Kantarci, Kejal

Abstract Background Dementia with Lewy Bodies (DLB) has been overlooked or misdiagnosed as Alzheimer's disease (AD) dementia due to its frequent concomitant AD pathology with Lewy Body Disease (LBD) pathology. Although autopsy confirmation has been the gold standard for the precise diagnosis of DLB, time‐course 123 I‐FP‐CIT SPECT (DaT‐SPECT) findings in autopsy‐confirmed DLB are not well characterized. We previously reported that the DaTQUANT z‐score of the more affected side of the putamen has the best discriminatory power in detecting LBD pathology and nigrostriatal degeneration in dementia patients and demonstrated z‐score of −1 as the cutoff value. We sought to examine how DaT‐SPECT findings change over time in autopsy confirmed LBD patients in preparation for its use in LBD targeted clinical trials. Method Eight autopsy confirmed neocortical or limbic LBD patients who underwent two or more DaT‐SPECT were included. Nigrostriatal dopamine transporter (DaT) binding and age‐adjusted z‐scores were analyzed using the DaTQUANT 2.0 software (GE Healthcare). Result Six patients (75%) were male. The patients had 2.5±0.7 longitudinal DaT‐SPECT scans. Clinical diagnosis at initial scan was: DLB (75%), mild cognitive impairment (MCI) with REM sleep behavior disorder (RBD) (13%), and isolated RBD (iRBD) (13%). Clinical diagnosis at last scan was: DLB (88%) and iRBD (12%). All patients developed dementia during life. Mean age at initial scan/last scan/autopsy were 71.1±7.0/73.4±6.9/75.1±7.3 years old. Time from initial and last scan to autopsy were 4.0±1.9 and 1.8±1.9 years respectively. Seven patients (88%) had neocortical LBD and one (12%) had limbic LBD. Concomitant AD pathology was observed in four patients (two males (33%), two females (100%)). All patients had DaTQUANT putamen z‐score <‐1.0 at their initial scan including in MCI+RBD (‐1.76) and iRBD (‐1.53) patients. In the DLB patients at their initial scans, five (83%) had DaTQUANT putamen z‐score <‐2.0 and one (17%) had z‐score of ‐1.55. All patients (100%) showed DaTQUANT putamen z‐score <‐2.0 at their last scans. Conclusion DaTQUANT using cut‐off putamen z‐score of ‐1 was associated with underlying LBD pathology including at their iRBD and MCI stages. Nigrostriatal DaT binding tends to decline over time with DaTQUANT z‐score <‐2 at their last scans.

Abstract Background A hexanucleotide repeat expansion in C9orf72 is the leading genetic cause of frontotemporal lobar degeneration and amyotrophic lateral sclerosis. There remains a critical need for biomarkers that track disease progression across clinical stages. Cross‐sectionally, intrinsic connectivity networks (ICNs) derived from task‐free fMRI (tf‐fMRI) detects abnormalities in C9orf72 expansion carriers ( C9orf72+ ), even when brain structural differences are subtle (Lee et al. , 2017). Few studies have examined longitudinal connectivity changes in C9orf72+ , however. Methods We analyzed longitudinal structural and tf‐fMRI data and plasma neurofilament light chain (NfL) concentrations of C9orf72+ recruited from UCSF and the ALLFTD Consortia. Mean time from first to last scan was 2.4±1.3 years. Participants included 36 asymptomatic (aSx‐ C9 ), 17 prodromal (prodromal‐ C9 ), 29 symptomatic (Sx‐ C9 ) carriers, and 107 healthy controls (HC). For structural MRI analyses, smoothed gray matter maps were parcellated into 246 regions‐of‐interest based on the Brainnetome atlas. We conducted voxelwise seed‐based tf‐fMRI analyses to examine ICNs showing alterations C9orf72+ based on previous literature: salience network (SN), sensorimotor network (SMN), default mode network (DMN), and a medial pulvinar thalamus network (pulvinar). General linear models and linear mixed models (LMM) compared C9orf72+ groups to HC in baseline and longitudinal gray matter and functional connectivity, as well as examined associations between longitudinal functional connectivity changes and baseline NfL concentrations. Results Despite a lack of longitudinal gray matter decline, aSx‐ and Sx‐ C9orf72+ showed functional connectivity changes. Compared to HC, aSx‐ C9 had baseline hypoconnectivity in the SN, SMN, and pulvinar network. Longitudinally, this group showed declines in the SN and pulvinar network, alongside DMN increases. Prodromal‐ C9 exhibited baseline SMN hypoconnectivity and hyperconnectivity in the DMN and pulvinar network, but no significant longitudinal changes. Sx‐ C9 showed baseline hypoconnectivity in SN, SMN, and DMN, with additional regions of DMN hyperconnectivity, while longitudinally, SN and SMN connectivity increased. In aSx‐ C9 , higher baseline NfL concentrations correlated with regions of SMN decreases over time and both increases and decreases in the pulvinar network. In prodromal‐ C9 and Sx‐ C9 combined, higher NfL was associated with DMN increases longitudinally. Conclusions Though gray matter declines were undetectable over a span of several years, functional connectivity networks changed dynamically in C9orf72+ .

