Explore the vast range of titles available.

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined.

We investigated automated quantitative measures of background parenchymal enhancement (BPE) derived from an early versus delayed post-contrast sequence in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for association with breast cancer presence in a case-control study. DCE-MRIs were retrospectively analyzed for 51 cancer cases and 51 controls with biopsy-proven benign lesions, matched by age and year-of-MRI. BPE was quantified using fully-automated validated computer algorithms, separately from three sequential DCE-MRI post-contrast-subtracted sequences (SUB1, SUB2, and SUB3). The association of BPE computed from the three SUBs and other known factors with breast cancer were assessed in terms of odds ratio (OR) and area under the receiver operating characteristic curve (AUC). The OR of breast cancer for the percentage BPE measure (BPE%) quantified from SUB1 was 3.5 (95% Confidence Interval: 1.3, 9.8; p = 0.015) for 20% increments. Slightly lower and statistically significant ORs were also obtained for BPE quantified from SUB2 and SUB3. There was no significant difference (p > 0.2) in AUC for BPE quantified from the three post-contrast sequences and their combination. Our study showed that quantitative measures of BPE are associated with breast cancer presence and the association was similar across three breast DCE-MRI post-contrast sequences.

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

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 ( 18 F-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 18 F-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 18 F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18 F-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. 18 F-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 18 F-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 18 F-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.

TMPRSS2/ERG rearrangement, PTEN gene deletion, and androgen receptor (AR) gene amplification have been observed in various stages of human prostate cancer. We hypothesized that using these markers as a combined panel would allow better differentiation between low-risk and high-risk prostate cancer. We analyzed 110 primary prostate cancer samples, 70 metastatic tumor samples from 11 patients, and 27 xenograft tissues derived from 22 advanced prostate cancer patients using fluorescence in situ hybridization (FISH) analysis with probes targeting the TMPRSS2/ERG, PTEN, and AR gene loci. Heterogeneity of the aberrations detected was evaluated. Genetic patterns were also correlated with transcript levels. Among samples with complete data available, the three-marker FISH panel detected chromosomal abnormalities in 53% of primary prostate cancers and 87% of metastatic (Met) or castration-resistant (CRPC) tumors. The number of markers with abnormal FISH result had a different distribution between the two groups (P<0.001). At the patient level, Met/CRPC tumors are 4.5 times more likely to show abnormalities than primary cancer patients (P<0.05). Heterogeneity among Met/CRPC tumors is mostly inter-patient. Intra-patient heterogeneity is primarily due to differences between the primary prostate tumor and the metastases while multiple metastatic sites show consistent abnormalities. Intra-tumor variability is most prominent with the AR copy number in primary tumors. AR copy number correlated well with the AR mRNA expression (rho = 0.52, P<0.001). Especially among TMPRSS2:ERG fusion-positive CRPC tumors, AR mRNA and ERG mRNA levels are strongly correlated (rho = 0.64, P<0.001). Overall, the three-marker FISH panel may represent a useful tool for risk stratification of prostate cancer patients.

The response of bone-dominant (BD) breast cancer to therapy is difficult to assess by conventional imaging. Our preliminary studies have shown that quantitative serial 2-[(18)F] fluoro-2-deoxy-D: -glucose positron emission tomography (FDG PET) correlates with therapeutic response of BD breast cancer, but the relationship to long-term outcome measures is unknown. Our goal was to evaluate the prognostic power of serial FDG PET in BD breast cancer patients undergoing treatment. We reviewed medical records of 405 consecutive breast cancer patients referred for FDG PET. Of these, 28 demonstrated metastatic BD breast cancer, were undergoing treatment, had at least 2 serial PET scans, and had abnormal FDG uptake on the first scan. Standardized uptake value (SUV) for the most conspicuous bone lesion at the initial scan, absolute change in SUV over an interval of 1-17 months, and percent change in SUV were considered as predictors of time-to-progression (TTP) and time to skeletal-related event (t-SRE). Using proportional hazards regression, smaller percentage decreases in SUV (or increases in SUV) were associated with a shorter TTP (P < 0.006). A patient with no change in SUV was twice as likely to progress compared to a patient with a 42% median decrease in SUV. A higher SUV on the initial FDG PET predicted a shorter t-SRE (hazard ratio = 1.30, P < 0.02). Changes in serial FDG PET may predict TTP in BD metastatic breast cancer patients. However, larger prospective trials are needed to validate changes in FDG PET as a surrogate endpoint for treatment response.

