14.
Sporns PB, Hanning U, Schwindt W, Velasco A, Minnerup J, Zoubi T, et al. Ischemic Stroke: What Does the Histological Composition Tell Us About the Origin of the Thrombus? Stroke. 2017;48:2206–10.CrossRefPubMed
15.
Jolugbo P, Ariëns RAS. Thrombus Composition and Efficacy of Thrombolysis and Thrombectomy in Acute Ischemic Stroke. Stroke. 2021;52:1131–42.CrossRefPubMedPubMedCentral
16.
Boeckh-Behrens T, Kleine JF, Zimmer C, Neff F, Scheipl F, Pelisek J, et al. Thrombus Histology Suggests Cardioembolic Cause in Cryptogenic Stroke. Stroke. 2016;47:1864–71.CrossRefPubMed
17.
Staessens S, Denorme F, Francois O, Desender L, Dewaele T, Vanacker P, et al. Structural analysis of ischemic stroke thrombi: histological indications for therapy resistance. Haematologica. 2020;105:498–507.CrossRefPubMedPubMedCentral
18.
Gács G, Mérei FT, Bodosi M. Balloon catheter as a model of cerebral emboli in humans. Stroke. 1982;13:39–42.CrossRefPubMed
19.
Tatu L, Moulin T, Bogousslavsky J, Duvernoy H. Arterial territories of human brain: brainstem and cerebellum. Neurology. 1996;47:1125–35.CrossRefPubMed
20.
Gibo H, Carver CC, Rhoton AL, Lenkey C, Mitchell RJ. Microsurgical anatomy of the middle cerebral artery. J Neurosurg. 1981;54:151–69.CrossRefPubMed
21.
Donnan GA, Bladin PF, Berkovic SF, Longley WA, Saling MM. The stroke syndrome of striatocapsular infarction. Brain. 1991;114:51–70.PubMed
22.
Kaesmacher J, Boeckh-Behrens T, Simon S, Maegerlein C, Kleine JF, Zimmer C, et al. Risk of Thrombus Fragmentation during Endovascular Stroke Treatment. Am J Neuroradiol. 2017;38:991–8.CrossRefPubMedPubMedCentral
23.
Goebel J, Gaida BJ, Wanke I, Kleinschnitz C, Koehrmann M, Forsting M, et al. Is Histologic Thrombus Composition in Acute Stroke Linked to Stroke Etiology or to Interventional Parameters? Am J Neuroradiol. 2020;41:650–7.CrossRefPubMedPubMedCentral
24.
Mukherjee D, Shadden SC. Inertial particle dynamics in large artery flows—Implications for modeling arterial embolisms. J Biomech. 2017;52:155–64.CrossRefPubMed
25.
Fabbri D, Long Q, Das S, Pinelli M. Computational modelling of emboli travel trajectories in cerebral arteries: influence of microembolic particle size and density. Biomech Model Mechanobiol. 2014;13:289–302.CrossRefPubMedPubMedCentral
26.
Aleman MM, Walton BL, Byrnes JR, Wolberg AS. Fibrinogen and red blood cells in venous thrombosis. Thromb Res. 2014;133(Suppl 1):S38–40.CrossRefPubMedPubMedCentral
27.
Boutet C, Rouffiange-Leclair L, Garnier P, Quenet S, Delsart D, Varvat J, et al. Brain magnetic resonance imaging findings in cryptogenic stroke patients under 60 years with patent foramen ovale. Eur J Radiol. 2014;83:824–8.CrossRefPubMed
28.
Chung JW, Park SH, Kim N, Kim WJ, Park JH, Ko Y, et al. Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification and vascular territory of ischemic stroke lesions diagnosed by diffusion-weighted imaging. J Am Heart Assoc. 2014;3:e1119.CrossRefPubMedPubMedCentral
29.
Lee SH, Cha JH, Jung IE, Yu SW, Moon JS, Cho KH, et al. Relationship between the Angle of the Posterior Inferior Cerebellar Artery and Cardioembolic Stroke. J Stroke Cerebrovasc Dis. 2019;28:693–8.CrossRefPubMed
30.
Kent DM, Ruthazer R, Weimar C, Mas JL, Serena J, Homma S, et al. An index to identify stroke-related vs incidental patent foramen ovale in cryptogenic stroke. Neurology. 2013;81:619–25.CrossRefPubMedPubMedCentral
31.
Kim SW, Kim YD, Chang HJ, Hong GR, Shim CY, Chung SJ, et al. Different infarction patterns in patients with aortic atheroma compared to those with cardioembolism or large artery atherosclerosis. J Neurol. 2018;265:151–8.CrossRefPubMed
32.
Ezzeddine MA, Primavera JM, Rosand J, Hedley-Whyte ET, Rordorf G. Clinical characteristics of pathologically proved cholesterol emboli to the brain. Neurology. 2000;54:1681–3.CrossRefPubMed
Metadaten
Titel
How Topographic Diffusion-Weighted Imaging Patterns can Predict the Potential Embolic Source
verfasst von
Y Yamamoto
Y Nagakane
E Tanaka
T Yamada
J Fujinami
T Ohara
Publikationsdatum
02.01.2024
Verlag
Springer Berlin Heidelberg
Erschienen in
Clinical Neuroradiology
Print ISSN: 1869-1439
Elektronische ISSN: 1869-1447
DOI
https://doi.org/10.1007/s00062-023-01366-z

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