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Reyes A, Hermann BP, Prabhakaran D, Ferguson L, Almane DN, Shih JJ, Iragui‐Madoz VJ, Struck A, Punia V, Jones JE, Busch RM, McDonald CR. Validity of the MoCA as a cognitive screening tool in epilepsy: Are there implications for global care and research? Epilepsia Open 2024; 9:1526-1537. [PMID: 38874380 PMCID: PMC11296095 DOI: 10.1002/epi4.12991] [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: 03/25/2024] [Revised: 05/06/2024] [Accepted: 05/28/2024] [Indexed: 06/15/2024] Open
Abstract
OBJECTIVE This study evaluated the diagnostic performance of a widely available cognitive screener, the Montreal cognitive assessment (MoCA), to detect cognitive impairment in older patients (age ≥ 55) with epilepsy residing in the US, using the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) as the gold standard. METHODS Fifty older adults with focal epilepsy completed the MoCA and neuropsychological measures of memory, language, executive function, and processing speed/attention. The IC-CoDE taxonomy divided participants into IC-CoDE Impaired and Intact groups. Sensitivity and specificity across several MoCA cutoffs were examined. Spearman correlations examined relationships between the MoCA total score and clinical and demographic variables and MoCA domain scores and individual neuropsychological tests. RESULTS IC-CoDE impaired patients demonstrated significantly lower scores on the MoCA total, visuospatial/executive, naming, language, delayed recall, and orientation domain scores (Cohen's d range: 0.336-2.77). The recommended MoCA cutoff score < 26 had an overall accuracy of 72%, 88.2% sensitivity, and 63.6% specificity. A MoCA cutoff score < 24 yielded optimal sensitivity (70.6%) and specificity (78.8%), with overall accuracy of 76%. Higher MoCA total scores were associated with greater years of education (p = 0.016) and fewer antiseizure medications (p = 0.049). The MoCA memory domain was associated with several standardized measures of memory, MoCA language domain with category fluency, and MoCA abstraction domain with letter fluency. SIGNIFICANCE This study provides initial validation of the MoCA as a useful screening tool for older adults with epilepsy that can be used to identify patients who may benefit from comprehensive neuropsychological testing. Further, we demonstrate that a lower cutoff (i.e., <24) better captures cognitive impairment in older adults with epilepsy than the generally recommended cutoff and provides evidence for construct overlap between MoCA domains and standard neuropsychological tests. Critically, similar efforts in other regions of the world are needed. PLAIN LANGUAGE SUMMARY The Montreal cognitive assessment (MoCA) can be a helpful tool to screen for cognitive impairment in older adults with epilepsy. We recommend that adults 55 or older with epilepsy who score less than 24 on the MoCA are referred to a neuropsychologist for a comprehensive evaluation to assess any changes in cognitive abilities and mood.
