FDG-PET Measures Research Articles

Coupling motor evoked potentials and brain [18F]FDG-PET in Amyotrophic Lateral Sclerosis: preliminary findings on disease severity

BackgroundThe diagnosis of amyotrophic lateral sclerosis (ALS) is primarily clinical, supported by the electromyographic examination to reveal signs of lower motor neuron damage. Identifying reliable markers of upper motor neuron (UMN) involvement is challenging. On this regard, the role of transcranial magnetic stimulation-induced motor-evoked potentials (TMS-MEPs), and its relationship with UMN burden, is still under investigation. ObjectiveTo evaluate the ability of TMS-MEPs in delineating the neurophysiological UMN damage, and to determine the relationship between TMS-MEPs and [18F]FDG-PET measures of neural dysfunction. MethodsWe retrospectively selected 13 ALS patients who underwent, during the diagnostic process, the TMS-MEPs and [18F]FDG-PET scans. Demographic and clinical data were collected. For the MEP evaluation, we considered normal MEP, absent MEP, or significantly increased central-motor-conduction-time. For [18F]FDG-PET, we conducted voxel-wise analyses, both at single-subject and group levels, exploring hypometabolism and hypermetabolism patterns in comparison with a large dataset of healthy controls (HC). ResultsBased on TMS-MEPs, we identified 4/13 patients with normal MEP in all limbs (GROUP-NO), while 9/13 had an abnormal MEP in at least one limb (GROUP-AB). Despite the [18F]FDG-PET single-subject analysis revealed heterogenous expression of regional hypo- and hyper-metabolism patterns in the patients, the group-level analysis revealed a common hypometabolism, involving the precentral gyrus and the supplementary motor area, the paracentral lobule and the anterior cingulate cortex in the GROUP-AB. Moreover, exclusively for the GROUP-AB compared with HC, a relative hypermetabolism was observed in the right cerebellum, right inferior and middle temporal gyrus. The GROUP-NO showed no specific cluster of hypo- and hyper-metabolism compared to HC. ConclusionThis study showed altered brain metabolism only in the ALS group with abnormal MEPs, suggesting an association between the two biomarkers in defining the UMN damage.

Analysis of cerebral glucose metabolism following experimental subarachnoid hemorrhage over 7 days

Little is known about changes in brain metabolism following SAH, possibly leading towards secondary brain damage. Despite sustained progress in the last decade, analysis of in vivo acquired data still remains challenging. The present interdisciplinary study uses a semi-automated data analysis tool analyzing imaging data independently from the administrated radiotracer. The uptake of 2-[18F]Fluoro-2-deoxy-glucose ([18F]FDG) was evaluated in different brain regions in 14 male Sprague–Dawley rats, randomized into two groups: (1) SAH induced by the endovascular filament model and (2) sham operated controls. Serial [18F]FDG-PET measurements were carried out. Quantitative image analysis was performed by uptake ratio using a self-developed MRI-template based data analysis tool. SAH animals showed significantly higher [18F]FDG accumulation in gray matter, neocortex and olfactory system as compared to animals of the sham group, while white matter and basal forebrain region showed significant reduced tracer accumulation in SAH animals. All significant metabolic changes were visualized from 3 h, over 24 h (day 1), day 4 and day 7 following SAH/sham operation. This [18F]FDG-PET study provides important insights into glucose metabolism alterations following SAH—for the first time in different brain regions and up to day 7 during course of disease.

Differential impact of body mass index and leptin on baseline and longitudinal positron emission tomography measurements of the cerebral metabolic rate for glucose in amnestic mild cognitive impairment.

Several studies have suggested that greater adiposity in older adults is associated with a lower risk of Alzheimer's disease (AD) related cognitive decline, some investigators have postulated that this association may be due to the protective effects of the adipose tissue-derived hormone leptin. In this study we sought to demonstrate that higher body mass indices (BMIs) are associated with greater baseline FDG PET measurements of the regional cerebral metabolic rate for glucose (rCMRgl), a marker of local neuronal activity, slower rCMRgl declines in research participants with amnestic mild cognitive impairment (aMCI). We then sought to clarify the extent to which those relationships are attributable to cerebrospinal fluid (CSF) or plasma leptin concentrations. We used baseline PET images from 716 73 ± 8 years-old aMCI participants from the AD Neuroimaging Initiative (ADNI) of whom 453 had follow up images (≥6 months; mean follow up time 3.3 years). For the leptin analyses, we used baseline CSF samples from 81 of the participants and plasma samples from 212 of the participants. As predicted, higher baseline BMI was associated with greater baseline CMRgl measurements and slower declines within brain regions preferentially affected by AD. In contrast and independently of BMI, CSF, and plasma leptin concentrations were mainly related to less baseline CMRgl within mesocorticolimbic brain regions implicated in energy homeostasis. While higher BMIs are associated with greater baseline CMRgl and slower declines in persons with aMCI, these associations appear not to be primarily attributable to leptin concentrations.

