Nick A Weaver1, Hugo J Kuijf2, Hugo P Aben3, Jill Abrigo4, Hee-Joon Bae5, Mélanie Barbay6, Jonathan G Best7, Régis Bordet8, Francesca M Chappell9, Christopher P L H Chen10, Thibaut Dondaine8, Ruben S van der Giessen11, Olivier Godefroy6, Bibek Gyanwali10, Olivia K L Hamilton9, Saima Hilal12, Irene M C Huenges Wajer13, Yeonwook Kang14, L Jaap Kappelle1, Beom Joon Kim5, Sebastian Köhler15, Paul L M de Kort3, Peter J Koudstaal11, Gregory Kuchcinski8, Bonnie Y K Lam16, Byung-Chul Lee17, Keon-Joo Lee5, Jae-Sung Lim18, Renaud Lopes8, Stephen D J Makin19, Anne-Marie Mendyk8, Vincent C T Mok16, Mi Sun Oh17, Robert J van Oostenbrugge20, Martine Roussel6, Lin Shi21, Julie Staals20, Maria Del C Valdés-Hernández9, Narayanaswamy Venketasubramanian22, Frans R J Verhey15, Joanna M Wardlaw9, David J Werring7, Xu Xin10, Kyung-Ho Yu17, Martine J E van Zandvoort13, Lei Zhao23, J Matthijs Biesbroek1, Geert Jan Biessels24. 1. Department of Neurology and Neurosurgery, University Medical Centre (UMC) Utrecht Brain Center, Utrecht, Netherlands. 2. Image Sciences Institute, UMC Utrecht, Utrecht, Netherlands. 3. Department of Neurology, Elisabeth Tweesteden Hospital, Tilburg, Netherlands. 4. Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China. 5. Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, South Korea. 6. Department of Neurology, Amiens University Hospital, Laboratory of Functional Neurosciences, Jules Verne Picardy University, Amiens, France. 7. Stroke Research Centre, Department of Brain Repair and Rehabilitation, University College London Queen Square Institute of Neurology, London, UK. 8. Université Lille, Inserm, CHU Lille, U1172-LilNCog-Lille Neuroscience and Cognition, Lille, France. 9. Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK. 10. Department of Pharmacology, National University of Singapore, Singapore; Memory, Aging and Cognition Center, National University Health System, Singapore. 11. Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands. 12. Department of Pharmacology, National University of Singapore, Singapore; Memory, Aging and Cognition Center, National University Health System, Singapore; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore. 13. Department of Neurology and Neurosurgery, University Medical Centre (UMC) Utrecht Brain Center, Utrecht, Netherlands; Experimental Psychology, Helmholtz Institute, Utrecht University, Netherlands. 14. Department of Psychology, Hallym University, Chuncheon, South Korea. 15. Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands. 16. Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Therese Pei Fong Chow Research Centre for Prevention of Dementia, Margaret Kam Ling Cheung Research Centre for Management of Parkinsonism, Gerald Choa Neuroscience Centre, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China. 17. Department of Neurology, Hallym University Sacred Hospital, Hallym Neurological Institute, Hallym University College of Medicine, Anyang, South Korea. 18. Department of Neurology, Asan Medical Center, Seoul, South Korea. 19. Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK. 20. Department of Neurology, Maastricht University Medical Center, Maastricht, Netherlands. 21. Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; BrainNow Research Institute, Shenzhen, China. 22. Raffles Neuroscience Centre, Raffles Hospital, Singapore. 23. BrainNow Research Institute, Shenzhen, China. 24. Department of Neurology and Neurosurgery, University Medical Centre (UMC) Utrecht Brain Center, Utrecht, Netherlands. Electronic address: g.j.biessels@umcutrecht.nl.
