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Kinetic modeling of dynamic PET data requires knowledge of tracer concentration in blood plasma, described by the arterial input function (AIF). Arterial blood sampling is the gold standard for AIF measurement, but is invasive and labour intensive. A number of methods have been proposed to accurately estimate the AIF directly from blood sampling and/or imaging data. Here we consider fitting a patient-adaptive mixture of historical population time course profiles to estimate individual AIFs. Travel time of a tracer atom from the injection site to the right ventricle of the heart is modeled as a realization from a Gamma distribution, and the time this atom spends in circulation before being sampled is represented by a subject-specific linear mixture of population profiles. These functions are estimated from independent population data. Individual AIFs are obtained by projection onto this basis of population profile components. The model incorporates knowledge of injection duration into the fit, allowing for varying injection protocols. Analyses of arterial sampling data from 18F-FDG, 15O-H2O and 18F-FLT clinical studies show that the proposed model can outperform reference techniques. The statistically significant gain achieved by using population data to train the basis components, instead of fitting these from the single individual sampling data, is measured on the FDG cohort. Kinetic analyses of simulated data demon- strate the reliability and potential benefit of this approach in estimating physiological parameters. These results are further supported by numerical simulations that demonstrate convergence and stability of the proposed technique under varying training population sizes and noise levels.

Purpose: Structural and functional alterations in tumor vasculature are thought to contribute to tumor hypoxia which is a primary driver of malignancy through its negative impact on the efficacy of radiation, immune surveillance, apoptosis, genomic stability, and accelerated angiogenesis. We performed a prospective, multicenter study to test the hypothesis that abnormal tumor vasculature and hypoxia, as measured with MRI and PET, will negatively impact survival in patients with newly diagnosed glioblastoma.Experimental Design: Prior to the start of chemoradiation, patients with glioblastoma underwent MRI scans that included dynamic contrast enhanced and dynamic susceptibility contrast perfusion sequences to quantitate tumor cerebral blood volume/flow (CBV/CBF) and vascular permeability (ktrans) as well as 18F-Fluoromisonidazole (18F-FMISO) PET to quantitate tumor hypoxia. ROC analysis and Cox regression models were used to determine the association of imaging variables with progression-free and overall survival.Results: Fifty patients were enrolled of which 42 had evaluable imaging data. Higher pretreatment 18F-FMISO SUVpeak (P = 0.048), mean ktrans (P = 0.024), and median ktrans (P = 0.045) were significantly associated with shorter overall survival. Higher pretreatment median ktrans (P = 0.021), normalized RCBV (P = 0.0096), and nCBF (P = 0.038) were significantly associated with shorter progression-free survival. SUVpeak [AUC = 0.75; 95% confidence interval (CI), 0.59–0.91], nRCBV (AUC = 0.72; 95% CI, 0.56–0.89), and nCBF (AUC = 0.72; 95% CI, 0.56–0.89) were predictive of survival at 1 year.Conclusions: Increased tumor perfusion, vascular volume, vascular permeability, and hypoxia are negative prognostic markers in newly diagnosed patients with gioblastoma, and these important physiologic markers can be measured safely and reliably using MRI and 18F-FMISO PET. Clin Cancer Res; 22(20); 5079–86. ©2016 AACR.

Supplemental Table 1: Participating centers that enrolled patients; Supplemental Table 2: Serial FMISO PET Imaging.

Glioblastoma multiforme (GBM) are aggressive and uniformly fatal primary brain tumors characterized by their diffuse invasion of the normal-appearing parenchyma peripheral to the clinical imaging abnormality. Hypoxia, a hallmark of aggressive tumor behavior often noted in GBMs, has been associated with resistance to therapy, poorer survival, and more malignant tumor phenotypes. Based on the existence of a set of novel imaging techniques and modeling tools, our objective was to assess a hypothesized quantitative link between tumor growth kinetics [assessed via mathematical models and routine magnetic resonance imaging (MRI)] and the hypoxic burden of the tumor [assessed via positron emission tomography (PET) imaging]. Our biomathematical model for glioma kinetics describes the spatial and temporal evolution of a glioma in terms of concentration of malignant tumor cells. This model has already been proven useful as a novel tool to dynamically quantify the net rates of proliferation (ρ) and invasion (D) of the glioma cells in individual patients. Estimates of these kinetic rates can be calculated from routinely available pretreatment MRI in vivo. Eleven adults with GBM were imaged preoperatively with 18F-fluoromisonidazole (FMISO)–PET and serial gadolinium-enhanced T1- and T2-weighted MRIs to allow the estimation of patient-specific net rates of proliferation (ρ) and invasion (D). Hypoxic volumes were quantified from each FMISO-PET scan following standard techniques. To control for tumor size variability, two measures of hypoxic burden were considered: relative hypoxia (RH), defined as the ratio of the hypoxic volume to the T2-defined tumor volume, and the mean intensity on FMISO-PET scaled to the blood activity of the tracer (mean T/B). Pearson correlations between RH and the net rate of cell proliferation (ρ) reached significance (P < 0.04). Moreover, highly significant positive correlations were found between biological aggressiveness ratio (ρ/D) and both RH (P < 0.00003) and the mean T/B (P < 0.0007). [Cancer Res 2009;69(10):4502–9]Major FindingsOverall, biological aggressiveness assessed by serial MRI is linked with hypoxic burden assessed on FMISO-PET using a novel biomathematical model for glioma growth and invasion. This study suggests that patient-specific modeling of growth kinetics can provide novel and valuable insight into the quantitative connections between disparate information provided by multimodality imaging.