Meta-Analysis of the Test-Retest Repeatability of [18F]-Fluorodeoxyglucose Standardized Uptake Values: Implications for Assessment of Tumor Response.

Currently, guidelines for PET with 18F-fluorodeoxyglucose (FDG-PET) interpretation for assessment of therapy response in oncology primarily involve visual evaluation of FDG-PET/CT scans. However, quantitative measurements of the metabolic activity in tumors may be even more useful in evaluating response to treatment. Guidelines based on such measurements, including the European Organization for Research and Treatment of Cancer Criteria and PET Response Criteria in Solid Tumors, have been proposed. However, more rigorous analysis of response criteria based on FDG-PET measurements is needed to adopt regular use in practice. Well-defined boundaries of repeatability and reproducibility of quantitative measurements to discriminate noise from true signal changes are a needed initial step. An extension of the meta-analysis from de Langen and colleagues (2012) of the test-retest repeatability of quantitative FDG-PET measurements, including mean, maximum, and peak standardized uptake values (SUVmax, SUVmean, and SUVpeak, respectively), was performed. Data from 11 studies in the literature were used to estimate the relationship between the variance in test-retest measurements with uptake level and various study-level, patient-level, and lesion-level characteristics. Test-retest repeatability of percentage fluctuations for all three types of SUV measurement (max, mean, and peak) improved with higher FDG uptake levels. Repeatability in all three SUV measurements varied for different lesion locations. Worse repeatability in SUVmean was also associated with higher tumor volumes. On the basis of these results, recommendations regarding SUV measurements for assessing minimal detectable changes based on repeatability and reproducibility are proposed. These should be applied to differentiate between response categories for a future set of FDG-PET-based criteria that assess clinically significant changes in tumor response.

Neuronal efficiency following n-back training task is accompanied by a higher cerebral glucose metabolism

Recent functional magnetic resonance imaging (fMRI) studies revealed lower neural activation during processing of an n-back task following working memory training, indicating a training-related increase in neural efficiency. In the present study, we asked if the training induced regional neural activation is accompanied by changes in glucose consumption. An active control and an experimental group of healthy middle-aged volunteers conducted 32 sessions of visual and verbal n-back trainings over 8 weeks. We analyzed data of 52 subjects (25 experimental and 27 control group) for practice effects underlying verbal working memory task and 50 subjects (24 experimental and 26 control group) for practice effects underlying visual WM task. The samples of these two tasks were nearly identical (data of 47 subjects were available for both verbal and visual tasks). Both groups completed neuroimaging sessions at a hybrid PET/MR system before and after training. Each session included criterion task fMRI and resting state positron emission tomography with FDG (FDG-PET). As reported previously, lower neural activation following n-back training was found in regions of the fronto-parieto-cerebellar circuitry during a verbal n-back task. Notably, these changes co-occurred spatially with a higher relative FDG-uptake. Decreased neural activation within regions of the fronto-parietal network during visual n-back task did not show co-occurring changes in relative FDG-uptake. There was no direct association between neuroimaging and behavioral measures, which could be due to the inter-subjects’ variability in reaching capacity limits. Our findings provide new details for working memory training induced neural efficiency on a molecular level by integrating FDG-PET and fMRI measures.

P62.07 Pre-surgical Assessment of Mediastinal Lymph Node Metastases in Stage IA Non-small-cell Lung Cancers

CT and FDG-PET measurements of mediastinal lymph nodes (MLNs) of patients with non small cell lung cancers (NSCLCs) are recommended for pre-surgical prediction of MLN metastases. As the frequency of MLN metastases differs markedly by the cancer consistency on CT, and clinical staging determines the possible treatment choices, particularly surgery, we decided to assess the sensitivity and specificity of CT and FDG-PET for predicting MLN metastases in a prospectively collected cohort of clinical Stage IA NSCLC patients.

