{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:20:31Z","timestamp":1753881631574,"version":"3.41.2"},"reference-count":48,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"2","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["SVIN"],"published-print":{"date-parts":[[2023,3]]},"abstract":"<jats:sec xml:lang=\"en\">\n            <jats:title>Background<\/jats:title>\n            <jats:p xml:lang=\"en\">Vascular geometry plays an important role in stroke thrombectomy outcomes, but few studies have examined complex characteristics of vessel morphology. The authors hypothesized that engineered vessel cross\u2010section features could be used to predict thrombectomy first\u2010pass effect (FPE).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Methods<\/jats:title>\n            <jats:p xml:lang=\"en\">The authors analyzed computed tomography angiography and noncontrast computed tomagraphy from 50 patients with anterior circulation stroke thrombectomy. After segmentation, traditional metrics (vessel tortuosity and angulation) were calculated from vessel centerlines that were transformed into the same coordinate system and same region of interest. Univariate statistical analysis and geometric morphometrics were used to interrogate differences in geometry between cases that did and did not achieve FPE, which classical angulation and tortuosity did not quantify. To describe these differences, complex cross\u2010section features were engineered and quantified using a semiautomatic pipeline. Machine learning was used to train predictive models of FPE based on significant cross\u2010section features.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Results<\/jats:title>\n            <jats:p xml:lang=\"en\">\n              Only one local tortuosity metric was significantly different (\n              <jats:italic>q<\/jats:italic>\n              =0.019) between FPE and first\u2010pass failure cases. The most significant principal component score (\n              <jats:italic>q<\/jats:italic>\n              =0.012) from geometric morphometrics highlighted the M1 segment of the middle cerebral artery and upper cavernous internal carotid artery variation as morphological indicators of first\u2010pass outcome. Fifteen cross\u2010section features, corresponding to internal carotid artery and middle cerebral artery regions, were significantly different between cases that did and did not achieve FPE. Predictive models exhibited a strong prediction of FPE (area under the curve=0.98\u00b10.05) and outperformed models using traditional tortuosity and angulation features.\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p xml:lang=\"en\">Cross\u2010section features are a novel class of powerful and interpretable predictors of FPE, which could assist in treatment decision\u2010making.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/svin.122.000646","type":"journal-article","created":{"date-parts":[[2022,12,29]],"date-time":"2022-12-29T15:45:25Z","timestamp":1672328725000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":2,"title":["Vascular Cross\u2010Section, Rather Than Tortuosity, Can Classify First\u2010Pass Outcome of Mechanical Thrombectomy for Ischemic Stroke"],"prefix":"10.1161","volume":"3","author":[{"given":"Seyyed Mostafa","family":"Mousavi Janbeh Sarayi","sequence":"first","affiliation":[{"name":"Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY"},{"name":"Department of Mechanical and Aerospace Engineering University at Buffalo Buffalo NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Briana A.","family":"Santo","sequence":"additional","affiliation":[{"name":"Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY"},{"name":"Department of Biomedical Engineering University at Buffalo Buffalo NY"},{"name":"Department of Pathology and Anatomical Sciences University at Buffalo Buffalo NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad","family":"Waqas","sequence":"additional","affiliation":[{"name":"Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY"},{"name":"Department of Biomedical Engineering University at Buffalo Buffalo NY"},{"name":"Department of Neurosurgery University at Buffalo Buffalo NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andre","family":"Monterio","sequence":"additional","affiliation":[{"name":"Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY"},{"name":"Department of Neurosurgery University at Buffalo Buffalo NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sricharan S.","family":"Veeturi","sequence":"additional","affiliation":[{"name":"Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY"},{"name":"Department of Mechanical and Aerospace Engineering University at Buffalo Buffalo NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"TaJania D.","family":"Jenkins","sequence":"additional","affiliation":[{"name":"Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY"},{"name":"Department