Effect of sample size for normal database on diagnostic performance of brain FDG PET for the detection of Alzheimer's disease using automated image analysis

Normal cohorts in automated brain atrophy estimation: how many healthy subjects to include?

OBJECTIVES

This study investigates the influence of normal cohort (NC) size and the impact of different NCs on automated MRI-based brain atrophy estimation.

METHODS

A pooled NC of 3945 subjects (NCpool) was retrospectively created from five publicly available cohorts. Voxel-wise gray matter volume atrophy maps were calculated for 48 Alzheimer's disease (AD) patients (55-82 years) using veganbagel and dynamic normal templates with an increasing number of healthy subjects randomly drawn from NCpool (initially three, and finally 100 subjects). Over 100 repeats of the process, the mean over a voxel-wise standard deviation of gray matter z-scores was established and plotted against the number of subjects in the templates. The knee point of these curves was defined as the minimum number of subjects required for consistent brain atrophy estimation. Atrophy maps were calculated using each NC for AD patients and matched healthy controls (HC). Two readers rated the extent of mesiotemporal atrophy to discriminate AD/HC.

RESULTS

The maximum knee point was at 15 subjects. For 21 AD/21 HC, a sufficient number of subjects were available in each NC for validation. Readers agreed on the AD diagnosis in all cases (Kappa for the extent of atrophy, 0.98). No differences in diagnoses between NCs were observed (intraclass correlation coefficient, 0.91; Cochran's Q, p = 0.19).

CONCLUSION

At least 15 subjects should be included in age- and sex-specific normal templates for consistent brain atrophy estimation. In the study's context, qualitative interpretation of regional atrophy allows reliable AD diagnosis with a high inter-reader agreement, irrespective of the NC used.

CLINICAL RELEVANCE STATEMENT

The influence of normal cohorts (NCs) on automated brain atrophy estimation, typically comparing individual scans to NCs, remains largely unexplored. Our study establishes the minimum number of NC-subjects needed and demonstrates minimal impact of different NCs on regional atrophy estimation.

KEY POINTS

• Software-based brain atrophy estimation often relies on normal cohorts for comparisons. • At least 15 subjects must be included in an age- and sex-specific normal cohort. • Using different normal cohorts does not influence regional atrophy estimation.

Brain hypometabolism in non-demented microtubule-associated protein tau H1 carriers with Parkinson's disease

BACKGROUND AND PURPOSE

The microtubule-associated protein tau (MAPT) H1 homozygosity (H1/H1 haplotype) is a genetic risk factor for neurodegenerative diseases, such as Parkinson's disease (PD). MAPT H1 homozygosity has been associated with conversion to PD; however, results are conflicting since some studies did not find a strong influence. Cortical hypometabolism is associated with cognitive impairment in PD. In this study, we aimed to evaluate the metabolic pattern in nondemented PD patients MAPT H1/H1 carriers in comparison with MAPT H1/H2 haplotype. In addition, we evaluated domain-specific cognitive differences according to MAPT haplotype.

METHODS

We compared a group of 26 H1/H1 and 20 H1/H2 carriers with late-onset PD. Participants underwent a comprehensive neuropsychological cognitive evaluation and a [18F]-Fluorodeoxyglucose PET-MR scan.

RESULTS

MAPT H1/H1 carriers showed worse performance in the digit span forward test of attention compared to MAPT H1/H2 carriers. In the [18F]-Fluorodeoxyglucose PET comparisons, MAPT H1/H1 displayed hypometabolism in the frontal cortex, parahippocampal, and cingulate gyrus, as well as in the caudate and globus pallidus.

CONCLUSION

PD patients MAPT H1/H1 carriers without dementia exhibit relative hypometabolism in several cortical areas as well as in the basal ganglia, and worse performance in attention than MAPT H1/H2 carriers. Longitudinal studies should assess if lower scores in attention and dysfunction in these areas are predictors of dementia in MAPT H1/H1 homozygotes.

Comparison of an in-house acquired brain F-18 FDG PET normal database with commercially available normal data

INTRODUCTION

Current guidelines recommend the use of semiautomated assessment of F-18 FDG PET brain studies. Accuracy is influenced by the normal data, which requires knowledge of the included subjects and how they were acquired. Due to confidentiality, such information is often not completely disclosed. Our aim was to determine the variation in FDG uptake between several commercially available and our in-house normal database.

