Head-to-Head Comparison among Semi-Quantification Tools of Brain FDG-PET to Aid the Diagnosis of Prodromal Alzheimer's Disease

Combined 18F-FDG PET-CT markers in dementia with Lewy bodies

INTRODUCTION

18F-Fluoro-deoxyglucose-positron emission tomography (FDG-PET) is a supportive biomarker in dementia with Lewy bodies (DLB) diagnosis and its advanced analysis methods, including radiomics and machine learning (ML), were developed recently. The aim of this study was to evaluate the FDG-PET diagnostic performance in predicting a DLB versus Alzheimer's disease (AD) diagnosis.

METHODS

FDG-PET scans were visually and semi-quantitatively analyzed in 61 patients. Radiomics and ML analyses were performed, building five ML models: (1) clinical features; (2) visual and semi-quantitative PET features; (3) radiomic features; (4) all PET features; and (5) overall features.

RESULTS

At follow-up, 34 patients had DLB and 27 had AD. At visual analysis, DLB PET signs were significantly more frequent in DLB, having the highest diagnostic accuracy (86.9%). At semi-quantitative analysis, the right precuneus, superior parietal, lateral occipital, and primary visual cortices showed significantly reduced uptake in DLB. The ML model 2 had the highest diagnostic accuracy (84.3%).

DISCUSSION

FDG-PET is a valuable tool in DLB diagnosis, having visual and semi-quantitative analyses with the highest diagnostic accuracy at ML analyses.

Neuroimaging analyses from a randomized, controlled study to evaluate plasma exchange with albumin replacement in mild-to-moderate Alzheimer's disease: additional results from the AMBAR study

PURPOSE

This study was designed to detect structural and functional brain changes in Alzheimer's disease (AD) patients treated with therapeutic plasma exchange (PE) with albumin replacement, as part of the recent AMBAR phase 2b/3 clinical trial.

METHODS

Mild-to-moderate AD patients were randomized into four arms: three arms receiving PE with albumin (one with low-dose albumin, and two with low/high doses of albumin alternated with IVIG), and a placebo (sham PE) arm. All arms underwent 6 weeks of weekly conventional PE followed by 12 months of monthly low-volume PE. Magnetic resonance imaging (MRI) volumetric analyses and regional and statistical parametric mapping (SPM) analysis on 18F-fluorodeoxyglucose positron emission tomography (18FDG-PET) were performed.

RESULTS

MRI analyses (n = 198 patients) of selected subcortical structures showed fewer volume changes from baseline to final visit in the high albumin + IVIG treatment group (p < 0.05 in 3 structures vs. 4 to 9 in other groups). The high albumin + IVIG group showed no statistically significant reduction of right hippocampus. SPM 18FDG-PET analyses (n = 213 patients) showed a worsening of metabolic activity in the specific areas affected in AD (posterior cingulate, precuneus, and parieto-temporal regions). The high-albumin + IVIG treatment group showed the greatest metabolic stability over the course of the study, i.e., the smallest percent decline in metabolism (MaskAD), and least progression of defect compared to placebo.

CONCLUSIONS

PE with albumin replacement was associated with fewer deleterious changes in subcortical structures and less metabolic decline compared to the typical of the progression of AD. This effect was more marked in the group treated with high albumin + IVIG.

TRIAL REGISTRATION

(AMBAR trial registration: EudraCT#: 2011-001,598-25; ClinicalTrials.gov ID: NCT01561053).

Added value of semiquantitative analysis of brain FDG-PET for the differentiation between MCI-Lewy bodies and MCI due to Alzheimer's disease

PURPOSE

FDG-PET is an established supportive biomarker in dementia with Lewy bodies (DLB), but its diagnostic accuracy is unknown at the mild cognitive impairment (MCI-LB) stage when the typical metabolic pattern may be difficultly recognized at the individual level. Semiquantitative analysis of scans could enhance accuracy especially in less skilled readers, but its added role with respect to visual assessment in MCI-LB is still unknown.

METHODS

We assessed the diagnostic accuracy of visual assessment of FDG-PET by six expert readers, blind to diagnosis, in discriminating two matched groups of patients (40 with prodromal AD (MCI-AD) and 39 with MCI-LB), both confirmed by in vivo biomarkers. Readers were provided in a stepwise fashion with (i) maps obtained by the univariate single-subject voxel-based analysis (VBA) with respect to a control group of 40 age- and sex-matched healthy subjects, and (ii) individual odds ratio (OR) plots obtained by the volumetric regions of interest (VROI) semiquantitative analysis of the two main hypometabolic clusters deriving from the comparison of MCI-AD and MCI-LB groups in the two directions, respectively.

