Classifying Alzheimer's disease and frontotemporal dementia using machine learning with cross-sectional and longitudinal magnetic resonance imaging data

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are common causes of dementia with partly overlapping, symptoms and brain signatures. There is a need to establish an accurate diagnosis and to obtain markers for disease tracking. We combined unsupervised and supervised machine learning to discriminate between AD and FTD using brain magnetic resonance imaging (MRI). We included baseline 3T-T1 MRI data from 339 subjects: 99 healthy controls (CTR), 153 AD and 87 FTD patients; and 2-year follow-up data from 114 subjects. We obtained subcortical gray matter volumes and cortical thickness measures using FreeSurfer. We used dimensionality reduction to obtain a single feature that was later used in a support vector machine for classification. Discrimination patterns were obtained with the contribution of each region to the single feature. Our algorithm differentiated CTR versus AD and CTR versus FTD at the cross-sectional level with 83.3% and 82.1% of accuracy. These increased up to 90.0% and 88.0% with longitudinal data. When we studied the classification between AD versus FTD we obtained an accuracy of 63.3% at the cross-sectional level and 75.0% for longitudinal data. The AD versus FTD versus CTR classification has reached an accuracy of 60.7%, and 71.3% for cross-sectional and longitudinal data respectively. Disease discrimination brain maps are in concordance with previous results obtained with classical approaches. By using a single feature, we were capable to classify CTR, AD, and FTD with good accuracy, considering the inherent overlap between diseases. Importantly, the algorithm can be used with cross-sectional and longitudinal data.© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC

Influence of personality profile in patients with drug-resistant epilepsy on quality of life following surgical treatment : A 1-year follow-up study

Acord transformatiu CRUE-CSICThe objectives of this study are to determine the influence of personality profile in patients with drug-resistant epilepsy on quality of life (QoL) after surgical treatment and compare the results with a non-surgical control group at the 1-year follow-up. We conducted a prospective, comparative, controlled study, including 70 patients suffering from drug-resistant epilepsy. Demographic, psychiatric, neurological, and psychological data were recorded at the baseline and at the 1-year follow-up. Assessment of personality dimensions was performed using the NEO-FFI-R questionnaire; severity of anxiety and depression were assessed by the Hospital Anxiety and Depression Scale (HADS), and QoL was evaluated using the QOLIE-31. At the 1-year follow-up, comparing the control and the surgical groups, we detected differences in scores of most items of QoL, which were higher in those patients who had undergone surgery. High levels of Conscientiousness and Openness to experience at the baseline in patients who underwent surgery predicted better post-surgical outcomes in the QoL scores, whereas high neurotic patients showed worse QoL results. Postoperative changes in QoL in patients were associated with the personality profile at the baseline. QoL measures significantly improved in the surgical group compared with the non-surgical group but were not associated with baseline or postoperative seizure frequency at 1 year

Firewood and hearths: Middle Palaeolithic woody taxa distribution from El Salt, stratigraphic unit Xb (Eastern Iberia)

Spatial analyses of Palaeolithic sites typically defined by hearth-related assemblages have been mostly based on lithic and faunal remains. By using spatial analysis methods in conjunction with analytical units with higher temporal resolution than typical stratigraphic units, synchronic and diachronic relationships between artifacts deposited during successive occupation events have been elucidated. Spatial analyses applied to archaeobotanical remains are scarce, and when available, are typically focused on carpological remains (seeds and fruits). The lack of spatial indicators among anthracological remains hampers obtaining significant data linked to the relationships established between the combustion features and scattered charcoal fragments recovered from excavated occupation surfaces. To address this problem, the charcoal assemblage from El Salt Stratigraphic Unit (SU) Xb (Archaeosedimentary Facies Association 2 [AFA 2]) is analyzed using spatial analysis methods. Results suggest that the integration of anthracological remains into a palimpsest dissection analyses is vital to better understand the relationship between combustion structures and activity areas. These results highlight the utility of spatial and statistical methods as important tools for future anthracological analyses to provide meaningful information related to taxa distribution and the last firewood used in combustion structures

Structural and functional magnetic resonance imaging in isolated REM sleep behavior disorder: A systematic review of studies using neuroimaging software.

Isolated rapid eye movement sleep behavior disorder (iRBD) is a harbinger for developing clinical synucleinopathies. Magnetic resonance imaging (MRI) has been suggested as a tool for understanding the brain bases of iRBD and its evolution. This review systematically analyzed original full text articles on structural and functional MRI in patients with video-polysomnography-confirmed iRBD according to systematic procedures suggested by Reviews and Meta-analyses (PRISMA). The literature search was conducted via the PubMed database for articles related to structural and functional MRI in iRBD from 2000 to 2020. Investigations to date have been diverse in terms of methodology, but most agree that patients with iRBD have structural changes in deep gray matter nuclei, cortical gray matter atrophy, and disrupted functional connectivity within the basal ganglia, the cortico-striatal and cortico-cortical networks. Furthermore, there is evidence that MRI detects structural and functional brain changes associated with the motor and non-motor symptoms of iRBD. The current review highlights the need for larger multicenter and longitudinal studies, using complex approaches based on data-driven and unsupervised machine learning that will help to identify structural and functional patterns of brain degeneration. In turn, this may even allow for the prediction of subsequent phenoconversion from iRBD to the clinically defined synucleinopathie

