Search Results (38)

Background and Objectives: Dual-phase amyloid PET imaging has been proposed to provide complementary information regarding amyloid burden and cerebral perfusion. This exploratory pilot study evaluated whether semiquantitative parameters derived from dual-phase PET/CT could differentiate individuals operationally classified as Alzheimer’s disease with mild functional impairment (AD-MFI) from those with mild cognitive impairment (MCI). Materials and Methods: Twenty-four participants (AD-MFI, n = 19; MCI, n = 5) underwent dual-phase amyloid PET/CT and structural MRI. Early phase SUV (eSUV), delayed-phase SUV (dSUV), standardized uptake value ratios (SUVR), and the difference between early and delayed uptake (SUV_diff) were analyzed across predefined cortical regions. Group differences were assessed using nonparametric tests, with false discovery rate (FDR) and Bonferroni corrections applied for multiple comparisons. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Results: Several regional parameters demonstrated nominally significant group differences in uncorrected analyses; however, none remained statistically significant after correction for multiple comparisons. Among the evaluated metrics, SUV_diff demonstrated the highest diagnostic performance (sensitivity 84.2%, specificity 80.0%), followed by eSUV (68.4%, 100%) and MRI cortical volume (47.4%, 100%). Delayed-phase parameters alone showed limited discriminatory robustness despite observed group-level differences. Conclusions: In this exploratory cohort, SUV_diff showed moderate discriminatory potential between AD-MFI and MCI. However, given the small sample size and multiplicity of comparisons, the results should be interpreted as hypothesis-generating. Larger, prospective studies are required to determine the reproducibility and clinical utility of dual-phase semiquantitative parameters. Full article

Background: Amyloid positron emission tomography (PET) has been proposed as a tool to monitor myelination in multiple sclerosis (MS). We present baseline results from an ongoing prospective study, which is the first to include both early and standard phases of amyloid PET in patients with newly diagnosed MS. Methods: The prospective study includes patients with newly diagnosed MS (January 2023–February 2024). Clinical evaluation includes neurological disability (EDSS) and neuropsychological assessment. Brain MRI, early [¹⁸F]florbetaben (FBB) PET (eFBB; 0–5, 0–10 min post-injection), and standard FBB PET (sFBB; 90 min post-injection) were acquired. Normal-appearing white matter (NAWM) and damaged white matter (DWM) in MRI were segmented and co-registered with PET images. Results are presented as standardized uptake values (SUV), with the ratio using cerebellum as the reference region (SUVR) and the percentage of change between the DWM and NAWM. Results: Twenty patients were included (35.05 ± 10.72 years; 75% women). Both eFBB and sFBB acquisitions showed significantly lower SUVRmax and SUVRmean, and higher SUVRmin in the DWM compared to NAWM (p < 0.001) in all patients. SUV parameters in both DWM and NAWM from eFBB and sFBB PET correlated with the number of relapses and EDSS (r = −0.454 and r = −0.446, respectively; p < 0.05). Additionally, SUVR values in the DWM during eFBB correlated with cognitive impairment (SDMT; r = −0.516, p < 0.01), fatigue (MFIS-5; r = −0.450, p < 0.05), and quality of life (EQ-5D; r = −0.490, p < 0.05). Conclusions: Quantitative analysis of dual-phase FBB PET demonstrates differential uptake between DWM and NAWM, which is probably associated with demyelination and neurodegeneration. These preliminary findings suggest that amyloid PET may have predictive value for disease activity and progression, supporting its potential as a biomarker in MS. Follow-up data from this study are needed to support the baseline results. Full article