Free Article from Quantitative Metrics of Net Proliferation and Invasion Link Biological Aggressiveness Assessed by MRI with Hypoxia Assessed by FMISO-PET in Newly Diagnosed Glioblastomas

Background: 18F-Fluorodeoxyglucose (FDG) has long been used for measuring tumor glycolytic activity in clinical PET imaging. The FDA recently approved 18F-Fluoroestradiol (FES) (Cerianna) as a PET imaging tracer for characterizing disease in patients with estrogen-receptor positive (ER+) breast cancer. As FES PET enters clinical practice it is important to establish its utility in the full population of hormone-receptor positive patients, including for patients with human epidermal growth factor 2 (HER2)-overexpressing tumors. Patients with HER2-positive metastatic breast cancer have historically been treated with combination cytotoxic and HER2-directed therapy, with the understanding that HER2 is the primary driver in this disease state. This retrospective study examined uptake in matched lesions for both FES and FDG PET and compared activity in patients with HER2 positive versus HER2 negative metastatic breast cancer. Methods: Patients were selected from the UW research database who had a history of biopsy-proven primary ER+ breast cancer as well as FES and FDG PET scans within 30 days. We examined FDG and FES scans and recorded SUVmax in up to 16 matched lesions between the two scans. Patients were also divided by HER2 status (+/-). In addition, a subset of patients who underwent at least 2 paired FDG and FES scans were reviewed. Results: 270 matched FDG and FES scans were analyzed in 216 patients with history of ER+, and HER2+ or HER2- breast cancer who were not part of an ongoing clinical trial. 158 (73%) had ductal disease, 38 (18%) had lobular disease. 183 (85%) had HER2- breast cancer. Of the 33 patients who had HER2+ breast cancer, 28 (85%) had ductal carcinoma. 40 patients underwent serial scans, allowing tracking over multiple timepoints. A total of 1323 metastatic sites were recorded (average = 5/scan (range 1,16)), with the majority (71%) representing bony lesions. No difference in quantitative FES or FDG avidity was observed between soft tissue and osseous sites. FES and FDG SUVmax were similar among patients with either HER2- or HER2+ breast cancer (Table 1). Among 40 patients with multiple paired FDG and FES scans, 26 (65%) had 2 scans while the remaining 14 had 3, with FES avidity remaining stable over time. There was no correlation between FES or FDG scans and HER2 status. Conclusion: In a cohort of ER+, HER2+ and HER2- patients undergoing concurrent FDG and FES PET scans, FDG and FES activity was similar regardless of HER2 status. FES uptake in both HER2- and HER2+ patients and stability over time in serial scans suggest that HER2 does not affect ER density. This suggests that in many patients with so-called “triple positive” disease, endocrine therapy may offer a powerful primary rather than ancillary tool in select patients. FES combined with FDG PET may offer utility in predicting and assessing response to therapy in this patient population. Table 1. FES and FDG uptake in patients with HER2- or HER2+ disease Citation Format: Natasha Hunter, Lanell M. Peterson, David A. Mankoff, Mark Muzi, Delphine Chen, William R. Gwin, Shaveta Vinayak, Nancy E Davidson, Jennifer M. Specht, Hannah Linden. Fluoroestradiol (FES) and Fluorodeoxyglucose (FDG) PET imaging in patients with ER+, HER2+ or HER2- 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 P2-03-17.

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.

ACRIN 6687, a multi-center clinical trial evaluating differential response of bone metastases to dasatinib in men with metastatic castration-resistant prostate cancer (mCRPC), used [18F]-fluoride (NaF) PET imaging. We extend previous ACRIN 6687 dynamic imaging results by examining NaF whole-body (WB) static SUV PET scans acquired after dynamic scanning. Eighteen patients underwent WB NaF imaging prior to and 12 weeks into dasatinib treatment. Regional VOI analysis of the most NaF avid bone metastases and an automated whole-body method using Quantitative Total Bone Imaging software (QTBI, AIQ Solutions, Inc., Madison, WI, USA) were used. We assessed differences in tumor and normal bone, between pre- and on-treatment dasatinib, and evaluated parameters in association with PFS and OS. Significant decrease in average SUVmax and average SUVpeak occurred in response to dasatinib. Univariate and multivariate analysis showed NaF uptake had significant association with PFS. Pharmacodynamic changes with dasatinib in tumor bone can be identified by WB NaF PET in men with mCRPC. WB PET has the benefit of examining the entire body and is less complicated than single FOV dynamic imaging.

Purpose Probe-based dynamic (4-D) imaging modalities capture breast intratumor heterogeneity both spatially and kinetically. Characterizing heterogeneity through tumor sub-populations with distinct functional behavior may elucidate tumor biology to improve targeted therapy specificity and enable precision clinical decision making. Methods We propose an unsupervised clustering algorithm for 4-D imaging that integrates Markov-Random Field (MRF) image segmentation with time-series analysis to characterize kinetic intratumor heterogeneity. We applied this to dynamic FDG PET scans by identifying distinct time-activity curve (TAC) profiles with spatial proximity constraints. We first evaluated algorithm performance using simulated dynamic data. We then applied our algorithm to a dataset of 50 women with locally advanced breast cancer imaged by dynamic FDG PET prior to treatment and followed to monitor for disease recurrence. A functional tumor heterogeneity (FTH) signature was then extracted from functionally distinct sub-regions within each tumor. Cross-validated time-to-event analysis was performed to assess the prognostic value of FTH signatures compared to established histopathological and kinetic prognostic markers. Results Adding FTH signatures to a baseline model of known predictors of disease recurrence and established FDG PET uptake and kinetic markers improved the concordance statistic (C-statistic) from 0.59 to 0.74 (p = 0.005). Unsupervised hierarchical clustering of the FTH signatures identified two significant (p p = 0.04) across the two phenotypes. Conclusions Our findings suggest that imaging markers of FTH add independent value beyond standard PET imaging metrics in predicting recurrence-free survival in breast cancer and thus merit further study.