Abstract
BACKGROUND: Post-stroke cognitive impairment (PSCI) occurs in approximately half of people in the first year after stroke. Infarct location is a potential determinant of PSCI, but a comprehensive map of strategic infarct locations predictive of PSCI is unavailable. We aimed to identify infarct locations most strongly predictive of PSCI after acute ischaemic stroke and use this information to develop a prediction model. METHODS: In this large-scale multicohort lesion-symptom mapping study, we pooled and harmonised individual patient data from 12 cohorts through the Meta-analyses on Strategic Lesion Locations for Vascular Cognitive Impairment using Lesion-Symptom Mapping (Meta VCI Map) consortium. The identified cohorts (as of Jan 1, 2019) comprised patients with acute symptomatic infarcts on CT or MRI (with available infarct segmentations) and a cognitive assessment up to 15 months after acute ischaemic stroke onset. PSCI was defined as performance lower than the fifth percentile of local normative data, on at least one cognitive domain on a multidomain neuropsychological assessment or on the Montreal Cognitive Assessment. Voxel-based lesion-symptom mapping (VLSM) was used to calculate voxel-wise odds ratios (ORs) for PSCI that were mapped onto a three-dimensional brain template to visualise PSCI risk per location. For the prediction model of PSCI risk, a location impact score on a 5-point scale was derived from the VLSM results on the basis of the mean voxel-wise coefficient (ln[OR]) within each patient's infarct. We did combined internal-external validation by leave-one-cohort-out cross-validation for all 12 cohorts using logistic regression. Predictive performance of a univariable model with only the location impact score was compared with a multivariable model with addition of other clinical PSCI predictors (age, sex, education, time interval between stroke onset and cognitive assessment, history of stroke, and total infarct volume). Testing of visual ratings was done by three clinicians, and accuracy, inter-rater reliability, and intra-rater reliability were assessed with Cohen's weighted kappa. FINDINGS: In our sample of 2950 patients (mean age 66·8 years [SD 11·6]; 1157 [39·2%] women), 1286 (43·6%) had PSCI. We achieved high lesion coverage of the brain in our analyses (86·9%). Infarcts in the left frontotemporal lobes, left thalamus, and right parietal lobe were strongly associated with PSCI (after false discovery rate correction, q<0·01; voxel-wise ORs >20). On cross-validation, the location impact score showed good correspondence, based on visual assessment of goodness of fit, between predicted and observed risk of PSCI across cohorts after adjusting for cohort-specific PSCI occurrence. Cross-validations showed that the location impact score by itself had similar performance to the combined model with other PSCI predictors, while allowing for easy visual assessment. Therefore the univariable model with only the location impact score was selected as the final model. Correspondence between visual ratings and actual location impact score (Cohen's weighted kappa: range 0·88-0·92), inter-rater agreement (0·85-0·87), and intra-rater agreement (for a single rater, 0·95) were all high. INTERPRETATION: To the best of our knowledge, this study provides the first comprehensive map of strategic infarct locations associated with risk of PSCI. A location impact score was derived from this map that robustly predicted PSCI across cohorts. Furthermore, we developed a quick and reliable visual rating scale that might in the future be applied by clinicians to identify individual patients at risk of PSCI. FUNDING: The Netherlands Organisation for Health Research and Development.
BACKGROUND: Post-stroke cognitive impairment (PSCI) occurs in approximately half of people in the first year after stroke. Infarct location is a potential determinant of PSCI, but a comprehensive map of strategic infarct locations predictive of PSCI is unavailable. We aimed to identify infarct locations most strongly predictive of PSCI after acute ischaemic stroke and use this information to develop a prediction model. METHODS: In this large-scale multicohort lesion-symptom mapping study, we pooled and harmonised individual patient data from 12 cohorts through the Meta-analyses on Strategic Lesion Locations for Vascular Cognitive Impairment using Lesion-Symptom Mapping (Meta VCI Map) consortium. The identified cohorts (as of Jan 1, 2019) comprised patients with acute symptomatic infarcts on CT or MRI (with available infarct