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Pérez-Millan A, Borrego-Écija S, Falgàs N, Juncà-Parella J, Bosch B, Tort-Merino A, Antonell A, Bargalló N, Rami L, Balasa M, Lladó A, Sala-Llonch R, Sánchez-Valle R. Cortical thickness modeling and variability in Alzheimer's disease and frontotemporal dementia. J Neurol 2024; 271:1428-1438. [PMID: 38012398 PMCID: PMC10896866 DOI: 10.1007/s00415-023-12087-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/29/2023] [Accepted: 10/31/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND AND OBJECTIVE Alzheimer's disease (AD) and frontotemporal dementia (FTD) show different patterns of cortical thickness (CTh) loss compared with healthy controls (HC), even though there is relevant heterogeneity between individuals suffering from each of these diseases. Thus, we developed CTh models to study individual variability in AD, FTD, and HC. METHODS We used the baseline CTh measures of 379 participants obtained from the structural MRI processed with FreeSurfer. A total of 169 AD patients (63 ± 9 years, 65 men), 88 FTD patients (64 ± 9 years, 43 men), and 122 HC (62 ± 10 years, 47 men) were studied. We fitted region-wise temporal models of CTh using Support Vector Regression. Then, we studied associations of individual deviations from the model with cerebrospinal fluid levels of neurofilament light chain (NfL) and 14-3-3 protein and Mini-Mental State Examination (MMSE). Furthermore, we used real longitudinal data from 144 participants to test model predictivity. RESULTS We defined CTh spatiotemporal models for each group with a reliable fit. Individual deviation correlated with MMSE for AD and with NfL for FTD. AD patients with higher deviations from the trend presented higher MMSE values. In FTD, lower NfL levels were associated with higher deviations from the CTh prediction. For AD and HC, we could predict longitudinal visits with the presented model trained with baseline data. For FTD, the longitudinal visits had more variability. CONCLUSION We highlight the value of CTh models for studying AD and FTD longitudinal changes and variability and their relationships with cognitive features and biomarkers.
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Affiliation(s)
- Agnès Pérez-Millan
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, 08036, Barcelona, Spain
- Department of Biomedicine, Faculty of Medicine, University of Barcelona, 08036, Barcelona, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
| | - Neus Falgàs
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
- Atlantic Fellow for Equity in Brain Health, Global Brain Health Institute, University of California San Francisco, San Francisco, 94143, USA
| | - Jordi Juncà-Parella
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
| | - Beatriz Bosch
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
| | - Adrià Tort-Merino
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
| | - Nuria Bargalló
- Image Diagnostic Centre, CIBER de Salud Mental, Instituto de Salud Carlos III, Magnetic Resonance Image Core Facility, IDIBAPS, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Lorena Rami
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
- Atlantic Fellow for Equity in Brain Health, Global Brain Health Institute, University of California San Francisco, San Francisco, 94143, USA
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, 08036, Barcelona, Spain
| | - Roser Sala-Llonch
- Institut de Neurociències, University of Barcelona, 08036, Barcelona, Spain
- Department of Biomedicine, Faculty of Medicine, University of Barcelona, 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 08036, Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit. Service of Neurology, Hospital Clínic de Barcelona. Fundació Recerca Clínic Barcelona-IDIBAPS, Villarroel, 170, 08036, Barcelona, Spain.
- Institut de Neurociències, University of Barcelona, 08036, Barcelona, Spain.
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, 08036, Barcelona, Spain.
