Volume 39, Issue 10 pp. 2033-2042

Original Research

Carotid Plaque Strain Indices Were Correlated With Cognitive Performance in a Cohort With Advanced Atherosclerosis, and Traditional Doppler Measures Showed no Association

Corresponding Author

Carol C. Mitchell PhD

[email protected]

orcid.org/0000-0001-6445-3306

Department of Medicine, Division of Cardiovascular Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Address correspondence to Carol C. Mitchell, PhD, Department of Medicine, Division of Cardiovascular Medicine, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI 53792, USA. E-mail: [email protected]

Search for more papers by this author

Stephanie M. Wilbrand PhD,

Stephanie M. Wilbrand PhD

Department of Neurological Surgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Thomas D. Cook PhD,

Thomas D. Cook PhD

Department of Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Nirvedh H. Meshram PhD,

Nirvedh H. Meshram PhD

orcid.org/0000-0003-4005-9798

Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin, USA

Department of Electrical and Computer Engineering, University of Wisconsin–Madison, Madison, Wisconsin, USA

Department of Biomedical Engineering, Columbia University, New York, New York, USA

Search for more papers by this author

Catherine N. Steffel MS,

Catherine N. Steffel MS

Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin, USA

Search for more papers by this author

Rebecca Nye MPH,

Rebecca Nye MPH

Department of Medicine, Division of Cardiovascular Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Tomy Varghese PhD,

Tomy Varghese PhD

orcid.org/0000-0003-3299-9130

Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin, USA

Department of Electrical and Computer Engineering, University of Wisconsin–Madison, Madison, Wisconsin, USA

Search for more papers by this author

Bruce P. Hermann PhD,

Bruce P. Hermann PhD

Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Robert J. Dempsey MD,

Robert J. Dempsey MD

Department of Neurological Surgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Carol C. Mitchell PhD,

Corresponding Author

Carol C. Mitchell PhD

[email protected]

orcid.org/0000-0001-6445-3306

Department of Medicine, Division of Cardiovascular Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Stephanie M. Wilbrand PhD,

Stephanie M. Wilbrand PhD

Department of Neurological Surgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Thomas D. Cook PhD,

Thomas D. Cook PhD

Department of Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Nirvedh H. Meshram PhD,

Nirvedh H. Meshram PhD

orcid.org/0000-0003-4005-9798

Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin, USA

Department of Electrical and Computer Engineering, University of Wisconsin–Madison, Madison, Wisconsin, USA

Department of Biomedical Engineering, Columbia University, New York, New York, USA

Search for more papers by this author

Catherine N. Steffel MS,

Catherine N. Steffel MS

Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin, USA

Search for more papers by this author

Rebecca Nye MPH,

Rebecca Nye MPH

Department of Medicine, Division of Cardiovascular Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Tomy Varghese PhD,

Tomy Varghese PhD

orcid.org/0000-0003-3299-9130

Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin, USA

Department of Electrical and Computer Engineering, University of Wisconsin–Madison, Madison, Wisconsin, USA

Search for more papers by this author

Bruce P. Hermann PhD,

Bruce P. Hermann PhD

Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

Robert J. Dempsey MD,

Robert J. Dempsey MD

Department of Neurological Surgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Search for more papers by this author

First published: 12 May 2020

https://doi.org/10.1002/jum.15311

Citations: 2

We thank Megan Evans for assistance with manuscript preparation and all of the participants in this study. This work was supported by National Institutes of Health (NIH) grant R01 NS064034; the National Heart, Lung, and Blood Institute (NHLBI) of the NIH, under award F31 HL 141008; and the NIH, under Ruth L. Kirschstein National Research Service Award T32 HL-007936, from the NHLBI to the University of Wisconsin–Madison Cardiovascular Research Center. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Tesla K40 graphics-processing unit used for carotid strain imaging. Support for carotid strain imaging research was also provided by the Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin–Madison with funding from the Wisconsin Alumni Research Foundation. We are grateful to Siemens Medical Solutions USA, Inc, for providing the S2000 Axius direct ultrasound research interface and software licenses. Drs Varghese, Hermann, and Dempsey have a patent (Varghese T, Dempsey RJ, Hermann BP. Characterization of vulnerable plaque using dynamic analysis. US2009/0198129 A1). Dr Mitchell reports other activities with Davies Publishing, Inc, textbook author, Elsevier, Wolters-Kluwer, author textbook chapters, and W. L. Gore & Associates contracted research grants to University of Wisconsin-Madison, outside the submitted work. All other authors report no disclosures.

