Increased [18F]fluorodeoxyglucose uptake in the left pallidum in military Veterans with blast-related mild traumatic brain injury: potential as an imaging biomarker and mediation with executive dysfunction and cognitive impairment

Blast-related mild traumatic brain injury (blast-mTBI) can result in a spectrum of persistent symptoms leading to substantial functional impairment and reduced quality of life. Clinical evaluation and discernment from other conditions common to military service can be challenging and subject to patient recall bias and the limitations of available assessment measures. The need for objective biomarkers to facilitate accurate diagnosis, not just for symptom management and rehabilitation but for prognostication and disability compensation purposes is clear. Toward this end, we compared regional brain [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) intensity-scaled uptake measurements and motor, neuropsychological, and behavioral assessments in 79 combat Veterans with retrospectively recalled blast-mTBI with 41 control participants having no lifetime history of TBI. Using an agnostic and unbiased approach, we found significantly increased left pallidum [18F]FDG-uptake in Veterans with blast-mTBI versus control participants, p<0.0001; q=3.29 x 10-9 (Cohen's d, 1.38, 95% CI (.96, 1.79)). The degree of left pallidum [18F]FDG-uptake correlated with the number of self-reported blast-mTBIs, r2=0.22; p<0.0001. Greater [18F]FDG-uptake in the left pallidum provided excellent discrimination between Veterans with blast-mTBI and controls, with a Receiver Operator Characteristic Area Under the Curve of 0.859 (p<0.0001) and likelihood ratio of 21.19 (threshold:SUVR≥0.895). Deficits in executive function assessed using the Behavior Rating Inventory of Executive Function-Adult Global Executive Composite T-score were identified in Veterans with blast-mTBI compared to controls, p<0.0001. Regression-based mediation analyses determined that in Veterans with blast-mTBI, increased [18F]FDG-uptake in the left pallidum mediated executive function impairments, adjusted causal mediation estimate p=0.021; total effect estimate, p=0.039. Measures of working and prospective memory (Auditory Consonant Trigrams test and Memory for Intentions Test, respectively) were negatively correlated with left pallidum [18F]FDG-uptake, p<0.0001, with mTBI as a covariate. Increased left pallidum [18F]FDG-uptake in Veterans with blast-mTBI compared to controls did not covary with dominant handedness or with motor activity assessed using the Unified Parkinson's Disease Rating Scale. Localized increased [18F]FDG-uptake in the left pallidum may reflect a compensatory response to functional deficits following blast-mTBI. Limited imaging resolution does not allow us to distinguish subregions of the pallidum, however the significant correlation of our data with behavioral but not motor outcomes suggests involvement of the ventral pallidum, which is known to regulate motivation, behavior, and emotions via basal ganglia-thalamo-cortical circuits. Increased [18F]FDG-uptake in the left pallidum in blast-mTBI versus control participants was consistently identified using two different PET scanners, supporting the generalizability of this finding. While confirmation of our results by single-subject-to-cohort analyses will be required prior to clinical deployment, this study provides proof-of-concept that [18F]FDG-PET bears promise as a readily available noninvasive biomarker for blast-mTBI. Further, our findings support a causative relationship between executive dysfunction and increased [18F]FDG-uptake in the left pallidum.

Equivalent uniform aerobic dose in radiotherapy for hypoxic tumors

Objective.Equivalent uniform aerobic dose (EUAD) is proposed for comparison of integrated cell survival in tumors with different distributions of hypoxia and radiation dose.Approach.The EUAD assumes that for any non-uniform distributions of radiation dose and oxygen enhancement ratio (OER) within a tumor, there is a uniform distribution of radiation dose under hypothetical aerobic conditions with OER = 1 that produces equal integrated survival of clonogenic cells. This definition of EUAD has several advantages. First, the EUAD allows one to compare survival of clonogenic cells in tumors with intra-tumor and inter-tumor variation of radio sensitivity due to hypoxia because the cell survival is recomputed under the same benchmark oxygen level (OER = 1). Second, the EUAD for homogeneously oxygenated tumors is equal to the concept of equivalent uniform dose.Main results. We computed the EUAD using radiotherapy dose and the OER derived from the18F-Fluoromisonidazole PET (18F-FMISO PET) images of hypoxia in patients with glioblastoma, the most common and aggressive type of primary malignant brain tumor. The18F-FMISO PET images include a distribution of SUV (Standardized Uptake Value); therefore, the SUV is converted to partial oxygen pressure (pO2) and then to the OER. The prognostic value of EUAD in radiotherapy for hypoxic tumors is demonstrated using correlation between EUAD and overall survival (OS) in radiotherapy for glioblastoma. The correction to the EUAD for the absolute hypoxic volume that traceable to the tumor control probability improves the correlation with OS.Significance. While the analysis proposed in this research is based on the18F-FMISO PET images for glioblastoma, the EUAD is a universal radiobiological concept and is not associated with any specific cancer or any specific PET or MRI biomarker of hypoxia. Therefore, this research can be generalized to other cancers, for example stage III lung cancer, and to other hypoxia biomarkers.

