{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T03:41:31Z","timestamp":1791862891059,"version":"4.3.4"},"reference-count":30,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T00:00:00Z","timestamp":1703808000000},"content-version":"vor","delay-in-days":28,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"},{"start":{"date-parts":[[2023,12,30]],"date-time":"2023-12-30T00:00:00Z","timestamp":1703894400000},"content-version":"unspecified","delay-in-days":29,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61971451"],"award-info":[{"award-number":["61971451"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81671671"],"award-info":[{"award-number":["81671671"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61971451"],"award-info":[{"award-number":["61971451"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81671671"],"award-info":[{"award-number":["81671671"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Clinical Research Center for Medical Imaging In Hunan Province","award":["2020SK4001"],"award-info":[{"award-number":["2020SK4001"]}]},{"name":"Leading talents of scientific and technological innovation in Hunan Province in 2021","award":["2021RC4016"],"award-info":[{"award-number":["2021RC4016"]}]},{"DOI":"10.13039\/100016104","name":"Key Project of Research and Development Plan of Hunan Province","doi-asserted-by":"publisher","award":["2019SK2131"],"award-info":[{"award-number":["2019SK2131"]}],"id":[{"id":"10.13039\/100016104","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["Gen. Psychiatry"],"published-print":{"date-parts":[[2023,12]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Individual differences have been detected in individuals with opioid use disorders (OUD) in rehabilitation following protracted abstinence. Recent studies suggested that prediction models were effective for individual\u2010level prognosis based on neuroimage data in substance use disorders (SUD).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>This prospective cohort study aimed to assess neuroimaging biomarkers for individual response to protracted abstinence in opioid users using connectome\u2010based predictive modelling (CPM).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      One hundred and eight inpatients with OUD underwent structural and functional magnetic resonance imaging (fMRI) scans at baseline. The Heroin Craving Questionnaire (HCQ) was used to assess craving levels at baseline and at the 8\u2010month follow\u2010up of abstinence. CPM with leave\u2010one\u2010out cross\u2010validation was used to identify baseline networks that could predict follow\u2010up HCQ scores and changes in HCQ (HCQ\n                      <jats:sub>follow\u2010up<\/jats:sub>\n                      \u2212HCQ\n                      <jats:sub>baseline)<\/jats:sub>\n                      . Then, the predictive ability of identified networks was tested in a separate, heterogeneous sample of methamphetamine individuals who underwent MRI scanning before abstinence for SUD.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      CPM could predict craving changes induced by long\u2010term abstinence, as shown by a significant correlation between predicted and actual HCQ\n                      <jats:sub>follow\u2010up<\/jats:sub>\n                      (r=0.417, p&lt;0.001) and changes in HCQ (negative: r=0.334, p=0.002\uff1bpositive: r=0.233, p=0.038). Identified craving\u2010related prediction networks included the somato\u2010motor network (SMN), salience network (SALN), default mode network (DMN), medial frontal network, visual network and auditory network. In addition, decreased connectivity of frontal\u2010parietal network (FPN)\u2010SMN, FPN\u2010DMN and FPN\u2010SALN and increased connectivity of subcortical network (SCN)\u2010DMN, SCN\u2010SALN and SCN\u2010SMN were positively correlated with craving levels.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>These findings highlight the potential applications of CPM to predict the craving level of individuals after protracted abstinence, as well as the generalisation ability; the identified brain networks might be the focus of innovative therapies in the future.<\/jats:p>\n                  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