Classification of Symptomatic and Asymptomatic Patients with and without Cognitive Decline Using Non-invasive Carotid Plaque Strain Indices as Biomarkers
Abstract Vascular cognitive decline may be caused by micro-emboli generated by carotid plaque instability. We previously found that maximum strain indices in carotid plaque were significantly correlated with cognitive function. In the work described here, we examined these associations with a larger...
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description | Abstract Vascular cognitive decline may be caused by micro-emboli generated by carotid plaque instability. We previously found that maximum strain indices in carotid plaque were significantly correlated with cognitive function. In the work described here, we examined these associations with a larger sample size, as well as evaluated the performance of these maximum strain indices in predicting cognitive impairment. Ultrasound-based strain imaging and cognition assessment were conducted on 75 human patients. Patients underwent one of two standardized cognitive test batteries, either the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) or the National Institute of Neurologic Disorder and Stroke–Canadian Stroke Network (NINDS-CSN) Vascular Cognitive Impairment Harmonization Standards (60 min). Scores were standardized within each battery to allow these data to be combined across all participants. Radiofrequency signals for ultrasound strain imaging were acquired on the carotid arteries using either a Siemens Antares with a VFX 13-5 linear array transducer or a Siemens S2000 with an 18 L6 linear array transducer. The same hierarchical block-matching motion tracking algorithm developed in our laboratory was used to estimate accumulated axial, lateral, and shear strain indices in carotid plaque, with inclusion of adventitia regardless of the ultrasound system and transducer used. Associations between cognitive z -scores and maximum strain indices were examined using Pearson's correlation coefficients. Maximum strain indices were also employed to predict cognitive impairment using receiver operating characteristic analysis. All correlations between maximum strain indices and total cognition were statistically significant ( p |
doi_str_mv | 10.1016/j.ultrasmedbio.2015.11.025 |
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We previously found that maximum strain indices in carotid plaque were significantly correlated with cognitive function. In the work described here, we examined these associations with a larger sample size, as well as evaluated the performance of these maximum strain indices in predicting cognitive impairment. Ultrasound-based strain imaging and cognition assessment were conducted on 75 human patients. Patients underwent one of two standardized cognitive test batteries, either the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) or the National Institute of Neurologic Disorder and Stroke–Canadian Stroke Network (NINDS-CSN) Vascular Cognitive Impairment Harmonization Standards (60 min). Scores were standardized within each battery to allow these data to be combined across all participants. Radiofrequency signals for ultrasound strain imaging were acquired on the carotid arteries using either a Siemens Antares with a VFX 13-5 linear array transducer or a Siemens S2000 with an 18 L6 linear array transducer. The same hierarchical block-matching motion tracking algorithm developed in our laboratory was used to estimate accumulated axial, lateral, and shear strain indices in carotid plaque, with inclusion of adventitia regardless of the ultrasound system and transducer used. Associations between cognitive z -scores and maximum strain indices were examined using Pearson's correlation coefficients. Maximum strain indices were also employed to predict cognitive impairment using receiver operating characteristic analysis. All correlations between maximum strain indices and total cognition were statistically significant ( p < 0.05), indicating that these indices have good utility in predicting cognitive impairment. Maximum lateral strain indices provided an area under the curve of 0.85 for symptomatic patients and 0.68 for asymptomatic patients. Our results indicate the important relationship of maximum strain indices to cognitive function and the feasibility of using maximum strain indices to predict cognitive decline with inclusion of the adventitia layer into the segmentation of plaque.