A retrospective study of branch atheromatous disease: Analyses of risk factors and prognosis

Abstract

The theory of branch atheromatous disease (BAD) has been commonly underused in clinical practice and research since it was proposed in 1989. In this study, we sought to explore clinical characteristics of its substypes and biomarkers for prognosis of BAD. A total of 176 consecutive patients with BAD were classified into two groups: paramedianpontine artery group (PPA group, n=70) and lenticulostriate artery group (LSA group, n=106). Bivariate analyses were used to explore the relationship between white matter hyperintensities (WMHs), National Institutes of Health Stroke Scale (NIHSS) scores and prognosis evaluated by the modified Rank Scale (mRS) at 6th month after stroke. The differences in prevalence of diabetes mellitus and a history of ischemic heart disease were statistically significant between PPA group and LSA group (χ²=8.255, P=0.004; χ²=13.402, P<0.001). The bivariate analyses demonstrated a positive correlation between NIHSS and poor prognosis in patients with BAD and in the two subtype groups, and a positive correlation between WMHs and poor prognosis in the PPA group. It is concluded that a significantly higher prevalence of diabetes mellitus and a history of ischemic heart disease exist in the PPA group than in the LSA group. In addition, high grades of NIHSS scores imply poor prognosis in patients with BAD and in the two subtype groups. Moreover, WMHs are a positive predictor for poor prognosis in patients in the PPA group.

Keywords

branch atheromatous disease / diabetes mellitus / white matter hyperintensities / prognosis / National Institutes of Health Stroke Scale

References

[1] CaplanLR. Intracranial branch atheromatous disease: a neglected, understudied, and underused concept. Neurology, 1989, 39(9): 1246-1250 PMID: 2671793

[2] QureshiAI, CaplanLR. Intracranial atherosclerosis. Lancet, 2014, 383(9921): 984-998 PMID: 24007975

[3] WarlowCP. Epidemiology of stroke. Lancet, 1998, 352: I1-I4

[4] SaccoRL, WolfPA, GorelickPB. Risk factors and their management for stroke prevention: outlook for 1999 and beyond. Neurology, 1999, 53: S15-S24 PMID: 10532644

[5] KaarisaloMM, RaihaI, SiveniusJ, et al. . Diabetes worsens the outcome of acute ischemic stroke. Diabetes Res Clin Pract, 2005, 699(3): 293-298

[6] KullerLH, LongstrethWJ, ArnoldAM, et al. . White matter hyperintensity on cranial magnetic resonance imaging: a predictor of stroke. Stroke, 2004, 35(8): 1821-1825 PMID: 15178824

[7] StreiflerJY, EliasziwM, BenaventeOR, et al. . Prognostic importance of leukoaraiosis in patients with symptomatic internal carotid artery stenosis. Stroke, 2002, 33(6): 1651-1655 PMID: 12053006

[8] ArsavaEM, RahmanR, RosandJ, et al. . Severity of leukoaraiosis correlates with clinical outcome after ischemic stroke. Neurology, 2009, 72(16): 1403-1410 PMID: 19380699 PMCID: 2677507

[9] HenonH, VroylandtP, DurieuI, et al. . Leukoaraiosis more than dementia is a predictor of stroke recurrence. Stroke, 2003, 4(12): 2935-2940

[10] DelBA, CiolliL, BorgheresiL, et al. . Is type 2 diabetes related to leukoaraiosis? an updated review. Acta Neurol Scand, 2015, 132(3): 147-155

[11] TamuraY, ArakiA. Diabetes mellitus and white matter hyperintensity. Geriatr Gerontol Int, 2015, 15: 34-42 PMID: 26671155

[12] MenX, WuA, ZhangB, et al. . Leukoaraiosis and NIHSS score help to differentiate subtypes of intracranial branch atheromatous disease in Southern Han Chinese patients with stroke. Neurol Sci, 2013, 34(10): 1727-1733 PMID: 23430170