Background: The histology and pattern of spread in lobular breast cancer has presented challenges in estimating extent of disease by traditional imaging methods. 18F-FES is an estrogen analogue PET imaging tracer which measures tumor ER expression at multiple tumor sites simultaneously. It is FDA approved in the US and will be available in 2021, pressing clinicians to define the role of FES in patients with breast cancer before use in practice. We compared quantitative FES-PET and clinical FDG-PET SUV uptake between patients with metastatic lobular carcinoma. Methods: Metastatic lesions in patients with primary ER+ lobular breast cancer were retrospectively evaluated with FES- and FDG-PET. SUV uptake was calculated in 38 patients enrolled in various studies at our institution. Up to ten matched lesions in each patient were assessed for a total of 192 lesions. Pairwise t-tests were performed to measure the difference between paired FES and FDG lesions. Results: Among metastatic breast cancer patients with lobular histology, 87% of patients had a positive FES scan. The majority of positive scans demonstrated uptake in all sites, with only a small percentage (6%) lacking FES uptake in at least one lesion. Uptake was noted in various metastatic tumor sites including bone (78%), soft tissue/lymph node (17%), breast (8%) and lung (1%). Mean (range) SUVmax in FES and FDG respectively was 3.38 (0.88, 9.08) and 4.14 (1.25, 9.49). Paired lesion analysis showed concordance between the two imaging modalities in lesions with low SUV uptake. FES and FDG uptake, however, could be discordant in both directions (FES > FDG, and FDG > FES) when there is higher level of uptake in at least one of the tracers. This was specifically seen in the 150 bone lesions, possibly indicating differences in lesion phenotype or response to therapy. Conclusions: FES and FDG scans demonstrate similar average SUV uptake in metastatic lobular breast cancer, suggesting that both scans have utility in detecting lobular histology. Our data suggests that at higher SUV values, FES may provide additional information to FDG. Discordance between FES and FDG SUV uptake in the same lesions, especially in bone, has important implications for staging and assessing response to therapy. Large prospective trials are needed to define the clinical utility of FES-PET in metastatic lobular breast cancer. Research Support: P01CA42045, R01CA72064, U01CA148131, DOD W81XWH-04-01-0675 Citation Format: Poorni Manohar, Lanell Peterson, Vicky Wu, Isaac Jenkins, Mark Muzi, Jennifer Specht, Delphine Chen, Jeanne Link, Kenneth Krohn, Paul Kinahan, David Mankoff, Hannah Linden. 18F-fluoroestradiol (fes) and 18f-fluorodeoxyglucose (fdg) pet imaging in metastatic lobular breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD6-10.

Long axial field-of-view (AFOV) PET scanners allow for full-body dynamic imaging in a single bed-position at very high sensitivity. However, the benefits for kinetic parameter estimation have yet to be studied. This work uses 1) a dynamic Geant4 Application for Tomographic Emission (GATE) simulation of [18F]-fluorothymidine (FLT) in a modified NEMA IQ phantom and 2) a lesion embedding study of spheres in a dynamic [18F]-fluorodeoxyglucose (FDG) human subject imaged on the PennPET Explorer. Both studies were designed using published kinetic data of lung and liver cancers and modeled using two tissue compartments. Data were reconstructed at various emulated doses. Sphere time-activity curves (TACs) were measured on resulting dynamic images, and TACs were fit using a two-tissue-compartment model ( $k_{4}\neq 0$ ) for the FLT study and both a two-tissue-compartment model ( $k_{4}=0$ ) and Patlak graphical analysis for the FDG study to estimate flux ( $K_{i}$ ) and delivery ( $K_{1}$ ) parameters. Quantification of flux and $K_{1}$ shows lower bias and better precision for both radiotracers on the long AFOV scanner, especially at low doses. Dynamic imaging on a long AFOV system can be achieved for a greater range of injected doses, as low as 0.5–2 mCi depending on the sphere size and flux, compared to a standard AFOV scanner, while maintaining good kinetic parameter estimation.

Quantitative imaging biomarkers (QIBs) provide medical image–derived intensity, texture, shape, and size features that may help characterize cancerous tumors and predict clinical outcomes. Successful clinical translation of QIBs depends on the robustness of their measurements. Biomarkers derived from positron emission tomography images are prone to measurement errors owing to differences in image processing factors such as the tumor segmentation method used to define volumes of interest over which to calculate QIBs. We illustrate a new Bayesian statistical approach to characterize the robustness of QIBs to different processing factors. Study data consist of 22 QIBs measured on 47 head and neck tumors in 10 positron emission tomography/computed tomography scans segmented manually and with semiautomated methods used by 7 institutional members of the NCI Quantitative Imaging Network. QIB performance is estimated and compared across institutions with respect to measurement errors and power to recover statistical associations with clinical outcomes. Analysis findings summarize the performance impact of different segmentation methods used by Quantitative Imaging Network members. Robustness of some advanced biomarkers was found to be similar to conventional markers, such as maximum standardized uptake value. Such similarities support current pursuits to better characterize disease and predict outcomes by developing QIBs that use more imaging information and are robust to different processing factors. Nevertheless, to ensure reproducibility of QIB measurements and measures of association with clinical outcomes, errors owing to segmentation methods need to be reduced.

Hypoxia is associated with resistance to radiotherapy and chemotherapy in malignant gliomas, and it can be imaged by positron emission tomography with 18F-fluoromisonidazole (18F-FMISO). Previous results for patients with brain cancer imaged with 18F-FMISO at a single center before conventional chemoradiotherapy showed that tumor uptake via T/Bmax (tissue SUVmax/blood SUV) and hypoxic volume (HV) was associated with poor survival. However, in a multicenter clinical trial (ACRIN 6684), traditional uptake parameters were not found to be prognostically significant, but tumor SUVpeak did predict survival at 1 year. The present analysis considered both study cohorts to reconcile key differences and examine the potential utility of adding radiomic features as prognostic variables for outcome prediction on the combined cohort of 72 patients with brain cancer (30 University of Washington and 42 ACRIN 6684). We used both 18F-FMISO intensity metrics (T/Bmax, HV, SUV, SUVmax, SUVpeak) and assessed radiomic measures that determined first-order (histogram), second-order, and higher-order radiomic features of 18F-FMISO uptake distributions. A multivariate model was developed that included age, HV, and the intensity of 18F-FMISO uptake. HV and SUVpeak were both independent predictors of outcome for the combined data set (P &lt, 001) and were also found significant in multivariate prognostic models (P &lt, 002 and P &lt, 001, respectively). Further model selection that included radiomic features showed the additional prognostic value for overall survival of specific higher order texture features, leading to an increase in relative risk prediction performance by a further 5%, when added to the multivariate clinical model..