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Affiliation(s)
- Anny Reyes
- Department of Radiation Medicine & Applied SciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Bruce P. Hermann
- Department of NeurologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Divya Prabhakaran
- Department of Radiation Medicine & Applied SciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Lisa Ferguson
- Epilepsy CenterNeurological Institute, Cleveland ClinicClevelandOhioUSA
| | - Dace N. Almane
- Department of NeurologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Jerry J. Shih
- Department of NeuroscienceUniversity of CaliforniaSan DiegoCaliforniaUSA
| | | | - Aaron Struck
- Department of NeurologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Vineet Punia
- Epilepsy CenterNeurological Institute, Cleveland ClinicClevelandOhioUSA
- Department of NeurologyCleveland ClinicClevelandOhioUSA
| | - Jana E. Jones
- Department of NeurologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Robyn M. Busch
- Epilepsy CenterNeurological Institute, Cleveland ClinicClevelandOhioUSA
- Department of NeurologyCleveland ClinicClevelandOhioUSA
| | - Carrie R. McDonald
- Department of Radiation Medicine & Applied SciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
- Department of PsychiatryUniversity of CaliforniaSan DiegoCaliforniaUSA
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Yang M, Zhang Y, Zhang T, Zhou H, Ren J, Zhou D, Yang T. Altered dynamic functional connectivity of motor cerebellum with sensorimotor network and default mode network in juvenile myoclonic epilepsy. Front Neurol 2024; 15:1373125. [PMID: 38903166 PMCID: PMC11187336 DOI: 10.3389/fneur.2024.1373125] [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: 01/19/2024] [Accepted: 05/21/2024] [Indexed: 06/22/2024] Open
Abstract
Objective To investigate whether changes occur in the dynamic functional connectivity (dFC) of motor cerebellum with cerebral cortex in juvenile myoclonic epilepsy (JME). Methods We adopted resting-state electroencephalography-functional magnetic resonance imaging (EEG-fMRI) and a sliding-window approach to explore the dFC of motor cerebellum with cortex in 36 JME patients compared with 30 and age-matched health controls (HCs). The motor cerebellum was divided into five lobules (I-V, VI, VIIb, VIIIa, and VIIIb). Additionally, correlation analyses were conducted between the variability of dFC and clinical variables in the Juvenile Myoclonic Epilepsy (JME) group, such as disease duration, age at disease onset, and frequency score of myoclonic seizures. Results Compared to HCs, the JME group presented increased dFC between the motor cerebellum with SMN and DMN. Specifically, connectivity between lobule VIIb and left precentral gyrus and right inferior parietal lobule (IPL); between lobule VIIIa and right inferior frontal gyrus (IFG) and left IPL; and between lobule VIIIb and left middle frontal gyrus (MFG), bilateral superior parietal gyrus (SPG), and left precuneus. In addition, within the JME group, the strength of dFC between lobule VIIIb and left precuneus was negatively (r = -0.424, p = 0.025, Bonferroni correction) related with the frequency score of myoclonic seizures. Conclusion In patients with JME, there is a functional dysregulation between the motor cerebellum with DMN and SMN, and the variability of dynamic functional connectivity may be closely associated with the occurrence of motor symptoms in JME.
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Affiliation(s)
- Menghan Yang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yingying Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Tianyu Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Huanyu Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiechuan Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Tianhua Yang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Pertichetti M, Corbo D, Belotti F, Saviola F, Gasparotti R, Fontanella MM, Panciani PP. Neuropsychological Evaluation and Functional Magnetic Resonance Imaging Tasks in the Preoperative Assessment of Patients with Brain Tumors: A Systematic Review. Brain Sci 2023; 13:1380. [PMID: 37891749 PMCID: PMC10605177 DOI: 10.3390/brainsci13101380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 09/19/2023] [Accepted: 09/25/2023] [Indexed: 10/29/2023] Open
Abstract
BACKGROUND Current surgical treatment of gliomas relies on a function-preserving, maximally safe resection approach. Functional Magnetic Resonance Imaging (fMRI) is a widely employed technology for this purpose. A preoperative neuropsychological evaluation should accompany this exam. However, only a few studies have reported both neuropsychological tests and fMRI tasks for preoperative planning-the current study aimed to systematically review the scientific literature on the topic. METHODS PRISMA guidelines were followed. We included studies that reported both neuropsychological tests and fMRI. Exclusion criteria were: no brain tumors, underage patients, no preoperative assessment, resting-state fMRI only, or healthy sample population/preclinical studies. RESULTS We identified 123 papers, but only 15 articles were included. Eight articles focused on language; three evaluated cognitive performance; single papers studied sensorimotor cortex, prefrontal functions, insular cortex, and cerebellar activation. Two qualitative studies focused on visuomotor function and language. According to some authors, there was a strong correlation between performance in presurgical neuropsychological tests and fMRI. Several papers suggested that selecting well-adjusted and individualized neuropsychological tasks may enable the development of personalized and more efficient protocols. The fMRI findings may also help identify plasticity phenomena to avoid unintentional damage during neurosurgery. CONCLUSIONS Most studies have focused on language, the most commonly evaluated cognitive function. The correlation between neuropsychological and fMRI results suggests that altered functions during the neuropsychological assessment may help identify patients who could benefit from an fMRI and, possibly, functions that should be tested. Neuropsychological evaluation and fMRI have complementary roles in the preoperative assessment.