METHODS

Our database contains 83 healthy subjects. Outlier detection using SPM further ensured normality, resulting in exclusion of three subjects. The remaining 80 subjects were analyzed using three commercially available software packages. Z-score data per patient and per lobe were extracted and pooled in predefined age groups (18-40, 41-60 and 61-80 years old) with a calculation of mean Z-scores and SD. Correlation between Z-score output of different software was investigated.

RESULTS

In the 18-40 years age group, frontotemporal hypermetabolism was found with all software. Decreased cerebellar uptake was found with two software packages. Mean Z-scores are closer to zero in the 41-60 years age group compared to the younger group, and mostly within the normal range in the 61-80 years age group with all software. A moderate to high linear correlation between Z-score output was found, but individual Z-scores varied widely.

CONCLUSIONS

The three software packages yielded varying Z-score output, partially explained by an age mismatch between our subjects and subjects in their normal databases. A definitive explanation for the remaining differences is lacking. This emphasizes the importance of age-matched normal data and knowledge of the included databases to allow adequate preprocessing.

Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps

PURPOSE

An appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating [18F]FDG PET brain datasets of healthy controls (HC), based on publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level.

METHODS

Selection of HC images was based on visual rating, after Cook's distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB.

RESULTS

Two-step Cook's distance analysis and the subsequent jack-knife analysis resulted in the selection of n = 125 subjects from the AIMN-HC dataset and n = 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes.

CONCLUSIONS

The applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.

Normative brain volume reports may improve differential diagnosis of dementing neurodegenerative diseases in clinical practice

OBJECTIVES

Normative brain volume reports (NBVRs) are becoming more and more available for the workup of dementia patients in clinical routine. However, it is yet unknown how this information can be used in the radiological decision-making process. The present study investigates the diagnostic value of NBVRs for detection and differential diagnosis of distinct regional brain atrophy in several dementing neurodegenerative disorders.

METHODS

NBVRs were obtained for 81 consecutive patients with distinct dementing neurodegenerative diseases and 13 healthy controls (HC). Forty Alzheimer's disease (AD; 18 with dementia, 22 with mild cognitive impairment (MCI), 11 posterior cortical atrophy (PCA)), 20 frontotemporal dementia (FTD), and ten semantic dementia (SD) cases were analyzed, and reports were tested qualitatively for the representation of atrophy patterns. Gold standard diagnoses were based on the patients' clinical course, FDG-PET imaging, and/or cerebrospinal fluid (CSF) biomarkers following established diagnostic criteria. Diagnostic accuracy of pattern representations was calculated.

RESULTS

NBVRs improved the correct identification of patients vs. healthy controls based on structural MRI for rater 1 (p < 0.001) whereas the amount of correct classifications was rather unchanged for rater 2. Correct differential diagnosis of dementing neurodegenerative disorders was significantly improved for both rater 1 (p = 0.001) and rater 2 (p = 0.022). Furthermore, interrater reliability was improved from moderate to excellent for both detection and differential diagnosis of neurodegenerative diseases (κ = 0.556/0.894 and κ = 0.403/0.850, respectively).

CONCLUSION

NBVRs deliver valuable and observer-independent information, which can improve differential diagnosis of neurodegenerative diseases.

KEY POINTS

• Normative brain volume reports increase detection of neurodegenerative atrophy patterns compared to visual reading alone. • Differential diagnosis of regionally distinct atrophy patterns is improved. • Agreement between radiologists is significantly improved from moderate to excellent when using normative brain volume reports.

Aiginition Longitudinal Biomarker Investigation Of Neurodegeneration (ALBION): study design, cohort description, and preliminary data