Repeatability of 18F-FDG uptake in metastatic bone lesions of breast cancer patients and implications for accrual to clinical trials

BACKGROUND

Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients that have bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases.

METHODS

For this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified by the most commonly used PET parameter, the maximum tumor voxel normalized by dose and body weight (SUVmax) and also by the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals for SUVmax and SULpeak were used to determine the limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment.

RESULTS

The mean relative difference of SUVmax and SULpeak in 38 bone tumors of the first cohort were 4.3% and 6.7%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and - 16.3% for SUVmax, and 21.2% and - 17.5% for SULpeak. 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification using SULpeak for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria for SULpeak changed the status of 3 patients compared to the standard Positron Emission Tomography Response Criteria in Solid Tumors of ± 30% SULpeak.

CONCLUSION

In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG SUVmax, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions in these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response.

Repeatability of 18F-FDG uptake in metastatic bone lesions of breast cancer patients and implications for accrual to clinical trials

BACKGROUND

Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients with bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases.In this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified as the maximum tumor voxel normalized by dose and body weight (SUVmax) and the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals of SUVmax and SULpeak were used to determine limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment.

RESULTS

The mean relative difference of SUVmax in 38 bone tumors of the first cohort was 4.3%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and -16.3%, respectively. The 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria changed the status of 3 patients compared to standard the standard Positron Emission Tomography Response Criteria in Solid Tumors of ±30% SULpeak.

CONCLUSIONS

In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG uptake, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions from these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response.

Abstract P2-03-17: Fluoroestradiol (FES) and Fluorodeoxyglucose (FDG) PET imaging in patients with ER+, HER2+ or HER2- metastatic breast cancer

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.

Abstract P2-03-25: 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

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.

Evaluation of Apparent Diffusion Coefficient Repeatability and Reproducibility for Preclinical MRIs Using Standardized Procedures and a Diffusion-Weighted Imaging Phantom

Relevant to co-clinical trials, the goal of this work was to assess repeatability, reproducibility, and bias of the apparent diffusion coefficient (ADC) for preclinical MRIs using standardized procedures for comparison to performance of clinical MRIs. A temperature-controlled phantom provided an absolute reference standard to measure spatial uniformity of these performance metrics. Seven institutions participated in the study, wherein diffusion-weighted imaging (DWI) data were acquired over multiple days on 10 preclinical scanners, from 3 vendors, at 6 field strengths. Centralized versus site-based analysis was compared to illustrate incremental variance due to processing workflow. At magnet isocenter, short-term (intra-exam) and long-term (multiday) repeatability were excellent at within-system coefficient of variance, wCV [±CI] = 0.73% [0.54%, 1.12%] and 1.26% [0.94%, 1.89%], respectively. The cross-system reproducibility coefficient, RDC [±CI] = 0.188 [0.129, 0.343] µm2/ms, corresponded to 17% [12%, 31%] relative to the reference standard. Absolute bias at isocenter was low (within 4%) for 8 of 10 systems, whereas two high-bias (>10%) scanners were primary contributors to the relatively high RDC. Significant additional variance (>2%) due to site-specific analysis was observed for 2 of 10 systems. Base-level technical bias, repeatability, reproducibility, and spatial uniformity patterns were consistent with human MRIs (scaled for bore size). Well-calibrated preclinical MRI systems are capable of highly repeatable and reproducible ADC measurements.

Patient-Adaptive Population-Based Modeling of Arterial Input Functions

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 demonstrate 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.

Federated learning enables big data for rare cancer boundary detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Matched FES and FDG PET imaging in patients with hormone receptor-positive, HER2+ advanced breast cancer

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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.

Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness

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 < 0.05 corrected for multiple comparisons was considered statistically significant.

RESULTS

The DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72-0.76, 0.76-0.81, and 0.76-0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53-0.80, 0.51-0.81, and 0.52-0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from, for example, 0.75 to 0.87 for MEADC varying cluster size.

DATA CONCLUSION

We found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 3.