BACKGROUND Diffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease. PURPOSE To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms. STUDY TYPE Prospective. POPULATION Thirty-three patients prospectively imaged prior to prostatectomy. FIELD STRENGTH/SEQUENCE 3 T, field-of-view optimized and constrained undistorted single-shot DWI sequence. ASSESSMENT Datasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono-exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC). STATISTICAL TEST Levene's test, P

PurposeThis study evaluated the ability of18F-Fluorodeoxyglucose (FDG) and18F-Fluorothymidine (FLT) imaging with positron emission tomography (PET) to measure early response to endocrine therapy from baseline to just prior to surgical resection in estrogen receptor positive (ER+) breast tumors.MethodsIn two separate studies, women with early stage ER+ breast cancer underwent either paired FDG-PET (n = 22) or FLT-PET (n = 27) scans prior to endocrine therapy and again in the pre-operative setting. Tissue samples for Ki-67 were taken for all patients both prior to treatment and at the time of surgery.ResultsFDG maximum standardized uptake value (SUVmax) declined in 19 of 22 lesions (mean 17% (range −45 to 28%)). FLT SUVmax declined in 24 of 27 lesions (mean 26% (range −77 to 7%)). The Ki-67 index declined in both studies, from pre-therapy (mean 23% (range 1 to 73%)) to surgery [mean 8% (range ConclusionsA window-of-opportunity approach using PET imaging to assess early response of breast cancer therapy is feasible. FDG and FLT-PET imaging following a short course of neoadjuvant endocrine therapy demonstrated measurable changes in SUVmax in early stage ER+ positive breast cancers. The percentage change in FDG and FLT-PET uptake did not correlate with changes in Ki-67; post-therapy SUVmax for both tracers was significantly associated with post-therapy Ki-67, an established predictor of endocrine therapy response.

Multiple injection dynamic positron emission tomography (PET) scanning is used in the clinical management of certain groups of patients and in medical research. The analysis of these studies can be approached in two ways: (i) separate analysis of data from individual tracer injections, or (ii), concatenate/pool data from separate injections and carry out a combined analysis. The simplicity of separate analysis has some practical appeal but may not be statistically efficient. We use a linear model framework associated with a kinetic mapping scheme to develop a simplified theoretical understanding of separate and combined analysis. The theoretical framework is explored numerically using both 1D and 2D simulation models. These studies are motivated by the breast cancer flow-metabolism mismatch studies involving 15O-water (H2O) and 18F-Fluorodeoxyglucose (FDG) and repeat 15O-H2O injections used in brain activation investigations. Numerical results are found to be substantially in line with the simple theoretical analysis: mean square error characteristics of alternative methods are well described by factors involving the local voxel-level resolution of the imaging data, the relative activities of the individual scans and the number of separate injections involved. While voxel-level resolution has dependence on scan dose, after adjustment for this effect, the impact of a combined analysis is understood in simple terms associated with the linear model used for kinetic mapping. This is true for both data reconstructed by direct filtered backprojection or iterative maximum likelihood. The proposed analysis has potential to be applied to the emerging long axial field-of-view PET scanners.

1042 Background: The recently FDA approved 18F-Fluoroestradiol (FES) is a PET imaging tracer for characterizing disease in patients with ER+ breast cancer. As FES PET enters clinical practice it will be important to establish its utility in the full population of hormone-receptor positive patients, including those with HER2+ tumors. Historically the consensus around ER+/HER+ disease has been that these tumors are primarily driven by HER2, with therapies focused on targeting this pathway. Emerging research suggests that ER+ and HER2+ tumors represent a distinct phenotype, with bidirectional crosstalk between ER and HER2 pathways contributing to resistance to therapies targeting these critical pathways. Methods: Our cross-sectional database of patients with one or more FES scans stretches back to 1996. We selected all patients with HER2+ advanced breast cancer to determine whether ER is functional in the ER+/HER2+ subset. We examined paired FDG and FES scans and recorded SUVmax in matched lesions between the FDG and FES scans. We also looked at a subset of patients who underwent scans at more than one time-points and examined the clinical characteristics of these cases over time. Results: 36 patients with metastatic ER+, HER2+ breast cancer underwent concurrent FDG and FES PET scans between 1996 and 2013. 34 subjects (94%) were female; 32 (89%) were Caucasian, and 4 (11%) were Asian. Eight patients underwent serial scans. A total of 200 metastatic sites were recorded with the majority (67%) being bony lesions. No difference in quantitative FES avidity was observed between soft tissue and osseous sites. Six patients (16%) had negative FES scans despite displaying FDG avid lesions; three patients had at least one negative FES scan on serial scans, and two demonstrated FES-avid lesions with no FDG activity. Average FES SUVmax for positive scans was 3.5, with a range of 0.8 to 10.7. Among eight patients with multiple scans, half had 2 scans, three had 3 scans, and one had 4 scans. In 7/8 patients (88%) FES avidity increased over time even as FDG decreased or stayed stable with treatment; in one, both FES and FDG decreased on follow up scan. Conclusions: In a cohort of ER+, HER2+ patients undergoing FDG and FES PET scans, robust concordance between FDG and FES uptake was observed. FES avidity increased in patients with multiple scans, suggesting that the ER pathway remained active during treatment. The strong FES positivity in many HER2+ patients in this cohort suggests that FES PET could be used to guide patient selection for trials examining deescalated regimens employing a non-chemotherapy partner for HER2-directed therapy or emphasizing more ER-directed therapies such as CDK4/6 inhibitors, which are not currently approved in this population. With the ongoing development of HER2- PET imaging, combination scans could carry the potential for discrimination between sites, possibly serving as a tool to guide biopsy.

Learning Objectives: On successful completion of this activity, participants should be able to describe (1) describe principles of PET tracer kinetic analysis for oncologic applications; (2) list methods used for PET kinetic analysis for oncology; and (3) discuss application of kinetic modeling for cancer-specific diagnostic needs. Financial Disclosure: This work was supported by KL2 TR001879, R01 CA211337, R01 CA113941, R33 CA225310, Komen SAC130060, R50 CA211270, and K01 DA040023. Dr. Pantel is a consultant or advisor for Progenics and Blue Earth Diagnostics and is a meeting participant or lecturer for Blue Earth Diagnostics. Dr. Mankoff is on the scientific advisory boards of GE Healthcare, Philips Healthcare, Reflexion, and ImaginAb and is the owner of Trevarx; his wife is the chief executive officer of Trevarx. The authors of this article have indicated no other relevant relationships that could be perceived as a real or apparent conflict of interest. CME Credit: SNMMI is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to sponsor continuing education for physicians. SNMMI designates each JNM continuing education article for a maximum of 2.0 AMA PRA Category 1 Credits. Physicians should claim only credit commensurate with the extent of their participation in the activity. For CE credit, SAM, and other credit types, participants can access this activity through the SNMMI website (http://www.snmmilearningcenter.org) through March 2025 PET enables noninvasive imaging of regional in vivo cancer biology. By engineering a radiotracer to target specific biologic processes of relevance to cancer (e.g., cancer metabolism, blood flow, proliferation, and tumor receptor expression or ligand binding), PET can detect cancer spread, characterize the cancer phenotype, and assess its response to treatment. For example, imaging of glucose metabolism using the radiolabeled glucose analog (18)F-FDG has widespread applications to all 3 of these tasks and plays an important role in cancer care. However, the current clinical practice of imaging at a single time point remote from tracer injection (i.e., static imaging) does not use all the information that PET cancer imaging can provide, especially to address questions beyond cancer detection. Reliance on tracer measures obtained only from static imaging may also lead to misleading results. In this 2-part continuing education paper, we describe the principles of tracer kinetic analysis for oncologic PET (part 1), followed by examples of specific implementations of kinetic analysis for cancer PET imaging that highlight the added benefits over static imaging (part 2). This review is designed to introduce nuclear medicine clinicians to basic concepts of kinetic analysis in oncologic imaging, with a goal of illustrating how kinetic analysis can augment our understanding of in vivo cancer biology, improve our approach to clinical decision making, and guide the interpretation of quantitative measures derived from static images.