[13] MenX, LiJ, ZhangB, et al. . Homocysteine and C-reactive protein associated with progression and prognosis of intracranial branch atheromatous disease. PLoS One, 2013, 8(9): e73030 PMID: 24039853 PMCID: 3770607

[14] VemmosKN, SpengosK, TsivgoulisG, et al. . Aetiopathogenesis and long-term outcome of isolated pontine infarcts. J Neurol, 2005, 252(2): 212-217 PMID: 15729529

[15] SaiaV, PantoniL. Progressive stroke in pontine infarction. Acta Neurol Scand, 2009, 120(4): 213-215 PMID: 19769777

[16] YamamotoY, NagakaneY, MakinoM, et al. . Aggressive antiplatelet treatment for acute branch atheromatous disease type infarcts: a 12-year prospective study. Int J Stroke, 2014, 9(3): E8 PMID: 24636587 PMCID: 4235423

[17] KernanWN, ViscoliCM, InzucchiSE, et al. . Prevalence of abnormal glucose tolerance following a transient ischemic attack or ischemic stroke. Arch Intern Med, 2005, 165(2): 227-233 PMID: 15668371

[18] MegherbiSE, MilanC, MinierD, et al. . Association between diabetes and stroke subtype on survival and functional outcome 3 months after stroke: data from the European BIOMED Stroke Project. Stroke, 2003, 34(3): 688-694 PMID: 12624292

[19] FullerJH, ShipleyMJ, RoseG, et al. . Coronary heart disease risk and impaired glucose tolerance. The Whitehall study. Lancet, 1980, 1(8183): 1373-1376 PMID: 6104171

[20] SubramanianG, SilvaJ, SilverFL, et al. . Risk factors for posterior compared to anterior ischemic stroke: An observational study of the Registry of the Canadian Stroke Network. Neuroepidemiology, 2009, 33(1): 12-16 PMID: 19299902

[21] KimJS, NahHW, ParkSM, et al. . Risk factors and stroke mechanisms in atherosclerotic stroke: intracranial compared with extracranial and anterior compared with posterior circulation disease. Stroke, 2012, 43(12): 3313-3318 PMID: 23160885

[22] MiyamotoN, TanakaY, UenoY, et al. . Comparison of clinical backgrounds with anterior versus posterior circulation infarcts. J Stroke Cerebrovasc Dis, 2010, 19(5): 393-397 PMID: 20472466

[23] BogousslavskyJ, RegliF, MaederP, et al. . The etiology of posterior circulation infarcts: A prospective study using magnetic resonance imaging and magnetic resonance angiography. Neurology, 1993, 43(8): 1528-1533 PMID: 8351006

[24] LongstrethWJ, ArnoldAM, BeauchampNJ, et al. . Incidence, manifestations, and predictors of worsening white matter on serial cranial magnetic resonance imaging in the elderly: the Cardiovascular Health Study. Stroke, 2005, 36(1): 56-61 PMID: 15569873

[25] RostNS, BottleA, LeeJM, et al. . Stroke severity is a crucial predictor of outcome: an international Prospective Validation Study. J Am Heart Assoc, 2016, 5(1): e002433 PMID: 26796252 PMCID: 4859362

[26] KonigIR, ZieglerA, BluhmkiE, et al. . Predicting long-term outcome after acute ischemic stroke: a simple index works in patients from controlled clinical trials. Stroke, 2008, 39(6): 1821-1826 PMID: 18403738

[27] MoodyDM, ThoreCR, AnstromJA, et al. . Quantification of afferent vessels shows reduced brain vascular density in subjects with leukoaraiosis. Radiology, 2004, 233(3): 883-890 PMID: 15564412

[28] O’SullivanM, LythgoeDJ, PereiraAC, et al. . Patterns of cerebral blood flow reduction in patients with ischemic leukoaraiosis. Neurology, 2002, 59(3): 321-326 PMID: 12177363

[29] HeistadDD, MayhanWG, CoyleP, et al. . Impaired dilatation of cerebral arterioles in chronic hypertension. Blood Vessels, 1990, 27(2-5): 258-262 PMID: 2242446