Share a link

Email
Wechat
Bluesky

Abstract

Objectives

Traditional Doppler measures have been used to predict cognitive performance in patients with carotid atherosclerosis. Novel measures, such as carotid plaque strain indices (CPSIs), have shown associations with cognitive performance. We hypothesized that lower mean middle cerebral artery (MCA) velocities, higher bulb–internal carotid artery (ICA) velocities, the MCA pulsatility index (PI), and CPSIs would be associated with poorer cognitive performance in individuals with advanced atherosclerosis.

Methods

Neurocognitive testing, carotid ultrasound imaging, transcranial Doppler imaging, and carotid strain imaging were performed on 40 patients scheduled for carotid endarterectomy. Kendall tau correlations were used to examine relationships between cognitive tests and the surgical-side maximum peak systolic velocity (PSV; from the bulb, proximal, mid, or distal ICA), mean MCA velocity and PI, and maximum CPSIs (axial, lateral, and shear strain indices used to characterize plaque deformations with arterial pulsation). Cognitive measures included age-adjusted indices of verbal fluency, verbal and visual learning/memory, psychomotor speed, auditory attention/working memory, visuospatial construction, and mental flexibility.

Results

Participants had a median age of 71.0 (interquartile range, 9.75) years; 26 were male (65%), and 14 were female (35%). Traditional Doppler parameters, PSV, mean MCA velocity, and MCA PI did not predict cognitive performance (all P > .05). Maximum CPSIs were significantly associated with cognitive performance (P < .05).

Conclusions

Traditional velocity measurements of the maximum bulb-ICA PSV, mean MCA velocity, and PI were not associated with cognitive performance in patients with advanced atherosclerotic disease; however, maximum CPSIs were associated with cognitive performance. These findings suggest that cognition may be associated with unstable plaque rather than blood flow.