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Hafiz R, Irfanoglu MO, Nayak A, Pierpaoli C. "Pscore": A Novel Percentile-Based Metric to Accurately Assess Individual Deviations in Non-Gaussian Distributions of Quantitative MRI Metrics. J Magn Reson Imaging 2024. [PMID: 38291798 DOI: 10.1002/jmri.29248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 01/08/2024] [Accepted: 01/09/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Quantitative magnetic resonance imaging (MRI) metrics could be used in personalized medicine to assess individuals against normative distributions. Conventional Zscore analysis is inadequate in the presence of non-Gaussian distributions. Therefore, if quantitative MRI metrics deviate from normality, an alternative is needed. PURPOSE To confirm non-Gaussianity of diffusion MRI (dMRI) metrics on a publicly available dataset, and to propose a novel percentile-based method, "Pscore" to address this issue. STUDY TYPE Retrospective cohort. POPULATION Nine hundred and sixty-one healthy young adults (age: 22-35 years, females: 53%) from the Human Connectome Project. FIELD STRENGTH/SEQUENCE 3-T, spin-echo diffusion echo-planar imaging, T1-weighted: MPRAGE. ASSESSMENT The dMRI data were preprocessed using the TORTOISE pipeline. Forty-eight regions of interest (ROIs) from the JHU atlas were redrawn on a study-specific diffusion tensor (DT) template and average values were computed from various DT and mean apparent propagator (MAP) metrics. For each ROI, percentile ranks across participants were computed to generate "Pscores"-which normalized the difference between the median and a participant's value with the corresponding difference between the median and the 5th/95th percentile values. STATISTICAL TESTS ROI-wise distributions were assessed using log transformations, Zscore, and the "Pscore" methods. The percentages of extreme values above-95th and below-5th percentile boundaries (PEV>95 (%), PEV<5 (%)) were also assessed in the overall white matter. Bootstrapping was performed to test the reliability of Pscores in small samples (N = 100) using 100 iterations. RESULTS The dMRI metric distributions were systematically non-Gaussian, including positively skewed (eg, mean and radial diffusivity) and negatively skewed (eg, fractional and propagator anisotropy) metrics. This resulted in unbalanced tails in Zscore distributions (PEV>95 ≠ 5%, PEV<5 ≠ 5%) whereas "Pscore" distributions were symmetric and balanced (PEV>95 = PEV<5 = 5%); even for small bootstrapped samples (averagePEV > 95 ¯ = PEV < 5 ¯ = 5 ± 0 % $$ \overline{{\mathrm{PEV}}_{>95}}=\overline{{\mathrm{PEV}}_{<5}}=5\pm 0\% $$ [SD]). DATA CONCLUSION The inherent skewness observed for dMRI metrics may preclude the use of conventional Zscore analysis. The proposed "Pscore" method may help estimating individual deviations more accurately in skewed normative data, even from small datasets. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Rakibul Hafiz
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, USA
| | - M Okan Irfanoglu
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, USA
| | - Amritha Nayak
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, USA
- Military Traumatic Brain Injury Initiative (MTBI2-formerly known as the Center for Neuroscience and Regenerative Medicine [CNRM]), Bethesda, Maryland, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, USA
| | - Carlo Pierpaoli
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, USA
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Hafiz R, Irfanoglu MO, Nayak A, Pierpaoli C. 'Pscore' - A Novel Percentile-Based Metric to Accurately Assess Individual Deviations in Non-Gaussian Distributions of Quantitative MRI Metrics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.10.571016. [PMID: 38105995 PMCID: PMC10723480 DOI: 10.1101/2023.12.10.571016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
