{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T04:17:03Z","timestamp":1789186623939,"version":"build-2803163510"},"reference-count":52,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T00:00:00Z","timestamp":1758067200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000697","name":"Rhodes Scholarships","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000697","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014748","name":"Clarendon Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100014748","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/S021507\/1"],"award-info":[{"award-number":["EP\/S021507\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","award":["DSG\u2010193252"],"award-info":[{"award-number":["DSG\u2010193252"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>\n                      A precise understanding of the interplay between cerebral blood flow (CBF) and blood oxygen level\u2010dependent (BOLD) fMRI signals is essential for advancing cerebrovascular research. Although calibrated BOLD approaches often rely on arterial spin labelling (ASL) to estimate CBF, alternative validation using transcranial Doppler ultrasound (TCD) has not been explored. This study aims to determine whether a simplified hemodynamic model and linear regression can accurately characterize the relationship between TCD\u2010derived CBF velocity and BOLD\u2010fMRI responses during a ramp CO\n                      <jats:sub>2<\/jats:sub>\n                      stimulus. We hypothesized that both models would provide robust fits within the moderate partial pressure of end\u2010tidal carbon dioxide (PETCO\n                      <jats:sub>2<\/jats:sub>\n                      ) and BOLD signal ranges tested.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Twenty\u2010five healthy participants underwent two sessions. In session 1, right middle cerebral artery velocity (MCAv) was acquired using clinical TCD. In session 2, 3\u2009T BOLD\u2010fMRI data were collected. Both sessions used a ramp PETCO\n                      <jats:sub>2<\/jats:sub>\n                      protocol with deep breaths followed by 5% and 10% CO\n                      <jats:sub>2<\/jats:sub>\n                      . Data processing included motion correction, spatial smoothing, fieldmap correction, high\u2010pass filtering, and PETCO\n                      <jats:sub>2<\/jats:sub>\n                      alignment with smoothed MCAv (MCA ) and BOLD signals from the right parietal lobe. A simplified hemodynamic model and linear regression were applied to assess the MCA \u2010BOLD relationship, with model performance evaluated by R\n                      <jats:sup>2<\/jats:sup>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Final analysis included 21 participants. The hemodynamic model produced consistent fits (R\n                      <jats:sup>2<\/jats:sup>\n                      \u2009\u2265\u20090.69). Linear regression showed strong agreement between MCA  and BOLD (R\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u20090.759).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Both modeling approaches successfully linked TCD\u2010derived MCA  and BOLD\u2010fMRI responses during hypercapnia. These findings support the use of TCD as a complementary surrogate for CBF in BOLD calibration and cerebrovascular research.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mrm.70091","type":"journal-article","created":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T19:09:34Z","timestamp":1758136174000},"page":"939-950","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Transcranial\n                    <scp>Doppler<\/scp>\n                    ultrasound validation of\n                    <scp>BOLD<\/scp>\n                    \u2010\n                    <scp>fMRI<\/scp>\n                    cerebral blood flow relationship"],"prefix":"10.1002","volume":"95","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4658-9925","authenticated-orcid":false,"given":"Genevieve","family":"Hayes","sequence":"first","affiliation":[{"name":"IBME, Department of Engineering Science University of Oxford   Oxford 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