Visual Rating and Computer-Assisted Analysis of FDG PET in the Prediction of Conversion to Alzheimer's Disease in Mild Cognitive Impairment.

To assess the extent to which multiple Alzheimer disease (AD) biomarkers improve the ability to predict future decline in subjects with mild cognitive impairment (MCI) compared with predictions based on clinical parameters alone. All protocols were approved by the institutional review board at each site, and written informed consent was obtained from all subjects. The study was HIPAA compliant. Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline magnetic resonance (MR) imaging and fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) studies for 97 subjects with MCI were used. MR imaging-derived gray matter probability maps and FDG PET images were analyzed by using independent component analysis, an unbiased data-driven method to extract independent sources of information from whole-brain data. The loading parameters for all MR imaging and FDG components, along with cerebrospinal fluid (CSF) proteins, were entered into logistic regression models (dependent variable: conversion to AD within 4 years). Eight models were considered, including all combinations of MR imaging, PET, and CSF markers with the covariates (age, education, apolipoprotein E genotype, Alzheimer's Disease Assessment Scale-Cognitive subscale score). Combining MR imaging, FDG PET, and CSF data with routine clinical tests significantly increased the accuracy of predicting conversion to AD compared with clinical testing alone. The misclassification rate decreased from 41.3% to 28.4% (P < .00001). FDG PET contributed more information to routine tests (P < .00001) than CSF (P = .32) or MR imaging (P = .08). Imaging and CSF biomarkers can improve prediction of conversion from MCI to AD compared with baseline clinical testing. FDG PET appears to add the greatest prognostic information.

e14501 Background: The type 1 insulin-like growth factor receptor (IGF-1R) plays a critical role in mitogenesis and survival in a variety of human tumor cells. IGF-1R is also closely related to the insulin receptor (IR). It is becoming increasingly evident that stimulation of IR or IR/IGF-1R hybrid receptors by insulin or IGF-1/2 may contribute to cancer growth, suggesting that both IGF-1R and IR may be targets for cancer therapy. BMS-754807 (‘807) is an oral IGF-1R tyrosine kinase antagonist under development that also blocks IR activity. This study explores the feasibility of fluorodeoxyglucose (FDG) and fluorothymidine (FLT) positron emission tomography (PET) as pharmacodynamic imaging biomarkers in a xenograft model. Methods: Mice were implanted with fragments of Sal-IGF, a transgenic salivary gland tumor expressing constitutively active IGF-1R. Once tumors reached desired size, the mice were divided into 3 treatment groups (vehicle, 6.25 mg/kg ‘807, &amp; 50 mg/kg ‘807 on days 1–4). FDG-PET scans were performed on day -2 (prior to treatment), days 1 &amp; 2 (max/min concentrations post day 1 dose), and days 4 &amp; 5 (max/min day 4 dose). FLT-PET scans were performed on days -2, 2 (min day 1 dose), &amp; 5 (min day 4 dose). Results: With FDG-PET imaging, a 66% reduction (P&lt;0.05, paired t-test) in tumor SUVmean was observed at the end of the 50 mg/kg therapy (day 4) and sustained for 24h (day 5) with a concomitant reduction of 37% in tumor burden by day 5 (P&lt;0.05). FLT-PET studies demonstrated a 45% reduction (P&lt;0.05) in tumor SUVmean observed 24h after the end of 50 mg/kg therapy (day 5) with a concomitant reduction of 50% in tumor burden (day 5, P&lt;0.05). Conclusions: Correlation with tumor growth inhibition suggests feasibility of FDG- PET despite IR blockade. These results support the use of both FDG and FLT PET imaging in clinical trials with ‘807. [Table: see text]