Tumoral hypoxia correlates with worse outcomes in glioblastoma (GBM). While bevacizumab is routinely used to treat recurrent GBM, it may exacerbate hypoxia. Evofosfamide is a hypoxia-targeting prodrug being tested for recurrent GBM. To characterize resistance to bevacizumab and identify those with recurrent GBM who may benefit from evofosfamide, we ascertained MRI features and hypoxia in patients with GBM progression receiving both agents. Thirty-three patients with recurrent GBM refractory to bevacizumab were enrolled. Patients underwent MR and 18F-FMISO PET imaging at baseline and 28 days. Tumor volumes were determined, MRI and 18F-FMISO PET-derived parameters calculated, and Spearman correlations between parameters assessed. Progression-free survival decreased significantly with hypoxic volume [hazard ratio (HR) = 1.67, 95% confidence interval (CI) 1.14 to 2.46, P = 0.009] and increased significantly with time to the maximum value of the residue (Tmax) (HR = 0.54, 95% CI 0.34 to 0.88, P = 0.01). Overall survival decreased significantly with hypoxic volume (HR = 1.71, 95% CI 1.12 to 12.61, p = 0.01), standardized relative cerebral blood volume (srCBV) (HR = 1.61, 95% CI 1.09 to 2.38, p = 0.02), and increased significantly with Tmax (HR = 0.31, 95% CI 0.15 to 0.62, p s = 0.77, P s = 0.75, P

We have previously characterized the reproducibility of brain tumor relative cerebral blood volume (rCBV) using a dynamic susceptibility contrast magnetic resonance imaging digital reference object across 12 sites using a range of imaging protocols and software platforms. As expected, reproducibility was highest when imaging protocols and software were consistent, but decreased when they were variable. Our goal in this study was to determine the impact of rCBV reproducibility for tumor grade and treatment response classification. We found that varying imaging protocols and software platforms produced a range of optimal thresholds for both tumor grading and treatment response, but the performance of these thresholds was similar. These findings further underscore the importance of standardizing acquisition and analysis protocols across sites and software benchmarking.

Radiomic features are being increasingly studied for clinical applications. We aimed to assess the agreement among radiomic features when computed by several groups by using different software packages under very tightly controlled conditions, which included standardized feature definitions and common image data sets. Ten sites (9 from the NCI's Quantitative Imaging Network] positron emission tomography–computed tomography working group plus one site from outside that group) participated in this project. Nine common quantitative imaging features were selected for comparison including features that describe morphology, intensity, shape, and texture. The common image data sets were: three 3D digital reference objects (DROs) and 10 patient image scans from the Lung Image Database Consortium data set using a specific lesion in each scan. Each object (DRO or lesion) was accompanied by an already-defined volume of interest, from which the features were calculated. Feature values for each object (DRO or lesion) were reported. The coefficient of variation (CV), expressed as a percentage, was calculated across software packages for each feature on each object. Thirteen sets of results were obtained for the DROs and patient data sets. Five of the 9 features showed excellent agreement with CV &lt, 1%, 1 feature had moderate agreement (CV &lt, 10%), and 3 features had larger variations (CV ≥ 10%) even after attempts at harmonization of feature calculations. This work highlights the value of feature definition standardization as well as the need to further clarify definitions for some features.

BACKGROUND AND PURPOSE: Standard assessment criteria for brain tumors that only include anatomic imaging continue to be insufficient. While numerous studies have demonstrated the value of DSC-MR imaging perfusion metrics for this purpose, they have not been incorporated due to a lack of confidence in the consistency of DSC-MR imaging metrics across sites and platforms. This study addresses this limitation with a comparison of multisite/multiplatform analyses of shared DSC-MR imaging datasets of patients with brain tumors. MATERIALS AND METHODS: DSC-MR imaging data were collected after a preload and during a bolus injection of gadolinium contrast agent using a gradient recalled-echo–EPI sequence (TE/TR = 30/1200 ms; flip angle = 72°). Forty-nine low-grade ( n = 13) and high-grade ( n = 36) glioma datasets were uploaded to The Cancer Imaging Archive. Datasets included a predetermined arterial input function, enhancing tumor ROIs, and ROIs necessary to create normalized relative CBV and CBF maps. Seven sites computed 20 different perfusion metrics. Pair-wise agreement among sites was assessed with the Lin concordance correlation coefficient. Distinction of low- from high-grade tumors was evaluated with the Wilcoxon rank sum test followed by receiver operating characteristic analysis to identify the optimal thresholds based on sensitivity and specificity. RESULTS: For normalized relative CBV and normalized CBF, 93% and 94% of entries showed good or excellent cross-site agreement (0.8 ≤ Lin concordance correlation coefficient ≤ 1.0). All metrics could distinguish low- from high-grade tumors. Optimum thresholds were determined for pooled data (normalized relative CBV = 1.4, sensitivity/specificity = 90%:77%; normalized CBF = 1.58, sensitivity/specificity = 86%:77%). CONCLUSIONS: By means of DSC-MR imaging data obtained after a preload of contrast agent, substantial consistency resulted across sites for brain tumor perfusion metrics with a common threshold discoverable for distinguishing low- from high-grade tumors.