The study assesses the relationship between thalamic proton-MR spectroscopy (¹H-MRS) metabolites and thalamic ¹¹C-ER176 translocator-protein positron emission tomography (TSPO-PET) standardized uptake value ratios (SUVR) to advance our understanding of thalamic involvement in multiple sclerosis (MS)-associated neurodegeneration and disability. In this prospective cross-sectional study, patients with MS (pwMS) and controls underwent 3T-MRI, ¹H-MRS, and ¹¹C-ER176-PET targeting the thalamus. MRI-derived thalamic volume was normalized by intracranial volume. ¹H-MRS metabolites—N-acetylaspartate (NAA), glutamate (Glu), glutamine (Gln), total choline (tCho), and myo-inositol (mIns)—were normalized to total creatine (tCr). Clinical disability was evaluated using MS-specific tests of Expanded Disability Status Scale-EDSS and MS-functional composite-MSFC (including Paced Auditory Serial Addition Test-PASAT). Compared to controls (n = 30), pwMS (n = 21) exhibited smaller thalamic volume, higher thalamic ¹H-MRS mIns/tCr (putative gliosis marker), and higher thalamic ¹¹C-ER176-PET SUVR (glial density marker). In pwMS, higher thalamic mIns/tCr (r = −0.67) and tCho/tCr (r = −0.52) correlated with smaller thalamic volume. In pwMS, higher thalamic mIns/tCr correlated with higher thalamic ¹¹C-ER176-PET SUVR (r = 0.48) and decreased cognitive function (PASAT, rho = −0.48). In controls, decreased thalamic NAA/tCr correlated with increased thalamic ¹¹C-ER176-PET SUVR (r = −0.41). Thalamus, a core central nervous system relay, is affected early in MS disease course. Glial-mediated innate immune activation in the thalamus, evaluated by increased ¹H-MRS mIns/tCr and ¹¹C-ER176-PET SUVR, is associated with loss of thalamic volume and increased disability in pwMS. The multimodal imaging approach with ¹H-MRS mIns/tCr and ¹¹C-ER176-PET SUVR emerges as potential glial biomarkers, to better understand disease mechanisms and evaluate therapeutic interventions targeting glial activity in MS. Full article

Background/Objectives: Quantitative analysis of amyloid PET imaging plays a crucial role in diagnosing Alzheimer’s disease (AD), particularly in cases where visual interpretation is equivocal. Multiple commercial software tools are available for this purpose, yet differences in their quantification and diagnostic performance remain understudied, especially for Neurophet SCALE PET. Methods: We retrospectively analyzed ¹⁸F-florbetaben PET/CT scans from 129 patients with cognitive impairment, comprising 39 patients with AD and 90 with non-AD diagnoses, using three software tools: MIMneuro, CortexID Suite, and Neurophet SCALE PET. Standardized uptake value ratios (SUVRs) were obtained for six brain regions known for amyloid accumulation. Diagnostic accuracy was evaluated using ROC curve analysis, while inter-software correlations and reliability were assessed via Pearson correlation coefficients and intraclass correlation coefficients (ICC). Results: All three software programs significantly distinguished AD from non-AD patients in most brain regions. MIMneuro and Neurophet SCALE PET demonstrated the highest diagnostic performance, with MIMneuro achieving an AUC of 1.000 in the anterior cingulate gyrus. While MIMneuro and Neurophet SCALE PET showed moderate-to-strong SUVR correlations (r = 0.715–0.865), CortexID Suite showed limited correlation with the other tools. Inter-software reliability was moderate only in selected regions (ICC ≈ 0.5), indicating potential variability in SUVR measurements across platforms. Conclusions: MIMneuro, CortexID Suite, and Neurophet SCALE PET are effective for the semi-quantitative analysis of amyloid PET and can aid in the diagnosis of AD. However, clinicians should be cautious when interpreting SUVRs across different software tools due to limited inter-software consistency. Standardization efforts or consistent use of a single platform are recommended to avoid diagnostic discrepancies. Full article