Abstract 2817: Metabolic heterogeneity in breast cancer integrative clusters to screen metabolic vulnerabilities for diagnosis and treatment response

Abstract Introduction: Metabolic adaptation occurs in transformed cells and can be exploited clinically for diagnosis and disease monitoring. Metabolic profiles can be influenced by genetic heterogeneity, both within and between tumors. Breast tumors show considerable intra and inter tumor genomic heterogeneity, which partly accounts for the variable clinical course of the disease and response to treatment. Imaging tumor metabolism may provide a metabolic signature that can be used to stratify patients. Methods: We have investigated eight patient-derived xenograft (PDX) models of breast cancer to determine whether metabolic imaging can be linked to different “integrative clusters” (Int-Cluster), which are defined by their distinctive genomic profiles and clinical outcomes. Metabolic imaging was performed using PET measurements of the uptake, phosphorylation, and trapping of the glucose analog, 2-deoxy-2-[18F]fluorodeoxyglucose ([18F]FDG), catalyzed by hexokinase II, and 13C magnetic resonance spectroscopy (MRS) measurements of hyperpolarized 13C label exchange between [1-13C]pyruvate and the endogenous tumor lactate pool, catalyzed by lactate dehydrogenase A. Results: Lactate labelling was higher in Int-Clusters dominated by ER- basal-like PDXs from patients with a poor short-term prognosis. Lower levels of lactate labelling were observed in Int-Clusters dominated by estrogen receptor positive (ER+) PDXs and the Pam50 subtypes, Luminal A and B, from patients which have an intermediate to good prognosis. More importantly, tumors that had a similar genomic profile nevertheless showed differences in lactate labeling, that was not observed in the [18F]FDGPET measurements. Although lactate labelling was low in the ER+ tumor models, decreases in lactate labeling could be used to detect treatment response, for example to drugs targeted at the most frequently mutated oncogene in this tumor subtype, PI3KCA. Discussion: These results illustrate the potential importance of metabolism-based stratification of breast cancer and demonstrate that metabolic imaging can provide diagnostic information that could be important for non-invasive diagnosis and for designing and monitoring therapeutic strategies. Citation Format: Susana Ros, Alan J. Wright, Flaviu Bulat, Wendy Greenwood, De-en Hu, Maurizio Callari, Ming Li Chia, Violeta Serra, Oscar Rueda, Alejandra Bruna, Carlos Caldas, Kevin M. Brindle. Metabolic heterogeneity in breast cancer integrative clusters to screen metabolic vulnerabilities for diagnosis and treatment response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2817.

Clinical Relevance of [18F]Florbetaben and [18F]FDG PET/CT Imaging on the Management of Patients with Dementia.

PET of β-Amyloid plaques (Aβ) using [18F]florbetaben ([18F]FBB) and [18F]fluorodeoxyglucose ([18F]FDG) increasingly aid clinicians in early diagnosis of dementia, including Alzheimer’s disease (AD), frontotemporal disease, dementia with Lewy bodies, and vascular dementia. The aim of this retrospective analysis was to evaluate clinical relevance of [18F]FBB, [18F]FDG PET and complimentary CSF measurements in patients with suspected dementia. In this study, 40 patients with clinically suspected or history of dementia underwent (1) measurement of Aβ peptides, total tau, and p-tau protein levels in the cerebrospinal fluid (CSF) compared with healthy controls (HC); (2) clinical and neuropsychological assessment, which included Consortium to Establish a Registry for Alzheimer’s Disease neuropsychological assessment battery (CERAD-NAB); (3) [18F]FBB and [18F]FDG PET imaging within an average of 3 weeks. The subjects were within 15 days stratified using PET, CSF measurements as HC, mild cognitive impaired (MCI) and dementia including Alzheimer´s disease. The predictive dementia-related cognitive decline values were supporting the measurements. PET images were evaluated visually and quantitatively using standard uptake value ratios (SUVR). Twenty-one (52.5%) subjects were amyloid-positive (Aβ+), with a median neocortical SUVR of 1.80 for AD versus 1.20 relative to the respective 19 (47.5 %) amyloid-negative (Aβ-) subjects. Moreover, the [18F]FDG and [18F]FBB confirmed within a sub-group of 10 patients a good complimentary role by correlation between amyloid pathology and brain glucose metabolism in 8 out of 10 subjects. The results suggest the clinical relevance for [18F]FBB combined with [18F]FDG PET retention and CFS measurements serving the management of our patients with dementia. Therefore, [18F]FBB combined with [18F]FDG PET is a helpful tool for differential diagnosis, and supports the patients’ management as well as treatment.