[30] GrefkesC, NowakDA, EickhoffSB, et al. . Cortical connectivity after subcortical stroke assessed with functional magnetic resonance imaging. Ann Neurol, 2008, 63(2): 236-246 PMID: 17896791

[31] YamanouchiH, SugiuraS, TomonagaM. Decrease in nerve fibres in cerebral white matter in progressive subcortical vascular encephalopathy of Binswanger type. An electron microscopic study. J Neurol, 1989, 236(7): 382-387 PMID: 2809638

[32] IshiharaM, KumitaS, HayashiH, et al. . Loss of interhemispheric connectivity in patients with lacunar infarction reflected by diffusion-weighted MR imaging and single-photon emission CT. AJNR Am J Neuroradiol, 1999, 20(6): 991-998 PMID: 10445434

[33] FisherCM. Binswanger’s encephalopathy: a review. J Neurol, 1989, 236(2): 65-79 PMID: 2651569

[34] ArakiE, NishikawaT. Oxidative stress: A cause and therapeutic target of diabetic complications. J Diabetes Investig, 2010, 1(3): 90-96 PMID: 24843413 PMCID: 4008021

[35] SinyorD, AmatoP, KaloupekDG, et al. . Post-stroke depression: relationships to functional impairment, coping strategies, and rehabilitation outcome. Stroke, 1986, 17(6): 1102-1107 PMID: 3810708

[36] de GrootJC, de LeeuwFE, OudkerkM, et al. . Periventricular cerebral white matter lesions predict rate of cognitive decline. Ann Neurol, 2002, 52(3): 335-341 PMID: 12205646

[37] NordahlCW, RanganathC, YonelinasAP, et al. . White matter changes compromise prefrontal cortex function in healthy elderly individuals. J Cogn Neurosci, 2006, 18(3): 418-429 PMID: 16513006 PMCID: 3776596

[38] TuttolomondoA, PintoA, SalemiG, et al. . Diabetic and non-diabetic subjects with ischemic stroke: Differences, subtype distribution and outcome. Nutr Metab Cardiovasc Dis, 2008, 18(2): 152-157 PMID: 17702553

[39] SchmidtR, FazekasF, KapellerP, et al. . MRI white matter hyperintensities: three-year follow-up of the Austrian Stroke Prevention Study. Neurology, 1999, 53(1): 132-139 PMID: 10408549

[40] PatankarT, WidjajaE, ChantH, et al. . Relationship of deep white matter hyperintensities and cerebral blood flow in severe carotid artery stenosis. Eur J Neurol, 2006, 13(1): 10-16 PMID: 16420388

[41] TatsumiS, YamamotoT. An autopsied case of an apparent pontine branch atheromatous disease. Eur Neurol, 2010, 63(3): 184-185 PMID: 20203514

[42] FisherCM, CaplanLR. Basilar artery branch occlusion: a cause of pontine infarction. Neurology, 1971, 21(9): 900-905 PMID: 5106254

[43] KleinIF, LavalleePC, MazighiM, et al. . Basilar artery atherosclerotic plaques in paramedian and lacunar pontine infarctions: a high-resolution MRI study. Stroke, 2010, 41(7): 1405-1409 PMID: 20538696

[44] ChungJW, KimBJ, SohnCH, et al. . Branch atheromatous plaque: a major cause of lacunar infarction (high-resolution MRI study). Cerebrovasc Dis Extra, 2012, 2(1): 36-44 PMID: 23060895 PMCID: 3468813

[45] CaiJ, HatsukamiTS, FergusonMS, et al. . In vivo quantitative measurement of intact fibrous cap and lipid-rich necrotic core size in atherosclerotic carotid plaque: comparison of high-resolution, contrast-enhanced magnetic resonance imaging and histology. Circulation, 2005, 112(22): 3437-3444 PMID: 16301346

[46] MeiB, LiuGZ, YangY, et al. . Comparative analysis of general characteristics of ischemic stroke of BAD and non-BAD CISS subtypes. J Huazhong Univ Sci Technol Med Sci, 2015, 35(6): 885-890 PMID: 26670441