Principles of Tracer Kinetic Analysis in Oncology, Part II: Examples and Future Directions

Learning Objectives: On successful completion of this activity, participants should be able to (1) describe examples of the application of PET tracer kinetic analysis to oncology; (2) list applications research and possible clinical applications in oncology where kinetic analysis is helpful; and (3) discuss future applications of kinetic modeling to cancer research and possible clinical cancer imaging practice.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 April 2025.Kinetic analysis of dynamic PET imaging enables the estimation of biologic processes relevant to disease. Through mathematic analysis of the interactions of a radiotracer with tissue, information can be gleaned from PET imaging beyond static uptake measures. Part I of this 2-part continuing education paper reviewed the underlying principles and methodology of kinetic modeling. In this second part, the benefits of kinetic modeling for oncologic imaging are illustrated through representative case examples that demonstrate the principles and benefits of kinetic analysis in oncology. Examples of the model types discussed in part I are reviewed here: a 1-tissue-compartment model (15O-water), an irreversible 2-tissue-compartment model (18F-FDG), and a reversible 2-tissue-compartment model (3'-deoxy-3'-18F-fluorothymidine). Kinetic approaches are contrasted with static uptake measures typically used in the clinic. Overall, this 2-part review provides the reader with background in kinetic analysis to understand related research and improve the interpretation of clinical nuclear medicine studies with a focus on oncologic imaging.

Principles of Tracer Kinetic Analysis in Oncology, Part I: Principles and Overview of Methodology

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 2025PET 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 ¹⁸F-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.

Quantitation of multiple injection dynamic PET scans: an investigation of the benefits of pooling data from separate scans when mapping kinetics

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 involving15O-water (H2O) and18F-Fluorodeoxyglucose (FDG) and repeat15O-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.

Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets

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 < 1%; 1 feature had moderate agreement (CV < 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.

Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images

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.

Assessment of the Prognostic Value of Radiomic Features in 18F-FMISO PET Imaging of Hypoxia in Postsurgery Brain Cancer Patients: Secondary Analysis of Imaging Data from a Single-Center Study and the Multicenter ACRIN 6684 Trial

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 < .001) and were also found significant in multivariate prognostic models (P < .002 and P < .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..

Functional 4-D clustering for characterizing intratumor heterogeneity in dynamic imaging: evaluation in FDG PET as a prognostic biomarker for breast cancer

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 < 0.001) phenotypes of tumor heterogeneity corresponding to high and low FTH. Distributions of FDG flux, or Ki, were significantly different (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.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05265-8.

Abstract PD6-10: 18F-fluoroestradiol (fes) and 18f-fluorodeoxyglucose (fdg) pet imaging in metastatic lobular breast cancer

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 &gt; FDG, and FDG &gt; 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.

18F-fluorodeoxyglucose (FDG) PET or 18F-fluorothymidine (FLT) PET to assess early response to aromatase inhibitors (AI) in women with ER+ operable breast cancer in a window-of-opportunity study

PURPOSE

This study evaluated the ability of ¹⁸F-Fluorodeoxyglucose (FDG) and ¹⁸F-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.

METHODS

In 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.

RESULTS

FDG 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 < 1 to 41%)]. Pre- and post-therapy PET measures showed strong rank-order agreement with Ki-67 percentages for both tracers; however, the percent change in FDG or FLT SUVmax did not demonstrate a strong correlation with Ki-67 index change or Ki-67 at time of surgery.

CONCLUSIONS

A 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.

Chronic elevation of plasma vascular endothelial growth factor-A (VEGF-A) is associated with a history of blast exposure

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.

Quantifying bias and precision of kinetic parameter estimation on the PennPET Explorer, a long axial field-of-view scanner

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 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 (k₄ ≠ 0) for the FLT study and both a two-tissue-compartment model (k₄ = 0) and Patlak graphical analysis for the FDG study to estimate flux (K_i) and delivery (K₁) parameters. Quantification of flux and K1 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.

Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge

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.

4D radiomic biomarker of functional tumor heterogeneity to predict breast cancer recurrence in pretreatment dynamic FDG-PET

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.

Abstract P1-01-07: The role of 18F-Fluoroestradiol (FES) and 18F-Fluorodeoxyglucose (FDG) PET imaging in identification of bone metastases in metastatic breast cancer

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.

Positron Emission Tomography Imaging of [11 C]Rosuvastatin Hepatic Concentrations and Hepatobiliary Transport in Humans in the Absence and Presence of Cyclosporin A

Using positron emission tomography imaging, we determined the hepatic concentrations and hepatobiliary transport of [¹¹ C]rosuvastatin (RSV; i.v. injection) in the absence (n = 6) and presence (n = 4 of 6) of cyclosporin A (CsA; i.v. infusion) following a therapeutic dose of unlabeled RSV (5 mg, p.o.) in healthy human volunteers. The sinusoidal uptake, sinusoidal efflux, and biliary efflux clearance (CL; mL/minute) of [¹¹ C]RSV, estimated through compartment modeling were 1,205.6 ± 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, Na⁺ -taurocholate cotransporting polypeptide, and breast cancer resistance protein inhibitor increased [¹¹ C]RSV systemic blood exposure (45%; P < 0.05), reduced its biliary efflux CL (52%; P < 0.05) and hepatic uptake (25%; P > 0.05) but did not 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 < 0.05). These data can be used in the future to verify predictions of hepatic concentrations and hepatobiliary transport of RSV.

Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO)

Relative cerebral blood volume (rCBV) cannot be used as a response metric in clinical trials, in part, because of variations in biomarker consistency and associated interpretation across sites, stemming from differences in image acquisition and postprocessing methods (PMs). 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).

The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II

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 K^trans (volume transfer rate constant), v_e (extravascular, extracellular volume fraction), k_ep (efflux rate constant), and τ_i (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 K^trans, v_e, k_ep, and τ_i, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in K^trans and v_e (wCV = 0.50 and 0.10, respectively), but had smaller effects on k_ep and τ_i (wCV = 0.39 and 0.22, respectively). k_ep is less sensitive to AIF variation than K^trans, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τ_i parameter may have advantages over the conventional PK parameters in a longitudinal study.

Test-Retest Reproducibility of 18F-FDG PET/CT Uptake in Cancer Patients Within a Qualified and Calibrated Local Network

Calibration and reproducibility of quantitative ¹⁸F-FDG PET measures are essential for adopting integral ¹⁸F-FDG PET/CT biomarkers and response measures in multicenter clinical trials. We implemented a multicenter qualification process using National Institute of Standards and Technology-traceable reference sources for scanners and dose calibrators, and similar patient and imaging protocols. We then assessed SUV in patient test-retest studies. Methods: Five ¹⁸F-FDG PET/CT scanners from 4 institutions (2 in a National Cancer Institute-designated Comprehensive Cancer Center, 3 in a community-based network) were qualified for study use. Patients were scanned twice within 15 d, on the same scanner (n = 10); different but same model scanners within an institution (n = 2); or different model scanners at different institutions (n = 11). SUV_max was recorded for lesions, and SUV_mean for normal liver uptake. Linear mixed models with random intercept were fitted to evaluate test-retest differences in multiple lesions per patient and to estimate the concordance correlation coefficient. Bland-Altman plots and repeatability coefficients were also produced. Results: In total, 162 lesions (82 bone, 80 soft tissue) were assessed in patients with breast cancer (n = 17) or other cancers (n = 6). Repeat scans within the same institution, using the same scanner or 2 scanners of the same model, had an average difference in SUV_max of 8% (95% confidence interval, 6%-10%). For test-retest on different scanners at different sites, the average difference in lesion SUV_max was 18% (95% confidence interval, 13%-24%). Normal liver uptake (SUV_mean) showed an average difference of 5% (95% confidence interval, 3%-10%) for the same scanner model or institution and 6% (95% confidence interval, 3%-11%) for different scanners from different institutions. Protocol adherence was good; the median difference in injection-to-acquisition time was 2 min (range, 0-11 min). Test-retest SUV_max variability was not explained by available information on protocol deviations or patient or lesion characteristics. Conclusion: ¹⁸F-FDG PET/CT scanner qualification and calibration can yield highly reproducible test-retest tumor SUV measurements. Our data support use of different qualified scanners of the same model for serial studies. Test-retest differences from different scanner models were greater; more resolution-dependent harmonization of scanner protocols and reconstruction algorithms may be capable of reducing these differences to values closer to same-scanner results.

ACRIN 6684: Multicenter, phase II assessment of tumor hypoxia in newly diagnosed glioblastoma using magnetic resonance spectroscopy

A multi-center imaging trial by the American College of Radiology Imaging Network (ACRIN) "A Multicenter, phase II assessment of tumor hypoxia in glioblastoma using 18F Fluoromisonidazole (FMISO) with PET and MRI (ACRIN 6684)", was conducted to assess hypoxia in patients with glioblastoma (GBM). The aims of this study were to support the role of proton magnetic resonance spectroscopic imaging (1H MRSI) as a prognostic marker for brain tumor patients in multi-center clinical trials. Seventeen participants from four sites had analyzable 3D MRSI datasets acquired on Philips, GE or Siemens scanners at either 1.5T or 3T. MRSI data were analyzed using LCModel to quantify metabolites N-acetylaspartate (NAA), creatine (Cr), choline (Cho), and lactate (Lac). Receiver operating characteristic curves for NAA/Cho, Cho/Cr, lactate/Cr, and lactate/NAA were constructed for overall survival at 1-year (OS-1) and 6-month progression free survival (PFS-6). The OS-1 for the 17 evaluable patients was 59% (10/17). Receiver operating characteristic analyses found the NAA/Cho in tumor (AUC = 0.83, 95% CI: 0.61 to 1.00) and in peritumoral regions (AUC = 0.95, 95% CI 0.85 to 1.00) were predictive for survival at 1 year. PFS-6 was 65% (11/17). Neither NAA/Cho nor Cho/Cr was effective in predicting 6-month progression free survival. Lac/Cr in tumor was a significant negative predictor of PFS-6, indicating that higher lactate/Cr levels are associated with poorer outcome. (AUC = 0.79, 95% CI: 0.54 to 1.00). In conclusion, despite the small sample size in the setting of a multi-center trial comprising different vendors, field strengths, and varying levels of expertise at data acquisition, MRS markers NAA/Cho, Lac/Cr and Lac/NAA predicted overall survival at 1 year and 6-month progression free survival. This study validates that MRSI may be useful in evaluating the prognosis in glioblastoma and should be considered for incorporating into multi-center clinical trials.

Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project

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.

Prospective Study of Serial 18F-FDG PET and 18F-Fluoride PET to Predict Time to Skeletal-Related Events, Time to Progression, and Survival in Patients with Bone-Dominant Metastatic Breast Cancer

Assessing therapy response of breast cancer bone metastases is challenging. In retrospective studies, serial ¹⁸F-FDG PET was predictive of time to skeletal-related events (tSRE) and time to progression (TTP). ¹⁸F-NaF PET improves bone metastasis detection compared with bone scanning. We prospectively tested ¹⁸F-FDG PET and ¹⁸F-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 ¹⁸F-FDG PET and ¹⁸F-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 ¹⁸F-FDG PET and ¹⁸F-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 ¹⁸F-FDG SUL_peak at scan2 predicted shorter time to tSRE (P = <0.001) and TTP (P = 0.044). Higher ¹⁸F-FDG SUV_max at scan2 predicted a shorter time to tSRE (P = <0.001). A multivariable model using ¹⁸F-FDG SUV_max of the index lesion at scan1 plus the difference in SUV_max of up to 5 lesions between scans was predictive for tSRE and TTP. Among 24 patients evaluable by ¹⁸F-FDG PET mPERCIST, tSRE and TTP were longer in responders (complete response, partial response, or stable disease) than in nonresponders (progressive disease) (P = 0.007, 0.028, respectively), with a trend toward improved survival (P = 0.1). An increase in the uptake between scans of up to 5 lesions by ¹⁸F-NaF PET was associated with longer OS (P = 0.027). Conclusion: Changes in ¹⁸F-FDG PET parameters during therapy are predictive of tSRE and TTP, but not OS. mPERCIST evaluation in bone lesions may be useful in assessing response to therapy and is worthy of evaluation in multicenter, prospective trials. Serial ¹⁸F-NaF PET was associated with OS but was not useful for predicting TTP or tSRE in bone-dominant MBC.

Inter-operator variability in compartmental kinetic analysis of 18F-fluoromisonidazole dynamic PET

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-V_B = 0.53; ICC-K₁ = 0.91; ICC-K₁/k₂ = 0.25; ICC-k3 = 0.32; ICC-K_i = 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.

Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network

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.

Assessment of a statistical AIF extraction method for dynamic PET studies with 15O water and 18F fluorodeoxyglucose in locally advanced breast cancer patients

Blood flow-metabolism mismatch from dynamic positron emission tomography (PET) studies with O15-labeled water (H2O) and F18-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.

Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies

This paper reports on results of a multisite collaborative project launched by the MRI subgroup of Quantitative Imaging Network to assess current capability and provide future guidelines for generating a standard parametric diffusion map Digital Imaging and Communication in Medicine (DICOM) in clinical trials that utilize quantitative diffusion-weighted imaging (DWI). Participating sites used a multivendor DWI DICOM dataset of a single phantom to generate parametric maps (PMs) of the apparent diffusion coefficient (ADC) based on two models. The results were evaluated for numerical consistency among models and true phantom ADC values, as well as for consistency of metadata with attributes required by the DICOM standards. This analysis identified missing metadata descriptive of the sources for detected numerical discrepancies among ADC models. Instead of the DICOM PM object, all sites stored ADC maps as DICOM MR objects, generally lacking designated attributes and coded terms for quantitative DWI modeling. Source-image reference, model parameters, ADC units and scale, deemed important for numerical consistency, were either missing or stored using nonstandard conventions. Guided by the identified limitations, the DICOM PM standard has been amended to include coded terms for the relevant diffusion models. Open-source software has been developed to support conversion of site-specific formats into the standard representation.