Abstract Background Neuroinflammation plays a crucial role in neuronal damage, synaptic dysfunction, and impaired neurogenesis, significantly contributing to Alzheimer's Disease (AD) progression. To address this, we assessed ER176's effectiveness in detecting neuroinflammation in cognitively unimpaired (CU) A–, CU A+, mild cognitive impairment (MCI), and AD participants, with a particular focus on their amyloid and tau status. This research aims to help identify suitable candidates for specialized treatment when adversely impacted by neuroinflammation. Method Participants from the Mayo Clinic Study of Aging were recruited for this study. The study included four participant groups: CU A– ( n = 25), CU A+ ( n = 25), MCI A+ ( n = 25), and AD ( n = 15). We explored the variations in neuroinflammation PET results among different groups. Result When compared to CU A–, both CU A+ and MCI A+ groups (Figure 1) showed greater regional neuroinflammation. AD exhibited more widely affected regions with neuroinflammation (temporal, occipital, and parietal lobes) than CU A‐ over the PVC spectrum (Figure 1). Minimally more neuroinflammation was seen (temporal lobes) in MCI A+ than CU A+ (Figure 1). AD had more widespread regional neuroinflammation vs CU A+ (Figure 1) than in MCI A+ vs CU+. The least difference in neuroinflammation is seen in MCI A+ vs AD (Figure 1). For A+ vs A‐, A+ showed more widespread neuroinflammation (Figure 2). T+ (tau>=1.29) vs T‐ (tau<1.29) showed more neuro inflammation with T+ (Figure 2). Comparisons varied modestly in significance level with PVC method (Figures 1 and 2). Conclusion The findings demonstrate that neuroinflammatory changes are associated with AD pathology. Even at early stages, neuroinflammation is associated with CU+. As the condition progresses, neuroinflammation extends to more brain regions and is associated with increased A+ and T+ pathology in MCI A+ and AD. These results suggest an early and persistent role of neuroinflammation in the progression AD pathology, indicating that therapy options could include early anti‐inflammatory intervention, even prior to clinical symptoms, along with treatment during clinical manifestations. PVC methods used may provide somewhat variable results.

Abstract Background Neuroimaging data typically arrives as Digital Imaging and Communications in Medicine (DICOM) files, batched by exam. We use exam or study to denote a single imaging session of a participant, containing up to ∼40 series (the generic term for scans and derived products). Different series have different properties and applications, making their labeling complex. Filenames often change in transit, and Series Description tags (0008, 103E) are arbitrary, operator‐entered, and unreliably coupled to the series type. Furthermore, label preferences vary from site to site, making the application of a common classification system mandatory for multisite studies. Here we describe the system that we have developed and applied to the Alzheimer's Disease Neuroimaging Initiative (ADNI) and SCAN. Method Although Series Description is unreliable, DICOM includes other tags that parameterize MR pulse sequences and suggest their purpose. The mapping from these features to types is difficult to explicitly specify, especially since different manufacturers and protocols use different conventions. Thus we developed a machine learning classifier using 4060 semiautomatically labeled head and spinal series from 1.5 to 7T MR scanners, including both site‐specific and standard protocols designed to study a wide range of neurological conditions, including dementia, hydrocephalus, and multiple sclerosis. An 80%/20% split, stratified by type, was used for the training/test sets. After initial training, a few cases in the training set with high errors due to rarity were augmented and the model retrained. Performance was evaluated on the clean test set. Result The taxonomy is presented in Table 1. The classifier correctly identified 807 out of 812 (99.4%) series, with the error cases coming from outside the ADNI or SCAN protocols (Table 2). The confusion matrix is shown in Figure 1. Conclusion We implemented an automatic series type classifier with labels chosen to be generally useful for the brain MRI community. Some errors were noted, but the test set was deliberately challenging and the errors appear to be ones that could easily be made by a human. The classifier is expected to have good tolerance for as yet unseen head MR protocols but is likely unsatisfactory for body MRI.