Objectives: Aiginition Longitudinal Biomarker Investigation Of Neurodegeneration (ALBION) is a longitudinal ongoing study initiated in 2018 that takes place in the Cognitive Disorders Clinic of Aiginition Hospital of the National and Kapodistrian University of Athens. Its aim is to address several research questions concerning the preclinical and prodromal stage of Alzheimer's disease and explore potential markers for early detection, prediction, and primary prevention of dementia. Methods: We here present the design and the preliminary baseline characteristics of ALBION. The sample of our study consists of people aged over 50 who are concerned about their memory but are cognitively normal (CN) or have mild cognitive deficits. Each participant undergoes an extensive assessment including several demographic, medical, social, environmental, clinical, nutritional, neuropsychological determinants and lifestyle activities. Furthermore, we are collecting data from portable devices, neuroimaging techniques and biological samples (blood, stools, CSF). All participants are assessed annually for a period of 10 years. Results: In total, 47 participants have completed the initial evaluation up to date and are divided in two groups, CN individuals (N = 26) and MCI patients (N = 21), based on their cognitive status. The participants are, on average, 64 years old, 46.3% of the sample is male with an average of 12.73 years of education. MCI patients report more comorbidities and have a lower score in the MMSE test. Regarding APOE status, 2 participants are ε4 homozygotes and 10 ε4 heterozygotes. CSF analyses (Aβ42, Τ-tau, P-tau) revealed no differences between the two groups. Conclusion: The ALBION study offers an opportunity to explore preclinical dementia and identify new and tailored markers, particularly relating to lifestyle. Further investigation of these populations may provide a wider profile of the changes taking place in the preclinical phase of dementia, leading to potentially effective therapeutic and preventive strategies.

Quantitative and qualitative evaluation of hybrid iterative reconstruction, with and without noise power spectrum models: A phantom study

The purpose of this phantom study was to investigate the feasibility of dose reduction with hybrid iterative reconstruction, with and without a noise power spectrum (NPS) model, using both quantitative and qualitative evaluations. Standard dose (SD), three‐quarter dose (TQD), and half‐dose (HD) of radiation were used. Images were reconstructed with filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR 3D) (MILD, STR), and AIDR 3D enhanced (eAIDR 3D) (eMILD, eSTR). An NPS analysis, task‐based modulation transfer function (MTF_task) analysis, and comparisons of low‐contrast detectability and image texture were performed. Although the eAIDR 3D had a higher NPS value in the high‐frequency range and improved image texture and resolution as compared with AIDR 3D at the same radiation dose and iteration levels, it yielded higher noise than AIDR 3D. Additionally, although there was no statistically significant difference between SD‐FBP and the TQD series in the comparison of the mean area under the curve (AUC), the mean AUC was statistically significantly different between SD‐FBP and the HD series. NPS values in the high‐frequency range, 10% MTF_task values, low‐contrast detectability, and image textures of TQD‐eMILD were comparable to those of SD‐FBP. Our findings suggested that using eMILD can reduce the radiation dose by 25%, while potentially maintaining diagnostic performance, spatial resolution, and image texture; this could support selecting the appropriate protocol in a clinical setting.

The Use of 18F-FDG PET in the Diagnostic Workup of Alzheimer's Dementia

The diagnosis of dementia probably due to Alzheimer's disease is still primarily a clinical one. In cases that remain clinically unclear, however, biomarkers for amyloid deposition and neuronal injury can help to identify the underlying cause. One biomarker even for early neuronal injury in the stage of mild cognitive impairment is cerebral glucose hypometabolism measured by ¹⁸F-FDG PET. Distinct patterns of hypometabolism can be seen, for example, in dementia due to Alzheimer's disease, frontotemporal lobar degeneration, and dementia with Lewy bodies. This makes it possible to distinguish between different neurodegenerative diseases as well as major depressive disorder. While the sensitivity of ¹⁸F-FDG PET to detect Alzheimer's disease is high, specificity is low and the additional use of biomarkers for amyloid deposition might be beneficial in some cases. In conclusion, ¹⁸F-FDG PET is a useful tool when the cause for dementia remains unclear and different diagnosis would lead to different treatment approaches. Due to the lack of treatment options in pre-dementia stages, the use of ¹⁸F-FDG PET is currently not recommended for these cases in a purely clinical setting.

Clinical validity of brain fluorodeoxyglucose positron emission tomography as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

The use of Alzheimer's disease (AD) biomarkers is supported in diagnostic criteria, but their maturity for clinical routine is still debated. Here, we evaluate brain fluorodeoxyglucose positron emission tomography (FDG PET), a measure of cerebral glucose metabolism, as a biomarker to identify clinical and prodromal AD according to the framework suggested for biomarkers in oncology, using homogenous criteria with other biomarkers addressed in parallel reviews. FDG PET has fully achieved phase 1 (rational for use) and most of phase 2 (ability to discriminate AD subjects from healthy controls or other forms of dementia) aims. Phase 3 aims (early detection ability) are partly achieved. Phase 4 studies (routine use in prodromal patients) are ongoing, and only preliminary results can be extrapolated from retrospective observations. Phase 5 studies (quantify impact and costs) have not been performed. The results of this study show that specific efforts are needed to complete phase 3 evidence, in particular comparing and combining FDG PET with other biomarkers, and to properly design phase 4 prospective studies as a basis for phase 5 evaluations.