of Pathology and Anatomical Sciences University at Buffalo Buffalo NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elad I.","family":"Levy","sequence":"additional","affiliation":[{"name":"Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY"},{"name":"Department of Neurosurgery University at Buffalo Buffalo NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adnan H.","family":"Siddiqui","sequence":"additional","affiliation":[{"name":"Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY"},{"name":"Department of Neurosurgery University at Buffalo Buffalo NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincent M.","family":"Tutino","sequence":"additional","affiliation":[{"name":"Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY"},{"name":"Department of Mechanical and Aerospace Engineering University at Buffalo Buffalo NY"},{"name":"Department of Biomedical Engineering University at Buffalo Buffalo NY"},{"name":"Department of Pathology and Anatomical Sciences University at Buffalo Buffalo NY"},{"name":"Department of Neurosurgery University at Buffalo Buffalo NY"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"276","reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jstrokecerebrovasdis.2014.07.018"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1136\/neurintsurg-2018-014239"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCINTERVENTIONS.117.005362"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1136\/neurintsurg-2014-011125"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1161\/STROKEAHA.118.020700"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1136\/neurintsurg-2018-014127"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1136\/neurintsurg-2019-015215"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A7459"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1161\/STROKEAHA.117.020315"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1136\/neurintsurg-2018-014060"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.5853\/jos.2020.00227"},{"key":"e_1_3_2_13_2","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1002\/ca.22847","article-title":"A reassessment of cervical surface anatomy via CT scan in an adult population","volume":"30","author":"Shen XH","year":"2017","unstructured":"Shen XH, Xue HD, Chen Y, Wang M, Mirjalili SA, Zhang ZH, Ma C. A reassessment of cervical surface anatomy via CT scan in an adult population. Clin Anat. 2017;30:330\u2013335. https:\/\/doi.org\/10.1002\/CA.22847","journal-title":"Clin Anat"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1136\/neurintsurg-2018-014061"},{"key":"e_1_3_2_15_2","doi-asserted-by":"crossref","first-page":"i70","DOI":"10.1136\/neurintsurg-2012-010438","article-title":"Difficult catheter access to the occluded vessel during endovascular treatment of acute ischemic stroke is associated with worse clinical outcome","volume":"5","author":"Ribo M","year":"2013","unstructured":"Ribo M, Flores A, Rubiera M, Pagola J, Mendonca N, Rodriguez\u2010Luna D, Pi\u00f1eiro S, Meler P, Alvarez\u2010Sabin J, Molina CA. Difficult catheter access to the occluded vessel during endovascular treatment of acute ischemic stroke is associated with worse clinical outcome. J Neurointerv Surg. 2013;5:i70\u2010i73. https:\/\/doi.org\/10.1136\/neurintsurg\u20102012\u2010010438","journal-title":"J Neurointerv Surg"},{"key":"e_1_3_2_16_2","first-page":"67","article-title":"Arterial tortuosity","volume":"13","author":"Ciuric\u0103 S","year":"2019","unstructured":"Ciuric\u0103 S, Lopez\u2010Sublet M, Loeys BL, Radhouani I, Natarajan N, Vikkula M, Maas AHEM, Adlam D, Persu A. Arterial tortuosity. Hypertension. 2019;13:67\u201370. https:\/\/doi.org\/10.1161\/HYPERTENSIONAHA.118.11647","journal-title":"Hypertension"},{"key":"e_1_3_2_17_2","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1007\/s00234-020-02525-6","article-title":"Semi\u2010automated measurement of vascular tortuosity and its implications for mechanical thrombectomy performance","volume":"63","author":"Mokin M","year":"2020","unstructured":"Mokin M, Waqas M, Chin F, Rai H, Senko J, Sparks A, Ducharme RW, Springer M, Borlongan CV, Levy EI. Semi\u2010automated measurement of vascular tortuosity and its implications for mechanical thrombectomy performance. Neuroradiology. 