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Affiliation(s)
- Marta Pertichetti
- Neurosurgery Unit, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia and ASST Spedali Civili Hospital, 25123 Brescia, Italy (M.M.F.); (P.P.P.)
| | - Daniele Corbo
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, 25123 Brescia, Italy; (D.C.); (F.S.); (R.G.)
| | - Francesco Belotti
- Neurosurgery Unit, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia and ASST Spedali Civili Hospital, 25123 Brescia, Italy (M.M.F.); (P.P.P.)
| | - Francesca Saviola
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, 25123 Brescia, Italy; (D.C.); (F.S.); (R.G.)
| | - Roberto Gasparotti
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, 25123 Brescia, Italy; (D.C.); (F.S.); (R.G.)
- Neuroradiology Unit, ASST Spedali Civili of Brescia, 25123 Brescia, Italy
| | - Marco Maria Fontanella
- Neurosurgery Unit, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia and ASST Spedali Civili Hospital, 25123 Brescia, Italy (M.M.F.); (P.P.P.)
| | - Pier Paolo Panciani
- Neurosurgery Unit, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia and ASST Spedali Civili Hospital, 25123 Brescia, Italy (M.M.F.); (P.P.P.)
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Brain Tumor at Diagnosis: From Cognition and Behavior to Quality of Life. Diagnostics (Basel) 2023; 13:diagnostics13030541. [PMID: 36766646 PMCID: PMC9914203 DOI: 10.3390/diagnostics13030541] [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: 01/12/2023] [Revised: 01/30/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND The present narrative review aims to discuss cognitive-emotional-behavioral symptoms in adults with brain tumors at the time of diagnosis. METHODS The PubMed database was searched considering glioma, pituitary adenoma, and meningioma in adulthood as pathologies, together with cognitive, neuropsychological, or behavioral aspects. RESULTS Although a significant number of studies describe cognitive impairment after surgery or treatment in adults with brain tumors, only few focus on cognitive-emotional-behavioral symptoms at diagnosis. Furthermore, the importance of an effective communication and its impact on patients' quality of life and compliance with treatment are seldom discussed. CONCLUSIONS Adults with brain tumors have needs in terms of cognitive-emotional-behavioral features that are detectable at the time of diagnosis; more research is needed to identify effective communication protocols in order to allow a higher perceived quality of life in these patients.
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Liu Y, McAfee SS, Van Der Heijden ME, Dhamala M, Sillitoe RV, Heck DH. Causal Evidence for a Role of Cerebellar Lobulus Simplex in Prefrontal-Hippocampal Interaction in Spatial Working Memory Decision-Making. CEREBELLUM (LONDON, ENGLAND) 2022; 21:762-775. [PMID: 35218525 PMCID: PMC10230449 DOI: 10.1007/s12311-022-01383-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/14/2022] [Indexed: 11/27/2022]
Abstract
Spatial working memory (SWM) is a cerebrocerebellar cognitive skill supporting survival-relevant behaviors, such as optimizing foraging behavior by remembering recent routes and visited sites. It is known that SWM decision-making in rodents requires the medial prefrontal cortex (mPFC) and dorsal hippocampus. The decision process in SWM tasks carries a specific electrophysiological signature of a brief, decision-related increase in neuronal communication in the form of an increase in the coherence of neuronal theta oscillations (4-12 Hz) between the mPFC and dorsal hippocampus, a finding we replicated here during spontaneous exploration of a plus maze in freely moving mice. We further evaluated SWM decision-related coherence changes within frequency bands above theta. Decision-related coherence increases occurred in seven frequency bands between 4 and 200 Hz and decision-outcome-related differences in coherence modulation occurred within the beta and gamma frequency bands and in higher frequency oscillations up to 130 Hz. With recent evidence that Purkinje cells in the cerebellar lobulus simplex (LS) represent information about the phase and phase differences of gamma oscillations in the mPFC and dorsal hippocampus, we hypothesized that LS might be involved in the modulation of mPFC-hippocampal gamma coherence. We show that optical stimulation of LS significantly impairs SWM performance and decision-related mPFC-dCA1 coherence modulation, providing causal evidence for an involvement of cerebellar LS in SWM decision-making at the behavioral and neuronal level. Our findings suggest that the cerebellum might contribute to SWM decision-making by optimizing the decision-related modulation of mPFC-dCA1 coherence.