The use of 18F-fluoroestradiol (FES) and 18F-fluorodeoxyglucose (FDG) PET in the evaluation of breast cancer heterogeneity

11572

Background: 18F-Fluoroestradiol (FES) is an estrogen analogue that has been shown to be a promising biomarker in ER imaging of breast cancer. FES uptake correlates to ER expression, provides qualitative and quantitative assessment of multiple tumor sites simultaneously, and can predict response to endocrine therapies. Tumor heterogeneity is a known feature of metastatic breast cancer. Our work and others has shown that patients that have tumors with high FDG-PET SUV and low FES-PET SUV uptake have a poorer prognosis. Biopsies of metastatic disease may be done initially for diagnosis of metastatic disease, but are generally only performed in the setting of target identification for clinical trials. A change in ER or HER2 expression, however, can result in a change in therapy. FES-PET imaging offers a virtual biopsy and can reveal heterogeneity of the entire tumor burden. Methods: We reviewed our prior evaluations of tumor heterogeneity with FES-PET from 3 different studies. 46 breast cancer patients with metastatic disease (de novo or recurrent) who had biopsy proven ER+ primary breast cancer underwent FES-PET and FDG-PET imaging and a biopsy of a metastatic lesion prior to therapy initiation. ER and HER-2 expression was reviewed. Results: Of the 46 patients, 5 (11%) had ER- metastatic biopsies. One (2%) biopsy changed from ER+/HER-2 neg to ER-/HER-2+, and one (2%) biopsy changed from ER+/HER-2+ to ER+/HER-2-. All 5 patients (11%) with changes in ER/HER2 expression underwent a change in therapy due to the unexpected findings by metastatic biopsy. FDG findings helped to guide selection of biopsy sites. FES quantitative measures correlated with biopsy findings. Conclusions: Biopsy resulted in a change in therapy for > 10 % of patients enrolled in trials of FES imaging. Imaging can help identify heterogeneous tumor locations to assist identification of evolving tumor targets in breast cancer. In addition, FES imaging may reveal a change in tumor phenotype that can ultimately affect choice of therapy. Research Support: P01CA42045, R01CA72064

Assessment of tumor hypoxia in BEV resistant GBM using FMISO 18F-PET and MRI

2045

Background: Glioblastoma (GBM) is the most common malignant brain tumor in adults, and is characterized by poor survival and marked resistance to treatment. Hypoxic volume is directly correlated with poor outcome in GBM, with structural and functional tumor vasculature changes regarded as a primary driver of tumor hypoxia. As part of an ongoing clinical trial with a hypoxia activated prodrug, we sought to explore the correlation between abnormal tumor vasculature and hypoxia in bevacizumab (BEV) resistant GBM. Methods: MRI and 18F-FMISO PET scans were acquired at study entry. The MRI protocols include standard anatomical sequences as well as Dynamic Susceptibility Contrast (DSC/perfusion) imaging. Enhancing tumor ROIs were determined from Delta T1 maps, non-enhancing tumor ROIs were obtained from FLAIR images, ratio between enhancing and non-enhancing volumes were calculated, values from standardized rCBV maps were extracted from corresponding enhancing ROIs. Decay correction was applied to18F-FMISO images and converted to SUV units. After registration to MR images, cerebellar regions were used as surrogates for blood activity. The FMISO images were then normalized to generate tissue to blood ratio (TB). A threshold of TB > 1.2 was used in discriminating the hypoxia volume (HV). Correlation between parameters was assessed using Pearson correlation. Results: 7 patients from University of Texas Health Science center and 7 patients from Dana-Farber Cancer Institute had evaluable MR and PET imaging. We compared MRI parameters (enhancing and non-enhancing tumor volumes, srCBV) with hypoxia (HV and maxSUV). There was a positive correlation between HV and enhancing volume (R = 0.732, p = 0.0029) as well as between HV and ratio (R = 0.644, p = 0.013. The correlation between other pairs were not statistically significant (HV vs srCBV: p = 0.862, T1 vs maxSUV p = 0.492, srCBV vs maxSUV: p = 0.393, ratio vs maxSUV = 0.178). Conclusions: The hypoxic volume following bevacizumab failure correlates with both the volume of enhancement and the fraction of enhancement within the mass. The clinical implications of this is being assessed in an ongoing phase 2 study. Clinical trial information: NCT02342379.

Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data

PURPOSE

Radiomics utilizes a large number of image-derived features for quantifying tumor characteristics that can in turn be correlated with response and prognosis. Unfortunately, extraction and analysis of such image-based features is subject to measurement variability and bias. The challenge for radiomics is particularly acute in Positron Emission Tomography (PET) where limited resolution, a high noise component related to the limited stochastic nature of the raw data, and the wide variety of reconstruction options confound quantitative feature metrics. Extracted feature quality is also affected by tumor segmentation methods used to define regions over which to calculate features, making it challenging to produce consistent radiomics analysis results across multiple institutions that use different segmentation algorithms in their PET image analysis. Understanding each element contributing to these inconsistencies in quantitative image feature and metric generation is paramount for ultimate utilization of these methods in multi-institutional trials and clinical oncology decision making.

