Quantitative and simplified [18F] fluoroestradiol positron emission tomography (PET) measures of brain estrogen receptor expression.

Matilde Nerattini^1,2,3, Valentina Berti⁴, Dawn C Matthews⁵, Schantel Williams⁶, Caroline Andy⁷, Francesca Fauci⁶, Camila Boneu⁶, Trisha Ajila⁶, Silky Pahlajani^6,8, Michael Battista⁶, Randolph Andrews⁵, Alberto Pupi⁴, Joseph R Osborne⁸, Matthew Fink⁶, Roberta Diaz Brinton⁹, Jonathan P Dyke⁸, Lisa Mosconi^6,8

¹Department of Neurology, Weill Cornell Medicine, New York, NY, USA. matilde.nerattini@unifi.it.

²Department of Biomedical Experimental and Clinical Sciences "Mario Serio", University of Florence, Viale Morgagni, 50, Florence, 50134, FI, Italy. matilde.nerattini@unifi.it.

³Weill Cornell Neurology, 402 East 70th Street, New York, NY, 10021, USA. matilde.nerattini@unifi.it.

⁴Department of Biomedical Experimental and Clinical Sciences "Mario Serio", University of Florence, Viale Morgagni, 50, Florence, 50134, FI, Italy.

⁵ADM Diagnostics, Northbrook, IL, USA.

⁶Department of Neurology, Weill Cornell Medicine, New York, NY, USA.

⁷Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.

⁸Department of Radiology, Weill Cornell Medicine, New York, NY, USA.

⁹Department of Pharmacology and Neurology, University of Arizona, Tucson, AZ, USA.

PubMed PMC DOI PDF

Abstract

PURPOSE: Positron emission tomography (PET) with 16α-[18F]fluoro-17β-estradiol (18F-FES) allows for the in vivo assessment of brain estrogen receptor (ER) expression. This study examines brain 18F-FES uptake to define an optimal acquisition time for static late images suitable for clinical application. METHODS: Fifty-five healthy, 40-65-year-old women at different endocrine aging stages (n = 18 p…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free Account Sign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.