This study aimed to examine associations between functional capacity (FC), brain β-amyloid (Aβ) burden, and longitudinal cognitive performance. Data from 89 cognitively normal women (70.0 ± 2.7 years) in the Women’s Healthy Ageing Project cohort were analyzed. FC was assessed using the timed up and go (TUG) test and the Aβ burden was quantified via a F-18 Florbetaben PET scan with Standardized Uptake Value Ratio (SUVR). Cognition was evaluated longitudinally using the Preclinical Alzheimer Cognitive Composite (PACC) over 3.9 ± 2.6 years. Multiple linear regression, mediation analysis, and linear mixed-effects models were applied. Baseline Aβ burden and years of education were associated with cognitive performance two to six years later, while the TUG performance was associated with cognitive outcomes at two years. Aβ burden was found to mediate the relationship between FC and cognition over time. A significant three-way interaction (TUG × SUVR × time) was observed, indicating that declines in the TUG performance over time were exclusively associated with steeper cognitive decline among women with elevated Aβ burden (SUVR ≥ 1.42). These findings suggest that maintaining functional mobility may be particularly relevant for women with increased Aβ burden and support future research targeting early motor-cognitive markers. Full article

Background/Objectives: This study aimed to investigate the predictive power of integrated longitudinal amyloid positron emission tomography (PET) and brain magnetic resonance imaging (MRI) data for determining the likelihood of conversion to Alzheimer’s disease (AD) in patients with mild cognitive impairment (MCI). Methods: We included 180 patients with MCI from the Alzheimer’s Disease Neuroimaging Initiative, with baseline and 2-year follow-up scans obtained using F-18 florbetapir PET and MRI. Patients were categorized as converters (progressing to AD) or nonconverters based on a 6-year follow-up. Quantitative analyses included the calculation of amyloid burden using the standardized uptake value ratio (SUVR), brain amyloid smoothing scores (BASSs), brain atrophy indices (BAIs), and their integration into shape features. Longitudinal changes and receiver operating characteristic analyses assessed the predictive power of these biomarkers. Results: Among 180 patients with MCI, 76 (42.2%) were converters, who exhibited significantly higher baseline and 2-year follow-up values for SUVR, BASS, BAI, and shape features than nonconverters (p < 0.001). Shape features demonstrated the highest predictive accuracy for conversion, with areas under the curve of 0.891 at baseline and 0.898 at 2 years. Percent change analyses revealed significant increases in brain atrophy; amyloid deposition changes showed a paradoxical decrease in converters. Additionally, strong associations were observed between longitudinal changes in shape features and neuropsychological test results. Conclusions: The integration of amyloid PET and MRI biomarkers enhances the prediction of AD progression in patients with MCI. These findings support the potential of combined imaging approaches for early diagnosis and targeted interventions in AD. Full article

In amyloid brain PET, after parcellation using the finite element method (FEM)-based algorithm FreeSurfer and voxel-based algorithm PMOD, SUVr examples can be extracted and compared. This study presents the classification SUVr threshold in PET images of F-18 florbetaben (FBB), F-18 flutemetamol (FMM), and F-18 florapronol (FPN) and compares and analyzes the classification performance according to computational algorithm in each brain region. PET images were co-registered after the generated MRI was registered with standard template information. Using MATLAB script, SUVr was calculated using the built-in parcellation number labeled in the brain region. PMOD and FreeSurfer with different algorithms were used to load the PET image, and after registration in MRI, it was normalized to the MRI template. The volume and SUVr of the individual gray matter space region were calculated using an automated anatomical labeling atlas. The SUVr values of eight regions of the frontal cortex (FC), lateral temporal cortex (LTC), mesial temporal cortex (MTC), parietal cortex (PC), occipital cortex (OC), anterior and posterior cingulate cortex (GCA, GCP), and composite were calculated. After calculating the correlation of SUVr using the FreeSurfer and PMOD algorithms and calculating the AUC for amyloid-positive/negative subjects, the classification ability was calculated, and the SVUr threshold was calculated using the Youden index. The correlation coefficients of FreeSurfer and PMOD SUVr calculations of the eight regions of the brain cortex were FBB (0.95), FMM (0.94), and FPN (0.91). The SUVr threshold was SUVr(LTC,min) = 1.264 and SUVr(THA,max) = 1.725 when calculated using FPN-FreeSurfer, and SUVr(MTC,min) = 1.093 and SUVr(MCT,max) = 1.564 when calculated using FPN-PMOD. The AUC comparison showed that there was no statistically significant difference (p > 0.05) in the SUVr classification results using the three radiopharmaceuticals, specifically for the LTC and OC regions in the PMOD analysis, and the LTC and PC regions in the FreeSurfer analysis. The SUVr calculation using PMOD (voxel-based algorithm) has a strong correlation with the calculation using FreeSurfer (FEM-based algorithm); therefore, they complement each other. Quantitative classification analysis with high accuracy is possible using the suggested SUVr threshold. The SUVr classification performance was good in the order of FMM, FBB, and FPN, and showed a good classification performance in the LTC region regardless of the type of radiotracer and analysis algorithm. Full article