Abstract Background The Overlap Index (OI) as previously published (Lee et al., 2022) is a reliable method for detecting tau accumulation using tau‐PET imaging (flortaucipir; AV1451). It identifies voxel‐wise standardized uptake value ratio (SUVr) elevations across serial scans. Although OI showed more sensitivity to tau signal elevation and longitudinal change than standard ROI measures, to our knowledge, the relationship of the tau PET overlap index to neuropathologic findings is still unclear. This study aims to investigate the potential of OI to detect NFTs of the neuropathologic Braak tangle stage, especially the early Braak tangle stage (I–IV). Method This study included 57 participants from the Mayo Clinic Study of Aging or Mayo Alzheimer's Disease Research Center, all of whom underwent autopsy and at least two serial AV1451 tau‐PET scans and 3T T1‐weighted MRI within an average of 16 months. Tau‐PET SUVr images were normalized to cerebellar crus grey matter, and MR images were co‐registered to a single‐subject MRI mean. Tau‐PET scans were resampled into MRI space, and OI was calculated by applying intensity thresholds 1.3. Clusters with fewer than 20 contiguous voxels were excluded. An OI cutoff of 0.5 was used and an SUVr cutoff of 1.29. Postmortem immunohistochemistry (IHC) using phospho‐tau antibodies (AT8, PHF‐1) was performed on the amygdala, temporal cortex (middle and superior), and anterior/posterior hippocampus. Neuropathological Braak staging was determined based on AT8‐stained sections. We conducted visual comparison of tau‐PET overlap signal in these regions with IHC‐confirmed tau pathology across Braak tangle stages. Result OI‐detected voxels corresponded to NFT distribution across Braak stages. In early Braak stages, standard SUVr‐based META‐ROI values remained negative, whereas OI showed positive signals, indicating greater sensitivity to early tau pathology (Figure 1). The spatial distribution of OI‐derived overlap regions aligned with high NFT burden, suggesting that OI captures early‐stage tau pathology more effectively than conventional SUVr methods. Conclusion OI in serial tau‐PET imaging demonstrated better detection of early‐stage tau pathology than standard ROI‐based SUVr measures. The alignment between OI‐detected voxels and neuropathological tau burden supports its potential as an in vivo biomarker for detecting early neurofibrillary tangles.

Abstract Background T2*‐weighted imaging is of paramount importance for patient treatment eligibility and safety monitoring in anti‐amyloid pharmaceutical clinical trials and clinical care. Recently with the adoption of multi‐echo GRE (GRE) sequences, susceptibility weighted imaging (SWI), and quantitative susceptibility mapping (QSM) can be obtained in the same acquisition. In 2024, the QSM Consensus Organization Committee released a white paper recommending at least 1 mm isotropic voxel size for QSM. In clinical workflows microbleed detection is performed with higher in‐plane resolution (0.5x0.5mm 2 ), and large out‐of‐plane resolution (∼1.8mm), which was used in the ADNI4 protocol. In the CLARiTI protocol, a 1mm isotropic resolution was adopted. The objective of this work was to compare susceptibility estimates between the ADNI4 (0.5x0.5x1.8mm 3 ) and CLARiTI (1mm 3 ) protocols. Method The ADNI4 and CLARiTI QSM protocols were acquired on forty‐seven subjects (33 cognitively unimpaired (CU), 14 cognitively impaired (CI), in the same scan session. The groups were defined by their Clinical Demential Rating (CDR) global score (CDR global = 0 for CU, and CDR global >= 0.5 for CI subjects). QSM images were generated using publically available software (STI Suite, UC Berkeley). Mean susceptibility values in atlas regions were compared. Result Significant group differences (CU vs. CI) were observed in the fusiform and middle occipital gyrus with the ADNI4 protocol, only in the rectus with the CLARiTI protocol (Figure 1). These three regions are small in size and closer to surface‐air interfaces, which may have impacted estimation accuracy. However, in the substantia nigra and its sub‐regions (pars compacta and pars reticulata), which shows increased susceptibility in Lewy body disease, the ADNI4 and CLARiTI protocols were in good agreement (r 2 > 0.9) (Figure 2). Conclusion Group differences were observed between the ADNI4 and CLARiTI QSM only in 3 small regions close to surface‐air interfaces in this small dataset. The two techniques showed highly correlated (r 2 = 0.93) estimates in the substantia nigra, a region with high susceptibility due to iron deposition. Strong correlations between the two protocols are encouraging. Radiologists have historically preferred submillimeter in‐plane resolution for microbleed detection, which is more time manageable with anisotropic imaging.