Differences in breast cancer risk after benign breast disease by type of screening diagnosis

Neoplàsies de mama; Detecció precoç del càncer; Factors de riscNeoplasias de mama; Detección precoz del cáncer; Factores de riesgoBreast neoplasms; Early cancer detection; Risk factorsIntroduction: We aimed to assess differences in breast cancer risk across benign breast disease diagnosed at prevalent or incident screens. Materials and methods: We conducted a retrospective cohort study with data from 629,087 women participating in a long-standing population-based breast cancer screening program in Spain. Each benign breast disease was classified as non-proliferative, proliferative without atypia, or roliferative with atypia, and whether it was diagnosed in a prevalent or incident screen. We used partly conditional Cox hazard regression to estimate the adjusted hazard ratios of the risk of breast cancer. Results: Compared with women without benign breast disease, the risk of breast cancer was significantly higher (p-value ¼ 0.005) in women with benign breast disease diagnosed in an incident screen (aHR, 2.67; 95%CI: 2.24e3.19) than in those with benign breast disease diagnosed in a prevalent screen (aHR, 1.87; 95%CI: 1.57e2.24). The highest risk was found in women with a proliferative benign breast disease with atypia (aHR, 4.35; 95%CI: 2.09e9.08, and 3.35; 95%CI: 1.51e7.40 for those diagnosed at incident and prevalent screens, respectively), while the lowest was found in women with non-proliferative benign breast disease (aHR, 2.39; 95%CI: 1.95e2.93, and 1.63; 95%CI: 1.32e2.02 for those diagnosed at incident and prevalent screens, respectively). Conclusion: Our study showed that the risk of breast cancer conferred by a benign breast disease differed according to type of screen (prevalent or incident). To our knowledge, this is the first study to analyse the impact of the screening type on benign breast disease prognosisThis study was supported by grants from Instituto de Salud Carlos III FEDER (grant numbers: PI15/00098 and PI17/00047), and by the Research Network on Health Services in Chronic Diseases (RD12/0001/0015

Assessing the Reliability of Ultrasound Imaging to Examine Radial Nerve Excursion

AbstractUltrasound imaging allows cost effective in vivo analysis for quantifying peripheral nerve excursion. This study used ultrasound imaging to quantify longitudinal radial nerve excursion during various active and passive wrist movements in healthy participants. Frame-by-frame cross-correlation software allowed calculation of nerve excursion from video sequences. The reliability of ultrasound measurement of longitudinal radial nerve excursion was moderate to high (intraclass correlation coefficient range = 0.63–0.86, standard error of measurement 0.19–0.48). Radial nerve excursion ranged from 0.41 to 4.03 mm induced by wrist flexion and 0.28 to 2.91 mm induced by wrist ulnar deviation. No significant difference was seen in radial nerve excursion during either wrist movement (p > 0.05). Wrist movements performed in forearm supination produced larger overall nerve excursion (1.41 ± 0.32 mm) compared with those performed in forearm pronation (1.06 ± 0.31 mm) (p < 0.01). Real-time ultrasound is a reliable, cost-effective, in vivo method for analysis of radial nerve excursion

Multivariate consistency of resting-state fMRI connectivity maps acquired on a single individual over 2.5 years, 13 sites and 3 vendors

Studies using resting-state functional magnetic resonance imaging (rsfMRI) are increasingly collecting data at multiple sites in order to speed up recruitment or increase sample size. The main objective of this study was to assess the long-term consistency of rsfMRI connectivity maps derived at multiple sites and vendors using the Canadian Dementia Imaging Protocol (CDIP, www.cdip-pcid.ca). Nine to 10 min of functional BOLD images were acquired from an adult cognitively healthy volunteer scanned repeatedly at 13 Canadian sites on three scanner makes (General Electric, Philips and Siemens) over the course of 2.5 years. The consistency (spatial Pearson’s correlation) of rsfMRI connectivity maps for seven canonical networks ranged from 0.3 to 0.8, with a negligible effect of time, but significant site and vendor effects. We noted systematic differences in data quality (i.e. head motion, number of useable time frames, temporal signal-to-noise ratio) across vendors, which may also confound some of these results, and could not be disentangled in this sample. We also pooled the long-term longitudinal data with a single-site, short-term (1 month) data sample acquired on 26 subjects (10 scans per subject), called HNU1. Using randomly selected pairs of scans from each subject, we quantified the ability of a data-driven unsupervised cluster analysis to match two scans of the same subjects. In this “fingerprinting” experiment, we found that scans from the Canadian subject (Csub) could be matched with high accuracy intra-site (>95% for some networks), but that the accuracy decreased substantially for scans drawn from different sites and vendors, even falling outside of the range of accuracies observed in HNU1. Overall, our results demonstrate good multivariate stability of rsfMRI measures over several years, but substantial impact of scanning site and vendors. How detrimental these effects are will depend on the application, yet our results demonstrate that new methods for harmonizing multisite analysis represent an important area for future work