2020;63:381\u2013389. https:\/\/doi.org\/10.1007\/S00234\u2010020\u201002525\u20106","journal-title":"Neuroradiology"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1161\/STROKEAHA.121.037904"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10072-020-04813-8"},{"key":"e_1_3_2_20_2","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1136\/neurintsurg-2013-010655","article-title":"Balloon\u2010assisted guide catheter positioning to overcome extreme cervical carotid tortuosity: technique and case experience","volume":"6","author":"Peeling L","year":"2014","unstructured":"Peeling L, Fiorella D. Balloon\u2010assisted guide catheter positioning to overcome extreme cervical carotid tortuosity: technique and case experience. J Neurointerv Surg. 2014;6:129\u2013133. https:\/\/doi.org\/10.1136\/NEURINTSURG\u20102013\u2010010655","journal-title":"J Neurointerv Surg"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.3340\/jkns.2018.0165"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.3340\/jkns.2019.0114"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1136\/neurintsurg-2013-010665"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A6866"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2012.05.001"},{"key":"e_1_3_2_26_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1096\/fasebj.2020.34.s1.05773","article-title":"Seckel syndrome and the skull: quantifying characteristics","volume":"34","author":"Lewis SA","year":"2020","unstructured":"Lewis SA, Inglis S, Doyle S. Seckel syndrome and the skull: quantifying characteristics. FASEB J. 2020;34:1. https:\/\/doi.org\/10.1096\/FASEBJ.2020.34.S1.05773","journal-title":"FASEB J"},{"key":"e_1_3_2_27_2","doi-asserted-by":"crossref","first-page":"725","DOI":"10.2174\/1567202617999201214230944","article-title":"Landmark\u2010based shape analysis on middle cerebral intracranial aneurysms: a geometric morphometrics approach to infer natural history","volume":"17","author":"Tutino VM","year":"2020","unstructured":"Tutino VM, Yan AJ, Veeturi SS, Patel TR, Rajabzadeh\u2010Oghaz H, Waqas M, Siddiqui AH, Tseng J, Kolega J. Landmark\u2010based shape analysis on middle cerebral intracranial aneurysms: a geometric morphometrics approach to infer natural history. Curr Neurovasc Res. 2020;17:725\u2013735. https:\/\/doi.org\/10.2174\/1567202617999201214230944","journal-title":"Curr Neurovasc Res"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1002\/wics.101"},{"key":"e_1_3_2_29_2","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1016\/j.ecolmodel.2004.06.043","article-title":"Use of principal component scores in multiple linear regression models for prediction of Chlorophyll\u2010a in reservoirs","volume":"181","author":"\u00c7amdev\u00fdren H","year":"2005","unstructured":"\u00c7amdev\u00fdren H, Dem\u00fdr N, Kanik A, Kesk\u00fdn S. Use of principal component scores in multiple linear regression models for prediction of Chlorophyll\u2010a in reservoirs. Ecol Modell. 2005;181:581\u2013589. https:\/\/doi.org\/10.1016\/J.ECOLMODEL.2004.06.043","journal-title":"Ecol Modell"},{"issue":"1","key":"e_1_3_2_30_2","first-page":"A15733","article-title":"Investigation of cerebral vessel geometric morphometrics for prediction of mechanical thrombectomy first pass outcome","volume":"146","author":"Santo B","year":"2022","unstructured":"Santo B, MJ Sarayi SMM, Baig A, Monteiro A, Waqas M, Siddiqui AH, & Tutino VM. Investigation of cerebral vessel geometric morphometrics for prediction of mechanical thrombectomy first pass outcome. Circulation. 2022;146(Suppl_1):A15733\u2013A15733.","journal-title":"Circulation"},{"key":"e_1_3_2_31_2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.4103\/bc.bc_5_21","article-title":"Vascular tortuosity in endovascular mechanical thrombectomy","volume":"7","author":"Farooq J","year":"2021","unstructured":"Farooq J, Lee JY. Vascular tortuosity in endovascular mechanical thrombectomy. Brain Circ. 2021;7:3. https:\/\/doi.org\/10.4103\/BC.BC_5_21","journal-title":"Brain Circ"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A4222"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.2176\/nmc.oa2012-0348"},{"key":"e_1_3_2_34_2","article-title":"Tortuosity of middle cerebral artery M1 segment and outcomes after mechanical thrombectomy","author":"Hoshino T","unstructured":"Hoshino T, Sato S, Kushi K, Tanaka Y, Mochizuki T, Ishikawa T, Shima S, Ryu B, Inoue T, Okada Y, et\u00a0al. Tortuosity of middle cerebral artery M1 segment and outcomes after mechanical thrombectomy. Interv Neuroradiol. Published Online First: 2022. https:\/\/doi.org\/10.1177\/15910199221104922","journal-title":"Interv Neuroradiol"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1161\/strokeaha.110.612986"},{"key":"e_1_3_2_36_2","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1177\/1591019917729364","article-title":"Influence of carotid tortuosity on internal carotid artery access time in the treatment of acute ischemic stroke","volume":"23","author":"Kaymaz ZO","year":"2017","unstructured":"Kaymaz ZO, Nikoubashman O, Brockmann MA, Wiesmann M, Brockmann C. Influence of carotid tortuosity on internal carotid artery access time in the treatment of acute ischemic stroke. Interv. Neuroradiol. 