@article {Whisenant1196, author = {Jennifer Whisenant and Jason Williams and Hakmook Kang and Lori Arlinghaus and Richard Abramson and Vandana Abramson and Kareem Fakhoury and Anuradha Chakravarthy and Thomas Yankeelov}, title = {PERCIST measurements from prone and supine FDG-PET/CT of the breast are statistically identical}, volume = {60}, number = {supplement 1}, pages = {1196--1196}, year = {2019}, publisher = {Society of Nuclear Medicine}, abstract = {1196Objectives: Supine is the standard position for whole-body PET acquisition. However, patients are scanned in the prone position during breast MRI, as this improves visibility of breast tissue and the axilla. With the emergence of PET/MRI scanners that integrate functional information from PET and morphological and kinetic information from MRI, it is of great interest to determine if the prognostic utility of prone PET is equivalent to supine. This study compared PERCIST measurements between prone and supine FDG-PET/CT in patients with locally advanced breast cancer, as well as the ability of each scan position to predict pathologic complete response (pCR). Methods: Forty-seven patients were enrolled and received up to six cycles of neoadjuvant therapy (NAT) prior to surgery. All patients provided written informed consent. FDG-PET/CT prone and supine scans were performed at: baseline (t0;n=46), after Cycle 2 (t2; n=10), or after all NAT (t3; n=19). Four metrics were measured, including the standardized uptake value (SUV) normalized to lean body mass (SUL): SUVmax, SUVpeak, SULmax, and SULpeak from regions of interest drawn over the primary tumor and the right hepatic lobe (background). For all metrics, PERCIST measurements were performed for each baseline image that had at least one corresponding post-baseline scan. Receiver operating characteristic (ROC) analysis for the prediction of pCR was performed for each PERCIST measurement using a logistic regression model that included age and tumor size as covariates; areas under the ROC curve (AUC) were subsequently calculated. A Wilcoxon signed rank test was used to evaluate statistically significant differences. Results: SUV and SUL metrics measured from prone data were statistically lower than the supine values (p\<0.001). However, the prone and supine values were highly correlated, and a Bland Altman analysis revealed that the two measures were consistent. No statistically significant differences in SULmax or SULpeak were observed between PERCIST measurements from prone and supine images (Figure 1; p=0.61 and p=0.83, respectively). Similar results were observed for both SUV metrics. Additionally, no statistical differences, as seen with overlapping 95\% confidence intervals, were observed in the AUC values for either SUV or SUL metric (Table 1). Conclusions: Prone SUV and SUL metrics were statistically different than supine metrics, yet the values were consistent. No significant differences in PERCIST measurements of SUV and SUL metrics were observed between scan positions. Additionally, AUCs between prone and supine data were not different at predicting pCR in patients with locally advanced breast cancer. Research Support. National Cancer Institute for funding U01 CA142565, 1U01 CA174706, P50 CA098131, P30 CA68485, CPRIT RR00015, and the Kleberg Foundation. View this table:Table 1. AUC values with 95\% Confidence Intervals (CI)}, issn = {0161-5505}, URL = {https://jnm.snmjournals.org/content/60/supplement_1/1196}, eprint = {https://jnm.snmjournals.org/content}, journal = {Journal of Nuclear Medicine} }