References

1Biedert S, Förstl H, Hewer W. The value of transcranial Doppler sonography in the differential diagnosis of Alzheimer disease vs multi-infarct dementia. Mol Chem Neuropathol 1993; 19: 15–23.
10.1007/BF03160165
CAS PubMed Web of Science® Google Scholar
2Caplan GA, Lan Z, Newton L, Kvelde T, McVeigh C, Hill MA. Transcranial Doppler to measure cerebral blood flow in delirium superimposed on dementia: a cohort study. J Am Med Dir Assoc 2014; 15: 355–360.
10.1016/j.jamda.2013.12.079
PubMed Web of Science® Google Scholar
3Claassen JA, Diaz-Arrastia R, Martin-Cook K, Levine BD, Zhang R. Altered cerebral hemodynamics in early Alzheimer disease: a pilot study using transcranial Doppler. J Alzheimers Dis 2009; 17: 621–629.
10.3233/JAD-2009-1079
PubMed Web of Science® Google Scholar
4Demarin V, Morovic S. Ultrasound subclinical markers in assessing vascular changes in cognitive decline and dementia. J Alzheimers Dis 2014; 42(suppl 3): S259–S266.
10.3233/JAD-132507
PubMed Web of Science® Google Scholar
5Demarin V, Zavoreo I, Kes VB. Carotid artery disease and cognitive impairment. J Neurol Sci 2012; 322: 107–111.
10.1016/j.jns.2012.07.008
PubMed Web of Science® Google Scholar
6Doepp F, Valdueza JM, Schreiber SJ. Transcranial and extracranial ultrasound assessment of cerebral hemodynamics in vascular and Alzheimer's dementia. Neurol Res 2006; 28: 645–649.
10.1179/016164106X130380
PubMed Web of Science® Google Scholar
7Gommer ED, Martens EG, Aalten P, et al. Dynamic cerebral autoregulation in subjects with Alzheimer's disease, mild cognitive impairment, and controls: evidence for increased peripheral vascular resistance with possible predictive value. J Alzheimers Dis 2012; 30: 805–813.
10.3233/JAD-2012-111628
PubMed Web of Science® Google Scholar
8Roher AE, Garami Z, Alexandrov AV, et al. Interaction of cardiovascular disease and neurodegeneration: transcranial Doppler ultrasonography and Alzheimer's disease. Neurol Res 2006; 28: 672–678.
10.1179/016164106X130470
PubMed Web of Science® Google Scholar
9Roher AE, Garami Z, Tyas SL, et al. Transcranial Doppler ultrasound blood flow velocity and pulsatility index as systemic indicators for Alzheimer's disease. Alzheimers Dement 2011; 7: 445–455.
10.1016/j.jalz.2010.09.002
PubMed Web of Science® Google Scholar
10Silvestrini M, Pasqualetti P, Baruffaldi R, et al. Cerebrovascular reactivity and cognitive decline in patients with Alzheimer disease. Stroke 2006; 37: 1010–1015.
10.1161/01.STR.0000206439.62025.97
PubMed Web of Science® Google Scholar
11Silvestrini M, Vernieri F, Pasqualetti P, et al. Impaired cerebral vasoreactivity and risk of stroke in patients with asymptomatic carotid artery stenosis. JAMA 2000; 283: 2122–2127.
10.1001/jama.283.16.2122
CAS PubMed Web of Science® Google Scholar
12Roher AE, Esh C, Rahman A, et al. Atherosclerosis of cerebral arteries in Alzheimer disease. Stroke 2004; 35: 2623–2627.
10.1161/01.STR.0000143317.70478.b3
PubMed Web of Science® Google Scholar
13 Executive Committee for the Asymptomatic Carotid Atherosclerosis Study. Endarterectomy for asymptomatic carotid artery stenosis. JAMA 1995; 273: 1421–1428.
10.1001/jama.1995.03520420037035
PubMed Web of Science® Google Scholar
14 North American Symptomatic Carotid Endarterectomy Trial Collaborators, Barnett HJM, Taylor DW, Haynes RB, et al. Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis. N Engl J Med 1991; 325: 445–453.
10.1056/NEJM199108153250701
PubMed Web of Science® Google Scholar
15Wang X, Jackson DC, Mitchell CC, et al. Estimation of ultrasound strain indices in carotid plaque and correlation to cognitive dysfunction. Conf Proc IEEE Eng Med Biol Soc 2014; 2014: 5627–5630.
CAS PubMed Google Scholar
16Wang X, Jackson DC, Mitchell CC, et al. Classification of symptomatic and asymptomatic patients with and without cognitive decline using non-invasive carotid plaque strain indices as biomarkers. Ultrasound Med Biol 2016; 42: 909–918.
