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To evaluate its significance in detecting methamphetamine (MA) dependence, this study used a multivariate pattern classification algorithm, ie, a support vector machine (SVM), to construct classifiers for discriminating MA\u2010dependent subjects from normal controls. Forty\u2010five MA\u2010dependent subjects, 45 normal controls, and 36 heroin\u2010dependent subjects were enrolled. Classifiers trained with ASL\u2010CBF data from the left or right cerebrum showed significant hemispheric asymmetry in their cross\u2010validated prediction performance (<jats:italic>P<\/jats:italic>\u00a0&lt;\u00a00.001 for accuracy, sensitivity, specificity, kappa, and area under the curve [AUC] of the receiver operating characteristics [ROC] curve). A classifier trained with ASL\u2010CBF data from all cerebral regions (bilateral hemispheres and corpus callosum) was able to differentiate MA\u2010dependent subjects from normal controls with a cross\u2010validated prediction accuracy, sensitivity, specificity, kappa, and AUC of 89%, 94%, 84%, 0.78, and 0.95, respectively. The discrimination map extracted from this classifier covered multiple brain circuits that either constitute a network related to drug abuse and addiction or could be impaired in MA\u2010dependence. The cerebral regions contribute most to classification include occipital lobe, insular cortex, postcentral gyrus, corpus callosum, and inferior frontal cortex. This classifier was also specific to MA\u2010dependence rather than substance use disorders in general (ie, 55.56% accuracy for heroin dependence). These results support the future utilization of ASL with an SVM\u2010based classifier for the diagnosis of MA\u2010dependence and could help improve the understanding of MA\u2010related neuropathology.<\/jats:p>","DOI":"10.1111\/adb.12705","type":"journal-article","created":{"date-parts":[[2019,1,9]],"date-time":"2019-01-09T09:49:14Z","timestamp":1547027354000},"page":"1254-1262","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Support vector machine\u2010based multivariate pattern classification of methamphetamine dependence using arterial spin labeling"],"prefix":"10.1111","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1553-7922","authenticated-orcid":false,"given":"Yadi","family":"Li","sequence":"first","affiliation":[{"name":"Department of Radiology, Ningbo Medical Center Lihuili Hospital Ningbo University  Ningbo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zaixu","family":"Cui","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Preventative Medicine, Zhejiang Provincial Key Laboratory of Pathophysiology Medical School of Ningbo University  Ningbo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haibo","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Radiology, Ningbo Medical Center Lihuili Hospital Ningbo University  Ningbo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianbing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Laboratory of Behavioral Neuroscience, Ningbo Addiction Research and Treatment Center  Ningbo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenwen","family":"Shen","sequence":"additional","affiliation":[{"name":"Laboratory of Behavioral Neuroscience, Ningbo Addiction Research and Treatment Center  Ningbo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenhua","family":"Zhou","sequence":"additional","affiliation":[{"name":"Laboratory of Behavioral Neuroscience, Ningbo Addiction Research and Treatment Center  Ningbo China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2019,1,9]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.158.12.2015"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainres.2010.12.017"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0278-5846(97)00079-1"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.drugalcdep.2005.09.011"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-4927(02)00004-5"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.11.035"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2016150789"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0071461"},{"key":"e_1_2_7_10_1","first-page":"1","article-title":"Association of frontal gray matter volume and cerebral perfusion in heroin addiction a multimodal neuroimaging study","volume":"4","author":"Denier N","year":"2013","journal-title":"Front Psych"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpsychires.2008.11.009"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-016-1218-z"},{"key":"e_1_2_7_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"e_1_2_7_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainres.2011.05.054"},{"key":"e_1_2_7_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.02.079"},{"key":"e_1_2_7_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2012.01.004"},{"key":"e_1_2_7_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.04.009"},{"key":"e_1_2_7_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22956"},{"key":"e_1_2_7_19_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2014.00425"},{"key":"e_1_2_7_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910400308"},{"key":"e_1_2_7_21_1","unstructured":"R Development Core Team(2011)R: a language and environment for statistical computing. 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