Invited Commentary

e15665 Background: To determine the optimal method of using 3-deoxy-3-18F-fluorothymidine (FLT) positron emission tomography (PET) to estimate gross tumor length in esophageal carcinoma, and compared with that of 18F- fluorodeoxyglucose(FDG) PET. Methods: Twenty patients with esophageal squamous cell carcinoma treated with radical surgery were enrolled and detected by FLT PET, eighteen of them underwent FDG PET scan. Gross tumor volumes (GTVs) were delineated using seven different methods with FLT PET: visual interpretation, standardized uptake value (SUV) 1.3, SUV 1.4, SUV 1.5, and 20% of maximum standard uptake value (SUVmax), 25% SUVmax,30% SUVmax, on FLT PET imaging, and three different methods with FDG PET: visual interpretation, SUV 2.5, and 40%SUVmax on FDG PET imaging. The length of tumors on FLT PET scan were measured and recorded as LFLTvis, LFLT1.3, LFLT1.4, LFLT1.5, LFLT20%, LFLT25%, and LFLT30%, and FDG PET scan were measured and recorded as LFDGvis, LFDG2.5, and LFDG40%, respectively, and compared with the length of gross tumor in the resected specimen measured by pathological examination (LPath). Results: The mean (±SD) LPath was 5.16±2.19cm. The mean LFLTvis, LFLT1.3, LFLT1.4, LFLT1.5, LFLT20%, LFLT25%, and LFLT30%were 5.17±2.40cm, 5.55±2.43cm, 5.17±2.41cm, 4.95±2.44cm, 5.82±2.23cm, 5.32±2.31cm, and 5.04±2.28cm, respectively. Compared with the LPath, the P value were 0.971, 0.045, 0.972, 0.255, 0.066, 0.644, and 0.714, respectively. The correlation coefficients were 0.952, 0.944, 0.959, 0.948, 0.763, 0.783, and 0.800, respectively. The mean LFDGvis, LFDG2.5, and LFDG40% were 5.41±2.27cm, 5.38±2.25cm, and 4.02±1.57cm, respectively. Compared with the LPath, the P value were 0.098, 0.085 and 0.000, respectively. The correlation coefficients were 0.984, 0.990 and 0.932, respectively. On FLT PET, LFLT1.4, and on FDG PET, L FDG2.5 seem more approximate to LPath. The difference between LFLT1.4 and LFDG2.5 was not significantly (P=0.442), the correlation coefficients was 0.960. Conclusions: An SUV cutoff of 1.4 on FLT PET, and an SUV cutoff of 2.5 on FDG PET, provided the closest estimation of GTV length in this study No significant financial relationships to disclose.

This review article aims at providing a state-of-the-art review of the role of fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging (FDG-PET) in the prediction of Alzheimer's dementia in subjects suffering mild cognitive impairment (MCI), with a particular focus on the predictive power of FDG-PET compared to structural magnetic resonance imaging (sMRI). We also address perfusion single photon emission computed tomography (SPECT) as a less costly and more accessible alternative to FDG-PET. A search in PubMed was performed, taking into consideration relevant scientific articles published in English within the last five years and limited to human studies. This recent literature confirms the effectiveness of FDG-PET and sMRI for prediction of AD dementia in MCI. However, there are discordant results regarding which image modality is superior. This could be explained by the high variability of metrics used to evaluate both imaging modalities and/or by sampling/population issues such as age, disease severity and conversion time. FDG-PET seems to outperform sMRI in rapidly converting early-onset MCI individuals, whereas sMRI may outperform FDG-PET in late-onset MCI subjects, in which case FDG PET might only provide a complementary role. Although FDG-PET performs better than perfusion SPECT, current evidence confirms perfusion SPECT as a valid alternative when FDG- PET is not available. Finally, possible future directions in the field are discussed.

Positron emission tomography (PET) imaging studies have shown that amyloid beta (Aβ) is significantly correlated with glucose metabolism in mild cognitive impairment independently of the apolipoprotein E (APOE) ε4 genotype. We used a singular value decomposition (SVD) approach to pairwise cross-correlation among tau, Aβ, and fluorodeoxyglucose PET images. The resulting SVD-based tau and Aβ scores as well as the APOE ε4 genotype, were entered as predictors in a voxelwise general linear model for statistical assessment of their effect on FDG. We found cortical regions where a reduced glucose metabolism was maximally correlated with distributed patterns of tau, accounting for the effect of Aβ and APOE ε4 genotype. By highlighting the more significant role of tau, rather than Aβ, in the reduction of glucose metabolism, our results provide a better understanding of their combined effect in the development and progression of Alzheimer's disease. This study uses a data-driven singular value decomposition approach to the cross-correlation matrix between tau and fluorodeoxyglucose (FDG) images, as well as between FDG and amyloid beta (Aβ) positron emission tomography (PET) images. From a population of mild cognitive impairment subjects, we found that spatially distributed scores of tau PET are associated with an even stronger reduction of glucose metabolism, independent of the apolipoprotein E ε4 genotype and confounded by Aβ. By highlighting the more significant role of tau, rather than Aβ, on the reduction of glucose metabolism, our results provide a better understanding of their combined effects in the development of Alzheimer's disease.