segmentations) and a cognitive assessment up to 15 months after acute ischaemic stroke onset. PSCI was defined as performance lower than the fifth percentile of local normative data, on at least one cognitive domain on a multidomain neuropsychological assessment or on the Montreal Cognitive Assessment. Voxel-based lesion-symptom mapping (VLSM) was used to calculate voxel-wise odds ratios (ORs) for PSCI that were mapped onto a three-dimensional brain template to visualise PSCI risk per location. For the prediction model of PSCI risk, a location impact score on a 5-point scale was derived from the VLSM results on the basis of the mean voxel-wise coefficient (ln[OR]) within each patient's infarct. We did combined internal-external validation by leave-one-cohort-out cross-validation for all 12 cohorts using logistic regression. Predictive performance of a univariable model with only the location impact score was compared with a multivariable model with addition of other clinical PSCI predictors (age, sex, education, time interval between stroke onset and cognitive assessment, history of stroke, and total infarct volume). Testing of visual ratings was done by three clinicians, and accuracy, inter-rater reliability, and intra-rater reliability were assessed with Cohen's weighted kappa. FINDINGS: In our sample of 2950 patients (mean age 66·8 years [SD 11·6]; 1157 [39·2%] women), 1286 (43·6%) had PSCI. We achieved high lesion coverage of the brain in our analyses (86·9%). Infarcts in the left frontotemporal lobes, left thalamus, and right parietal lobe were strongly associated with PSCI (after false discovery rate correction, q<0·01; voxel-wise ORs >20). On cross-validation, the location impact score showed good correspondence, based on visual assessment of goodness of fit, between predicted and observed risk of PSCI across cohorts after adjusting for cohort-specific PSCI occurrence. Cross-validations showed that the location impact score by itself had similar performance to the combined model with other PSCI predictors, while allowing for easy visual assessment. Therefore the univariable model with only the location impact score was selected as the final model. Correspondence between visual ratings and actual location impact score (Cohen's weighted kappa: range 0·88-0·92), inter-rater agreement (0·85-0·87), and intra-rater agreement (for a single rater, 0·95) were all high. INTERPRETATION: To the best of our knowledge, this study provides the first comprehensive map of strategic infarct locations associated with risk of PSCI. A location impact score was derived from this map that robustly predicted PSCI across cohorts. Furthermore, we developed a quick and reliable visual rating scale that might in the future be applied by clinicians to identify individual patients at risk of PSCI. FUNDING: The Netherlands Organisation for Health Research and Development.
Authors: Terence J Quinn; Edo Richard; Yvonne Teuschl; Thomas Gattringer; Melanie Hafdi; John T O'Brien; Niamh Merriman; Celine Gillebert; Hanne Huyglier; Ana Verdelho; Reinhold Schmidt; Emma Ghaziani; Hysse Forchammer; Sarah T Pendlebury; Rose Bruffaerts; Milija Mijajlovic; Bogna A Drozdowska; Emily Ball; Hugh S Markus Journal: Eur Stroke J Date: 2021-10-08
Authors: John Y Rhee; Mia A Colman; Maanasa Mendu; Simran J Shah; Michael D Fox; Natalia S Rost; Eyal Y Kimchi Journal: J Stroke Cerebrovasc Dis Date: 2021-12-23 Impact factor: 2.136
Authors: Una Clancy; Stephen D J Makin; Caroline A McHutchison; Vera Cvoro; Francesca M Chappell; Maria Del C Valdés Hernández; Eleni Sakka; Fergus Doubal; Joanna M Wardlaw Journal: Neurology Date: 2022-02-07 Impact factor: 9.910
Authors: J Matthijs Biesbroek; Nick A Weaver; Hugo P Aben; Hugo J Kuijf; Jill Abrigo; Hee-Joon Bae; Mélanie Barbay; Jonathan G Best; Régis Bordet; Francesca M Chappell; Christopher P L H Chen; Thibaut Dondaine; Ruben S van der Giessen; Olivier Godefroy; Bibek Gyanwali; Olivia K L Hamilton; Saima Hilal; Irene M C Huenges Wajer; Yeonwook Kang; L Jaap Kappelle; Beom Joon Kim; Sebastian Köhler; Paul L M de Kort; Peter J Koudstaal; Gregory Kuchcinski; Bonnie Y K Lam; Byung-Chul Lee; Keon-Joo Lee; Jae-Sung Lim; Renaud Lopes; Stephen D J Makin; Anne-Marie Mendyk; Vincent C T Mok; Mi Sun Oh; Robert J van Oostenbrugge; Martine Roussel; Lin Shi; Julie Staals; Maria Del C Valdés-Hernández; Narayanaswamy Venketasubramanian; Frans R J Verhey; Joanna M Wardlaw; David J Werring; Xu Xin; Kyung-Ho Yu; Martine J E van Zandvoort; Lei Zhao; Geert Jan Biessels Journal: Neuroimage Clin Date: 2022-04-27 Impact factor: 4.891