Frailty, MRI, and FDG-PET Measures in an Australian Memory Clinic Cohort

Given that the global population is aging, the number of age-related syndromes, such as frailty, is expected to rise in conjunction. Frailty is characterized by the loss of homeostatic reserve, rendering the individual vulnerable to poor health outcomes. Many biological mechanisms have been proposed to contribute to frailty. However, few studies have assessed the associations between frailty and brain diseases or neuroimaging biomarkers.Aims: The aims of this study were to measure the prevalence of frailty in a memory clinic and to examine associations between frailty and brain changes found on magnetic resonance imaging (MRI) and 18-F deoxyglucose (FDG) positron emission tomography (PET) in memory clinic attendees.Methods: A 54-items Frailty Index was retrospectively assessed for all clinic attendees from 2014. Frailty was defined as FI > 0.25. MR images were analyzed for stroke, cerebral small vessel disease [CSVD, including cerebral microbleeds (CMBs), cortical superficial siderosis (CSS), and white matter hyperintensity (WMH)], and neurodegenerative changes [MRI: mesial temporal atrophy (MTA), FDG-PET: regional hypometabolism], blind to clinical findings.Results: There were 209 clinic attendees in 2014, of whom 121 had MRI performed. The prevalence of frailty (using FI) in the memory clinic in 2014 was 38.3% overall (patients without MRI: 43.2%, patients with MRI 34.7%, p = 0.25). Frailty was associated with presence of deep WMH, increased severity of periventricular WMH, and presence of CSS, but not neurodegeneration markers (MTA atrophy/FDG-PET hypometabolism).Conclusion: The findings support the idea that previously reported associations between frailty and imaging evidence of CSVD in other cohorts are also relevant to the Australian clinic setting. Given that a large proportion of memory clinic attendees are frail, there may be opportunities for interventions to reduce preventable adverse health outcomes, such as falls and fractures, and reduce the prevalence and impact of frailty in this cohort.

Improved Prediction of Imminent Progression to Clinically Significant Memory Decline Using Surface Multivariate Morphometry Statistics and Sparse Coding.

Besides their other roles, brain imaging and other biomarkers of Alzheimer's disease (AD) have the potential to inform a cognitively unimpaired (CU) person's likelihood of progression to mild cognitive impairment (MCI) and benefit subject selection when evaluating promising prevention therapies. We previously described that among baseline FDG-PET and MRI measures known to be preferentially affected in the preclinical and clinical stages of AD, hippocampal volume was the best predictor of incident MCI within 2 years (79%sensitivity/78%specificity), using standard automated MRI volumetric algorithmic programs, binary logistic regression, and leave-one-out procedures. To improve the same prediction by using different hippocampal features and machine learning methods, cross-validated via two independent and prospective cohorts (Arizona and ADNI). Patch-based sparse coding algorithms were applied to hippocampal surface features of baseline TI-MRIs from 78 CU adults who subsequently progressed to amnestic MCI in approximately 2 years ("progressors") and 80 matched adults who remained CU for at least 4 years ("nonprogressors"). Nonprogressors and progressors were matched for age, sex, education, and apolipoprotein E4 allele dose. We did not include amyloid or tau biomarkers in defining MCI. We achieved 92%prediction accuracy in the Arizona cohort, 92%prediction accuracy in the ADNI cohort, and 90%prediction accuracy when combining the two demographically distinct cohorts, as compared to 79%(Arizona) and 72%(ADNI) prediction accuracy using hippocampal volume. Surface multivariate morphometry and sparse coding, applied to individual MRIs, may accurately predict imminent progression to MCI even in the absence of other AD biomarkers.

Pyruvate-lactate exchange and glucose uptake in human prostate cancer cell models. A study in xenografts and suspensions by hyperpolarized [1-13 C]pyruvate MRS and [18 F]FDG-PET.