Assessing therapy response of breast cancer bone metastases is challenging. In retrospective studies, serial (18)F-FDG PET was predictive of time to skeletal-related events (tSRE) and time to progression (TTP). (18)F-NaF PET improves bone metastasis detection compared with bone scanning. We prospectively tested (18)F-FDG PET and (18)F-NaF PET to predict tSRE, TTP, and overall survival (OS) in patients with bone-dominant metastatic breast cancer (MBC). Methods: Patients with bone-dominant MBC were imaged with (18)F-FDG PET and (18)F-NaF PET before starting new therapy (scan1) and again at a range of times centered around approximately 4 mo later (scan2). Maximum standardized uptake value (SUV(max)) and lean body mass adjusted standardized uptake (SUL(peak)) were recorded for a single index lesion and up to 5 most dominant lesions for each scan. tSRE, TTP, and OS were assessed exclusive of the PET images. Univariate Cox regression was performed to test the association between clinical endpoints and (18)F-FDG PET and (18)F-NaF PET measures. mPERCIST (Modified PET Response Criteria in Solid Tumors) were also applied. Survival curves for mPERCIST compared response categories of complete response+partial response+stable disease versus progressive disease for tSRE, TTP, and OS. Results: Twenty-eight patients were evaluated. Higher (18)F-FDG SUL(peak) at scan2 predicted shorter time to tSRE (P =

Purpose To assess the inter-operator variability in compartment analysis (CA) of dynamic-FMISO (dyn-FMISO) PET. Methods Study-I: Five investigators conducted CA for 23 NSCLC dyn-FMISO tumor time-activity-curves. Study-II: Four operators performed CA for four NSCLC dyn-FMISO datasets. Repeatability of Kinetic-Rate-Constants (KRCs) was assessed. Results Study-I: Strong correlation (ICC > 0.9) and interchangeable results among operators existed for all KRCs. Study-II: Up to 103% variability in tumor segmentation, and weaker ICC in KRCs (ICC-VB = 0.53; ICC-K1 = 0.91; ICC-K1/k2 = 0.25; ICC-k3 = 0.32; ICC-Ki = 0.54) existed. All KRCs were repeatable among the different operators. Conclusions Inter-operator variability in CA of dyn-FMISO was shown to be within statistical errors.

A Correction to this paper has been published: 10.1007/s00259-021-05324-0

Kinetic mapping via mixture analysis[8], [10] involves comprehensive voxel-level analysis of dynamic PET data. Bootstrapping from the fitted mixture model gives the ability to directly simulate statistical copies of the 4-D PET data, and following suitable analysis, subsequent simulations of the associated kinetic maps. This gives the ability to numerically evaluate uncertainties in inferences associated with kinetic information. We provide a simple introduction to the concept of the model-based bootstrap and an illustration of the use of the approach for kinetic mapping from dynamic PET using results from recent work in Huang et al.[4]. The illustration is from a PET flow-metabolism imaging study in a breast cancer patient. It involves separate dynamic PET imaging following injections of O-15 H2O and F-18 FDG. The bootstrapped data is created in the image domain rather than the projection domain, so there is no reconstruction requirement involved.

The multiple injection dynamic Positron Emission Tomography (PET) scanning is used in the clinical management of certain groups of cancer patients and in medical research. The analysis of such studies can be approached in one of two ways: analyze individual injections separately to recover tracer kinetic information, or concatenate data from separate injections and carry out a combined analysis. Separate analysis offers some simplicity but may not be as efficient statistically. The mixture technique is readily implemented in a separated or combined analysis mode. We evaluate these approaches in a 1-D simulation setting matched to the mathematical complexity of PET. These simulations are largely guided by experience with breast cancer flow-metabolism mismatch studies using 15O-Water (H2O) and 18F-Fluorodeoxyglucose (FDG). An efficient implementation in the R (an open-source environment) is used to implement simulations. The simulations evaluate mean square error (MSE) characteristics, for separate and combined analysis, both as a function of dose. The relationship between MSE characteristics of the underlying source distribution is described and the combined analysis is found to reduce MSE by between 18.1% and 33.85%. The quantitative advantages of combined approach have been demonstrated.

Standard whole-body clinical fluoro-deoxyglucose (FDG)-PET scans typically involve imaging for around 15 minutes about 60 minutes after tracer injection. The scan duration is often the critical constraint limiting patient through-put. Scans taken long after tracer injection restrict the ability to assess vascular and perfusion information that might be revealed by the early pattern of tracer uptake. On the other hand, early scanning may compromise the recovery of the late time uptake (SUV) which in many contexts has well established prognostic value. In this study, we explore the potential for short-duration dynamic scans, acquired immediately after tracer injection, to recover information that can predict late-stage uptake of FDG. The work involves re-analysis of existing series of dynamic brain and breast tumour imaging data to simulate the type of information that would arise from early and late scanning. Using a collection of machine learning techniques (including random forests, neural networks, gradient boosting), we find that short-duration clinical protocols, soon after the tracer injection, show significant potential to recover the late stage FDG flux information.

608 Objectives: Co-administration of additional therapies, such as external beam radiation, with checkpoint immunotherapy may result in modulation of checkpoint molecule expression. This process is highly dynamic and difficult to capture with traditional biopsy-based analysis; therefore, molecular imaging, particularly positron emission tomography, may enable real-time insight into these expression levels. The human/mouse cross-reactive anti-PD-L1 antibody atezolizumab was utilized to visualize tumor PD-L1 expression changes following various external beam radiotherapy interventions. Methods: A humanized anti-PD-L1 antibody, atezolizumab, was radiolabeled with 89Zr (half-life: 78.4 h) for PET imaging following external beam radiation to PD-L1-expressing (H460) or PD-L1-negative (A549) lung cancer cells or tumor xenografts in mice. Using a biological irradiator, three schedules were utilized: 5 Gy in a single dose; five daily fractions of 2 Gy; or no irradiation. One day after completion of the respective radiotherapy regimens, mice were injected with 89Zr-Df-atezolizumab and serial PET imaging was performed out to 120 h post-injection. Biodistribution and histology studies were conducted to verify the in vivo findings, and tracer accumulation differences between irradiated groups and non-irradiated, as well as positive and negative tumors, were analyzed for statistical significance. Results: In vitro studies verified increased expression of PD-L1 by H460 cells following radiotherapy, particularly with the fractionated regimen, while PD-L1 expression could not be induced on A549 cells with the employed techniques. Imaging with the PD-L1-targeted tracer revealed high signals in the spleen and lymph nodes of all imaged mice (~10-20 %ID/g). Tumor accumulation was highest in the H460-bearing mice receiving 5 fractions of 2 Gy at 24 h post-injection at 4.44 ± 1.52 %ID/g, compared to that observed in the negative A549 fractionated regimen mice at 1.64 ± 0.65 %ID/g (p < 0.02, n=4-6). Both positive and negative non-irradiated tumors revealed similar accumulation of 89Zr-Df-atezolizumab at the end of the study, with uptakes of 1.51 ± 0.61 %ID/g in H460 tumors, and 1.42 ± 0.95 %ID/g in A549. Ex vivo analysis of tissues demonstrated significant PD-L1 expression in lymphoid organs, correlating with the high tracer accumulation in these tissues. In H460 tumors, PD-L1 expression by both tumor and myeloid cells was observed, and PD-L1 staining was minimal in A549 tissues. Conclusions: While the absolute level of 89Zr-Df-atezolizumab accumulation in tumor tissues was low due to the presence of notable sink tissues, significant differences were noted between treated and untreated tissues. PD-L1 imaging may therefore play a unique role for monitoring of treatment efficacy by comparing the dynamics of immune checkpoint expression before, during, and after therapeutic intervention.