Plasma phosphorylated tau at threonine 181 (p-tau181) has been proposed as an easily accessible biomarker for the detection of Alzheimer disease (AD) pathology, but its ability to monitor disease progression in AD remains unclear. To study the potential of longitudinal plasma p-tau181 measures for assessing neurodegeneration progression and cognitive decline in AD in comparison to plasma neurofilament light chain (NfL), a disease-nonspecific marker of neuronal injury. This longitudinal cohort study included data from the Alzheimer's Disease Neuroimaging Initiative from February 1, 2007, to June 6, 2016. Follow-up blood sampling was performed for up to 8 years. Plasma p-tau181 measurements were performed in 2020. This was a multicentric observational study of 1113 participants, including cognitively unimpaired participants as well as patients with cognitive impairment (mild cognitive impairment and AD dementia). Participants were eligible for inclusion if they had available plasma p-tau181 and NfL measurements and at least 1 fluorine-18-labeled fluorodeoxyglucose (FDG) positron emission tomography (PET) or structural magnetic resonance imaging scan performed at the same study visit. Exclusion criteria included any significant neurologic disorder other than suspected AD; presence of infection, infarction, or multiple lacunes as detected by magnetic resonance imaging; and any significant systemic condition that could lead to difficulty complying with the protocol. Plasma p-tau181 and NfL measured with single-molecule array technology. Longitudinal imaging markers of neurodegeneration (FDG PET and structural magnetic resonance imaging) and cognitive test scores (Preclinical Alzheimer Cognitive Composite and Alzheimer Disease Assessment Scale-Cognitive Subscale with 13 tasks). Data were analyzed from June 20 to August 15, 2020. Of the 1113 participants (mean [SD] age, 74.0 [7.6] years; 600 men [53.9%]; 992 non-Hispanic White participants [89.1%]), a total of 378 individuals (34.0%) were cognitively unimpaired (CU) and 735 participants (66.0%) were cognitively impaired (CImp). Of the CImp group, 537 (73.1%) had mild cognitive impairment, and 198 (26.9%) had AD dementia. Longitudinal changes of plasma p-tau181 were associated with cognitive decline (CU: r = -0.24, P < .001; CImp: r = 0.34, P < .001) and a prospective decrease in glucose metabolism (CU: r = -0.05, P = .48; CImp: r = -0.27, P < .001) and gray matter volume (CU: r = -0.19, P < .001; CImp: r = -0.31, P < .001) in highly AD-characteristic brain regions. These associations were restricted to amyloid-β-positive individuals. Both plasma p-tau181 and NfL were independently associated with cognition and neurodegeneration in brain regions typically affected in AD. However, NfL was also associated with neurodegeneration in brain regions exceeding this AD-typical spatial pattern in amyloid-β-negative participants. Mediation analyses found that approximately 25% to 45% of plasma p-tau181 outcomes on cognition measures were mediated by the neuroimaging-derived markers of neurodegeneration, suggesting links between plasma p-tau181 and cognition independent of these measures. Study findings suggest that plasma p-tau181 was an accessible and scalable marker for predicting and monitoring neurodegeneration and cognitive decline and was, unlike plasma NfL, AD specific. The study findings suggest implications for the use of plasma biomarkers as measures to monitor AD progression in clinical practice and treatment trials.

Relationships between plasma biomarkers, tau PET, FDG PET, and volumetric MRI in mild to moderate Alzheimer's disease patients.

To quantify the effect sizes of regional metabolic and morphometric measures in patients with preclinical and mild Alzheimer disease (AD) to aid in the identification of noninvasive biomarkers for the early detection of AD. The study was conducted with institutional review board approval and in compliance with HIPAA regulations. Written informed consent was obtained from each participant or participant's legal guardian. Fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and magnetic resonance (MR) imaging data were analyzed from 80 healthy control (HC) subjects, 68 individuals with AD, and 156 with amnestic mild cognitive impairment (MCI), 69 of whom had single-domain amnestic MCI. Regions of interest (ROIs) were derived after coregistering FDG PET and MR images by using high-throughput, subject-specific procedures. The Cohen d effect sizes were calculated for 42 predefined ROIs across the brain. Statistical comparison of the largest overall effect sizes for MR imaging and PET was performed. Metabolic effect sizes were determined with and without accounting for regional atrophy. Discriminative accuracy of ROIs showing the largest effect sizes were compared by calculating receiver operating characteristic curves. For all disease groups, the hippocampus showed the largest morphometric effect size and the entorhinal cortex showed the largest metabolic effect size. In mild AD, the Cohen d effect size for hippocampal volume (1.92) was significantly larger (P < .05) than that for entorhinal metabolism (1.43). Regression of regional atrophy substantially reduced most metabolic effects. For all group comparisons, the areas under the receiver operating characteristic curves were significantly larger for hippocampal volume than for entorhinal metabolism. The current results show no evidence that FDG PET is more sensitive than MR imaging to the degeneration occurring in preclinical and mild AD, suggesting that an MR imaging finding may be a more practical clinical biomarker for early detection of AD.