Reprogramming of energy metabolism in the development of prostate cancer can be exploited for a better diagnosis and treatment of the disease. The goal of this study was to determine whether differences in glucose and pyruvate metabolism of human prostate cancer cells with dissimilar aggressivenesses can be detected using hyperpolarized [1‐13C]pyruvate MRS and [18F]FDG‐PET imaging, and to evaluate whether these measures correlate. For this purpose, we compared murine xenografts of human prostate cancer LNCaP cells with those of more aggressive PC3 cells. [1‐13C]pyruvate was hyperpolarized by dissolution dynamic nuclear polarization (dDNP) and [1‐13C]pyruvate to lactate conversion was followed by 13C MRS. Subsequently [18F]FDG uptake was investigated by static and dynamic PET measurements.Standard uptake values (SUVs) for [18F]FDG were significantly higher for xenografts of PC3 compared with those of LNCaP. However, we did not observe a difference in the average apparent rate constant k pl of 13C label exchange from pyruvate to lactate between the tumor variants. A significant negative correlation was found between SUVs from [18F]FDG PET measurements and k pl values for the xenografts of both tumor types. The k pl rate constant may be influenced by various factors, and studies with a range of prostate cancer cells in suspension suggest that LDH inhibition by pyruvate may be one of these. Our results indicate that glucose and pyruvate metabolism in the prostate cancer cell models differs from that in other tumor models and that [18F]FDG‐PET can serve as a valuable complementary tool in dDNP studies of aggressive prostate cancer with [1‐13C]pyruvate.

Utility of FDG-PET in diagnosis of Alzheimer-related TDP-43 proteinopathy.

To evaluate FDG-PET as an antemortem diagnostic tool for Alzheimer-related TAR DNA-binding protein of 43 kDa (TDP-43) proteinopathy. We conducted a cross-sectional neuroimaging-histologic analysis of patients with antemortem FDG-PET and postmortem brain tissue from the Mayo Clinic Alzheimer's Disease Research Center and Study of Aging with Alzheimer spectrum pathology. TDP-43-positive status was assigned when TDP-43-immunoreactive inclusions were identified in the amygdala. Statistical parametric mapping (SPM) analyses compared TDP-43-positive (TDP-43[+]) with TDP-43-negative cases (TDP-43[-]), correcting for field strength, sex, Braak neurofibrillary tangle, and neuritic plaque stages. Cross-validated logistic regression analyses were used to determine whether regional FDG-PET values predict TDP-43 status. We also assessed the ratio of inferior temporal to medial temporal (IMT) metabolism as this was proposed as a biomarker of hippocampal sclerosis. Of 73 cases, 27 (37%) were TDP-43(+), of which 6 (8%) had hippocampal sclerosis. SPM analysis showed TDP-43(+) cases having greater hypometabolism of medial temporal, frontal superior medial, and frontal supraorbital (FSO) regions (p unc < 0.001). Logistic regression analysis showed only FSO and IMT to be associated with TDP-43(+) status, identifying up to 81% of TDP-43(+) cases (p < 0.001). An IMT/FSO ratio was superior to the IMT in discriminating TDP-43(+) cases: 78% vs 48%, respectively. Alzheimer-related TDP-43 proteinopathy is associated with hypometabolism in the medial temporal and frontal regions. Combining FDG-PET measures from these regions may be useful for antemortem prediction of Alzheimer-related TDP-43 proteinopathy. This study provides Class II evidence that hypometabolism in the medial temporal and frontal regions on FDG-PET is associated with Alzheimer-related TDP-43 proteinopathy.

Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis.

Brain imaging genetics aims to reveal genetic effects on brain phenotypes, where most studies examine phenotypes defined on anatomical or functional regions of interest (ROIs) given their biologically meaningful annotation and modest dimensionality compared with voxel-wise approaches. Typical ROI-level measures used in these studies are summary statistics from voxel-wise measures in the region, without making full use of individual voxel signals. In this paper, we propose a flexible and powerful framework for mining regional imaging genetic associations via voxel-wise enrichment analysis, which embraces the collective effect of weak voxel-level signals within an ROI. We demonstrate our method on an imaging genetic analysis using data from the Alzheimers Disease Neuroimaging Initiative, where we assess the collective regional genetic effects of voxel-wise FDGPET measures between 116 ROIs and 19 AD candidate SNPs. Compared with traditional ROI-wise and voxel-wise approaches, our method identified 102 additional significant associations, some of which were further supported by evidences in brain tissue-specific expression analysis. This demonstrates the promise of the proposed method as a flexible and powerful framework for exploring imaging genetic effects on the brain.