</description><identifier>ISSN: 0301-5629</identifier><identifier>EISSN: 1879-291X</identifier><identifier>DOI: 10.1016/j.ultrasmedbio.2015.11.025</identifier><identifier>PMID: 26778288</identifier><language>eng</language><publisher>England: Elsevier Inc</publisher><subject>Adult ; Adventitia ; Aged ; Aged, 80 and over ; Algorithms ; Asymptomatic Diseases ; Carotid Plaque ; Carotid Stenosis - complications ; Carotid Stenosis - diagnostic imaging ; Cognitive Dysfunction - complications ; Cognitive Dysfunction - diagnostic imaging ; Diagnosis, Differential ; Elasticity imaging ; Elasticity Imaging Techniques - methods ; Elastography ; Female ; Humans ; Male ; Middle Aged ; Motion tracking ; Multi-level ; Pattern Recognition, Automated - methods ; Radiology ; Reproducibility of Results ; Sensitivity and Specificity ; Strain imaging ; Vascular cognitive impairment</subject><ispartof>Ultrasound in medicine & biology, 2016-04, Vol.42 (4), p.909-918</ispartof><rights>World Federation for Ultrasound in Medicine & Biology</rights><rights>2016 World Federation for Ultrasound in Medicine & Biology</rights><rights>Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c720t-6cce3141f4d7e24aa82c5b44b15fae2e33695e4fe6078631e036a6f079232e783</citedby><cites>FETCH-LOGICAL-c720t-6cce3141f4d7e24aa82c5b44b15fae2e33695e4fe6078631e036a6f079232e783</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ultrasmedbio.2015.11.025$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,315,782,786,887,3552,27931,27932,46002</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26778288$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/1349695$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Xiao</creatorcontrib><creatorcontrib>Jackson, Daren C</creatorcontrib><creatorcontrib>Mitchell, Carol C</creatorcontrib><creatorcontrib>Varghese, Tomy</creatorcontrib><creatorcontrib>Wilbrand, Stephanie M</creatorcontrib><creatorcontrib>Rocque, Brandon G</creatorcontrib><creatorcontrib>Hermann, Bruce P</creatorcontrib><creatorcontrib>Dempsey, Robert J</creatorcontrib><title>Classification of Symptomatic and Asymptomatic Patients with and without Cognitive Decline Using Non-invasive Carotid Plaque Strain Indices as Biomarkers</title><title>Ultrasound in medicine & biology</title><addtitle>Ultrasound Med Biol</addtitle><description>Abstract Vascular cognitive decline may be caused by micro-emboli generated by carotid plaque instability. We previously found that maximum strain indices in carotid plaque were significantly correlated with cognitive function. In the work described here, we examined these associations with a larger sample size, as well as evaluated the performance of these maximum strain indices in predicting cognitive impairment. Ultrasound-based strain imaging and cognition assessment were conducted on 75 human patients. Patients underwent one of two standardized cognitive test batteries, either the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) or the National Institute of Neurologic Disorder and Stroke–Canadian Stroke Network (NINDS-CSN) Vascular Cognitive Impairment Harmonization Standards (60 min). Scores were standardized within each battery to allow these data to be combined across all participants. Radiofrequency signals for ultrasound strain imaging were acquired on the carotid arteries using either a Siemens Antares with a VFX 13-5 linear array transducer or a Siemens S2000 with an 18 L6 linear array transducer. The same hierarchical block-matching motion tracking algorithm developed in our laboratory was used to estimate accumulated axial, lateral, and shear strain indices in carotid plaque, with inclusion of adventitia regardless of the ultrasound system and transducer used. Associations between cognitive z -scores and maximum strain indices were examined using Pearson's correlation coefficients. Maximum strain indices were also employed to predict cognitive impairment using receiver operating characteristic analysis. All correlations between maximum strain indices and total cognition were statistically significant ( p < 0.05), indicating that these indices have good utility in predicting cognitive impairment. Maximum lateral strain indices provided an area under the curve of 0.85 for symptomatic patients and 0.68 for asymptomatic patients. Our results indicate the important relationship of maximum strain indices to cognitive function and the feasibility of using maximum strain indices to predict cognitive decline with inclusion of the adventitia layer into the segmentation of plaque.