10.1016/j.ultrasmedbio.2015.11.025
PubMed Web of Science® Google Scholar
17Wang X, Jackson DC, Varghese T, et al. Correlation of cognitive function with ultrasound strain indices in carotid plaque. Ultrasound Med Biol 2014; 40: 78–89.
10.1016/j.ultrasmedbio.2013.08.001
PubMed Web of Science® Google Scholar
18Wang X, Mitchell CC, Varghese T, et al. Improved correlation of strain indices with cognitive dysfunction with inclusion of adventitial layer with carotid plaque. Ultrason Imaging 2016; 38: 194–208.
10.1177/0161734615589252
CAS PubMed Web of Science® Google Scholar
19Jackson DC, Sandoval-Garcia C, Rocque BG, et al. Cognitive deficits in symptomatic and asymptomatic carotid endarterectomy surgical candidates. Arch Clin Neuropshycol 2016; 31: 1–7.
10.1093/arclin/acv082
PubMed Web of Science® Google Scholar
20Benton AL, Hamsher KD, Sivan AB. Multilingual Aphasia Examination: Manual of Instruction. Iowa City, IA: AJA Associates; 1994.
Google Scholar
21Ober BA, Dronkers NF, Koss E, Delis DC, Friedland RP. Retrieval from semantic memory in Alzheimer-type dementia. J Clin Exp Neuropsychol 1986; 8: 75–92.
10.1080/01688638608401298
CAS PubMed Web of Science® Google Scholar
22Wechsler D. Wechsler Adult Intelligence Scale. 4th ed. San Antonio, TX: Pearson; 2008.
Google Scholar
23Alexander MP, Stuss DT, Fansabedian N. California Verbal Learning Test: performance by patients with focal frontal and non-frontal lesions. Brain 2003; 126: 1493–1503.
10.1093/brain/awg128
CAS PubMed Web of Science® Google Scholar
24Brandt J, Benedict RHB. Hopkins Verbal Learning Test: Professional Manual. Lutz, FL: Psychological Assessment Resources; 2001.
Google Scholar
25Meyers JE, Meyers KR. Rey Complex Figure Test and Recognition Trial: Professional Manual. Odessa, TX: Psychological Assessment Resources; 1995.
Google Scholar
26 Natus Neurology Inc. SONARA® Systems and SONARA/tek® Systems User Manual. Middleton, WI: Natus Neurology Inc; 2013.
Google Scholar
27McCormick M, Varghese T, Wang X, Mitchell C, Kliewer MA, Dempsey RJ. Methods for robust in vivo strain estimation in the carotid artery. Phys Med Biol 2012; 57: 7329–7353.
10.1088/0031-9155/57/22/7329
CAS PubMed Web of Science® Google Scholar
28Meshram NH, Varghese T, Mitchell CC, et al. Quantification of carotid artery plaque stability with multiple region of interest based ultrasound strain indices and relationship with cognition. Phys Med Biol 2017; 62: 6341–6360.
10.1088/1361-6560/aa781f
CAS PubMed Web of Science® Google Scholar
29Meshram NH, Varghese T. GPU accelerated multilevel Lagrangian carotid strain imaging. IEEE Trans Ultrason Ferroelectr Freq Control 2018; 65: 1370–1379.
10.1109/TUFFC.2018.2841346
PubMed Web of Science® Google Scholar
30Dempsey RJ, Jackson DC, Wilbrand SM, et al. The preservation of cognition 1 year after carotid endarterectomy in patients with prior cognitive decline. Neurosurgery 2018; 82: 322–328.
10.1093/neuros/nyx173
PubMed Web of Science® Google Scholar
31Dempsey RJ, Varghese T, Jackson DC, et al. Carotid atherosclerotic plaque instability and cognition determined by ultrasound-measured plaque strain in asymptomatic patients with significant stenosis. J Neurosurg 2018; 128: 111–119.
10.3171/2016.10.JNS161299
PubMed Web of Science® Google Scholar
32Dempsey RJ, Vemuganti R, Varghese T, Hermann BP. A review of carotid atherosclerosis and vascular cognitive decline. Neurosurgery 2010; 67: 484–493.
10.1227/01.NEU.0000371730.11404.36
PubMed Web of Science® Google Scholar
33Grant EG, Benson CB, Moneta GL, et al. Carotid artery stenosis: gray-scale and Doppler US diagnosis—Society of Radiologists in Ultrasound Consensus Conference. Radiology 2003; 229: 340–346.
10.1148/radiol.2292030516
PubMed Web of Science® Google Scholar
34Nicolaides AN, Shifrin EG, Bradbury A, et al. Angiographic and duplex grading of internal carotid stenosis: can we overcome the confusion? J Endovasc Surg 1996; 3: 158–165.
10.1583/1074-6218(1996)003<0158:AADGIC>2.0.CO;2