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Affiliation(s)
- Yu Liu
- Department of Anatomy and Neurobiology, University of Tennessee HSC, Memphis, TN, USA
| | - Samuel S McAfee
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Meike E Van Der Heijden
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute of Texas Children's Hospital, Houston, TX, USA
| | - Mukesh Dhamala
- Department of Physics and Astronomy, Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - Roy V Sillitoe
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute of Texas Children's Hospital, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Development, Disease Models & Therapeutics Graduate Program, Baylor College of Medicine, Houston, TX, USA
| | - Detlef H Heck
- Department of Anatomy and Neurobiology, University of Tennessee HSC, Memphis, TN, USA.
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Novak A, Vizjak K, Gacnik A, Rakusa M. Cognitive impairment in people with epilepsy: Montreal Cognitive Assessment (MoCA) as a screening tool. Acta Neurol Belg 2022; 123:451-456. [PMID: 35925540 DOI: 10.1007/s13760-022-02046-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 07/19/2022] [Indexed: 12/01/2022]
Abstract
OBJECTIVES Although cognitive impairment is common in people with epilepsy, it is often neglected in outpatient clinics. MoCA is a simple and reliable test, which was validated for the cognitive screening of Alzheimer's and vascular dementia. The aim of our study was to evaluate MoCA as a tool for a cognitive screening of people with epilepsy. METHODS Our study included 50 people with epilepsy and 46 healthy individuals. All participants took the Slovenian version of the MoCA. Mean age, education and MoCA scores were compared between the two groups. RESULTS There was no significant difference between people with epilepsy and the controls in age (47.6, SD 18.1 vs 50.9, SD 14.0 years) or education (12.8, SD 2.8 vs 13.4, SD 2.8 years). People with epilepsy had significantly lower total MoCA scores than did the controls (23.3, SD 4.5 vs 27.5, SD 1.9 points; p < 0.001). CONCLUSIONS People with epilepsy achieved a lower score in several cognitive domains compared to the control group. MoCA can be used as an appropriate screening tool for cognitive impairment in people with epilepsy in the outpatient clinic. For a more accurate evaluation, neuropsychological assessments should be used.
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Affiliation(s)
- Ajda Novak
- Divison of Neurology, University Medical Centre Maribor, Maribor, Slovenia
| | - Karmen Vizjak
- Divison of Neurology, University Medical Centre Maribor, Maribor, Slovenia
| | - Albin Gacnik
- Divison of Neurology, University Medical Centre Maribor, Maribor, Slovenia
| | - Martin Rakusa
- Divison of Neurology, University Medical Centre Maribor, Maribor, Slovenia.