PurposeGlioblastoma is a lethal brain tumor, heavily infiltrated by tumor-associated myeloid cells (TAMCs). TAMCs are emerging as a promising therapeutic target as they suppress anti-tumor immune responses and promote tumor cell growth. Quantifying TAMCs using non-invasive immunoPET could facilitate patient stratification for TAMC-targeted treatments and monitoring of treatment efficacy. As TAMCs uniformly express the cell surface marker, integrin CD11b, we evaluated a Zr-89 labeled anti-CD11b antibody for non-invasive imaging of TAMCs in a syngeneic orthotopic mouse glioma model.ProceduresA human/mouse cross-reactive anti-CD11b antibody (clone M1/70) was conjugated to a DFO chelator and radiolabeled with Zr-89. PET/CT and biodistribution with or without a blocking dose of anti-CD11b Ab were performed 72 h post-injection (p.i.) of [89Zr]anti-CD11b Ab in mice bearing established orthotopic syngeneic GL261 gliomas and in non tumor-bearing mice. Flow cytometry and immunohistochemistry of dissected GL261 tumors were conducted to confirm the presence of CD11b+ TAMCs.ResultsSignificant uptake of [89Zr]anti-CD11b Ab was detected at the tumor site (SUVmean = 2.60 ± 0.24) compared with the contralateral hemisphere (SUVmean = 0.6 ± 0.11). Blocking with a 10-fold lower specific activity of [89Zr]anti-CD11b Ab markedly reduced the SUV in the right brain (SUVmean = 0.11 ± 0.06), demonstrating specificity. Spleen and lymph nodes (myeloid cell rich organs) also showed high uptake of the tracer, and biodistribution analysis correlated with the imaging results. CD11b expression within the tumor was validated using flow cytometry and immunohistochemistry, which showed high CD11b expression primarily in the tumoral hemisphere compared with the contralateral hemisphere with very minimal accumulation in non tumor-bearing brain.ConclusionThese data establish that [89Zr]anti-CD11b Ab immunoPET targets CD11b+ cells (TAMCs) with high specificity in a mouse model of GBM, demonstrating the potential for non-invasive quantification of tumor-infiltrating CD11b+ immune cells during disease progression and immunotherapy in patients with GBM.

Diverse analysis approaches have been proposed to distinguish data missing due to death from nonresponse, and to summarize trajectories of longitudinal data truncated by death. We demonstrate how these analysis approaches arise from factorizations of the distribution of longitudinal data and survival information. Models are illustrated using cognitive functioning data for older adults. For unconditional models, deaths do not occur, deaths are independent of the longitudinal response, or the unconditional longitudinal response is averaged over the survival distribution. Unconditional models, such as random effects models fit to unbalanced data, may implicitly impute data beyond the time of death. Fully conditional models stratify the longitudinal response trajectory by time of death. Fully conditional models are effective for describing individual trajectories, in terms of either aging (age, or years from baseline) or dying (years from death). Causal models (principal stratification) as currently applied are fully conditional models, since group differences at one timepoint are described for a cohort that will survive past a later timepoint. Partly conditional models summarize the longitudinal response in the dynamic cohort of survivors. Partly conditional models are serial cross-sectional snapshots of the response, reflecting the average response in survivors at a given timepoint rather than individual trajectories. Joint models of survival and longitudinal response describe the evolving health status of the entire cohort. Researchers using longitudinal data should consider which method of accommodating deaths is consistent with research aims, and use analysis methods accordingly.