CAS PubMed Web of Science® Google Scholar
35Salem MK, Bown MJ, Sayers RD, et al. Identification of patients with a histologically unstable carotid plaque using ultrasonic plaque image analysis. Eur J Vasc Endovasc Surg 2014; 48: 118–125.
10.1016/j.ejvs.2014.05.015
CAS PubMed Web of Science® Google Scholar
36Sabayan B, Jansen S, Oleksik AM, et al. Cerebrovascular hemodynamics in Alzheimer's disease and vascular dementia: a meta-analysis of transcranial Doppler studies. Ageing Res Rev 2012; 11: 271–277.
10.1016/j.arr.2011.12.009
PubMed Web of Science® Google Scholar
37Kidwell CS, el-Saden S, Livshits Z, Martin NA, Gleen TC, Saver JL. Transcranial Doppler pulsatility indices as a measure of diffuse small-vessel disease. J Neuroimaging 2001; 11: 229–235.
10.1111/j.1552-6569.2001.tb00039.x
CAS PubMed Web of Science® Google Scholar
38Mandani A, Bleletsky V, Tamayo A, Munoz C, Spence JD. High-risk asymptomatic carotid stenosis ulceration on 3D ultrasound vs TCD microemboli. Neurology 2011; 77: 744–750.
10.1212/WNL.0b013e31822b0090
PubMed Web of Science® Google Scholar
39Vinciguerra L, Lanza G, Puglisi V, et al. Transcranial Doppler ultrasound in vascular cognitive impairment–no dementia. PLoS One 2019; 14:e0216162.
10.1371/journal.pone.0216162
CAS PubMed Web of Science® Google Scholar
40Chen WH, Jin W, Lyu PY, et al. Carotid atherosclerosis and cognitive impairment in nonstroke patients. Chin Med J 2017; 130: 2375–2379.
PubMed Web of Science® Google Scholar
41Iadecola C. The pathobiology of vascular dementia. Neuron 2013; 80: 844–866.
10.1016/j.neuron.2013.10.008
CAS PubMed Web of Science® Google Scholar
42Kalaria RN. The pathology and pathophysiology of vascular dementia. Neuropharmacology 2018; 134: 226–239.
10.1016/j.neuropharm.2017.12.030
CAS PubMed Web of Science® Google Scholar
43Berman SE, Wang X, Mitchell CC, et al. The relationship between carotid artery plaque stability and white matter ischemic injury. Neuroimage Clin 2015; 9: 216–222.
10.1016/j.nicl.2015.08.011
PubMed Web of Science® Google Scholar
44Mitchell CC, Wilbrand SM, Kundu B, et al. Transcranial Doppler and microemboli detection: relationships to symptomatic status and histopathology findings. Ultrasound Med Biol 2017; 43: 1861–1867.
10.1016/j.ultrasmedbio.2017.04.025
PubMed Web of Science® Google Scholar
45Heaton RK, Miller SW, Taylor MJ, Grant I. Revised Comprehensive Norms for an Expanded Halstead Reitan Battery: Demographically Adjusted Neuropsychological Norms for African American and Caucasian Adults. Lutz, FL: Psychological Assessment Resources; 2004.
Google Scholar
46Strauss E, Sherman E, Spreen O. A Compendium of Neuropsychological Tests. 3rd ed. New York, NY: Oxford University Press; 2006.
Google Scholar
47Kaplan E, Goodglass H, Weintraub S. The Boston Naming Test. Philadelphia, PA: Lea & Febiger; 1983.
Google Scholar
48Kaplan EF, Goodglass H, Weintraub S. The Boston Naming Test. 2nd ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2001.
Google Scholar
49Mitchell C, Wilbrand SM, Cook TD, et al. Traditional Doppler measures do not predict cognition in a cohort with advanced atherosclerosis [abstract]. Stroke 2019; 50(suppl 1):WMP47.
10.1161/str.50.suppl_1.WMP47
Web of Science® Google Scholar

Citing Literature

Volume39, Issue10

October 2020

Pages 2033-2042

Carotid Plaque Strain Indices Were Correlated With Cognitive Performance in a Cohort With Advanced Atherosclerosis, and Traditional Doppler Measures Showed no Association

Abstract

Objectives

Methods

Results

Conclusions

References

Citing Literature

References

Information

About Wiley Online Library

Help & Support

Opportunities

Connect with Wiley

Carotid Plaque Strain Indices Were Correlated With Cognitive Performance in a Cohort With Advanced Atherosclerosis, and Traditional Doppler Measures Showed no Association

Abstract

Objectives

Methods

Results

Conclusions

References

Citing Literature

References

Related

Information