Brain fluorodeoxyglucose (FDG) PET in dementia

BackgroundCognitive unimpaired (CU) and mild cognitive impairment (MCI) subjects harboring beta‐amyloid (A+) and tau (T+) are at high‐risk for incident cognitive decline. Fluoro‐deoxyglucose (FDG) positron emission tomography (PET) likely represents both cumulative loss of the neuropil and functional impairment of neurons while magnetic resonance imaging (MRI) indicates cumulative loss and shrinkage of the neuropil. As PET and CSF analysis in detecting beta‐amyloid and tau are not easily accessible (either costly or invasive nature or radiation), we compared the performance of MRI‐based automated segmentation tool with FDG PET in identifying CU and MCI subjects harboring A+T+.MethodA total of 62 subjects (CU=37, MCI=25) underwent MRI, FDG PET, 11C‐ PIB and 18F‐T807 PET. MRIs were processed by an automated segmentation tool to obtain an Alzheimer’s Disease (AD) ‐ resemblance atrophy index (AD‐RAI) which was derived from a machine learning method (AccuBrain®) that analyzed multiple brain regions relevant to AD.ResultAD‐RAI yielded the same sensitivity (0.73) among all subjects with FDG PET while they had similar specificity. AD‐RAI performed the highest sensitivity (0.91) in MCI subjects over FDG PET (0.82) with an acceptable specificity (0.79) which was slightly lower than that of FDG PET. However, both AD‐RAI and FDG PET were suboptimal in CU group. Detailed results are demonstrated in the Table.ConclusionThe volumetric segmentation tool achieves a good diagnostic profile similar to FDG PET in identifying early AD. It has the potential to be more widely used as a tool to diagnose early AD for receiving treatment or recruitment into clinical trials.

The purpose of this study was to compare the diagnostic value of 11C-choline positron emission tomography (PET) and [18F]fluorodeoxyglucose (FDG) PET imaging in the detection of primary lung cancer and mediastinal lymph node metastases. Seventeen patients with histologically proven primary lung cancer were examined with both 11C-choline and FDG PET within a week of each study. Lung cancers were analysed visually and semiquantitatively using the ratio of tumour-to-normal radioactivity (T/N ratio) and standardized uptake value (SUV). Mediastinal lymph node metastases were analysed visually. Although both techniques delineated focal lesions with an increase in tracer accumulation in 13 patients, FDG PET identified three additional patients in whom 11C-choline PET did not visualize any lesion. In the detection of lung cancer <2 cm in size, FDG PET provided higher sensitivity (six of seven, 85.7%) than 11C-choline PET (four of seven, 57.1%). The T/N ratio and SUV were significantly higher with FDG PET (T/N ratio, 7.43+/-6.22; SUV, 4.05+/-3.05) than these were with 11C-choline PET (T/N ratio, 2.93+/-1.19; SUV, 2.93+/-0.79) (P<0.001). There was a significant positive correlation between the T/N ratios and SUVs of FDG and 11C-choline. In the assessment of mediastinal lymph node involvement, FDG PET detected lymph node metastases in two patients who were negative on 11C-choline PET, whereas both techniques could not detect tumour involvement in one patient. Both techniques have clinical value for the non-invasive detection of primary lung cancer that is 2 cm or greater in size. However, FDG PET is superior to 11C-choline PET in the detection of lung cancer that is less than 2 cm in diameter and in mediastinal lymph node metastases.

Fluorodeoxyglucose (FDG) positron emission tomography (PET) is increasingly used to support a diagnosis of Alzheimer's disease. The aim of the present study was to evaluate a new expert system (PALZ) for the fully automated analysis of FDG PET images for diagnosis of the disease. The PALZ tool is based on the detection of the typical disease pattern in FDG PET images. Its potential for this task was evaluated in 22 consecutive patients with suspected Alzheimer's disease who had been graded as positive for the pattern by an experienced reader (visual analysis supported by statistical parametric mapping (SPM)), and in 18 controls. Dependence on scanner performance was assessed by variation of the spatial resolution of the PET images. All the Alzheimer's disease subjects were classified as pattern-positive by the PALZ tool. Fifteen controls were classified as normal. Sensitivity and specificity for differentiation of the patients with suspected Alzheimer's disease from the controls were 100% and 83%, respectively. The false positive finding in three controls most likely was caused by differences in attenuation correction between the normal data base of the PALZ tool (cold transmission scan) and the local data sets (hot transmission scan). There was only mild dependence on spatial resolution. The results of the present study suggest that the PALZ tool provides similar performance for the detection of the typical Alzheimer's disease pattern in FDG PET images as an experienced reader supported by SPM. The PALZ tool is fully automated, easy to use, and insensitive to the spatial resolution of the PET scanner used. Therefore, it has the potential for widespread clinical use.