The diagnostic value of imaging Aβ plaques in Alzheimer’s disease (AD) has accelerated the development of fluorine-18 labeled radiotracers with a longer half-life for easier translation to clinical use. We have developed [¹⁸F]flotaza, which shows high binding to Aβ plaques in postmortem human AD brain slices with low white matter binding. We report the binding of [¹⁸F]flotaza in postmortem AD hippocampus compared to cognitively normal (CN) brains and the evaluation of [¹⁸F]flotaza in transgenic 5xFAD mice expressing Aβ plaques. [¹⁸F]Flotaza binding was assessed in well-characterized human postmortem brain tissue sections consisting of HP CA1-subiculum (HP CA1-SUB) regions in AD (n = 28; 13 male and 15 female) and CN subjects (n = 32; 16 male and 16 female). Adjacent slices were immunostained with anti-Aβ and analyzed using QuPath. In vitro and in vivo [¹⁸F]flotaza PET/CT studies were carried out in 5xFAD mice. Post-mortem human brain slices from all AD subjects were positively IHC stained with anti-Aβ. High [¹⁸F]flotaza binding was measured in the HP CA1-SUB grey matter (GM) regions compared to white matter (WM) of AD subjects with GM/WM > 100 in some subjects. The majority of CN subjects had no decipherable binding. Male AD exhibited greater WM than AD females (AD WM♂/WM♀ > 5; p < 0.001) but no difference amongst CN WM. In vitro studies in 5xFAD mice brain slices exhibited high binding [¹⁸F]flotaza ratios (>50 versus cerebellum) in the cortex, HP, and thalamus. In vivo, PET [¹⁸F]flotaza exhibited binding to Aβ plaques in 5xFAD mice with SUVR~1.4. [¹⁸F]Flotaza is a new Aβ plaque PET imaging agent that exhibited high binding to Aβ plaques in postmortem human AD. Along with the promising results in 5xFAD mice, the translation of [¹⁸F]flotaza to human PET studies may be worthwhile. Full article

Accurate quantification of amyloid positron emission tomography (PET) is essential for early detection of and intervention in Alzheimer’s disease (AD) but there is still a lack of studies comparing the performance of various automated methods. This study compared the PET-only method and PET-and-MRI-based method with a pre-trained deep learning segmentation model. A large sample of 1180 participants in the Catholic Aging Brain Imaging (CABI) database was analyzed to calculate the regional standardized uptake value ratio (SUVR) using both methods. The logistic regression models were employed to assess the discriminability of amyloid-positive and negative groups through 10-fold cross-validation and area under the receiver operating characteristics (AUROC) metrics. The two methods showed a high correlation in calculating SUVRs but the PET-MRI method, incorporating MRI data for anatomical accuracy, demonstrated superior performance in predicting amyloid-positivity. The parietal, frontal, and cingulate importantly contributed to the prediction. The PET-MRI method with a pre-trained deep learning model approach provides an efficient and precise method for earlier diagnosis and intervention in the AD continuum. Full article