Potential Clinical Value of Multiparametric PET in the Prediction of Alzheimer's Disease Progression

OBJECTIVE

To evaluate the potential clinical value of quantitative functional FDG PET and pathological amyloid-β PET with cerebrospinal fluid (CSF) biomarkers and clinical assessments in the prediction of Alzheimer's disease (AD) progression.

METHODS

We studied 82 subjects for up to 96 months (median = 84 months) in a longitudinal Alzheimer's Disease Neuroimaging Initiative (ADNI) project. All preprocessed PET images were spatially normalized to standard Montreal Neurologic Institute space. Regions of interest (ROI) were defined on MRI template, and standard uptake values ratios (SUVRs) to the cerebellum for FDG and amyloid-β PET were calculated. Predictive values of single and multiparametric PET biomarkers with and without clinical assessments and CSF biomarkers for AD progression were evaluated using receiver operating characteristic (ROC) analysis and logistic regression model.

RESULTS

The posterior precuneus and cingulate SUVRs were identified for both FDG and amyloid-β PET in predicating progression in normal controls (NCs) and subjects with mild cognitive impairment (MCI). FDG parietal and lateral temporal SUVRs were suggested for monitoring NCs and MCI group progression, respectively. 18F-AV45 global cortex attained (78.6%, 74.5%, 75.4%) (sensitivity, specificity, accuracy) in predicting NC progression, which is comparable to the 11C-PiB global cortex SUVR's in predicting MCI to AD. A logistic regression model to combine FDG parietal and posterior precuneus SUVR and Alzheimer's Disease Assessment Scale-Cognitive (ADAS-Cog) Total Mod was identified in predicating NC progression with (80.0%, 94.9%, 93.9%) (sensitivity, specificity, accuracy). The selected model including FDG posterior cingulate SUVR, ADAS-Cog Total Mod, and Mini-Mental State Exam (MMSE) scores for predicating MCI to AD attained (96.4%, 81.2%, 83.6%) (sensitivity, specificity, accuracy). 11C-PiB medial temporal SUVR with MMSE significantly increased 11C-PiB PET AUC to 0.915 (p<0.05) in predicating MCI to AD with (77.8%, 90.4%, 88.5%) (sensitivity, specificity, accuracy).

CONCLUSION

Quantitative FDG and 11C-PiB PET with clinical cognitive assessments significantly improved accuracy in the predication of AD progression.

Longitudinal Partial Volume Correction in 2-[18F]-Fluoro-2-Deoxy-D-Glucose Positron Emission Tomography Studies of Alzheimer Disease

OBJECTIVE

To investigate partial volume correction (PVC) of 2-[F]-fluoro-2-deoxy-D-glucose positron emission tomography in Alzheimer disease in a longitudinal context.

METHODS

A total of 115 participants were included, including 55 controls, 53 patients with mild cognitive impairment, and 7 patients with dementia of the Alzheimer type. Imaging was performed at baseline and 24 months. Partial volume corrected vs uncorrected rates of longitudinal change were compared for mesial temporal and cortical regions of interest.

RESULTS

Partial volume correction increased apparent uptake, and this effect was greater at 24 months compared with baseline. Partial volume correction decreased the rate of decline, causing an apparent increase in uptake at 24 months compared with baseline. This effect was correlated with the structural atrophy.

CONCLUSIONS

These findings suggest that applying PVC in a longitudinal context in Alzheimer disease might produce unpredictable results. Accordingly, both PVC corrected and uncorrected data should be reported to ensure that the results are physiologically plausible.

Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting

Diagnostic accuracy in FDG-PET imaging highly depends on the operating procedures. In this clinical study on dementia, we compared the diagnostic accuracy at a single-subject level of a) Clinical Scenarios, b) Standard FDG Images and c) Statistical Parametrical (SPM) Maps generated via a new optimized SPM procedure. We evaluated the added value of FDG-PET, either Standard FDG Images or SPM Maps, to Clinical Scenarios. In 88 patients with neurodegenerative diseases (Alzheimer's Disease—AD, Frontotemporal Lobar Degeneration—FTLD, Dementia with Lewy bodies—DLB and Mild Cognitive Impairment—MCI), 9 neuroimaging experts made a forced diagnostic decision on the basis of the evaluation of the three types of information. There was also the possibility of a decision of normality on the FDG-PET images. The clinical diagnosis confirmed at a long-term follow-up was used as the gold standard. SPM Maps showed higher sensitivity and specificity (96% and 84%), and better diagnostic positive (6.8) and negative (0.05) likelihood ratios compared to Clinical Scenarios and Standard FDG Images. SPM Maps increased diagnostic accuracy for differential diagnosis (AD vs. FTD; beta 1.414, p = 0.019). The AUC of the ROC curve was 0.67 for SPM Maps, 0.57 for Clinical Scenarios and 0.50 for Standard FDG Images. In the MCI group, SPM Maps showed the highest predictive prognostic value (mean LOC = 2.46), by identifying either normal brain metabolism (exclusionary role) or hypometabolic patterns typical of different neurodegenerative conditions.

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Brain FDG-PET was evaluated with a new optimized SPM procedure in dementias.

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We compared the diagnostic accuracy of clinical information, visual and SPM FDG-PET.

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SPM had the best sensitivity (96%), specificity (84%) and positive and negative LR.

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In an MCI subgroup, SPM had the highest predictive prognostic value.

Clinical applications of neuroimaging in patients with Alzheimer's disease: a review from the Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia 2012

In May 2012, the Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia brought together in Montreal experts from around Canada to update Canadian recommendations for the diagnosis and management of patients with neurodegenerative conditions associated with deterioration of cognition. Multiple topics were discussed. The present paper is a highly condensed version of those recommendations that were produced to support discussions in the field of neuroimaging for clinical diagnosis of those conditions.

Normal stress databases in myocardial perfusion scintigraphy--how many subjects do you need?

BACKGROUND

Commercial normal stress databases in myocardial perfusion scintigraphy (MPS) commonly consist of 30-40 individuals. The aim of the study was to determine how many subjects are needed.

METHODS

Four normal stress databases were developed using patients who underwent 99mTc MPS: non-corrected images (NC) for male, NC for female, attenuation-corrected images (AC) for male and AC for female subjects. 126 male and 205 female subjects were included. The normal database was created by alternatingly computing the mean of all normal subjects and normalizing the subjects with respect to this mean, until convergence. Coefficients of variation (CV) were created for increasing number of included patients in the four different normal stress databases.

RESULTS

Normal stress databases with < 35 subjects had a high CV. Mean CV -2 standard deviations (SD) decreased with 28% between two and five included subjects, 71% between two and 35 subjects and 83% between two and 100 included subjects for NC man.

CONCLUSIONS

We conclude that the commonly used 30-40 individuals for making a normal stress database might not be enough due to the high CV. We propose that normal stress databases should consist of more than 30-40 individuals, preferably more than 50 individuals, both for NC and AC studies.

Effectiveness and safety of 18F-FDG PET in the evaluation of dementia: a review of the recent literature

Imaging that can detect pathophysiologic change in the brain holds great promise for diagnostic assessment of patients with Alzheimer disease (AD) and dementia. Although a previous metaanalysis centering on literature from 1990 to 2000 showed a summary accuracy of 86% for (18)F-FDG PET for AD diagnosis, the clinical value was considered uncertain because of methodologic shortcomings. Review of the recent literature since 2000 demonstrates that the evidence for (18)F-FDG PET in assessment of dementia has increased with new studies that include autopsy confirmation, wide-diagnostic-spectrum recruitment in primary care settings, historical and prospective cohort studies, and multicenter data analyses. These data support the role of (18)F-FDG PET as an effective and useful adjunct to other diagnostic information in the assessment of patients with symptoms of dementia. Findings are in line with recently revised diagnostic criteria of AD that for the first time recognize the unique role of biomarker evidence in disease definition.

Relative Function: Nuclear Brain Imaging in United States Courts

Neuropsychological testing—medical imaging of the brain structure and function—allows the expert to inform the court on the brain structure and function of the forensic examinee. Supported by extensive clinical use, neuropsychological testing and structural imaging in the form of computerized tomography and structural magnetic resonance imaging have achieved general acceptance in court. However, functional imaging such as functional MRI and nuclear medicine techniques, such as positron emission tomography (PET), have faced more admissibility challenges. While functional imaging is becoming an increasingly important tool in assessing neuropsychiatric illness, we surmise that evidentiary challenges are largely related to the phase of trial in which the nuclear study is offered as evidence. This article will review the basic science of functional nuclear imaging including PET and single photon emission computed tomography. We will then review cases where admissibility of these techniques has been challenged and consider whether and how nuclear brain imaging can influence the outcome of the trial.