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7
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Cognitive deficits in adult patients with high-grade glioma: A systematic review. Clin Neurol Neurosurg 2022; 219:107296. [DOI: 10.1016/j.clineuro.2022.107296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 04/04/2022] [Accepted: 05/13/2022] [Indexed: 11/15/2022]
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Ng YS, Lax NZ, Blain AP, Erskine D, Baker MR, Polvikoski T, Thomas RH, Morris CM, Lai M, Whittaker RG, Gebbels A, Winder A, Hall J, Feeney C, Farrugia ME, Hirst C, Roberts M, Lawthom C, Chrysostomou A, Murphy K, Baird T, Maddison P, Duncan C, Poulton J, Nesbitt V, Hanna MG, Pitceathly RDS, Taylor RW, Blakely EL, Schaefer AM, Turnbull DM, McFarland R, Gorman GS. Forecasting stroke-like episodes and outcomes in mitochondrial disease. Brain 2022; 145:542-554. [PMID: 34927673 PMCID: PMC9014738 DOI: 10.1093/brain/awab353] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 07/16/2021] [Accepted: 08/06/2021] [Indexed: 12/03/2022] Open
Abstract
In this retrospective, multicentre, observational cohort study, we sought to determine the clinical, radiological, EEG, genetics and neuropathological characteristics of mitochondrial stroke-like episodes and to identify associated risk predictors. Between January 1998 and June 2018, we identified 111 patients with genetically determined mitochondrial disease who developed stroke-like episodes. Post-mortem cases of mitochondrial disease (n = 26) were identified from Newcastle Brain Tissue Resource. The primary outcome was to interrogate the clinico-radiopathological correlates and prognostic indicators of stroke-like episode in patients with mitochondrial encephalomyopathy, lactic acidosis and stroke-like episodes syndrome (MELAS). The secondary objective was to develop a multivariable prediction model to forecast stroke-like episode risk. The most common genetic cause of stroke-like episodes was the m.3243A>G variant in MT-TL1 (n = 66), followed by recessive pathogenic POLG variants (n = 22), and 11 other rarer pathogenic mitochondrial DNA variants (n = 23). The age of first stroke-like episode was available for 105 patients [mean (SD) age: 31.8 (16.1)]; a total of 35 patients (32%) presented with their first stroke-like episode ≥40 years of age. The median interval (interquartile range) between first and second stroke-like episodes was 1.33 (2.86) years; 43% of patients developed recurrent stroke-like episodes within 12 months. Clinico-radiological, electrophysiological and neuropathological findings of stroke-like episodes were consistent with the hallmarks of medically refractory epilepsy. Patients with POLG-related stroke-like episodes demonstrated more fulminant disease trajectories than cases of m.3243A>G and other mitochondrial DNA pathogenic variants, in terms of the frequency of refractory status epilepticus, rapidity of progression and overall mortality. In multivariate analysis, baseline factors of body mass index, age-adjusted blood m.3243A>G heteroplasmy, sensorineural hearing loss and serum lactate were significantly associated with risk of stroke-like episodes in patients with the m.3243A>G variant. These factors informed the development of a prediction model to assess the risk of developing stroke-like episodes that demonstrated good overall discrimination (area under the curve = 0.87, 95% CI 0.82-0.93; c-statistic = 0.89). Significant radiological and pathological features of neurodegeneration were more evident in patients harbouring pathogenic mtDNA variants compared with POLG: brain atrophy on cranial MRI (90% versus 44%, P < 0.001) and reduced mean brain weight (SD) [1044 g (148) versus 1304 g (142), P = 0.005]. Our findings highlight the often idiosyncratic clinical, radiological and EEG characteristics of mitochondrial stroke-like episodes. Early recognition of seizures and aggressive instigation of treatment may help circumvent or slow neuronal loss and abate increasing disease burden. The risk-prediction model for the m.3243A>G variant can help inform more tailored genetic counselling and prognostication in routine clinical practice.