Accurately diagnosing Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD) is challenging due to overlapping symptoms and limitations of current imaging methods. This study investigates the use of [11C]PBB3 PET/CT imaging to visualize tau pathology and improve diagnostic accuracy. Given diagnostic challenges with symptoms and conventional imaging, [11C]PBB3 PET/CT’s potential to enhance accuracy was investigated by correlating tau pathology with cerebrospinal fluid (CSF) biomarkers, positron emission tomography (PET), computed tomography (CT), amyloid-beta, and Mini-Mental State Examination (MMSE). We conducted [11C]PBB3 PET/CT imaging on 24 patients with suspected AD or FTLD, alongside [11C]PiB PET/CT (13 patients) and [18F]FDG PET/CT (15 patients). Visual and quantitative assessments of [11C]PBB3 uptake using standardized uptake value ratios (SUV-Rs) and correlation analyses with clinical assessments were performed. The scans revealed distinct tau accumulation patterns; 13 patients had no or faint uptake (PBB3-negative) and 11 had moderate to pronounced uptake (PBB3-positive). Significant inverse correlations were found between [11C]PBB3 SUV-Rs and MMSE scores, but not with CSF-tau or CSF-amyloid-beta levels. Here, we show that [11C]PBB3 PET/CT imaging can reveal distinct tau accumulation patterns and correlate these with cognitive impairment in neurodegenerative diseases. Our study demonstrates the potential of [11C]PBB3-PET imaging for visualizing tau pathology and assessing disease severity, offering a promising tool for enhancing diagnostic accuracy in AD and FTLD. Further research is essential to validate these findings and refine the use of tau-specific PET imaging in clinical practice, ultimately improving patient care and treatment outcomes. Full article

(1) Background: This study investigated changes in the gut microbial composition of individuals with mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) and their relationship with positron emission tomography (PET) amyloid accumulation. (2) Methods: In total, 17 cognitively normal individuals without amyloid-beta (Aβ) accumulation (Aβ⁻NC) and 24 with Aβ-positive mild cognitive impairment (Aβ⁺MCI) who underwent ¹⁸F-florbetaben PET and fecal bacterial 16S ribosomal RNA gene sequencing were enrolled. The taxonomic compositions of the Aβ⁻NC and Aβ⁺MCI groups were compared. The abundance of taxa was correlated with the standardized uptake value ratio (SUVR), using generalized linear models. (3) Results: There were significant differences in microbiome richness (ACE, p = 0.034 and Chao1, p = 0.024), alpha diversity (Shannon, p = 0.039), and beta diversity (Bray–Curtis, p = 0.018 and Generalized UniFrac, p = 0.034) between the Aβ⁻NC and Aβ⁺MCI groups. The global SUVR was positively correlated with the genus Intestinibacter (q = 0.006) and negatively correlated with the genera Roseburia (q = 0.008) and Agathobaculum (q = 0.029). (4) Conclusions: In this study, we identified significant changes in the gut microbiota composition that occur in individuals with MCI due to AD. In particular, the correlation analysis results between PET amyloid burden and gut microbial abundance showed that amyloid deposition is associated with a reduction in specific taxa involved in butyrate production. Full article

This research evaluated the modified RCTU score, derived from amyloid PET scans, for predicting the progression from amnestic Mild Cognitive Impairment (aMCI) to Alzheimer’s Disease (AD). aMCI patients underwent baseline evaluations, including amyloid PET. AD conversion was identified through neuropsychological tests after observation. The RCTU was modified by segmenting frontal, parietal, and temporal lobes into left and right, resulting in seven areas. Scores from both modified and conventional RCTU were analyzed and compared. Among 45 patients, 12 progressed to AD (over 17.8 ± 6.8 months). AD converters showed higher scores in modified RCTU scores. Modified RCTU score had strong correlations with amyloid SUVR (r > 0.7). Modified RCTU sum score was the significant covariate of AD conversion. Modified RCTU could determine the asymmetry of amyloid deposits. We demonstrated that symmetric deposits of amyloid showed a higher risk for AD conversion when analyzed using modified RCTU. The modified RCTU score is a promising method for predicting AD conversion, correlating strongly with amyloid SUVR. Full article