Functional resting-state brain connectivity is accompanied by dynamic correlations of application-dependent [18F]FDG PET-tracer fluctuations

Brain function is characterized by a convolution of various biochemical and physiological processes, raising the interest whether resting-state functional connectivity derived from hemodynamic scales shows underlying metabolic synchronies. Increasing evidence suggests that metabolic connectivity based on glucose consumption associated PET recordings may serve as a marker of cognitive functions and neuropathologies. However, to what extent fMRI-derived resting-state brain connectivity can also be characterized based on dynamic fluctuations of glucose metabolism and how metabolic connectivity is influenced by [18F]FDG pharmacokinetics remains unsolved.Simultaneous PET/MRI measurements were performed in a total of 26 healthy male Lewis rats. Simultaneously to resting-state fMRI scans, one cohort (n = 15) received classical bolus [18F]FDG injections and dynamic PET images were recorded. In a second cohort (n = 11) [18F]FDG was constantly infused over the entire functional PET/MRI scans. Resting-state fMRI and [18F]FDG-PET connectivity was evaluated using a graph-theory based correlation approach and compared on whole-brain level and for a default-mode network-like structure. Further, pharmacokinetic and tracer uptake influences on [18F]FDG-PET connectivity results were investigated based on the different PET protocols.By integrating simultaneous resting-state fMRI and dynamic [18F]FDG-PET measurements in the rat brain, we identified homotopic correlations between both modalities, suggesting an underlying synchrony between hemodynamic processes and glucose consumption.Furthermore, the presence of the prominent resting-state default-mode network-like structure was not only depicted on a functional scale but also from dynamic fluctuations of [18F]FDG. In addition, the present findings demonstrated strong pharmacokinetic and tracer uptake dependencies of [18F]FDG-PET connectivity outcomes.This study highlights the application of dynamic [18F]FDG-PET to study cognitive brain functions and to decode underlying brain networks in the resting-state. Thereby, PET-derived connectivity outcomes indicated strong dependencies on tracer application regimens and subsequent time-varying tracer pharmacokinetics.

Longitudinal Changes in Serum Glucose Levels are Associated with Metabolic Changes in Alzheimer's Disease Related Brain Regions.

The association between longitudinal changes in serum glucose level and longitudinal changes in [18F] Fluorodeoxyglucose-PET (FDG PET) measurements of Alzheimer's disease (AD) risk are unknown. To investigate whether variation in serum glucose levels across time are associated with changes in FDG PET measurements of cerebral metabolic rate for glucose (rCMRgl) in brain regions preferentially affected by Alzheimer's disease (AD). Participants are a subset of a prospective cohort study investigating FDG PET, apolipoprotein E (APOE) ɛ4, and risk for AD which includes data from baseline, interim, and follow up visits over 4.4±1.0-years. An automated brain-mapping algorithm was utilized to characterize and compare associations between longitudinal changes in serum glucose levels and longitudinal changes in rCMRgl. This study included 80 adults aged 61.5±5 years, including 38 carriers and 42 non-carriers of the APOE ɛ4 allele. Longitudinal increases in serum glucose levels were associated with longitudinal CMRgl decline in the vicinity of parietotemporal, precuneus/posterior cingulate, and prefrontal brain regions preferentially affected by AD (p < 0.05, corrected for multiple comparisons). Findings remained significant when controlled for APOE ɛ4 status and baseline and advancing age. Additional studies are needed to clarify and confirm the relationship between longitudinal changes in peripheral glucose and FDG PET measurements of AD risk. Future findings will set the stage on the use of FDG PET in the evaluation of possible interventions that target risk factors for the development of AD.

Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules.