Posterior cingulate atrophy and metabolic decline in early stage Alzheimer's disease

To test the hypothesis that Alzheimer's disease (AD) patients with posterior cingulate/precuneus (PCP) atrophy would be a distinct disease form in view of metabolic decline. Eighty-one AD patients underwent (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) and structural magnetic resonance imaging (MRI). Positron emission tomography and voxel-based morphometry (VBM) Z-score maps were generated for the individual patients using age-specific normal databases. The patients were classified into 3 groups based on atrophic patterns (no-Hipp-PCP, atrophy in neither hippocampus nor PCP; Hipp, hippocampal atrophy; PCP, PCP atrophy). There were 16 patients classified as no-Hipp-PCP, 55 as Hipp, and 10 as PCP. The Mini Mental State Examination (MMSE) score was similar among the groups. The greater FDG decline than atrophy was observed in all groups, including the no-Hipp-PCP. The PCP group was younger, and was associated with a greater degree of FDG decline in PCP than the others. There are diverse atrophic patterns in a spectrum of AD. In particular, a subset of patients show PCP atrophy, which is associated with greater metabolic burden.

Computer-assisted system for diagnosis of Alzheimer disease using data base- independent estimation and fluorodeoxyglucose- positron-emission tomography and 3D-stereotactic surface projection

BACKGROUND AND PURPOSE

Recently, voxel-based statistical parametric images have been developed as additional diagnostic tools for AD. However these methods require the generation of a data base of healthy brain images. The purpose of this study was to produce and evaluate an automatic method using a data base-independent estimation system for the diagnosis of mild AD.

MATERIALS AND METHODS

We retrospectively selected 66 subjects, including 33 patients with early AD and 33 age-matched healthy volunteers. Individual brain metabolic images were obtained by using FDG-PET. These were transformed by using 3D-SSP. We then produced CADDIES, which compares the parietal and sensorimotor metabolic counts by using t tests. If parietal metabolism was significantly lower than the sensorimotor metabolism, the subject was automatically diagnosed as having AD. The FDG-PET images were also analyzed by using a previous automatic diagnosis system (CAAD) that is dependent on the construction of a "normal data base" of healthy brain images. Diagnostic performance was compared between the 2 methods.

RESULTS

The CADDIES demonstrated a sensitivity of 88%, specificity of 79%, and accuracy of 85%, while the CAAD system demonstrated a sensitivity of 70%, specificity of 94%, and accuracy of 82%. The area under the ROC curve of CADDIES was 0.964. The areas under ROC curves of the CAAD method in the parietal and posterior cingulate gyri were 0.843 and 0.939, respectively.

CONCLUSIONS

The CADDIES method demonstrated a diagnostic accuracy similar to that of the CAAD system. Our results indicate that this method can be applied to the detection of patients with early AD in routine clinical examinations, with the benefit of not requiring the generation of a normal data base.

Construction of a (18)F-FDG PET normative database of Japanese healthy elderly subjects and its application to demented and mild cognitive impairment patients

OBJECTIVE

To construct a (18)F-FDG PET normative database of Japanese healthy elderly subjects and to apply it to demented and mild cognitive impairment (MCI) patients.

METHODS

Seventy-seven Japanese normal volunteers from 41 to 84 years of age (36 males and 41 females) who underwent clinical, neuropsychological, and MRI examinations were selected. In these subjects, (18)F-FDG PET/CT scans were performed, (18)F-FDG PET images were analyzed using the 3D-SSP program, and a normative database for cerebral glucose metabolism was constructed. Then, (18)F-FDG PET images from 14 demented and MCI patients were evaluated based on the normative database.

RESULTS

The 77 healthy elderly subjects were divided into three groups according to their age. In these subjects, the difference in glucose metabolism between males and females was minimal in contrast, glucose metabolism showed a weak reciprocal correlation with aging in several cerebral regions. The 3D-SSP images of 14 demented and MCI patients based on the age-matched (18)F-FDG PET normative database showed decreased patterns of glucose metabolism similar to those of previous studies on dementia diseases and MCI.

CONCLUSIONS

An age-matched normative database can be applied to the evaluation of single subjects, and the application of a mixed database of males and females is viable. Normative databases are useful for detecting dementia diseases and their MCI.