The use of rCBV as a response metric in clinical trials has been hampered, in part, due to variations in the biomarker consistency and associated interpretation across sites, stemming from differences in image acquisition and post-processing methods. This study leveraged a dynamic susceptibility contrast magnetic resonance imaging digital reference object to characterize rCBV consistency across 12 sites participating in the Quantitative Imaging Network (QIN), specifically focusing on differences in site-specific imaging protocols (IPs, n = 17), and PMs (n = 19) and differences due to site-specific IPs and PMs (n = 25). Thus, high agreement across sites occurs when 1 managing center processes rCBV despite slight variations in the IP. This result is most likely supported by current initiatives to standardize IPs. However, marked intersite disagreement was observed when site-specific software was applied for rCBV measurements. This study's results have important implications for comparing rCBV values across sites and trials, where variability in PMs could confound the comparison of therapeutic effectiveness and/or any attempts to establish thresholds for categorical response to therapy. To overcome these challenges and ensure the successful use of rCBV as a clinical trial biomarker, we recommend the establishment of qualifying and validating site- and trial-specific criteria for scanners and acquisition methods (eg, using a validated phantom) and the software tools used for dynamic susceptibility contrast magnetic resonance imaging analysis (eg, using a digital reference object where the ground truth is known).

This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate Ktrans (volume transfer rate constant), ve (extravascular, extracellular volume fraction), kep (efflux rate constant), and τi (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T1 values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for Ktrans, ve, kep, and τi, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in Ktrans and ve (wCV = 0.50 and 0.10, respectively), but had smaller effects on kep and τi (wCV = 0.39 and 0.22, respectively). kep is less sensitive to AIF variation than Ktrans, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τi parameter may have advantages over the conventional PK parameters in a longitudinal study.

Using positron emission tomography (PET) imaging, we determined the hepatic concentrations and hepatobiliary transport of [(11)C]rosuvastatin (IV injection) in the absence (n=6) and presence (n=4 of 6) of cyclosporine A (CsA, IV infusion) following a therapeutic dose of unlabeled rosuvastatin (RSV) (5 mg, PO) in healthy human volunteers. The sinusoidal uptake, sinusoidal efflux and biliary efflux clearance (mL/min) of [(11)C]rosuvastatin, estimated through compartment modeling were 1205.6±384.8, 16.2±11.2 and 5.1±1.8, respectively (n=6). CsA (blood concentration: 2.77±0.24 μM), an organic-anion-transporting polypeptide (OATP), Na(+)-taurocholate cotransporting polypeptide (NTCP) and breast cancer resistance protein (BCRP) inhibitor increased [(11)C]rosuvastatin systemic blood exposure (45%; p0.05) but didn’t affect its distribution into the kidneys. CsA increased plasma concentrations of coproporphyrin I and III and total bilirubin by 297±69%, 384±102% and 81±39%, respectively (p

Mounting evidence points to the significance of neurovascular-related dysfunction in veterans with blast-related mTBI, which is also associated with reduced [18F]-fluorodeoxyglucose (FDG) uptake. The goal of this study was to determine whether plasma VEGF-A is altered in veterans with blast-related mTBI and address whether VEGF-A levels correlate with FDG uptake in the cerebellum, a brain region that is vulnerable to blast-related injury 72 veterans with blast-related mTBI (mTBI) and 24 deployed control (DC) veterans with no lifetime history of TBI were studied. Plasma VEGF-A was significantly elevated in mTBIs compared to DCs. Plasma VEGF-A levels in mTBIs were significantly negatively correlated with FDG uptake in cerebellum. In addition, performance on a Stroop color/word interference task was inversely correlated with plasma VEGF-A levels in blast mTBI veterans. Finally, we observed aberrant perivascular VEGF-A immunoreactivity in postmortem cerebellar tissue and not cortical or hippocampal tissues from blast mTBI veterans. These findings add to the limited number of plasma proteins that are chronically elevated in veterans with a history of blast exposure associated with mTBI. It is likely the elevated VEGF-A levels are from peripheral sources. Nonetheless, increasing plasma VEGF-A concentrations correlated with chronically decreased cerebellar glucose metabolism and poorer performance on tasks involving cognitive inhibition and set shifting. These results strengthen an emerging view that cognitive complaints and functional brain deficits caused by blast exposure are associated with chronic blood-brain barrier injury and prolonged recovery in affected regions.