RESULTS

Mean diagnostic accuracy of visual assessment was 76.8 ± 5.0% and did not significantly benefit from adding the univariate VBA map reading (77.4 ± 8.3%) whereas VROI-derived OR plot reading significantly increased both accuracy (89.7 ± 2.3%) and inter-rater reliability (ICC 0.97 [0.96-0.98]), regardless of the readers' expertise.

CONCLUSION

Conventional visual reading of FDG-PET is moderately accurate in distinguishing between MCI-LB and MCI-AD, and is not significantly improved by univariate single-subject VBA but by a VROI analysis built on macro-regions, allowing for high accuracy independent of reader skills.

Optimizing Use of Neuroimaging Tools in Evaluation of Prodromal Alzheimer's Disease and Related Disorders

Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by preclinical, pre-dementia, and dementia phases. Progression of the disease leads to cognitive decline and is associated with loss of functional independence, personality changes, and behavioral disturbances. Current guidelines for AD diagnosis include the use of neuroimaging tools as biomarkers for identifying and monitoring pathological changes. Various imaging modalities, namely magnetic resonance imaging (MRI), fluorodeoxyglucose-positron emission tomography (FDG-PET) and PET with amyloid-beta tracers are available to facilitate early accurate diagnoses. Enhancing diagnosis in the early stages of the disease can allow for timely interventions that can delay progression of the disease. This paper will discuss the characteristic findings associated with each of the imaging tools for patients with AD, with a focus on FDG-PET due to its established accuracy in assisting with the differential diagnosis of dementia and discussion of other methods including MRI. Diagnostically-relevant features to aid clinicians in making a differential diagnosis will also be pointed out and multimodal imaging will be reviewed. We also discuss the role of quantification software in interpretation of brain imaging. Lastly, to guide evaluation of patients presenting with cognitive deficits, an algorithm for optimal integration of these imaging tools will be shared. Molecular imaging modalities used in dementia evaluations hold promise toward identifying AD-related pathology before symptoms are fully in evidence. The work describes state of the art functional and molecular imaging methods for AD. It will also overview a clinically applicable quantitative method for reproducible assessments of such scans in the early identification of AD.

Artificial intelligence for molecular neuroimaging

In recent years, artificial intelligence (AI) or the study of how computers and machines can gain intelligence, has been increasingly applied to problems in medical imaging, and in particular to molecular imaging of the central nervous system. Many AI innovations in medical imaging include improving image quality, segmentation, and automating classification of disease. These advances have led to an increased availability of supportive AI tools to assist physicians in interpreting images and making decisions affecting patient care. This review focuses on the role of AI in molecular neuroimaging, primarily applied to positron emission tomography (PET) and single photon emission computed tomography (SPECT). We emphasize technical innovations such as AI in computed tomography (CT) generation for the purposes of attenuation correction and disease localization, as well as applications in neuro-oncology and neurodegenerative diseases. Limitations and future prospects for AI in molecular brain imaging are also discussed. Just as new equipment such as SPECT and PET revolutionized the field of medical imaging a few decades ago, AI and its related technologies are now poised to bring on further disruptive changes. An understanding of these new technologies and how they work will help physicians adapt their practices and succeed with these new tools.

Detection Gap of Right-Asymmetric Neuronal Degeneration by CERAD Test Battery in Alzheimer's Disease

Objectives: Asymmetric disease characteristics on neuroimaging are common in structural and functional imaging of neurodegenerative diseases, particularly in Alzheimer‘s disease (AD). However, a standardized clinical evaluation of asymmetric neuronal degeneration and its impact on clinical findings has only sporadically been investigated for F-18-fluorodeoxyglucose positron emission tomography (F-18-FDG-PET). This study aimed to evaluate the impact of lateralized neuronal degeneration on the detection of AD by detailed clinical testing. Furthermore, we compared associations between clinical evaluation and lateralized neuronal degeneration between FDG-PET hypometabolism and hippocampal atrophy. Finally, we investigated if specific subtests show associations with lateralized neuronal degeneration.