2017;23:583. https:\/\/doi.org\/10.1177\/1591019917729364","journal-title":"Interv. Neuroradiol"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1002\/ccd.23483"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1159\/000335123"},{"key":"e_1_3_2_39_2","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1177\/1591019919891295","article-title":"Cervical internal carotid artery tortuosity: a morphologic analysis of patients with acute ischemic stroke","volume":"26","author":"Benson JC","year":"2020","unstructured":"Benson JC, Brinjikji W, Messina SA, Lanzino G, Kallmes DF. Cervical internal carotid artery tortuosity: a morphologic analysis of patients with acute ischemic stroke. Interv Neuroradiol. 2020;26:216\u2013221. https:\/\/doi.org\/10.1177\/1591019919891295","journal-title":"Interv Neuroradiol"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1177\/23969873211067662"},{"key":"e_1_3_2_41_2","doi-asserted-by":"publisher","DOI":"10.5115\/acb.2017.50.3.163"},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.1161\/01.STR.27.12.2244"},{"key":"e_1_3_2_43_2","doi-asserted-by":"crossref","first-page":"1180","DOI":"10.1038\/jcbfm.2014.67","article-title":"Determination of vessel cross\u2010sectional area by thresholding in Radon space","volume":"34","author":"Gao YR","year":"2014","unstructured":"Gao YR, Drew PJ. Determination of vessel cross\u2010sectional area by thresholding in Radon space. J Cereb Blood Flow Metab. 2014;34:1180. https:\/\/doi.org\/10.1038\/JCBFM.2014.67","journal-title":"J Cereb Blood Flow Metab"},{"key":"e_1_3_2_44_2","first-page":"1","article-title":"Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network","volume":"11","author":"Fu F","year":"2020","unstructured":"Fu F, Wei J, Zhang M, Yu F, Xiao Y, Rong D, Shan Y, Li Y, Zhao C, Liao F, et\u00a0al. Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network. Nat Commun. 2020;11:1\u201312. https:\/\/doi.org\/10.1038\/s41467\u2010020\u201018606\u20102","journal-title":"Nat Commun"},{"key":"e_1_3_2_45_2","doi-asserted-by":"crossref","first-page":"537","DOI":"10.3389\/fnins.2020.00537","article-title":"A fully automated method for segmenting arteries and quantifying vessel radii on magnetic resonance angiography images of varying projection thickness","volume":"14","author":"Avadiappan S","year":"2020","unstructured":"Avadiappan S, Payabvash S, Morrison MA, Jakary A, Hess CP, Lupo JM. A fully automated method for segmenting arteries and quantifying vessel radii on magnetic resonance angiography images of varying projection thickness. Front Neurosci. 2020;14:537. https:\/\/doi.org\/10.3389\/FNINS.2020.00537\/BIBTEX","journal-title":"Front Neurosci"},{"key":"e_1_3_2_46_2","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1007\/s10278-010-9326-1","article-title":"A fast and fully automatic method for cerebrovascular segmentation on time\u2010of\u2010flight (TOF) MRA image","volume":"24","author":"Gao X","year":"2011","unstructured":"Gao X, Uchiyama Y, Zhou X, Hara T, Asano T, Fujita H. A fast and fully automatic method for cerebrovascular segmentation on time\u2010of\u2010flight (TOF) MRA image. J Digit Imaging. 2011;24:609\u2013625. https:\/\/doi.org\/10.1007\/S10278\u2010010\u20109326\u20101","journal-title":"J Digit Imaging"},{"key":"e_1_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.26961"},{"key":"e_1_3_2_48_2","first-page":"593","article-title":"Automatic segmentation of blood vessels from dynamic MRI datasets","volume":"10","author":"Kubassova O","year":"2007","unstructured":"Kubassova O. Automatic segmentation of blood vessels from dynamic MRI datasets. Med Image Comput Comput Assist Interv. 2007;10:593\u2013600. https:\/\/doi.org\/10.1007\/978\u20103\u2010540\u201075757\u20103_72\/COVER","journal-title":"Med Image Comput Comput Assist Interv"},{"key":"e_1_3_2_49_2","article-title":"Biologically informed clot histomics are predictive of acute ischemic stroke etiology","author":"Patel TR","year":"2022","unstructured":"Patel TR, Santo B, Jenkins TD, Waqas M, Monteiro A, Baig A, & Tutino VM. Biologically informed clot histomics are predictive of acute ischemic stroke etiology. Stroke Vasc Interv Neurol. 2022.","journal-title":"Stroke Vasc Interv Neurol"}],"container-title":["Stroke: Vascular and Interventional Neurology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ahajournals.org\/doi\/full\/10.1161\/SVIN.122.000646","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T15:36:53Z","timestamp":1715614613000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ahajournals.org\/doi\/10.1161\/SVIN.122.000646"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3]]},"references-count":48,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["10.1161\/SVIN.122.000646"],"URL":"https:\/\/doi.org\/10.1161\/svin.122.000646","relation":{},"ISSN":["2694-5746"],"issn-type":[{"type":"electronic","value":"2694-5746"}],"subject":[],"published":{"date-parts":[[2023,3]]},"assertion":[{"value":"2022-08-07","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-11-11","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-12-29","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e000646"}}