Abstract A new technique for measuring tissue cellular volume fraction, based on an improved modeling of the dynamic distribution of Gd‐DTPA and the effect of proton exchange, is described. This technique uses peak T 1 enhancement and blood Gd‐DTPA concentration to compute tissue cellular volume fraction. The feasibility of this technique is demonstrated with computer simulations that explore the limits of the simplifying assumptions (small vascular space, slow vascular‐extravascular proton exchange), and by direct comparison of MR and radionuclide cell fraction measurements made in muscle, liver, and tumor tissue in a rat model. The computer simulations demonstrate that with slow to intermediate vascular proton exchange and vascular fractions less than 10% the error in our cell fraction measurements typically remains less than 10%. Consistent with this prediction, a direct comparison between MR and radionuclide measurements of cell fraction demonstrates mean percent differences of less than 10%: 1.9% in muscle ( n = 4); 9% in liver ( n = 1) and 9.5% in tumor ( n = 4). Similarly, for all rats studied, the MR‐measured cell fractions (muscle (0.92 ± 0.04, n = 20); liver (0.76 ± 0.11, n = 9); whole tumor (0.69 ± 0.15, n = 22)) agree with the cell fraction values reported in the literature. In general, the authors' results demonstrate the feasibility of a simple method for measuring tissue cell fraction that is robust across a broad range of vascular volume, flow, and exchange conditions. Consequently, this method may prove to be an important means for evaluating the response of tumors to therapy.
We report a novel forward-model implementation of the full reference tissue model (fFTRM) that addresses the fast-exchange approximation employed by the simplified reference tissue model (SRTM) by incorporating a non-zero dissociation time constant from the specifically bound compartment. The forward computational approach avoided errors associated with noisy and nonorthogonal basis functions using an inverse linear model. Compared to analysis by a multilinear single-compartment reference tissue model (MRTM), fFTRM provided improved accuracy for estimation of binding potentials at early times in the scan, with no worse reproducibility across sessions. To test the model’s ability to identify small focal changes in binding potential using a within-scan challenge, we employed a nonhuman primate model of focal dopamine release elicited by deep brain microstimulation remote to ventral striatum (VST) during imaging by simultaneous PET and fMRI. The new model reported an unambiguously lateralized response in VST consistent with fMRI, whereas the MRTM-derived response was not lateralized and was consistent with simulations of model bias. The proposed model enabled better accuracy in PET [ 11 C]raclopride displacement studies and may also facilitate challenges sooner after injection, thereby recovering some sensitivity lost to radioactive decay of the PET tracer.
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTMultipolar correlations between reactants in crystalline and semiamorphous zeolitesJoseph B. Mandeville, Joshua Golub, and John J. KozakCite this: J. Phys. Chem. 1988, 92, 6, 1575–1584Publication Date (Print):March 1, 1988Publication History Published online1 May 2002Published inissue 1 March 1988https://doi.org/10.1021/j100317a041RIGHTS & PERMISSIONSArticle Views18Altmetric-Citations4LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (1 MB) Get e-Alerts