METHODS

To assess segmentation quality and consistency at the multi-institutional level, we conducted a study of seven institutional members of the National Cancer Institute Quantitative Imaging Network. For the study, members were asked to segment a common set of phantom PET scans acquired over a range of imaging conditions as well as a second set of head and neck cancer (HNC) PET scans. Segmentations were generated at each institution using their preferred approach. In addition, participants were asked to repeat segmentations with a time interval between initial and repeat segmentation. This procedure resulted in overall 806 phantom insert and 641 lesion segmentations. Subsequently, the volume was computed from the segmentations and compared to the corresponding reference volume by means of statistical analysis.

RESULTS

On the two test sets (phantom and HNC PET scans), the performance of the seven segmentation approaches was as follows. On the phantom test set, the mean relative volume errors ranged from 29.9 to 87.8% of the ground truth reference volumes, and the repeat difference for each institution ranged between -36.4 to 39.9%. On the HNC test set, the mean relative volume error ranged between -50.5 to 701.5%, and the repeat difference for each institution ranged between -37.7 to 31.5%. In addition, performance measures per phantom insert/lesion size categories are given in the paper. On phantom data, regression analysis resulted in coefficient of variation (CV) components of 42.5% for scanners, 26.8% for institutional approaches, 21.1% for repeated segmentations, 14.3% for relative contrasts, 5.3% for count statistics (acquisition times), and 0.0% for repeated scans. Analysis showed that the CV components for approaches and repeated segmentations were significantly larger on the HNC test set with increases by 112.7% and 102.4%, respectively.

CONCLUSION

Analysis results underline the importance of PET scanner reconstruction harmonization and imaging protocol standardization for quantification of lesion volumes. In addition, to enable a distributed multi-site analysis of FDG PET images, harmonization of analysis approaches and operator training in combination with highly automated segmentation methods seems to be advisable. Future work will focus on quantifying the impact of segmentation variation on radiomics system performance.

Abstract P4-02-05: Test-retest fidelity of FDG SUVmax in bone and non-boney metastatic breast cancer lesions in local area network PET/CT scanners

Background: Metabolic activity in lesions, measured by FDG-PET, is often used for assessing tumor aggressiveness and response to therapy. Patients may be scanned on different machines, so quantitative measurements should be reproducible. Reducing SUV variability in PET machines throughout a local network can aid in monitoring patient response to therapy and increase access to clinical trials.

Methods: Eighteen female patients with advanced or metastatic breast cancer underwent paired FDG PET/CT test-retest studies with 1-15 days between scans, and without interim change in treatment. Ten patients were studied in the same scanner and 8 patients were studied in 2 different scanners. Five different PET/CT scanners were used (2 GE DSTE, 2 Siemens (BioGraph 6 and mCT), 1 Philips Ingenuity TF). Each PET/CT scanner was calibrated using NIST-traceable reference sources to characterize and reduce variability. All of the images were interpreted by two separate reviewers. SUVmax values in lesions, corresponding normal tissue, and normal liver were collected. Linear mixed models with random intercept (patient effects) were fitted to compare differences in log(|SUVmax % difference|+.01) in multiple lesions per patient.

Results: SUVmax was assessed in a total of 130 lesions (75 bone). The median number of lesions per patient was 5 (range 1-17). Average SUVmax ranged from 1.0 to 18.2 (mean±SD = 6.0±3.2). The median SUVmax difference was 0.4 (8%) for 47 lesions imaged twice in the same scanner, and was 0.6 (13%) for 83 lesions imaged in two different scanners. In a multivariable linear mixed effects model, SUVmax for different scanners within the same institution did not differ more than for the same scanner (p=0.39), but repeat scans with different scanners and site personnel at had an average of 78% greater percentage difference in SUVmax than for the same scanner (p=0.009). In the same model, the average percent difference in SUVmax for bone lesions was estimated as 30% lower than for other sites (p=0.06, 95% confidence interval 0-50%). Examining normal liver uptake, the median SUVmean was 2.5 (range 1.9-3.1) with an median 6.5% difference between measurements (range 1.1%-23.7%) that did not appear to differ based on scanners used for repeat measurements (p=0.47).

Conclusions: The variability in quantitative FDG SUVmax between scans is modest, suggesting reliable reproducibility in appropriately calibrated settings. In our study, bone lesions had somewhat higher fidelity than other tumor sites. Additional studies will address variability in other cancer types. Careful calibration and monitoring of PET/CT scanners, and consistent imaging protocols are necessary in clinical trials that utilize quantitative PET/CT imaging in order to confidently interpret results.

