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Background: 18F-FES is an FDA-approved estrogen analogue PET imaging tracer (Cerianna) which measures tumor estrogen receptor (ER) expression at multiple tumor sites simultaneously and predicts response to endocrine therapy. 18F-FDG is a commonly used glucose PET imaging tracer which measures glycolytic metabolic activity in tumors. Elevated plasma ctDNA has been associated with an increased risk of relapse and can identify actionable genomic alterations. This pilot research study explored the relationship between somatic copy-number variants (CNVs) and cell-free DNA mass using low-pass-whole-genome (LPWG) ctDNA in the blood to FES and FDG PET/CT findings with both qualitative and quantitative image analysis in metastatic breast cancer patients. Methods: Two(2) 10ml Streck tubes were collected from 20 patients with metastatic ER+ breast cancer +/-30 days of their FDG-PET/CT scan (n=19) or their FES-PET/CT scan (n=9). 8 patients had both scans. Somatic mutations were assessed using comprehensive genomic profiling of tissue samples from 19 patients using the clinically validated UW-Oncoplex assay. Qualitative analysis included detection of LPWG ctDNA, presence of PIK3A mutations in tissue, and intensity of uptake in PET/CT imaging. LPWG ctDNA of blood samples evaluated ctDNA mass and CNVs that comprised at least 8% of total ctDNA. Total lesion glycolysis (TLG) in FDG scans and total lesion estrogen receptors (TLER) in FES scans were calculated using a dedicated workflow in MiM software (MiM Software Inc. Cleveland OH). Quantitative analysis included the circulating fraction (ctDNA), PET/CT SUVmax of the index lesion, number of lesions, TLG and TLER. For TLG, the threshold for determining measurable lesions was calculated using liver SULmean + 1.5*SD. The threshold for TLER was calculated using SUVmean of the mediastinal blood pool. The ctDNA fraction and the number of lesions for both FDG and FES were each ranked into 3 categories. FDG and FES data (SUVmax of index lesion, # of lesions, and TLG or TLER) were correlated to the calculated ctDNA fraction values. TLG and TLER were also correlated to each other. Results: ctDNA was classified as no ctDNA present (n=9), ctDNA present (n=8) and indeterminate (n=3). Average neoplastic ctDNA fraction was 0.114 (range 0.03-0.423). PIKC3A mutations were: 10 absent and 9 present. Ranked categories for ctDNA fraction, FDG TLG and FES TLER are shown in Table 1. Table 2 shows results of FDG and FES analysis and correlation with ctDNA. Ranked ctDNA findings correlated with both the FDG number of lesions (R2=0.69) and TLG (R2=0.83), but not the SUVmax of the index lesion (R2=0.29). Correlation decreased for ctDNA versus FES number of lesions (R2=0.51), TLER (R2=0.61), and SUVmax of index lesion (R2=0.16). TLG and TLER significantly correlated with the 8 patients that had both an FDG and FES PET/CT scan (R2=0.77). Conclusions: In this pilot study, FDG TLG showed a significant correlation with ctDNA. There is an encouraging association with ctDNA fraction and number of FDG lesions and with ctDNA fraction and extent of FES avid disease (TLER) in the 9 patients that had FES. Research Support: RG1005258 Table 1. Categorical rankings for qualitative analysis of ctDNA, TLG and TLER Table 2. FDG and FES imaging results and correlation with ctDNA Citation Format: Natasha Hunter, Lanell M. Peterson, Mark Muzi, Eric Q. Konnick, Jonathan Reichel, Paul Kinahan, Jennifer M. Specht, Rachel Yung, William R. Gwin, Hannah Linden, Christina Tran. Pilot study to evaluate circulating tumor DNA (ctDNA) to PET/CT imaging using 18F-Fluorodeoxyglucose (FDG) and 18F-Fluoroestradiol (FES) PET/CT imaging as biomarkers in patients with metastatic breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-03-25.

Multiparameter quantitative imaging incorporates anatomical, functional, and/or behavioral biomarkers to characterize tissue, detect disease, identify phenotypes, define longitudinal change, or predict outcome. Multiple imaging parameters are sometimes considered separately but ideally are evaluated collectively. Often, they are transformed as Likert interpretations, ignoring the correlations of quantitative properties that may result in better reproducibility or outcome prediction. In this paper we present three use cases of multiparameter quantitative imaging: i) multidimensional descriptor, ii) phenotype classification, and iii) risk prediction. A fourth application based on data-driven markers from radiomics is also presented. We describe the technical performance characteristics and their metrics common to all use cases, and provide a structure for the development, estimation, and testing of multiparameter quantitative imaging. This paper serves as an overview for a series of individual articles on the four applications, providing the statistical framework for multiparameter imaging applications in medicine.