</description><subject>Adult</subject><subject>Adventitia</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Algorithms</subject><subject>Asymptomatic Diseases</subject><subject>Carotid Plaque</subject><subject>Carotid Stenosis - complications</subject><subject>Carotid Stenosis - diagnostic imaging</subject><subject>Cognitive Dysfunction - complications</subject><subject>Cognitive Dysfunction - diagnostic imaging</subject><subject>Diagnosis, Differential</subject><subject>Elasticity imaging</subject><subject>Elasticity Imaging Techniques - methods</subject><subject>Elastography</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Motion tracking</subject><subject>Multi-level</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Radiology</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Strain imaging</subject><subject>Vascular cognitive impairment</subject><issn>0301-5629</issn><issn>1879-291X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkstuEzEUhkcIREPhFZDVFZsJvszYYxaVSsqlUgWVQiV2luM5kzid2MH2BOVReFs8pFSBVTe-nd_nnN_-iuKM4CnBhL9dT4c-BR030C6sn1JM6ikhU0zrJ8WENEKWVJLvT4sJZpiUNafypHgR4xpjLDgTz4sTyoVoaNNMil-zXsdoO2t0st4h36H5frNNfpP3BmnXoot4dHCTR3Apop82rf6Ex4UfEpr5pbPJ7gBdgumtA3QbrVuiL96V1u10HEMzHXyyLbrp9Y8B0DzbsA5dudYaiEhH9N7mQuEOQnxZPOt0H-HV_Xxa3H788G32ubz--ulqdnFdGkFxKrkxwEhFuqoVQCutG2rqRVUtSN1poMAYlzVUHXAsGs4IYMY177CQlFEQDTstzg95t8Miv6jJ7oLu1TbY3MheeW3VvxFnV2rpd6oSomaS5QRnhwQ-JquisQnMynjnwCRFWCVzA1n05r5K8Nl5TGpjo4G-1w78EBUREstaUIYfIeWS05phkaXvDlITfIwBuoe2CVYjK2qtjllRIyuKEJVZyZdfHxt_uPoXjiy4PAggP__OQhjNgTPQ2jB6a719XJ3z_9KMeGTg-jvYQ1z7Ibj8wYqoSBVW85HaEVpSY8wloew3Sgjvvg</recordid><startdate>20160401</startdate><enddate>20160401</enddate><creator>Wang, Xiao</creator><creator>Jackson, Daren C</creator><creator>Mitchell, Carol C</creator><creator>Varghese, Tomy</creator><creator>Wilbrand, Stephanie M</creator><creator>Rocque, Brandon G</creator><creator>Hermann, Bruce P</creator><creator>Dempsey, Robert J</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QO</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>OTOTI</scope><scope>5PM</scope></search><sort><creationdate>20160401</creationdate><title>Classification of Symptomatic and Asymptomatic Patients with and without Cognitive Decline Using Non-invasive Carotid Plaque Strain Indices as Biomarkers</title><author>Wang, Xiao ; Jackson, Daren C ; Mitchell, Carol C ; Varghese, Tomy ; Wilbrand, Stephanie M ; Rocque, Brandon G ; Hermann, Bruce P ; Dempsey, Robert J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c720t-6cce3141f4d7e24aa82c5b44b15fae2e33695e4fe6078631e036a6f079232e783</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adult</topic><topic>Adventitia</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Algorithms</topic><topic>Asymptomatic Diseases</topic><topic>Carotid Plaque</topic><topic>Carotid Stenosis - complications</topic><topic>Carotid Stenosis - diagnostic imaging</topic><topic>Cognitive Dysfunction - complications</topic><topic>Cognitive Dysfunction - diagnostic imaging</topic><topic>Diagnosis, Differential</topic><topic>Elasticity imaging</topic><topic>Elasticity Imaging Techniques - methods</topic><topic>Elastography</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Motion tracking</topic><topic>Multi-level</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Radiology</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Strain imaging</topic><topic>Vascular cognitive impairment</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Xiao</creatorcontrib><creatorcontrib>Jackson, Daren C</creatorcontrib><creatorcontrib>Mitchell, Carol