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Affiliation(s)
- Yi Shiau Ng
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
- Department of Neurosciences, NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne NE2 4HH, UK
| | - Nichola Z Lax
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Alasdair P Blain
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Daniel Erskine
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Mark R Baker
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
- Campus for Ageing and Vitality, Newcastle Brain Tissue Resource, Newcastle University, Edwardson Building, Newcastle upon Tyne NE4 5PL, UK
| | - Tuomo Polvikoski
- Campus for Ageing and Vitality, Newcastle Brain Tissue Resource, Newcastle University, Edwardson Building, Newcastle upon Tyne NE4 5PL, UK
| | - Rhys H Thomas
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
- Department of Neurosciences, NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne NE2 4HH, UK
| | - Christopher M Morris
- Campus for Ageing and Vitality, Newcastle Brain Tissue Resource, Newcastle University, Edwardson Building, Newcastle upon Tyne NE4 5PL, UK
| | - Ming Lai
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
| | - Roger G Whittaker
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Alasdair Gebbels
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
| | - Amy Winder
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
| | - Julie Hall
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
| | - Catherine Feeney
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
- Department of Neurosciences, NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne NE2 4HH, UK
| | - Maria Elena Farrugia
- Institute of Neurological Sciences, Queen Elizabeth University Hospital, Glasgow G51 4TF, UK
| | - Claire Hirst
- Trust Headquarters, One Talbot Gateway, Baglan Energy Park, Baglan, Port Talbot SA12 7BR, UK
| | - Mark Roberts
- Greater Manchester Neuroscience Centre, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford M6 8HD, UK
| | - Charlotte Lawthom
- Aneurin Bevan Epilepsy Specialist Team, Aneurin Bevan University Health Board, Newport, NP20 2UB, UK
| | - Alexia Chrysostomou
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Kevin Murphy
- Department of Neurology, Sligo University Hospital, Sligo F91 H684, Ireland
| | - Tracey Baird
- Institute of Neurological Sciences, Queen Elizabeth University Hospital, Glasgow G51 4TF, UK
| | - Paul Maddison
- Department of Neurology, Queen’s Medical Centre, Nottingham NG7 2UH, UK
| | - Callum Duncan
- Department of Neurology, Aberdeen Royal Infirmary, NHS Grampian, Aberdeen AB25 2ZN, UK
| | - Joanna Poulton
- Nuffield Department of Women’s and Reproductive Health, University of Oxford, Oxford OX3 9DU, UK
| | - Victoria Nesbitt
- Department of Paediatrics, Medical Sciences Division, Oxford University, Oxford OX3 9DU, UK
- Department of Paediatrics, The Children's Hospital, Oxford, OX3 9DU, UK
| | - Michael G Hanna
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Robert D S Pitceathly
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Robert W Taylor
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
- Department of Neurosciences, NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne NE2 4HH, UK
| | - Emma L Blakely
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
- Department of Neurosciences, NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne NE2 4HH, UK
| | - Andrew M Schaefer
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
- Department of Neurosciences, NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne NE2 4HH, UK
| | - Doug M Turnbull
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
- Department of Neurosciences, NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne NE2 4HH, UK
| | - Robert McFarland
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
- Department of Neurosciences, NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne NE2 4HH, UK
| | - Gráinne S Gorman
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute; NIHR Newcastle Biomedical Research Centre and Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
- Directorate of Neurosciences, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
- Department of Neurosciences, NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne NE2 4HH, UK
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Fuzzy C-Means Algorithm-Based ARM-Linux-Embedded System Combined with Magnetic Resonance Imaging for Progression Prediction of Brain Tumors. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:4224749. [PMID: 35341006 PMCID: PMC8941506 DOI: 10.1155/2022/4224749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 02/20/2022] [Accepted: 02/22/2022] [Indexed: 11/30/2022]
Abstract
The aim of this research was to analyze the application of fuzzy C-means (FCM) algorithm-based ARM-Linux-embedded system in magnetic resonance imaging (MRI) images for prediction of brain tumors. The optimized FCM (OFCM) algorithm was proposed based on kernel function, and the ARM-Linux-embedded imaging system was designed under ARM9 chip and Linux recorder, which were applied in MRI images of brain tumor patients. It was found that the sensitivity, specificity, and accuracy of the OFCM algorithm (90.46%, 88.97%, and 97.46%) were greater obviously than those of the deterministic C-means clustering algorithm (80.38%, 77.98%, and 85.24%) and the traditional FCM algorithm (83.26%, 79.56%, and 86.45%), and the difference was statistically substantial (P < 0.05). The ME and running time of the OFCM algorithm decreased sharply in contrast to those of the deterministic C-means clustering algorithm and the traditional FCM algorithm (P < 0.05). There were great differences in fraction anisotropy (FA) and mean diffusion (MD) of tumor parenchymal area, surrounding edema area, and normal white matter area (P < 0.05). FA of stage III+IV was smaller than those of stage I and II (P < 0.05), while the apparent diffusion coefficient (ADC) of stage III+IV was greater than that of stage I and II (P < 0.05). In conclusion, the poor update data processing and low data clustering efficiency of FCM were solved by OFCM. Moreover, computational efficiency of ARM-Linux-embedded imaging system was improved, so as to better realize the prediction of brain tumor patients through ARM-Linux-embedded system based on adaptive FCM incremental clustering algorithm.