The use of positron emission tomography (PET) in radiation therapy (RT) is rapidly increasing in the areas of staging, segmentation, treatment planning, and response assessment. The most common radiotracer is

Prior reports have suggested that delayed 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) oncology imaging can improve the contrast-to-noise ratio (CNR) for known lesions. Our goal was to estimaterealistic bounds for lesion detectability for static measurements within 1 to 4 hours between FDG injectionand image acquisition. Tumor and normal tissue kinetic model parameters were estimated from dynamic PETstudies of patients with early-stage breast cancer. These parameters were used to generate time-activitycurves (TACs) for up to 4 hours, for which we assumed both nonreversible and reversible models with differ-ent rates of FDG dephosphorylation (k4). For each pair of tumor and normal tissue TACs, 600 PET sinogramrealizations were generated, and images were reconstructed using the ordered subsets expectation maximi-zation reconstruction algorithm. Test statistics for each tumor and normal tissue region of interest were outputfrom the computer model observers and evaluated using a receiver operating characteristic analysis, with thecalculated area under the curve (AUC) providing a measure of lesion detectability. For the nonreversiblemodel (k4 = 0), the AUC increased in 11 of 23 (48%) patients for 1 to 2 hours after the current standardpostradiotracer injection imaging window of 1 hour. This improvement was driven by increased tumor/nor-mal tissue contrast before the impact of increased noise that resulted from radiotracer decay began to domi-nate the imaging signal. Ask4was increased from 0 to 0.01 min−1, the time of maximum detectabilityshifted earlier, due to decreasing FDG concentration in the tumor lowering the CNR. These results imply thatdelayed PET imaging may reveal inconspicuous lesions that otherwise would have gone undetected.

The purpose of this study was to measure how (18)F-FDG PET standardized uptake values (SUVs) change over time in breast cancer and to examine the feasibility of a method to adjust for modest variations in the time of uptake measurement experienced in clinical practice.(18)F-FDG PET was performed as 60-min dynamic imaging with an additional image acquired at approximately 75 min after injection. For 20 newly diagnosed, untreated, locally advanced breast cancer patients, both the maximum SUV and the average SUV within the lesion were calculated with and without correction for blood glucose concentration. A linear regression analysis of the portion of the time-activity curves starting at 27 min after injection was used to estimate the rate of SUV change per minute during the interval from 27 to 75 min. The rate of SUV change with time was compared with the instantaneous SUV obtained at different times from 27 to 75 min.In untreated breast cancer, (18)F-FDG SUV values changed approximately linearly after 27 min at a rate ranging from -0.02 to 0.15 per minute. In addition, the rate of SUV change was linearly correlated with the instantaneous SUV measured at different times after injection (r(2) ranged from 0.82 to 0.94; P0.001). Using this information, an empirical linear model of SUV variation with time from injection to uptake measurement was formulated. The comparison method was then applied prospectively to a second set of 20 locally advanced breast cancer lesions not included in the initial analysis. The average percent error using the method to adjust for time differences was 8% and 5% for maximum SUVs and average SUVs ranging from 2 to 12.In untreated breast cancer, the SUV at any time point approximately predicts the rate of change of SUV over time. A comparison method based on this finding appears feasible and may improve the usefulness of the SUV by providing a means of comparing SUV acquired at different times after injection.

The availability of accurately aligned, whole-body anatomical (CT) and functional (PET) images could have a significant impact on diagnosing and staging malignant disease and on identifying and localizing metastases. Computer algorithms to align CT and PET images acquired on different scanners are generally successful for the brain, whereas image alignment in other regions of the body is more problematic.A combined PET/CT tomograph with the unique capability of acquiring accurately aligned functional and anatomical images for any part of the human body has been designed and built. The PET/CT scanner was developed as a combination of a Siemens Somatom AR.SP spiral CT and a partial-ring, rotating ECAT ART PET scanner. All components are mounted on a common rotational support within a single gantry. The PET and CT components can be operated either separately, or in combined mode. In combined mode, the CT images are used to correct the PET data for scatter and attenuation. Fully quantitative whole-body images are obtained for an axial extent of 100 cm in an imaging time of less than 1 h. When operated in PET mode alone, transmission scans are acquired with dual 137Cs sources.The scanner is fully operational and the combined device has been operated successfully in a clinical environment. Over 110 patients have been imaged, covering a range of different cancers, including lung, esophageal, head and neck, melanoma, lymphoma, pancreas, and renal cell. The aligned PET and CT images are used both for diagnosing and staging disease and for evaluating response to therapy. We report the first performance measurements from the scanner and present some illustrative clinical studies acquired in cancer patients.A combined PET and CT scanner is a practical and effective approach to acquiring co-registered anatomical and functional images in a single scanning session.

With the advantages of the increased sensitivity of fully 3-dimensional (3D) PET for whole-body imaging come the challenges of more complicated quantitative corrections and, in particular, an increase in the number of random coincidences. The most common method of correcting for random coincidences is the real-time subtraction of a delayed coincidence channel, which does not add bias but increases noise. An alternative approach is the postacquisition subtraction of a low-noise random coincidence estimate, which can be obtained either from a smoothed delayed coincidence sinogram or from a calibration scan or directly estimated. Each method makes different trade-offs between noise amplification, bias, and data-processing requirements. These trade-offs are dependent on activity injected, the local imaging environment (e.g., near the bladder), and the reconstruction algorithm. Methods: Using fully 3D whole-body simulations and phantom studies, we investigate how the gains in noise equivalent count (NEC) rates from using a noiseless random coincidence estimation method are translated to improvements in image signal-to-noise ratio (SNR). The image SNR, however, depends on the image reconstruction method and the local imaging environment. Results: We show that for fully 3D whole-body imaging using a particular set of scanners and clinical protocols, a low-noise estimate of random coincidences improves sinogram and image SNRs by approximately 15% compared with online subtraction of delayed coincidences. Conclusion: A 15% improvement in image SNR arises from a 32% increase in the NEC rate. Thus, scan duration can be reduced by 25% while still maintaining a constant total acquired NEC