{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T07:33:34Z","timestamp":1793345614974,"version":"4.5.0"},"reference-count":36,"publisher":"IOP Publishing","issue":"21","license":[{"start":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T00:00:00Z","timestamp":1793318400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T00:00:00Z","timestamp":1793318400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"Achievement Rewards for College Scientists Foundation","award":["Pat and John Anderson Scholarship"],"award-info":[{"award-number":["Pat and John Anderson Scholarship"]}],"id":[{"id":"https:\/\/ror.org\/054awkm93","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Clinical Center","award":["R01EY032222"],"award-info":[{"award-number":["R01EY032222"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2026,11,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective<\/jats:italic>\n                    . Quantitative retinal fluorescein videoangiography (FVA) can estimate extraction fraction (\n                    <jats:italic>E<\/jats:italic>\n                    ), but the 8-bit intensity resolution of clinical systems creates a dynamic-range tradeoff: preserving arterial input function (AIF) linearity can restrict tissue signal, particularly for pixel-level analysis. We developed a single-bolus correction method to broaden the usable acquisition range while maintaining\n                    <jats:italic>E<\/jats:italic>\n                    estimation accuracy.\n                    <jats:italic>Approach<\/jats:italic>\n                    . The method combined truncated-mean reconstruction when sufficient unsaturated arterial pixels remained with gamma-variate interpolation when saturation dominated the first-pass peak. Development simulations used four human-derived AIF templates, empirically characterized signal-dependent noise, and 20 paired realizations evaluated over arterial scaling factors\n                    <jats:italic>f<\/jats:italic>\n                    = 0.1\u20132.25. Tissue curves were generated using a distributed-transit-time AATH model and fitted using a plug-flow AATH model. The locked correction threshold was then evaluated by artificially clipping raw arterial-pixel time curves from 10 originally undersaturated FVAs without adding synthetic noise. Performance was compared with the clipped arterial mean, piecewise cubic Hermite interpolation, and gamma-variate interpolation alone.\n                    <jats:italic>Main results<\/jats:italic>\n                    . The combined method completed all 60 patient-by-clipping analyses and produced lower first-pass peak, normalized mean squared error (NMSE), and area-under-the-curve errors than the comparator methods under moderate-to-strong clipping. In kinetic simulations, mean absolute relative ROI\n                    <jats:italic>E<\/jats:italic>\n                    error with the uncorrected AIF increased from 17 \u00b1 9% at\n                    <jats:italic>f<\/jats:italic>\n                    = 1.25\u201360 \u00b1 20% at\n                    <jats:italic>f<\/jats:italic>\n                    = 2.25, whereas corrected-AIF error remained approximately 10%\u201320%. Single-pixel\n                    <jats:italic>E<\/jats:italic>\n                    error decreased as signal approached the detector ceiling, reached 17 \u00b1 11% at\n                    <jats:italic>f<\/jats:italic>\n                    = 1.75, and remained statistically similar across\n                    <jats:italic>f<\/jats:italic>\n                    = 0.8\u20132.0. No single-pixel fits failed at\n                    <jats:italic>f<\/jats:italic>\n                    \u2a7e 1.0.\n                    <jats:italic>Significance<\/jats:italic>\n                    . The correction framework converts modest AIF saturation from a restrictive acquisition limit into a manageable analytical condition. This broader operating range is valuable for 8-bit FVA, supporting acquisition near the detector ceiling to improve tissue signal and enable high-resolution\n                    <jats:italic>E<\/jats:italic>\n                    mapping without dual-bolus acquisition.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/aeb793","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T23:00:01Z","timestamp":1792623601000},"page":"215001","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Correction of arterial input-function saturation for extraction fraction estimation in retinal fluorescein videoangiography"],"prefix":"10.1088","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-8989-1593","authenticated-orcid":true,"given":"Sarah R","family":"Vavrek","sequence":"first","affiliation":[{"name":"Biomedical Engineering, Illinois Institute of Technology"},{"name":"Western 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