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Wang C, Van Dyk K, Cho N, Raymond C, Choi J, Salamon N, Pope WB, Lai A, Cloughesy TF, Nghiemphu PL, Ellingson BM. Characterization of cognitive function in survivors of diffuse gliomas using resting-state functional MRI (rs-fMRI). Brain Imaging Behav 2021; 16:239-251. [PMID: 34350525 PMCID: PMC8825610 DOI: 10.1007/s11682-021-00497-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/05/2021] [Indexed: 11/29/2022]
Abstract
As treatments for diffuse gliomas have advanced, survival for patients with gliomas has also increased. However, there remains limited knowledge on the relationships between brain connectivity and the lasting changes to cognitive function that glioma survivors often experience long after completing treatment. This resting-state functional magnetic resonance imaging (rs-fMRI) study explored functional connectivity (FC) alterations associated with cognitive function in survivors of gliomas. In this pilot study, 22 patients (mean age 43.8 ± 11.9) with diffuse gliomas who completed treatment within the past 10 years were evaluated using rs-fMRI and neuropsychological measures. Novel rs-fMRI analysis methods were used to account for missing brain in the resection cavity. FC relationships were assessed between cognitively impaired and non-impaired glioma patients, along with self-reported cognitive impairment, non-work daily functioning, and time with surgery. In the cognitively non-impaired patients, FC was stronger in the medial prefrontal cortex, rostral prefrontal cortex, and intraparietal sulcus compared to the impaired survivors. When examining non-work daily functioning, a positive correlation with FC was observed between the accumbens and the intracalcarine cortices, while a negative correlation with FC was observed between the parietal operculum cortex and the cerebellum. Additionally, worse self-reported cognitive impairment and worse non-work daily functioning were associated with increased FC between regions involved in cognition and sensorimotor processing. These preliminary findings suggest that neural correlates for cognitive and daily functioning in glioma patients can be revealed using rs-fMRI. Resting-state network alterations may serve as a biomarker for patients’ cognition and functioning.
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Affiliation(s)
- Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Kathleen Van Dyk
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, Semel Institute, University of California Los Angeles, Los Angeles, CA, USA
| | - Nicholas Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Justin Choi
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Albert Lai
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Phioanh L Nghiemphu
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA. .,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. .,Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, Semel Institute, University of California Los Angeles, Los Angeles, CA, USA.
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Cao S, Nie J, Zhang J, Chen C, Wang X, Liu Y, Mo Y, Du B, Hu Y, Tian Y, Wei Q, Wang K. The Cerebellum Is Related to Cognitive Dysfunction in White Matter Hyperintensities. Front Aging Neurosci 2021; 13:670463. [PMID: 34248601 PMCID: PMC8261068 DOI: 10.3389/fnagi.2021.670463] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 05/03/2021] [Indexed: 11/13/2022] Open
Abstract
Objective White matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) is frequently presumed to be secondary to cerebral small vessel disease (CSVD) and associated with cognitive decline. The cerebellum plays a key role in cognition and has dense connections with other brain regions. Thus, the aim of this study was to investigate if cerebellar abnormalities could occur in CSVD patients with WMHs and the possible association with cognitive performances. Methods A total of 104 right-handed patients with WMHs were divided into the mild WMHs group (n = 39), moderate WMHs group (n = 37), and severe WMHs group (n = 28) according to the Fazekas scale, and 36 healthy controls were matched for sex ratio, age, education years, and acquired resting-state functional MRI. Analysis of voxel-based morphometry of gray matter volume (GMV) and seed-to-whole-brain functional connectivity (FC) was performed from the perspective of the cerebellum, and their correlations with neuropsychological variables were explored. Results The analysis revealed a lower GMV in the bilateral cerebellum lobule VI and decreased FC between the left- and right-sided cerebellar lobule VI with the left anterior cingulate gyri in CSVD patients with WMHs. Both changes in structure and function were correlated with cognitive impairment in patients with WMHs. Conclusion Our study revealed damaged GMV and FC in the cerebellum associated with cognitive impairment. This indicates that the cerebellum may play a key role in the modulation of cognitive function in CSVD patients with WMHs.
