PT - JOURNAL ARTICLE AU - Hsueh, Wei-Ann AU - Kesner, Amanda L. AU - Gangloff, Anne AU - Pegram, Mark D. AU - Beryt, Malgorzata AU - Czernin, Johannes AU - Phelps, Michael E. AU - Silverman, Daniel H.S. TI - Predicting Chemotherapy Response to Paclitaxel with <sup>18</sup>F-Fluoropaclitaxel and PET DP - 2006 Dec 01 TA - Journal of Nuclear Medicine PG - 1995--1999 VI - 47 IP - 12 4099 - http://jnm.snmjournals.org/content/47/12/1995.short 4100 - http://jnm.snmjournals.org/content/47/12/1995.full SO - J Nucl Med2006 Dec 01; 47 AB - Paclitaxel is used as a chemotherapy drug for the treatment of various malignancies, including breast, ovarian, and lung cancers. To evaluate the potential of a noninvasive prognostic tool for specifically predicting the resistance of tumors to paclitaxel therapy, we examined the tumoral uptake of 18F-fluoropaclitaxel (18F-FPAC) in mice bearing human breast cancer xenografts by using small-animal–dedicated PET and compared 18F-FPAC uptake with the tumor response to paclitaxel treatment. Methods: PET data were acquired after tail vein injection of approximately 9 MBq of 18F-FPAC in anesthetized nude mice bearing breast cancer xenografts. Tracer uptake in reconstructed images was quantified by region-of-interest analyses and compared with the tumor response, as measured by changes in tumor volume, after treatment with paclitaxel. Results: Mice with tumors that progressed demonstrated lower tumoral uptake of 18F-FPAC than mice with tumors that did not progress or that regressed (r = 0.55, P &lt; 0.02; n = 19), indicating that low 18F-FPAC uptake was a significant predictor of chemoresistance. Conversely, high 18F-FPAC uptake predicted tumor regression. This relationship was found for mice bearing xenografts from cell lines selected to be either sensitive or intrinsically resistant to paclitaxel in vitro. Conclusion: PET data acquired with 18F-FPAC suggest that this tracer holds promise for the noninvasive quantification of its distribution in vivo in a straightforward manner. In combination with approaches for examining other aspects of resistance, such quantification could prove useful in helping to predict subsequent resistance to paclitaxel chemotherapy of breast cancer.