Research Support: NIH grant U01-CA148131 and NCI-SAIC Contract 24XS036-004.

Citation Format: Linden HM, Peterson LM, Kurland B, Roberts T, Specht J, Shields AT, Novakova A, Christopfel R, Byrd D, Muzi M, Mankoff DA, Kinahan P. Test-retest fidelity of FDG SUVmax in bone and non-boney metastatic breast cancer lesions in local area network PET/CT scanners [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-02-05.

A virtual clinical trial comparing static versus dynamic PET imaging in measuring response to breast cancer therapy

We developed a method to evaluate variations in the PET imaging process in order to characterize the relative ability of static and dynamic metrics to measure breast cancer response to therapy in a clinical trial setting. We performed a virtual clinical trial by generating 540 independent and identically distributed PET imaging study realizations for each of 22 original dynamic fluorodeoxyglucose (¹⁸F-FDG) breast cancer patient studies pre- and post-therapy. Each noise realization accounted for known sources of uncertainty in the imaging process, such as biological variability and SUV uptake time. Four definitions of SUV were analyzed, which were SUVmax, SUVmean, SUVpeak, and SUV50%. We performed a ROC analysis on the resulting SUV and kinetic parameter uncertainty distributions to assess the impact of the variability on the measurement capabilities of each metric. The kinetic macro parameter, K _i , showed more variability than SUV (mean CV K _i   =  17%, SUV  =  13%), but K _i pre- and post-therapy distributions also showed increased separation compared to the SUV pre- and post-therapy distributions (mean normalized difference K _i   =  0.54, SUV  =  0.27). For the patients who did not show perfect separation between the pre- and post-therapy parameter uncertainty distributions (ROC AUC  <  1), dynamic imaging outperformed SUV in distinguishing metabolic change in response to therapy, ranging from 12 to 14 of 16 patients over all SUV definitions and uptake time scenarios (p  <  0.05). For the patient cohort in this study, which is comprised of non-high-grade ER+  tumors, K _i outperformed SUV in an ROC analysis of the parameter uncertainty distributions pre- and post-therapy. This methodology can be applied to different scenarios with the ability to inform the design of clinical trials using PET imaging.

ACRIN 6684: Assessment of Tumor Hypoxia in Newly Diagnosed Glioblastoma Using 18F-FMISO PET and MRI

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 (k^trans) 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 SUV_peak (P = 0.048), mean k^trans (P = 0.024), and median k^trans (P = 0.045) were significantly associated with shorter overall survival. Higher pretreatment median k^trans (P = 0.021), normalized RCBV (P = 0.0096), and nCBF (P = 0.038) were significantly associated with shorter progression-free survival. SUV_peak [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.

The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge

Dynamic contrast-enhanced MRI (DCE-MRI) has been widely used in tumor detection and therapy response evaluation. Pharmacokinetic analysis of DCE-MRI time-course data allows estimation of quantitative imaging biomarkers such as K^trans(rate constant for plasma/interstitium contrast reagent (CR) transfer) and v_e (extravascular and extracellular volume fraction). However, the use of quantitative DCE-MRI in clinical prostate imaging islimited, with uncertainty in arterial input function (AIF, i.e., the time rate of change of the concentration of CR in the blood plasma) determination being one of the primary reasons. In this multicenter data analysis challenge to assess the effects of variations in AIF quantification on estimation of DCE-MRI parameters, prostate DCE-MRI data acquired at one center from 11 prostate cancer patients were shared among nine centers. Each center used its site-specific method to determine the individual AIF from each data set and submitted the results to the managing center. Along with a literature population averaged AIF, these AIFs and their reference-tissue-adjusted variants were used by the managing center to perform pharmacokinetic analysis of the DCE-MRI data sets using the Tofts model (TM). All other variables including tumor region of interest (ROI) definition and pre-contrast T₁ were kept the same to evaluate parameter variations caused by AIF variations only. Considerable pharmacokinetic parameter variations were observed with the within-subject coefficient of variation (wCV) of K^trans obtained with unadjusted AIFs as high as 0.74. AIF-caused variations were larger in K^trans than v_e and both were reduced when reference-tissue-adjusted AIFs were used. The parameter variations were largely systematic, resulting in nearly unchanged parametric map patterns. The CR intravasation rate constant, k_ep (= K^trans/v_e), was less sensitive to AIF variation than K^trans (wCV for unadjusted AIFs: 0.45 for k_epvs. 0.74 for K^trans), suggesting that it might be a more robust imaging biomarker of prostate microvasculature than K^trans.