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Quantification of in Vivo Tumor Uptake in Clinical Molecular Breast Imaging (MBI) Examinations


B Lopez

B Lopez*, M Rauch, B Adrada, S Bache, K Hess, S Kappadath, UT MD Anderson Cancer Center, Houston, TX

Presentations

WE-G-601-7 (Wednesday, August 2, 2017) 4:30 PM - 6:00 PM Room: 601


Purpose: To characterize the range, correlation, and changes of four quantitative metrics of tumor uptake in breast cancer patients undergoing neoadjuvant chemotherapy using Molecular Breast Imaging (MBI).

Methods: Twenty-five patients underwent MBI scans (CC and MLO with 8 mCi nominal administered activity) at 3 time points (pre-, mid-, post-chemotherapy). Lesion and background contours drawn by two radiologists in all images at all time points. Four quantitative metrics were calculated: 1) Average Tumor-to-Background Ratio (TBRave) = (Tumor Counts / Area) / (Background Counts / Area) in the geometric mean (GM) image; 2) Corrected Tumor-to-Background Ratio (TBRcorr) was similarly calculated using attenuation- and scatter-corrected GM images; 3) Fractional Activity Uptake (FAU) = (Tumor Uptake) / (Administered Activity), where uptake is the corrected counts normalized by the system sensitivity; and 4) Standardized Uptake Value (SUV) = (Tumor Uptake / Volume) / (Administered Activity) / (Patient Weight). The clinical range, correlations, and changes observed in these novel MBI metrics were quantified.

Results: Clinical ranges of the metrics defined as the median and (2.5%, 97.5%) quantile values across all time points and views are: TBRave = 2.14 (1.08, 4.75), TBRcorr = 3.19 (0.63, 14.47), FAU = 2.80e-4 (1.06e-5, 4.81e-3), and SUV = 1.57 (0.31, 6.69). The median values of all metrics decreased significantly after chemotherapy (p < 0.01). TBRcorr was positively correlated to TBRave (r = 0.54, p < 0.001), and the median change of TBR after scatter and attenuation correction was 33%. This TBR change was negatively correlated with tumor area (r = -0.35, p < 0.001) but not with breast thickness.

Conclusion: Quantitative tumor uptake metrics in clinical MBI show initial promise in assessing treatment response. Analysis is currently underway of differential variances between responders and non-responders. Future work may also demonstrate a role of these metrics in disease staging and planning treatment.

Funding Support, Disclosures, and Conflict of Interest: Research support in part by GE; SCK: Consultant for BTG


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