C</creatorcontrib><creatorcontrib>Varghese, Tomy</creatorcontrib><creatorcontrib>Wilbrand, Stephanie M</creatorcontrib><creatorcontrib>Rocque, Brandon G</creatorcontrib><creatorcontrib>Hermann, Bruce P</creatorcontrib><creatorcontrib>Dempsey, Robert J</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>OSTI.GOV</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Ultrasound in medicine & biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Xiao</au><au>Jackson, Daren C</au><au>Mitchell, Carol C</au><au>Varghese, Tomy</au><au>Wilbrand, Stephanie M</au><au>Rocque, Brandon G</au><au>Hermann, Bruce P</au><au>Dempsey, Robert J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Classification of Symptomatic and Asymptomatic Patients with and without Cognitive Decline Using Non-invasive Carotid Plaque Strain Indices as Biomarkers</atitle><jtitle>Ultrasound in medicine & biology</jtitle><addtitle>Ultrasound Med Biol</addtitle><date>2016-04-01</date><risdate>2016</risdate><volume>42</volume><issue>4</issue><spage>909</spage><epage>918</epage><pages>909-918</pages><issn>0301-5629</issn><eissn>1879-291X</eissn><abstract>Abstract Vascular cognitive decline may be caused by micro-emboli generated by carotid plaque instability. We previously found that maximum strain indices in carotid plaque were significantly correlated with cognitive function. In the work described here, we examined these associations with a larger sample size, as well as evaluated the performance of these maximum strain indices in predicting cognitive impairment. Ultrasound-based strain imaging and cognition assessment were conducted on 75 human patients. Patients underwent one of two standardized cognitive test batteries, either the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) or the National Institute of Neurologic Disorder and Stroke–Canadian Stroke Network (NINDS-CSN) Vascular Cognitive Impairment Harmonization Standards (60 min). Scores were standardized within each battery to allow these data to be combined across all participants. Radiofrequency signals for ultrasound strain imaging were acquired on the carotid arteries using either a Siemens Antares with a VFX 13-5 linear array transducer or a Siemens S2000 with an 18 L6 linear array transducer. The same hierarchical block-matching motion tracking algorithm developed in our laboratory was used to estimate accumulated axial, lateral, and shear strain indices in carotid plaque, with inclusion of adventitia regardless of the ultrasound system and transducer used. Associations between cognitive z -scores and maximum strain indices were examined using Pearson's correlation coefficients. Maximum strain indices were also employed to predict cognitive impairment using receiver operating characteristic analysis. All correlations between maximum strain indices and total cognition were statistically significant ( p < 0.05), indicating that these indices have good utility in predicting cognitive impairment. Maximum lateral strain indices provided an area under the curve of 0.85 for symptomatic patients and 0.68 for asymptomatic patients. Our results indicate the important relationship of maximum strain indices to cognitive function and the feasibility of using maximum strain indices to predict cognitive decline with inclusion of the adventitia layer into the segmentation of plaque.</abstract><cop>England</cop><pub>Elsevier Inc</pub><pmid>26778288</pmid><doi>10.1016/j.ultrasmedbio.2015.11.025</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Adventitia Aged Aged, 80 and over Algorithms Asymptomatic Diseases Carotid Plaque Carotid Stenosis - complications Carotid Stenosis - diagnostic imaging Cognitive Dysfunction - complications Cognitive Dysfunction - diagnostic imaging Diagnosis, Differential Elasticity imaging Elasticity Imaging Techniques - methods Elastography Female Humans Male Middle Aged Motion tracking Multi-level Pattern Recognition, Automated - methods Radiology Reproducibility of Results Sensitivity and Specificity Strain imaging Vascular cognitive impairment |
title | Classification of Symptomatic and Asymptomatic Patients with and without Cognitive Decline Using Non-invasive Carotid Plaque Strain Indices as Biomarkers |
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