BACKGROUND Quantitative MRI metrics could be used in personalized medicine to assess individuals against normative distributions. Conventional Zscore analysis is inadequate in the presence of non-Gaussian distributions. Therefore, if quantitative MRI metrics deviate from normality, an alternative is needed. PURPOSE To confirm non-Gaussianity of diffusion MRI (dMRI) metrics on a publicly available dataset, and to propose a novel percentile-based method, 'Pscore' to address this issue. STUDY TYPE Retrospective cohort. POPULATION 961 healthy young-adults (age:22-35 years, Females:53%) from the Human Connectome Project. FIELD STRENGTH/SEQUENCE 3-T, spin-echo diffusion echo-planar imaging, T1-weighted: MPRAGE. ASSESSMENT The dMRI data were preprocessed using the TORTOISE pipeline. Forty-eight regions of interest (ROIs) from the JHU-atlas were redrawn on a study-specific diffusion tensor (DT) template and average values were computed from various DT and mean apparent propagator (MAP) metrics. For each ROI, percentile ranks across participants were computed to generate 'Pscores'- which normalized the difference between the median and a participant's value with the corresponding difference between the median and the 5th/95th percentile values. STATISTICAL TESTS ROI-wise distributions were assessed using Log transformations, Zscore, and the 'Pscore' methods. The percentages of extreme values above-95th and below-5th percentile boundaries (PEV < 5 ( % ) ,PEV < 5 ( % ) ) were also assessed in the overall white matter. Bootstrapping was performed to test the reliability of Pscores in small samples (n=100) using 100 iterations. RESULTS The dMRI metric distributions were systematically non-Gaussian, including positively skewed (e.g., mean and radial distributions P E V > 95 ≠ 5 % , P E V < 5 ≠ 5 % whereas 'Pscore' distributions were symmetric and balanced P E V > 95 = P E V < 5 = 5 % ; even for small bootstrapped samples (average P E V > 95 ¯ = P E V < 5 ¯ = 5 ± 0 % S D ). DATA CONCLUSION The inherent skewness observed for dMRI metrics may preclude the use of conventional Zscore analysis. The proposed 'Pscore' method may help estimating individual deviations more accurately in skewed normative data, even from small datasets.
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Affiliation(s)
- Rakibul Hafiz
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD
| | - M. Okan Irfanoglu
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD
| | - Amritha Nayak
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD
- Military Traumatic Brain Injury Initiative (MTBI2 – formerly known as the Center for Neuroscience and Regenerative Medicine [CNRM]) Bethesda, MD
- The Henry Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Carlo Pierpaoli
- Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD
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Wang H, Chen Y, Wang L, Liu Q, Yang S, Wang C. Advancing herbal medicine: enhancing product quality and safety through robust quality control practices. Front Pharmacol 2023; 14:1265178. [PMID: 37818188 PMCID: PMC10561302 DOI: 10.3389/fphar.2023.1265178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 09/15/2023] [Indexed: 10/12/2023] Open
Abstract
This manuscript provides an in-depth review of the significance of quality control in herbal medication products, focusing on its role in maintaining efficiency and safety. With a historical foundation in traditional medicine systems, herbal remedies have gained widespread popularity as natural alternatives to conventional treatments. However, the increasing demand for these products necessitates stringent quality control measures to ensure consistency and safety. This comprehensive review explores the importance of quality control methods in monitoring various aspects of herbal product development, manufacturing, and distribution. Emphasizing the need for standardized processes, the manuscript delves into the detection and prevention of contaminants, the authentication of herbal ingredients, and the adherence to regulatory standards. Additionally, it highlights the integration of traditional knowledge and modern scientific approaches in achieving optimal quality control outcomes. By emphasizing the role of quality control in herbal medicine, this manuscript contributes to promoting consumer trust, safeguarding public health, and fostering the responsible use of herbal medication products.
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Affiliation(s)
- Hongting Wang
- Anhui Provincial Engineering Laboratory for Screening and Re-evaluation of Active Compounds of Herbal Medicines in Southern Anhui, Anhui Provincial Engineering Research Center for Polysaccharide Drugs, Anhui Innovative Center for Drug Basic Research of Metabolic Diseases, School of Pharmacy, Wannan Medical College, Wuhu, China
| | | | | | | | | | - Cunqin Wang
- Anhui Provincial Engineering Laboratory for Screening and Re-evaluation of Active Compounds of Herbal Medicines in Southern Anhui, Anhui Provincial Engineering Research Center for Polysaccharide Drugs, Anhui Innovative Center for Drug Basic Research of Metabolic Diseases, School of Pharmacy, Wannan Medical College, Wuhu, China
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