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Affiliation(s)
- Shanshan Cao
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Jiajia Nie
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Jun Zhang
- Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Chen Chen
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Xiaojing Wang
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Yuanyuan Liu
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Yuting Mo
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Baogen Du
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Yajuan Hu
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Yanghua Tian
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
| | - Qiang Wei
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Kai Wang
- The School of Mental Health and Psychological Sciences, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
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Shi J, Liu B. Stage detection of mild cognitive impairment via fMRI using Hilbert Huang transform based classification framework. Med Phys 2020; 47:2902-2915. [PMID: 32302413 DOI: 10.1002/mp.14183] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 03/27/2020] [Accepted: 04/06/2020] [Indexed: 02/03/2023] Open
Abstract
PURPOSE This work aims to establish a classification framework for the diagnosis of mild cognitive impairment (MCI) at different stages (early MCI and late MCI) through direct analysis of resting-state functional magnetic resonance imaging (rs-fMRI) signals and using the accuracy (total correct rate), specificity (correct rate of late MCI) and sensitivity (correct rate of early MCI) to validate its classification performance. METHODS All fMR images of subjects were parcellated into 116 regions of interest (ROIs) by applying the Anatomical Automatic Labeling (AAL) template, and the average rs-fMRI signals of each ROI were extracted. The Hilbert-Huang transform (HHT) was introduced into the framework to decompose each rs-fMRI signal into a series of intrinsic mode functions (IMFs) and to analyze these nonstationary and nonlinear time-series from the perspective of multiresolution. After obtaining the instantaneous frequencies and amplitudes of all IMFs of a signal, the Hilbert weighted frequencies (HWFs) were calculated and combined into a vector as the feature of the corresponding ROI. Support Vector Machine (SVM) was implemented to classify MCI at different stages. We used the independent two-sample t-test as the feature selection method and measured the classification performance through the leave-one-out cross-validation (LOOCV) method. RESULTS Results on 77 early MCI (eMCI) and 64 late MCI (lMCI) with baseline rs-fMRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) yielded 87.94% classification accuracy. Some of the brain regions with significant differences found by previous studies have been confirmed in this work. We found that HWF characteristics exhibited a significant downward trend in all cerebellar regions. The rs-fMRI signals in differential brain regions have not changed completely, but only altered in some narrow frequency bands. The analysis results showed that during the progress of MCI, the main changes of rs-fMRI were concentrated in IMF3, while IMFs with other indexes also contained HWF features with high SVM weights, such as Orbitofrontal superior frontal gyrus in IMF2, Insula in IMF4, and Lobule Ⅲ of vermis in IMF5, indicating that other IMFs provide important information for the diagnosis of MCI as well. CONCLUSIONS This work confirmed the classification ability of HHT-based classification framework in classification of at different stages of MCI. Through the analysis, we found that during the progress of MCI the main changes of rs-fMRI were concentrated in IMF3, and HWF characteristics showed a significant downward trend in all cerebellar regions.
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Affiliation(s)
- Jiahao Shi
- College of Intelligence and Computing, Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjin, 300350, P. R. China
| | - Baolin Liu
- School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, P. R. China
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