[Effects of transmission scan protocol and attenuation correction method on normal database of 2-[18F]fluoro-2-deoxy-D-glucose (18F-FDG) brain positron emission tomography study]

Although post-injection transmission scan (POST-TS) after 2-[(18)F]fluoro-2-deoxy- D-glucose ((18)F-FDG) injection[A1] is useful for short examination times, the emission count of (18)F-FDG[A2] in the regional brain area was not completely subtracted with use of the POST-TS method. The purpose of this study was to investigate the effect of POST-TS and attenuation correction (AC) methods on the normal database (NDB). A 10 min pre-injection transmission scan (PRE-TS) was performed before (18)F-FDG[A3] was injected in eighteen normal volunteers. A 10 min POST-TS was then conducted beginning 40 min after (18)F-FDG[A4] injection, followed by a 10 min 2-dimentional emission scanning. To reconstruct each image of normal volunteers, the reconstruction was performed using the filtered back-projection (FBP) method and the ordered subsets expectation maximization (OSEM) method, with transmission-based measured attenuation correction (MAC) and the segmented attenuation correction (SAC) technique. Subtraction images of NDB with PRE-TS or POST-TS were evaluated using 3D-SSP. A phantom study was also performed in addition to a human study, and assessment was by region of interests and profile curves. NDB images with POST-TS were significantly lower in the bilateral frontal lobes and higher in the parietal lobes and occipital lobes, including the precuneus, than those with PRE-TS, regardless of the different AC and reconstruction algorithms. Therefore, we have to be careful to confirm not only emission scan methods and reconstruction algorithms, but also TS methods and AC methods in the NDB. It will be best to perform PET examinations using the same TS methods and AC methods between NDB and patients.

Is it time to re-prioritize neuroimaging databases and digital repositories?

The development of in vivo brain imaging has lead to the collection of large quantities of digital information. In any individual research article, several tens of gigabytes-worth of data may be represented-collected across normal and patient samples. With the ease of collecting such data, there is increased desire for brain imaging datasets to be openly shared through sophisticated databases. However, very often the raw and pre-processed versions of these data are not available to researchers outside of the team that collected them. A range of neuroimaging databasing approaches has streamlined the transmission, storage, and dissemination of data from such brain imaging studies. Though early sociological and technical concerns have been addressed, they have not been ameliorated altogether for many in the field. In this article, we review the progress made in neuroimaging databases, their role in data sharing, data management, potential for the construction of brain atlases, recording data provenance, and value for re-analysis, new publication, and training. We feature the LONI IDA as an example of an archive being used as a source for brain atlas workflow construction, list several instances of other successful uses of image databases, and comment on archive sustainability. Finally, we suggest that, given these developments, now is the time for the neuroimaging community to re-prioritize large-scale databases as a valuable component of brain imaging science.

Optimization of the parameters of a method for computer-aided detection of perfusion deficiencies in brain images

OBJECTIVE

Simulated data from the recent Institute of Physics and Engineering in Medicine audit of quantitative cerebral perfusion were used to optimize the parameters of eigenimage analysis, a method for computer-aided detection.

METHODS

Twenty normal images provided by the audit were registered to the International Consortium for Brain Mapping 452 template using HERMES multimodality software and normalized to total counts. Six normal atlases were formed using the mean image and from zero to five eigenimages. Eight patient images, with computer-simulated lesions at known positions, were similarly registered and normalized. For each atlas, z-score images were formed for each patient. Thresholds of z0 = 2-5 in intervals of 0.5 were applied to the z-score images to form binary images of normal and abnormal voxels. A lesion was defined as a connected group of abnormal voxels with a minimum size of 1 ml. Lesions were assigned to one of 12 regions defined by the template. For eight patients, this gave 96 regions, 19 of which were known to contain an abnormality. Receiver-operating characteristic analysis was performed for the regions using z0 as a variable threshold.

RESULTS

For the receiver-operating characteristic analysis, an optimal area under the curve of approximately 0.90 was found using either one or three eigenimages, whereas good results (sensitivity = 0.75%; specificity = 90%) were obtained for a threshold of z0 approximately equal to 3. When the number of images in the normal dataset was considered, a meta-analysis showed consistency with other studies.

CONCLUSION

Eigenimage analysis was shown to give good diagnostic accuracy for cerebral perfusion images based on objective evaluation using simulated images.