Methods: One-hundred and forty-six patients with a clinical diagnosis of AD (age 71 ± 8) were investigated by FDG-PET and the “Consortium to Establish a Registry for Alzheimer’s disease” (CERAD) test battery. For assessment of neuronal degeneration, FDG-PET hypometabolism in brain regions typically affected in AD were graded by visual (3D-surface projections) and semiquantitative analysis. Asymmetry of the hippocampus (left-right) in magnetic resonance tomography (MRI) was rated visually by the Scheltens scale. Measures of asymmetry were calculated to quantify lateralized neuronal degeneration and asymmetry scores were subsequently correlated with CERAD.

Results: Asymmetry with left-dominant neuronal degeneration to FDG-PET was an independent predictor of cognitive impairment (visual: β = −0.288, p < 0.001; semiquantitative: β = −0.451, p < 0.001) when controlled for age, gender, years of education and total burden of neuronal degeneration, whereas hippocampal asymmetry to MRI was not (β = −0.034; p = 0.731). Direct comparison of CERAD-PET associations in cases with right- and left-lateralized neuronal degeneration estimated a detection gap of 2.7 years for right-lateralized cases. Left-hemispheric neuronal degeneration was significantly associated with the total CERAD score and multiple subscores, whereas only MMSE (semiquantitative: β = 0.429, p < 0.001) and constructional praxis (semiquantitative: β = 0.292, p = 0.008) showed significant associations with right-hemispheric neuronal degeneration.

Conclusions: Asymmetry of deteriorated cerebral glucose metabolism has a significant impact on the coupling between neuronal degeneration and cognitive function. Right dominant neuronal degeneration shows a delayed detection by global CERAD testing and requires evaluation of specific subdomains of cognitive testing.

Noninvasive Measurement of [11C]PiB Distribution Volume Using Integrated PET/MRI

A noninvasive image-derived input function (IDIF) method using PET/MRI was applied to quantitative measurements of [¹¹C] Pittsburgh compound-B (PiB) distribution volume (DV) and compared with other metrics. Fifty-three patients suspected of early dementia (71 ± 11 y) underwent 70 min [¹¹C]PiB PET/MRI. Nineteen of them (68 ± 11 y) without head motion during the scan were enrolled in this study and compared with 16 age-matched healthy controls (CTL: 68 ± 11 y). The dynamic frames reconstructed from listmode PET data were used for DV calculation. IDIF with metabolite correction was applied to the Logan plot method, and DV was normalized into DV ratio (DVR) images using the cerebellar reference (DVR_L). DVR and standardized uptake value ratio (SUVR) images were also calculated using the reference tissue graphical method (DVR_r) and the 50–70 min static data with cerebellar reference, respectively. Cortical values were compared using the 3D-T1WI MRI segmentation. All patients were assigned to the early Alzheimer’s disease (eAD) group because of positive [¹¹C]PiB accumulation. The correlations of regional values were better for DVR_L vs. DVR_r (r² = 0.97) than for SUVR vs. DVR_r (r² = 0.88). However, all metrics clearly differentiated eAD from CTL with appropriate thresholds. Noninvasive quantitative [¹¹C]PiB PET/MRI measurement provided equivalent DVRs with the two methods. SUVR images showed acceptable results despite inferior variability and image quality to DVR images.

Relevance of quantification in brain PET studies with 18F-FDG

The inclusion of ¹⁸F-FDG PET as a biomarker in the diagnostic criteria of neurodegenerative diseases and its indication in the presurgical assessment for drug-resistant epilepsies allow to improve specificity of these diagnosis. The traditional interpretation of neurological PET studies has been performed qualitatively, although in the last decade, several quantitative evaluation methods have emerged. This technical development has become relevant in clinical practice, improving specificity, reproducibility and reducing the interrater reliability derived from visual analysis. In this article we update/review the main imaging processing techniques currently used. This may allow the Nuclear Medicine physician to know their advantages and disadvantages when including these procedures in daily clinical practice.

Age-related Assessment of Postural Control Development: A Cross-sectional Study in Children and Adolescents

The aim of this study was to outline an age-dependent range of posturography measures obtained from healthy children. One hundred and fifty healthy 4-18-year-old children underwent video Head Impulse Test and static posturography testing. Surface, length and power spectra values were compared between each group of pupils and 32 healthy adults. As well as a significant (p < 0.025) increase in surface and length, when compared to healthy adults, increased values within the low/middle frequency domain and within the high frequency domain were also observed in 4-13 and 4-7-year-old children, respectively. In conclusion, although the nature of postural control development remains largely undetermined, this study represents a first attempt to outline an age-dependent normal range of the relative contribution of inputs in typically developing children.