Abstract Background Immunohistochemically detected phosphorylated α‐synuclein (p‐α‐syn) in cutaneous nerves has been found in >95% of patients meeting consensus criteria for dementia with Lewy bodies (DLB); however, its performance in prodromal stages (mild cognitive impairment‐Lewy body [MCI‐LB]) and clinical practice is unknown. Objective We evaluated skin biopsy for p‐α‐syn in a convenience cohort of patients with suspected MCI‐LB or DLB in a tertiary care setting. Methods 53 patients underwent commercially available skin biopsy for skin nerve p‐α‐syn as part of a clinical evaluation for suspected MCI‐LB/DLB. Consensus MCI‐LB/DLB criteria blinded to skin biopsy result were applied through retrospective chart review; those not definitively meeting criteria were considered questionable synucleinopathy (QS). Results Median age at skin biopsy was 70 years (range, 43–87 years) with 81% men. 36 patients (68%) had positive skin biopsies. 32/43 (74%) patients meeting clinical consensus criteria for DLB/MCI‐LB had a positive skin biopsy, with higher frequency in MCI‐LB (87%) compared with DLB (60%). 4/10 (40%) QS had positive biopsies. One patient with a positive skin biopsy had no evidence of central nervous system (CNS) α‐syn on autopsy. Conclusions Positive skin biopsy for p‐α‐syn occurs across the spectrum of cognitive presentations of Lewy body disease including prodromal DLB, albeit at a lower frequency in this retrospective review of atypical cases compared with typical clinical presentations. A positive skin biopsy may not reflect CNS synucleinopathy as the etiology for a patient's symptoms in some cases. Longitudinal studies of skin biopsies for p‐α‐syn in suspected MCI‐LB/DLB with autopsy confirmation are needed. © 2025 International Parkinson and Movement Disorder Society.

Abstract Background White matter (WM) plays a dual role in interacting with tau pathology. There is an intricate dynamic relationship with WM acting as highways for tau spreading, while the increasing tau burden ultimately compromises WM health. We aimed at studying the associations between tau accumulation and WM integrity using longitudinal data with focus on sex differences. Method We included 374 participants who had longitudinal multishell diffusion MRI and flortaucipir PET (baseline mean age = 70.9 years, 52% male, 17% MCI/AD dementia) scans from the Mayo ADRC and Mayo Clinic Study of Aging. Rate of tau accumulation was calculated from the entorhinal cortex (ERC) and inferior temporal cortex (IT) SUVRs, with IT‐WM serving as the WM highway between the two regions. IT‐WM was defined by JHU “Eve” WM atlas, and its integrity was assessed using neurite density index (NDI), which reflects the packing density of neurites. Structural equation modeling (SEM) evaluated relationships between tau and WM metrics. Result At baseline, males and females showed no significant differences in tau SUVR or IT‐WM NDI ( p >0.05), though males had higher vascular risk and averaged two years older than females (Table 1). Figure 1a showed that baseline ERC‐tau influenced baseline IT‐tau, as well as both rate of ERC‐tau and baseline IT‐tau influenced rate of IT‐tau. After incorporating IT‐WM NDI as a mediator (Figure 1b), we discovered 1) baseline ERC‐tau influencing rate of IT‐tau accumulation through baseline IT‐WM NDI, suggesting the role of WM health in the rate of tau accumulation; 2) Rate of IT‐tau accumulation negatively affected follow‐up IT‐WM NDI suggesting the deterioration of WM health as tau accumulation progresses. These relationships were stronger in males compared to females. We also observed greater impact of vascular risk on WM health in males and greater rates of IT‐tau accumulation in females. Conclusion Our work sheds light on the mechanistic role of intact WM in tau accumulation (through dense microtubules and synaptic connections) and the deterioration of WM that is associated with higher rates of tau accumulation. We found interesting sex differences that warrant further investigation.

