{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T23:14:31Z","timestamp":1792019671960,"version":"4.4.0"},"reference-count":32,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2004,12,1]],"date-time":"2004-12-01T00:00:00Z","timestamp":1101859200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["NMR in Biomedicine"],"published-print":{"date-parts":[[2005,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The standard pharmacokinetic model for the analysis of MRI contrast reagent (CR) bolus\u2010tracking (B\u2010T) data assumes that the mean intracellular water molecule lifetime (\u03c4<jats:sub>i<\/jats:sub>) is effectively zero. This assertion is inconsistent with a considerable body of physiological measurements. Furthermore, theory and simulation show the B\u2010T time\u2010course shape to be very sensitive to the \u03c4<jats:sub>i<\/jats:sub> magnitude in the physiological range (hundreds of milliseconds to several seconds). Consequently, this standard model aspect can cause significant underestimations (factors of 2 or 3) of the two parameters usually determined: <jats:italic>K<\/jats:italic><jats:sup>trans<\/jats:sup>, the vascular wall CR transfer rate constant, and <jats:italic>v<\/jats:italic><jats:sub>e<\/jats:sub>, the CR distribution volume (the extracellular, extravascular space fraction). Analyses of animal model data confirmed two predicted behaviors indicative of this standard model inadequacy: (1) a specific temporal pattern for the mismatch between the best\u2010fitted curve and data; and (2) an inverse dependence of the curve's <jats:italic>K<\/jats:italic><jats:sup>trans<\/jats:sup> and <jats:italic>v<\/jats:italic><jats:sub>e<\/jats:sub> magnitudes on the CR dose. These parameters should be CR dose\u2010independent. The most parsimonious analysis allowing for realistic \u03c4<jats:sub>i<\/jats:sub> values is the \u2018shutter\u2010speed\u2019 model. Its application to the experimental animal data essentially eliminated the two standard model signature inadequacies. This paper reports the first survey for the extent of this \u2018shutter\u2010speed effect\u2019 in human data. Retrospective analyses are made of clinical data chosen from a range of pathology (the active multiple sclerosis lesion, the invasive ductal carcinoma breast tumor, and osteosarcoma in the leg) that provides a wide variation, particularly of <jats:italic>K<\/jats:italic><jats:sup>trans<\/jats:sup>. The signature temporal mismatch of the standard model is observed in all cases, and is essentially eliminated by use of the shutter\u2010speed model. Pixel\u2010by\u2010pixel maps show that parameter values from the shutter\u2010speed analysis are increased by more than a factor of 3 for some lesion regions. This endows the lesions with very high contrast, and reveals heterogeneities that are often not seen in the standard model maps. Normal muscle regions in the leg allow validation of the shutter\u2010speed model <jats:italic>K<\/jats:italic><jats:sup>trans<\/jats:sup>, <jats:italic>v<\/jats:italic><jats:sub>e<\/jats:sub>, and \u03c4<jats:sub>i<\/jats:sub> magnitudes, by comparison with results of previous careful rat leg studies not possible for human subjects. Copyright \u00a9 2004 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/nbm.938","type":"journal-article","created":{"date-parts":[[2004,12,1]],"date-time":"2004-12-01T12:52:25Z","timestamp":1101905545000},"page":"173-185","source":"Crossref","is-referenced-by-count":80,"title":["Evidence for shutter\u2010speed variation in CR bolus\u2010tracking studies of human pathology"],"prefix":"10.1002","volume":"18","author":[{"given":"Thomas E.","family":"Yankeelov","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William D.","family":"Rooney","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan P.","family":"Dyke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alina","family":"Tudorica","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing\u2010Huei","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason A.","family":"Koutcher","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"Jr","given":"Charles S.","family":"Springer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2004,12]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.1880070113"},{"key":"e_1_2_1_3_2","first-page":"419","article-title":"Functional magnetic resonance imaging in oncology for diagnosis and therapy monitoring","volume":"2","author":"Knopp MV","year":"2003","journal-title":"Mol. 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