BackgroundThe treatment of patients with glioma depended on the nature of the lesion and on histological grade of the tumor. Positron emission tomography (PET) using 13N-ammonia (NH3), 11C-methionine (MET) and 18F-fluorodeoxyglucose (FDG) have been used to assess brain tumors. Our aim was to compare their diagnostic accuracies in patients with suspected cerebral glioma.MethodsNinety patients with suspicion of glioma based on previous CT/MRI, who underwent NH3 PET, MET PET and FDG PET, were prospectively enrolled in the study. The reference standard was established by histology or clinical and radiological follow-up. Images were interpreted by visual evaluation and semi-quantitative analysis using the lesion-to-normal white matter uptake ratio (L/WM ratio).ResultsFinally, 30 high-grade gliomas (HGG), 27 low-grade gliomas (LGG), 10 non-glioma tumors and 23 non-neoplastic lesions (NNL) were diagnosed. On visual evaluation, sensitivity and specificity for differentiating tumors from NNL were 62.7% (42/67) and 95.7% (22/23) for NH3 PET, 94.0% (63/67) and 56.5% (13/23) for MET PET, and 35.8% (24/67) and 65.2% (15/23) for FDG PET. On semi-quantitative analysis, brain tumors showed significantly higher L/WM ratios than NNL both in NH3 and MET PET (both P < 0.001). The sensitivity, specificity and the area under the curve (AUC) by receiver operating characteristic (ROC) analysis, respectively, were 64.2, 100% and 0.819 for NH3; and 89.6, 69.6% and 0.840 for MET. Besides, the L/WM ratios of NH3, MET and FDG PET in HGG all significantly higher than that in LGG (all P < 0.001). The predicted (by ROC) accuracy of the tracers (AUC shown in parentheses) were 86.0% (0.896) for NH3, 87.7% (0.928) for MET and 93.0% (0.964) for FDG. While no significant differences in the AUC were seen between them.ConclusionNH3 PET has remarkably high specificity for the differentiation of brain tumors from NNL, but low sensitivity for the detection of LGG. MET PET was found to be highly useful for detection of brain tumors. However, like FDG, high MET uptake is frequently observed in some NNL. NH3, MET and FDG PET all appears to be valuable for evaluating the histological grade of gliomas.

Mild cognitive impairment (MCI) refers to a memory impairment among non-demented adults. It is a condition that increases the risk of dementia, notably due to Alzheimer's disease (AD). MCI is heterogeneous and there is a need for novel diagnostic approaches. Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging provides robust AD biomarker characteristics, while anatomical and functional magnetic resonance imaging (MRI) offer complementary information. Classify MCI and cognitively normal (CN) adults using FDG-PET images; predict individuals with MCI that convert to AD dementia; determine if MRI can achieve comparable performance to FDG-PET classification. Four ADNI cohorts were created. Cohort 1: 805 participants (MCI n = 455; CN n = 350) that underwent FDG-PET. FDG-PET images were inputs to a one-channel 3-dimensional (3D) DenseNet deep learning model. Cohort 2: 348 participants (MCI n = 174; CN n = 174) with MRI and functional MRI. Cohort 3: overlapping cases from cohorts 1 and 2 (MCI n = 70; CN n = 70). Cohort 4: 336 participants (MCI-converters n = 168; MCI-stable n = 168) with FDG-PET from cohort 1. The one/two-channel models' inputs were T1-weighted MRI and/or amplitude of low-frequency fluctuations images, with classification metrics evaluated through 10-fold cross-validation. The FDG-PET model achieved 88.02%±3.82 accuracy for MCI versus CN classification, with 88.70%±4.70 sensitivity and 87.14%±5.03 specificity. Neither MRI model outperformed the FDG-PET model, as the highest MRI-based accuracy was 76.86%±1.95. The FDG-PET model achieved 63.23%±4.68 accuracy in classifying MCI-converters versus MCI-stable. FDG-PET images produced the highest accuracy in classifying MCI versus CN. While MRI-based approaches were inferior to FDG-PET, multi-contrast MRI still offers value for neurodegeneration classification.