Abstract Background Agitation is a clinically significant symptom contributing to behavioral and psychological symptoms of dementia (BPSD) but is poorly understood across the different syndromes related to Frontotemporal Lobar Degeneration (FTLD). This study investigates sex differences in agitation across FTLD‐related syndromes and its relationship to various neuropsychiatric symptoms (NPS). Method We analyzed data from 1,654 participants (916 males, 738 females; average ages 65.8 and 65.9, respectively) from the National Alzheimer's Coordinating Center (NACC) and ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study with a FTLD‐related syndrome: behavioral variant FTD (bvFTD), Primary Progressive Aphasia (non‐fluent variant (nfvPPA), semantic variant (svPPA)), Corticobasal syndrome (CBS) and Progressive Supranuclear Palsy (PSP). Participants’ symptoms were assessed using the Neuropsychiatric Inventory (NPI). Prevalence ratios and odds ratios were computed to assess the likelihood of NPS comorbidities when agitation was present in males and females. Principal Component Analysis (PCA) was performed to identify NPS associated with agitation and how they varied by sex. Result Males were more likely to experience anxiety (bvFTD: p <0.001, CBS: p <0.01, PSP: p <0.0001), apathy (nfvPPA: p <0.01, PSP: p <0.01), depression (bvFTD: p <0.0001, PSP<0.01), disinhibition (nfvPPA: p <0.0001), PSP: p <0.001), and motor symptoms (bvFTD: p <0.01, CBS: p <0.01) when agitation was present. In contrast, females had a higher likelihood of experiencing disinhibition in svPPA ( p <0.001). These findings suggest that agitation is associated with a wider range of NPS in males than in females. Agitation and NPS are especially prominent in males with PSP. Conclusion This study reveals significant sex differences in NPS in FTLD‐related syndromes when agitation is present. Males and especially PSP, are more likely to experience a broader range of NPS in association with agitation. These findings underscore the need for further investigation into the underlying mechanisms driving these sex differences, particularly focusing on the neurobiological impact of agitation, the recognition of symptoms in the presence of greater behavioral disturbances, and potential variations from informant reports. Understanding these factors will provide valuable insights into the role of agitation in the presentation of NPS across FTLD‐related syndromes. Ultimately, addressing these gaps will enhance our ability to effectively treat and manage agitation in both male and female patients with FTLD‐related syndromes.

Abstract Background Diffusion MRI (dMRI) measures are increasingly being used as biomarkers for aging and dementia in multi‐center studies. Measurements in longitudinal studies are often acquired on different systems, which can result in systematic differences of machine origin (e.g. vendor, hardware, algorithms). This may warrant harmonization prior to pooling multi‐site data. However, harmonization algorithms may introduce a risk of removing valuable information content and reducing sensitivity to physiological factors (e.g. sex, age, disease). Here, we tested the hypothesis that protocol standardization may minimize machine‐origin differences, obviating a need for post‐acquisition harmonization in a two‐site (Mississippi‐MS and Minnesota‐MN) cohort of the longitudinal Mayo Clinic Study of Aging (MCSA). Methods Two data sets were analyzed: first, a crossover dataset with 80 participants (scanned within 2 days) bridging two different protocols on GE and Siemens scanners; second, participants scanned using standardized protocols from the ongoing MCSA ( N MN‐MCSA =204; N MS‐MCSA =52). Parameters are listed in Figure 1. For crossover data, analyses were repeated with GE data resampled to 2‐mm isotropic resolution, and discarding Siemens‐only b‐shells to artificially reduce protocol disparities. Analysis encompassed visualization of overlain subjectwise histogram‐derived densities obtained from whole‐brain masks for dMRI measures; and median dMRI measures from within the genu of the corpus callosum (GCC) with nonparametric statistical testing. When available, both DTI and NODDI measures were compared. Results Pronounced visual distributional differences seen between MD and FA in crossover data were reduced with resampling of GE data and including only b‐shells shared across acquisitions. For the resampled/reshelled data, significant differences remained for all GCC‐FA comparisons, but not all GCC‐MD (Figure 2). For the ongoing MCSA data from two sites, MD and FA whole‐brain densities were more closely aligned, with GCC‐FA and GCC‐MD showing no significant differences (Figure 3). NODDI measures showed more discordant densities than DTI measures, including shifts in most probable values and differences in distributional arrangement. Conclusions Our work provides further evidence supporting protocol and processing standardization for minimizing machine‐origin differences prior to considering harmonization. Differences in dMRI metrics seen when comparing across unstandardized protocols were reduced when protocols were standardized. NODDI metrics had more apparent sensitivity to site than DTI measures.