{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T17:25:34Z","timestamp":1775064334236,"version":"3.50.1"},"reference-count":15,"publisher":"Journal of Neurosurgery Publishing Group (JNSPG)","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,8,1]]},"abstract":"<jats:sec>\n<jats:title>OBJECTIVE<\/jats:title>\n<jats:p>The objective of this study was to investigate the use of indocyanine green videoangiography with FLOW 800 hemodynamic parameters intraoperatively during superficial temporal artery\u2013middle cerebral artery (STA-MCA) bypass surgery to predict patency prior to anastomosis performance.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title>METHODS<\/jats:title>\n<jats:p>A retrospective and exploratory data analysis was conducted using FLOW 800 software prior to anastomosis to assess four regions of interest (ROIs; proximal and distal recipients and adjacent and remote gyri) for four hemodynamic parameters (speed, delay, rise time, and time to peak). Medical records were used to classify patients into flow and no-flow groups based on immediate or perioperative anastomosis patency. Hemodynamic parameters were compared using univariate and multivariate analyses. Principal component analysis was used to identify high risk of no flow (HRnf) and low risk of no flow (LRnf) groups, correlated with prospective angiographic follow-ups. Machine learning models were fitted to predict patency using FLOW 800 features, and the a posteriori effect of complication risk of those features was computed.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title>RESULTS<\/jats:title>\n<jats:p>A total of 39 cases underwent STA-MCA bypass surgery with complete FLOW 800 data collection. Thirty-five cases demonstrated flow after anastomosis revascularization and were compared with 4 cases with no flow after revascularization. Proximal and distal recipient speeds were significantly different between the no-flow and flow groups (proximal: 238.3 \u00b1 120.8 and 138.5 \u00b1 93.6, respectively [p &lt; 0.001]; distal: 241.0 \u00b1 117.0 and 142.1 \u00b1 103.8, respectively [p &lt; 0.05]). Based on principal component analysis, the HRnf group (n = 10) was characterized by high-flow speed (&gt; 75th percentile) in all ROIs, whereas the LRnf group (n = 10) had contrasting patterns. In prospective long-term follow-up, 6 of 9 cases in the HRnf group, including the original no-flow cases, had no or low flow, whereas 8 of 8 cases in the LRnf group maintained robust flow. Machine learning models predicted patency failure with a mean F1 score of 0.930 and consistently relied on proximal recipient speed as the most important feature. Computation of posterior likelihood showed a 95.29% chance of patients having long-term patency given a lower proximal speed.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title>CONCLUSIONS<\/jats:title>\n<jats:p>These results suggest that a high proximal speed measured in the recipient vessel prior to anastomosis can elevate the risk of perioperative no flow and long-term reduction of flow. With an increased dataset size, continued FLOW 800\u2013based ROI metric analysis could be used to guide intraoperative anastomosis site selection prior to anastomosis and predict patency outcome.<\/jats:p>\n<\/jats:sec>","DOI":"10.3171\/2024.4.jns24713","type":"journal-article","created":{"date-parts":[[2024,8,17]],"date-time":"2024-08-17T01:27:49Z","timestamp":1723858069000},"page":"1-10","source":"Crossref","is-referenced-by-count":7,"title":["Assessing superficial temporal artery\u2013middle cerebral artery anastomosis patency using FLOW 800 hemodynamics"],"prefix":"10.3171","author":[{"given":"Karl L.","family":"Sangwon","sequence":"first","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, UVA Health, Charlottesville, Virginia; and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel D.","family":"Wiggan","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruck","family":"Negash","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel A.","family":"Alber","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xujin Chris","family":"Liu","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Albert","family":"Liu","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Corinne","family":"Rabbin-Birnbaum","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vera","family":"Sharashidze","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jacob","family":"Baranoski","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eytan","family":"Raz","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"},{"name":"Radiology, NYU Langone Health, New York, New York;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maksim","family":"Shapiro","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"},{"name":"Radiology, NYU Langone Health, New York, New York;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Caleb","family":"Rutledge","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter Kim","family":"Nelson","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"},{"name":"Radiology, NYU Langone Health, New York, New York;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Howard","family":"Riina","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Russin","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Neurorestoration Center, USC Keck Hospital, Los Angeles, California"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric K.","family":"Oermann","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erez","family":"Nossek","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1754","reference":[{"issue":"2","key":"b1","series-title":"Skull Base","first-page":"133","article-title":"Superficial temporal artery to middle cerebral artery bypass","volume":"15","author":"Newell DW","year":"2005","unstructured":"Newell DW. 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