Network-based genome-wide association studies (GWAS) aim to identify functional modules from biological networks that are enriched by top GWAS findings. Although gene functions are relevant to tissue context, most existing methods analyze tissue-free networks without reflecting phenotypic specificity. We propose a novel module identification framework for imaging genetic studies using the tissue-specific functional interaction network. Our method includes three steps: (i) re-prioritize imaging GWAS findings by applying machine learning methods to incorporate network topological information and enhance the connectivity among top genes; (ii) detect densely connected modules based on interactions among top re-prioritized genes; and (iii) identify phenotype-relevant modules enriched by top GWAS findings. We demonstrate our method on the GWAS of [18F]FDG-PET measures in the amygdala region using the imaging genetic data from the Alzheimer's Disease Neuroimaging Initiative, and map the GWAS results onto the amygdala-specific functional interaction network. The proposed network-based GWAS method can effectively detect densely connected modules enriched by top GWAS findings. Tissue-specific functional network can provide precise context to help explore the collective effects of genes with biologically meaningful interactions specific to the studied phenotype. The R code and sample data are freely available at http://www.iu.edu/shenlab/tools/gwasmodule/. shenli@iu.edu. Supplementary data are available at Bioinformatics online.

Cognitive Composites Domain Scores Related to Neuroimaging Biomarkers within Probable-Amnestic Mild Cognitive Impairment-Storage Subtype.

The probable-amnestic (Pr-a) mild cognitive impairment (MCI)-storage subtype is a phenotype with 8.5 times more risk of conversion to dementia, mainly Alzheimer’s disease (AD), than the possible non-amnestic (Pss-na) MCI. The aim of this study was to find the optimized cognitive composites (CCs) domain scores most related to neuroimaging biomarkers within Pr-aMCI-storage subtype patients. The Fundació ACE (ACE) study with 20 Pr-aMCI-storage subtype subjects (MCI) were analyzed. All subjects underwent a neuropsychological assessment, a structural MRI, FDG-PET, and PIB-PET. The adjusted hippocampal volume (aHV) on MRI, the standard uptake value ratio (SUVR) on FDG-PET and PIB-PET SUVR measures were analyzed. The construction of the CCs domain scores, and the aHV on MRI and FDG-PET SUVR measures, were replicated in the parental AB255 study database (n = 133 MCI). Partial correlations adjusted by age, gender, and education were calculated with the associated p-value among every CC domain score and the neuroimaging biomarkers. The results were replicated in the “MCI due to AD” with memory storage impairments from ADNI. Delayed Recall CC domain score was significantly correlated with PIB-PET SUVR (β= –0.61, p = 0.003) in the ACE study and also with aHV on MRI (β= 0.27, p = 0.01) and FDG-PET SUVR (β= 0.27, p = 0.01) in the AB255 study. After a median survival time of 20.6 months, 85% from the ACE MCI converted to AD. The replication of our results in the ADNI dataset also confirmed our findings. Delayed Recall is the CC domain score best correlated with neuroimaging biomarkers associated with prodromal AD diagnosis.

Estrogen Receptor Binding (18F-FES PET) and Glycolytic Activity (18F-FDG PET) Predict Progression-Free Survival on Endocrine Therapy in Patients with ER+ Breast Cancer.

18F-fluoroestradiol (FES) PET scans measure regional estrogen binding, and 18F-fluorodeoxyglucose (FDG) PET measures tumor glycolytic activity. We examined quantitative and qualitative imaging biomarkers of progression-free survival (PFS) in breast cancer patients receiving endocrine therapy. Ninety patients with breast cancer from an estrogen receptor-positive (ER+), HER2- primary tumor underwent FES PET and FDG PET scans prior to endocrine therapy (63% aromatase inhibitor, 22% aromatase inhibitor and fulvestrant, 15% other). Eighty-four had evaluable data for PFS prediction. Recursive partitioning with 5-fold internal cross-validation used both FES PET and FDG PET measures to classify patients into three distinct response groups. FDG PET identified 24 patients (29%) with low FDG uptake, suggesting indolent tumors. These patients had a median PFS of 26.1 months (95% confidence interval, 11.2-49.7). Of patients with more FDG-avid tumors, 50 (59%) had high average FES uptake, and 10 (12%) had low average FES uptake. These groups had median PFS of 7.9 (5.6-11.8) and 3.3 months (1.4-not evaluable), respectively. Patient and tumor features did not replace or improve the PET measures' prediction of PFS. Prespecified endocrine resistance classifiers identified in smaller cohorts did not individually predict PFS. A wide range of therapy regimens are available for treatment of ER+ metastatic breast cancer, but no guidelines are established for sequencing these therapies. FDG PET and FES PET may help guide the timing of endocrine therapy and selection of targeted and/or cytotoxic chemotherapy. A multicenter trial is ongoing for external validation. Clin Cancer Res; 23(2); 407-15. ©2016 AACR.

