{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T20:48:25Z","timestamp":1789678105600,"version":"4.0.1"},"reference-count":66,"publisher":"American Medical Association (AMA)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Little is known about the associations of strict blood pressure (BP) control with microstructural changes in small vessel disease markers.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To investigate the regional associations of intensive vs standard BP control with small vessel disease biomarkers, such as white matter lesions (WMLs), fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF).<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n The Systolic Blood Pressure Intervention Trial (SPRINT) is a multicenter randomized clinical trial that compared intensive systolic BP (SBP) control (SBP target &amp;lt;120 mm Hg) vs standard control (SBP target &amp;lt;140 mm Hg) among participants aged 50 years or older with hypertension and without diabetes or a history of stroke. The study began randomization on November 8, 2010, and stopped July 1, 2016, with a follow-up duration of approximately 4 years. A total of 670 and 458 participants completed brain magnetic resonance imaging at baseline and follow-up, respectively, and comprise the cohort for this post hoc analysis. Statistical analyses for this post hoc analysis were performed between August 2020 and October 2022.<\/jats:p>\n <\/jats:sec>\n \n Interventions<\/jats:title>\n At baseline, 355 participants received intensive SBP treatment and 315 participants received standard SBP treatment.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n The main outcomes were regional changes in WMLs, FA, MD (in white matter regions of interest), and CBF (in gray matter regions of interest).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n At baseline, 355 participants (mean [SD] age, 67.7 [8.0] years; 200 men [56.3%]) received intensive BP treatment and 315 participants (mean [SD] age, 67.0 [8.4] years; 199 men [63.2%]) received standard BP treatment. Intensive treatment was associated with smaller mean increases in WML volume compared with standard treatment (644.5 mm\n 3<\/jats:sup>\n vs 1258.1 mm\n 3<\/jats:sup>\n ). The smaller mean increases were observed specifically in the deep white matter regions of the left anterior corona radiata (intensive treatment, 30.3 mm\n 3<\/jats:sup>\n [95% CI, 16.0-44.5 mm\n 3<\/jats:sup>\n ]; standard treatment, 80.5 mm\n 3<\/jats:sup>\n [95% CI, 53.8-107.2 mm\n 3<\/jats:sup>\n ]), left tapetum (intensive treatment, 11.8 mm\n 3<\/jats:sup>\n [95% CI, 4.4-19.2 mm\n 3<\/jats:sup>\n ]; standard treatment, 27.2 mm\n 3<\/jats:sup>\n [95% CI, 19.4-35.0 mm\n 3<\/jats:sup>\n ]), left superior fronto-occipital fasciculus (intensive treatment, 3.2 mm\n 3<\/jats:sup>\n [95% CI, 0.7-5.8 mm\n 3<\/jats:sup>\n ]; standard treatment, 9.4 mm\n 3<\/jats:sup>\n [95% CI, 5.5-13.4 mm\n 3<\/jats:sup>\n ]), left posterior corona radiata (intensive treatment, 26.0 mm\n 3<\/jats:sup>\n [95% CI, 12.9-39.1 mm\n 3<\/jats:sup>\n ]; standard treatment, 52.3 mm\n 3<\/jats:sup>\n [95% CI, 34.8-69.8 mm\n 3<\/jats:sup>\n ]), left splenium of the corpus callosum (intensive treatment, 45.4 mm\n 3<\/jats:sup>\n [95% CI, 25.1-65.7 mm\n 3<\/jats:sup>\n ]; standard treatment, 83.0 mm\n 3<\/jats:sup>\n [95% CI, 58.7-107.2 mm\n 3<\/jats:sup>\n ]), left posterior thalamic radiation (intensive treatment, 53.0 mm\n 3<\/jats:sup>\n [95% CI, 29.8-76.2 mm\n 3<\/jats:sup>\n ]; standard treatment, 106.9 mm\n 3<\/jats:sup>\n [95% CI, 73.4-140.3 mm\n 3<\/jats:sup>\n ]), and right posterior thalamic radiation (intensive treatment, 49.5 mm\n 3<\/jats:sup>\n [95% CI, 24.3-74.7 mm\n 3<\/jats:sup>\n ]; standard treatment, 102.6 mm\n 3<\/jats:sup>\n [95% CI, 71.0-134.2 mm\n 3<\/jats:sup>\n ]).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n This study suggests that intensive BP treatment, compared with standard treatment, was associated with a slower increase of WMLs, improved diffusion tensor imaging, and FA and CBF changes in several brain regions that represent vulnerable areas that may benefit from more strict BP control.<\/jats:p>\n <\/jats:sec>\n \n Trial Registration<\/jats:title>\n \n ClinicalTrials.gov Identifier:\n NCT01206062<\/jats:ext-link>\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2023.1055","type":"journal-article","created":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T11:01:11Z","timestamp":1677668471000},"page":"e231055","source":"Crossref","is-referenced-by-count":39,"title":["Association of Intensive vs Standard Blood Pressure Control With Regional Changes in Cerebral Small Vessel Disease Biomarkers"],"prefix":"10.1001","volume":"6","author":[{"given":"Tanweer","family":"Rashid","sequence":"first","affiliation":[{"name":"Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer\u2019s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karl","family":"Li","sequence":"additional","affiliation":[{"name":"Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer\u2019s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jon B.","family":"Toledo","sequence":"additional","affiliation":[{"name":"Department of Neurology, University of Florida, Gainesville"},{"name":"Department of Neurology, Houston Methodist Hospital, Houston, Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ilya","family":"Nasrallah","sequence":"additional","affiliation":[{"name":"Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia"},{"name":"Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas M.","family":"Pajewski","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sudipto","family":"Dolui","sequence":"additional","affiliation":[{"name":"Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Detre","sequence":"additional","affiliation":[{"name":"Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia"},{"name":"Department of Neurology, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David A.","family":"Wolk","sequence":"additional","affiliation":[{"name":"Department of Neurology, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hangfan","family":"Liu","sequence":"additional","affiliation":[{"name":"Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susan R.","family":"Heckbert","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, University of Washington, Seattle"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R. 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