e12573 Background: Breast cancer heterogeneity is thought to be associated with adverse outcomes. Dynamic molecular imaging modalities, including PET, permit 4-D sampling of tumor biologic properties and can therefore capture functional heterogeneity revealed by the temporal dimension of the dynamic tracer uptake. With the goal of improved non-invasive characterization of in vivo tumor biology, we have developed and tested a novel radiomic biomarker that characterizes 4-D functional tumor heterogeneity (FTH). We hypothesize subclonal populations are spatially contiguous regions of shared physiologic behavior that drive breast cancer heterogeneity and can be quantified. We describe an initial application of this approach to FDG PET imaging of breast cancer. Methods: We retrospectively analyzed data from a study of 50 patients with locally advanced breast cancer. Patients underwent 60-minute dynamic FDG PET over the chest prior to neoadjuvant chemotherapy and breast surgery and were followed for disease recurrence (DFS). A 3-D region bounding each tumor was identified by a radiologist and a novel Markov Random Field based 4-D segmentation paradigm segmented each tumor into three spatially constrained sub-regions with distinct time activity curve dynamics. From each tumor, an FTH imaging signature was extracted characterizing cluster compactness and separation. FTH imaging signatures were z-score normalized across all patients. Time-to-event analysis was used to assess the prognostic value of the FTH imaging signatures in predicting DFS. Discriminatory capacity compared to a baseline model of established prognostic factors (age, hormone receptor status, baseline tumor size) and standard PET uptake and kinetics markers (SUV, K1, and Ki) shown to be predictive of DFS (Dunnwald, J Clin Oncol 26:4449, 2008) was evaluated using the c-statistic and the log-likelihood statistical test. Results: 17 of 50 women (34%) had recurrence events. Adding FTH imaging signatures to the baseline model of age, baseline tumor size, and hormone receptor status improved a cross validated c-statistic from 0.51 to 0.74 (p < 0.05), and demonstrated higher discriminatory capacity over a model of age, tumor size, hormone receptor status, and standard PET measures (c-statistic = 0.59). Conclusions: Imaging biomarkers of 4-D metabolic tumor heterogeneity may add prognostic value in predicting recurrence-free survival in breast cancer and merit further study.

Background: Bone dominant metastatic breast cancer can be difficult to stage using conventional imaging. 18F-FES is an estrogen analogue PET imaging tracer that measures estrogen receptor (ER) expression at multiple tumor sites simultaneously and predicts response to endocrine therapy. We analyzed FES-PET and FDG-PET SUV uptake within bone in patients with metastatic lobular breast cancer from an ER+ primary. Methods: We retrospectively reviewed FES and FDG SUV uptake from scans in women with boney lesions or diffuse marrow uptake (n = 30). Our cohort was obtained from various cross-sectional studies at our institution and the majority received multiple lines of prior endocrine and/or chemotherapy. Up to 10 lesions in each patient were evaluated for a total of 200 lesions in both FES and FDG images. Diffuse marrow uptake was found in 7 women, and we compared this subgroup (bone marrow) vs the others by two-sample t-test for FES/FDG scans. Progression free survival (PFS), from time of earliest scan date to progression or death (whichever came first), and overall survival (OS), from time of earliest scan date to death, was evaluated using Kaplan-Meier curves and the Log-Rank test. Results: Mean (range) SUVmax in FES and FDG respectively for all bone lesions were 3.9 (1.5-9.1) and 4.7 (1.4-9.5). Higher FES and FDG uptake were noted in patients with bone marrow uptake (mean FES SUVmax 5.2 and mean FDG SUVmax 5.7) compared to non-marrow bone uptake (mean FES SUVmax 3.5 and mean FDG SUVmax 4.4), and the average difference for FES SUVmax was statistically significant higher in bone marrow uptake subgroup (p=0.032). Of the 200 lesions identified, 92 (46%) were located in the spine. Bone marrow uptake was visually more pronounced in the FES-PET scans. Compared to bone only uptake, patients with bone marrow uptake had a higher progression free survival (1.3 years vs 0.57 years p = 0.12), but similar overall survival (1.56 years vs 1.63 years, p = 0.69). Conclusions: Amongst patients with metastatic lobular carcinoma involving the bone marrow, there was significant higher uptake in both FES and FDG scans which provides insight in the pattern of spread of lobular breast cancer. Metastatic bone dominant breast cancers have similar FES and FDG avidity, suggesting that both imaging modalities can be used in identification of bone tumor sites. Further prospective trials are needed to confirm the utility of FES to stage extent of disease in bone dominant metastatic lobular breast cancer. Citation Format: Poorni Manohar, Lanell Peterson, Qian (Vicky) Wu, Isaac Jenkins, Brenda Kurland, Alena Novakova-Jiresova, Jennifer Specht, Mark Muzi, Jeanne Link, Kenneth Krohn, Paul Kinahan, David Mankoff, Hannah Linden. The role of 18F-Fluoroestradiol (FES) and 18F-Fluorodeoxyglucose (FDG) PET imaging in identification of bone metastases in metastatic breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-01-07.

INTRODUCTION: Evophosphamide is a hypoxia-activated prodrug that, when activated in hypoxic conditions, (

Blood flow-metabolism mismatch from dynamic positron emission tomography (PET) studies with O-15-labeled water (H2O) and F-18-labeled fluorodeoxyglucose (FDG) has been shown to be a promising diagnostic for locally advanced breast cancer (LABCa) patients. The mismatch measurement involves kinetic analysis with the arterial blood time course (AIF) as an input function. We evaluate the use of a statistical method for AIF extraction (SAIF) in these studies. Fifty three LABCa patients had dynamic PET studies with H2O and FDG. For each PET study, two AIFs were recovered, an SAIF extraction and also a manual extraction based on a region of interest placed over the left ventricle (LV-ROI). Blood flow-metabolism mismatch was obtained with each AIF, and kinetic and prognostic reliability comparisons were made. Strong correlations were found between kinetic assessments produced by both AIFs. SAIF AIFs retained the full prognostic value, for pathologic response and overall survival, of LV-ROI AIFs. (c) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Diffusion weighted MRI has become ubiquitous in many areas of medicine, including cancer diagnosis and treatment response monitoring. Reproducibility of diffusion metrics is essential for their acceptance as quantitative biomarkers in these areas. We examined the variability in the apparent diffusion coefficient (ADC) obtained from both postprocessing software implementations utilized by the NCI Quantitative Imaging Network and online scan time-generated ADC maps. Phantom and in vivo breast studies were evaluated for two ([Formula: see text]) and four ([Formula: see text]) [Formula: see text]-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and in vivo [Formula: see text], with relative biases [Formula: see text] ([Formula: see text]) and [Formula: see text] (phantom [Formula: see text]) but with higher deviations in ADC at the lowest phantom ADC values. In vivo [Formula: see text] concordance was good, with typical biases of [Formula: see text] to 3% but higher for online maps. Multiple b-value ADC implementations were separated into two groups determined by the fitting algorithm. Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for [Formula: see text] in vivo data. Some higher deviations were found for individual implementations and online parametric maps. Despite generally good concordance, implementation biases in ADC measures are sometimes significant and may be large enough to be of concern in multisite studies.