Role of 18F-fluorodeoxyglucose Positron Emission Tomography in the Monitoring of Inflammatory Activity in Crohnʼs Disease

Fluorine-fluorodeoxyglucose positron emission tomography (F-FDG PET) has recently attracted interest for the measurement of disease activity in Crohn's disease (CD). The aim of this study was to assess the utility of FDG-PET as a marker of progression of inflammatory activity and its response to treatment in patients with CD. Twenty-two patients with active CD were recruited prospectively to undergo FDG-PET scanning at 2 time points. All 22 index scans were used to assess sensitivity and specificity against a reference standard magnetic resonance imaging measure. Correlations with clinicopathological markers of severity (Harvey-Bradshaw Index, C-reactive protein, and calprotectin) were also performed. Of note, 17/22 patients participated in the longitudinal component and underwent scanning before and 12 weeks after the initiation of anti-tumor necrosis factor alpha therapy. Patients were subcategorized on the basis of a clinically significant response, and responsiveness of the PET measures was assessed using previously described indices. Of note, 5/22 patients took part in the test-retest component of the study and underwent scanning twice within a target interval of 1 week, to assess the reproducibility of the PET measures. The sensitivity and specificity of F-FDG PET were 88% and 70%, respectively. Standardized uptake value (SUV)-related PET measures correlated significantly both with C-reactive protein and Harvey-Bradshaw Index in cross-sectional and longitudinal analyses. (G)SUVMAX and (G)SUVMEAN demonstrated favorable responsiveness and reliability characteristics (responsiveness ratio of Guyatt >0.80 and % variability <20%) compared with volume-dependent FDG-PET measures. A proportion of the FDG signal (10%-30%) was found to originate from the lumen of diseased segments. F-FDG PET may be useful for longitudinal monitoring of inflammatory activity in CD.

PREDICTING PROGRESSION TO MILD COGNITIVE IMPAIRMENT IN COGNITIVELY UNIMPAIRED INDIVIDUALS USING NEUROIMAGING BIOMARKERS

Neuroimaging biomarkers can detect disease pre-clinically but their prognostic value, alone or in combination, is uncertain. Volumetric MRI and FDG-PET data were compared in 18 cognitively unimpaired participants approximately 2 years (1.8±0.8) before the clinical diagnosis of aMCI due to AD and 35 participants matched for age and sex who remained unimpaired for ≥4 years (nonprogressors) after their imaging acquisition. We further compared the 18 progressors to 20 nonprogresors matched for age, sex, and APOE status. Participants were followed in the Arizona APOE Cohort, have a reported first degree family history of possible AD dementia, and were enriched for APOE4 gene dose. Voxel-wise analyses were used to characterize reductions in regional gray matter volume and cerebral glucose metabolism between groups. Binary logistic regression, leave-one-out, and Receiver Operating Curve analyses were performed to characterize the extent to which posterior cingulate glucose metabolism, the AD-related hypometabolic conversion index (HCI), hippocampal volumes (HCV), and entorhinal cortical thickness, alone or in combination, could distinguish between subsequent progressors and non-progressors. The progressor and non-progressor groups did not differ significantly in their age (68±4), sex, education, or general intelligence. The progressor group had significantly more APOEe4 carriers than the group that was not matched for APOE. Compared to both nonprogressor groups, those who developed aMCI in approximately 2 years had significant (FWE corrected p ≤ 0.05) decreases in glucose metabolism, gray matter volume, and cortical thickness in regions known to be preferentially affected by AD. The best predictor of aMCI when matched for APOE was right and left HCV at 79% sensitivity and 78% specificity, with no improvement in performance when adding FDG-PET data. The best predictor for the groups not balanced for APOE was left HCV at 74% sensitivity and 72% specificity; combining MRI and FDG PET data increased the sensitivity and specificity to 77% and 78%. Based on logistic regression models, APOE e4 partially mediated the effect on the left hippocampus. This study supports the possibility that regional MRI and FDG PET measurements, individually or in combination, could help predict the likelihood of progressing to the clinical stages of AD.