Background We investigated dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) contrast enhancement kinetic variables quantified from normal breast parenchyma for association with presence of breast cancer, in a case-control study. Methods Under a Health Insurance Portability and Accountability Act compliant and Institutional Review Board-approved protocol, DCE-MRI scans of the contralateral breasts of 51 patients with cancer and 51 controls (matched by age and year of MRI) with biopsy-proven benign lesions were retrospectively analyzed. Applying fully automated computer algorithms on pre-contrast and multiple post-contrast MR sequences, two contrast enhancement kinetic variables, wash-in slope and signal enhancement ratio, were quantified from normal parenchyma of the contralateral breasts of both patients with cancer and controls. Conditional logistic regression was employed to assess association between these two measures and presence of breast cancer, with adjustment for other imaging factors including mammographic breast density and MRI background parenchymal enhancement (BPE). The area under the receiver operating characteristic curve (AUC) was used to assess the ability of the kinetic measures to distinguish patients with cancer from controls. Results When both kinetic measures were included in conditional logistic regression analysis, the odds ratio for breast cancer was 1.7 (95 % CI 1.1, 2.8; p  = 0.017) for wash-in slope variance and 3.5 (95 % CI 1.2, 9.9; p  = 0.019) for signal enhancement ratio volume, respectively. These odds ratios were similar on respective univariate analysis, and remained significant after adjustment for menopausal status, family history, and mammographic density. While percent BPE was associated with an odds ratio of 3.1 (95 % CI 1.2, 7.9; p  = 0.018), in multivariable analysis of the three measures, percent BPE was non-significant ( p  = 0.897) and the two kinetics measures remained significant. For the differentiation of patients with cancer and controls, the unadjusted AUC was 0.71 using a combination of the two measures, which significantly ( p  = 0.005) outperformed either measure alone (AUC = 0.65 for wash-in slope variance and 0.63 for signal enhancement ratio volume). Conclusions Kinetic measures of wash-in slope and signal enhancement ratio quantified from normal parenchyma in DCE-MRI are jointly associated with presence of breast cancer, even after adjustment for mammographic density and BPE.

Background Clinical validation of a predictive biomarker is especially difficult when the biomarker cannot be assessed retrospectively. A cost-effective, prospective multicenter replication study with rapid accrual is warranted prior to further validation studies such as a marker-based strategy for treatment selection. However, it is often unknown how measurement error and bias in a multicenter trial will differ from that in single-institution studies. Purpose Power calculations using simulated data may inform the efficient design of a multicenter study to replicate single-institution findings. This case study used serial standardized uptake value (SUV) measures from 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) to predict early response to breast cancer neoadjuvant chemotherapy. We examined the impact of accelerating accrual through increased inclusion of secondary sites with greater levels of measurement error and bias. We also examined whether enrichment designs based on breast cancer initial uptake could increase the study power for a fixed budget (200 total scans). Methods Reference FDG PET SUV data were selected with replacement from a single-institution trial; pathologic complete response (pCR) data were simulated using a logistic regression model predicting response by mid-therapy percent change in SUV. The impact of increased error for SUV measurements in multicenter trials was simulated by sampling from error and bias distributions: 20%−40% measurement error, 0%−40% bias, and fixed error/bias values. The proportion of patients recruited from secondary sites (with higher additional error/bias compared to primary sites) varied from 25% to 75%. Results Reference power (from source data with no added error) was 0.92 for N = 100 to detect an association between percentage change in SUV and response. With moderate (20%) simulated measurement error for 3/4, 1/2, and 1/4 of measurements and 40% for the remainder, power was 0.70, 0.61, and 0.53, respectively. Reduction of study power was similar for other manifestations of measurement error (bias as a percentage of true value, absolute error, and absolute bias). Enrichment designs, which recruit additional patients by not conducting a second scan in patients with unsuitable pre-therapy uptake (low baseline SUV), did not lead to greater power for studies constrained to the same total cost. Limitations Simulation parameters could be incorrect, or not generalizable. Under a different logistic regression model relating mid-therapy percent change in SUV to pCR (with no relationship for patients with low baseline SUV, rather than the modest point estimate from reference data), the enrichment design did have somewhat greater power than the unselected design. Conclusion Even moderate additional measurement error substantially reduced study power under both unselected and enrichment designs.