We developed a novel quantification method named “shape feature” by combining the features of amyloid positron emission tomography (PET) and brain magnetic resonance imaging (MRI) and evaluated its significance in predicting the conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. From the ADNI database, 334 patients with MCI were included. The brain amyloid smoothing score (AV45_BASS) and brain atrophy index (MR_BAI) were calculated using the surface area and volume of the region of interest in AV45 PET and MRI. During the 48-month follow-up period, 108 (32.3%) patients converted from MCI to AD. Age, Mini-Mental State Examination (MMSE), cognitive subscale of the Alzheimer’s Disease Assessment Scale (ADAS-cog), apolipoprotein E (APOE), standardized uptake value ratio (SUVR), AV45_BASS, MR_BAI, and shape feature were significantly different between converters and non-converters. Univariate analysis showed that age, MMSE, ADAS-cog, APOE, SUVR, AV45_BASS, MR_BAI, and shape feature were correlated with the conversion to AD. In multivariate analyses, high shape feature, SUVR, and ADAS-cog values were associated with an increased risk of conversion to AD. In patients with MCI in the ADNI cohort, our quantification method was the strongest prognostic factor for predicting their conversion to AD. Full article

Background: Approximately 20% of invasive ductal breast malignancies are human epidermal growth factor receptor 2 (HER2)-positive. These patients receive neoadjuvant systemic therapy (NAT) including HER2-targeting therapies. Up to 65% of patients achieve a pathological complete response (pCR). These patients might not have needed surgery. However, accurate preoperative identification of a pCR remains challenging. A radiologic complete response (rCR) on MRI corresponds to a pCR in only 73% of patients. The current feasibility study investigates if HER2-targeted PET/CT-imaging using Zirconium-89 (⁸⁹Zr)-radiolabeled trastuzumab can be used for more accurate NAT response evaluation. Methods: HER2-positive breast cancer patients scheduled to undergo NAT and subsequent surgery received a ⁸⁹Zr-trastuzumab PET/CT both before (PET/CT-1) and after (PET/CT-2) NAT. Qualitative and quantitative response evaluation was performed. Results: Six patients were enrolled. All primary tumors could be identified on PET/CT-1. Four patients had a pCR and two a pathological partial response (pPR) in the primary tumor. Qualitative assessment of PET/CT resulted in an accuracy of 66.7%, compared to 83.3% of the standard-of-care MRI. Quantitative assessment showed a difference between the SUV_R on PET/CT-1 and PET/CT-2 (ΔSUV_R) in patients with a pPR and pCR of −48% and −90% (p = 0.133), respectively. The difference in tumor-to-blood ratio on PET/CT-1 and PET/CT-2 (ΔTBR) in patients with pPR and pCR was −79% and −94% (p = 0.133), respectively. Three patients had metastatic lymph nodes at diagnosis that were all identified on PET/CT-1. All three patients achieved a nodal pCR. Qualitative assessment of the lymph nodes with PET/CT resulted in an accuracy of 66.7%, compared to 50% of the MRI. Conclusions: NAT response evaluation using ⁸⁹Zr-trastuzumab PET/CT is feasible. In the current study, qualitative assessment of the PET/CT images is not superior to standard-of-care MRI. Our results suggest that quantitative assessment of ⁸⁹Zr-trastuzumab PET/CT has potential for a more accurate response evaluation of the primary tumor after NAT in HER2-positive breast cancer. Full article

Recent studies have demonstrated the pivotal role of locus coeruleus (LC) and salience network (SN) resting state functional connectivity (rsFC) changes in the early stage of Alzheimer’s disease (AD). Moreover, sex has been a crucial point of discussion in understanding AD pathology. We aimed to demonstrate the sex-related disparities in the functional connectivity (FC) of the SN and LC in preclinical AD. A total of 89 cognitively normal patients with evidence of amyloid beta (Aβ) accumulation ([18F] flutemetamol +) were recruited in the study. A seed-to-voxel analysis was conducted to measure the LC and SN rsFC differences between sexes. In addition, sex by Aβ interactive effects on FC values were analyzed with a general linear model. There were statistically significant sex by regional standardized uptake value ratio (SUVR) interactions in the LC FC with the parietal, frontal, and occipital cortices. Moreover, there was a significant sex by global SUVR interaction in the SN FC with the temporal cortex. The findings suggest that there are differential patterns of LC FC and SN FC in males and females with preclinical AD, which interact with regional Aβ deposition. Full article