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Lauksio I, Wallenius L, Lindström I, Kärkkäinen JM, Khan N, Hernesniemi J, Protto S, Oksala NKJ. Multivariable Analysis of Pre-operative Brain Atrophy as a Predictor of Long Term Mortality After Carotid Endarterectomy. Eur J Vasc Endovasc Surg 2023; 65:339-345. [PMID: 36209966 DOI: 10.1016/j.ejvs.2022.10.001] [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: 10/13/2021] [Revised: 09/04/2022] [Accepted: 10/02/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Brain atrophy is associated with an increased mortality rate in elderly trauma patients and in patients treated with mechanical thrombectomy for acute ischaemic stroke. In the setting of ischaemic stroke, the association between brain atrophy and death is stronger than that of sarcopenia. It has previously been shown that lower masseter area, as a marker of sarcopenia, is linked to lower survival after carotid endarterectomy (CEA). The aim of this study was to investigate whether brain atrophy is also associated with long term mortality in patients undergoing CEA. METHODS A cohort of patients treated with CEA between 2004 and 2010 was retrieved from the Tampere University Hospital vascular registry and those with available pre-operative computed tomography (CT) imaging were analysed retrospectively. CT images were evaluated for brain atrophy index (BAI) and masseter muscle surface area and density. The association between BAI and mortality was investigated with Cox regression. RESULTS Two hundred and thirty-three patients with a median (interquartile range [IQR]) age of 71 years (64.0, 77.0) were included. Most patients were operated on for symptomatic stenosis (n = 203; 87.1%). The median (IQR) duration of follow up was 115.0 months (66.0, 153.0), and 155 patients (66.5%) died during follow up. BAI was statistically significantly correlated with age (r = .489), average masseter density (r = -.202), and smoking (r = -.186; all p <.005). Increased BAI was statistically significantly associated with overall mortality (hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.25 - 1.68, per one standard deviation [SD] increase) in the univariable analysis, and the association remained (HR 1.23, 95% CI 1.04 - 1.46, per one SD increase) in the multivariable models. Age, peripheral artery disease, and chronic obstructive pulmonary disease were also independently associated with mortality. The optimal cutoff value for BAI was 0.133. CONCLUSION Brain atrophy independently predicts the long term post-operative mortality rate after CEA in a cohort containing mainly symptomatic patients. Future studies are needed to validate the results in prospective settings and in asymptomatic patients.
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Affiliation(s)
- Iisa Lauksio
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
| | - Linda Wallenius
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Iisa Lindström
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | | | - Niina Khan
- Vascular Centre, Tampere University Hospital, Tampere, Finland
| | - Jussi Hernesniemi
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Department of Cardiology, Tampere University Hospital, Heart Hospital, Tampere, Finland; Finnish Cardiovascular Research Center, Tampere, Finland
| | - Sara Protto
- Vascular Centre, Tampere University Hospital, Tampere, Finland
| | - Niku K J Oksala
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Vascular Centre, Tampere University Hospital, Tampere, Finland; Finnish Cardiovascular Research Center, Tampere, Finland
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Pitkänen J, Koikkalainen J, Nieminen T, Marinkovic I, Curtze S, Sibolt G, Jokinen H, Rueckert D, Barkhof F, Schmidt R, Pantoni L, Scheltens P, Wahlund LO, Korvenoja A, Lötjönen J, Erkinjuntti T, Melkas S. Evaluating severity of white matter lesions from computed tomography images with convolutional neural network. Neuroradiology 2020; 62:1257-1263. [PMID: 32281028 PMCID: PMC7478948 DOI: 10.1007/s00234-020-02410-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 03/24/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE Severity of white matter lesion (WML) is typically evaluated on magnetic resonance images (MRI), yet the more accessible, faster, and less expensive method is computed tomography (CT). Our objective was to study whether WML can be automatically segmented from CT images using a convolutional neural network (CNN). The second aim was to compare CT segmentation with MRI segmentation. METHODS The brain images from the Helsinki University Hospital clinical image archive were systematically screened to make CT-MRI image pairs. Selection criteria for the study were that both CT and MRI images were acquired within 6 weeks. In total, 147 image pairs were included. We used CNN to segment WML from CT images. Training and testing of CNN for CT was performed using 10-fold cross-validation, and the segmentation results were compared with the corresponding segmentations from MRI. RESULTS A Pearson correlation of 0.94 was obtained between the automatic WML volumes of MRI and CT segmentations. The average Dice similarity index validating the overlap between CT and FLAIR segmentations was 0.68 for the Fazekas 3 group. CONCLUSION CNN-based segmentation of CT images may provide a means to evaluate the severity of WML and establish a link between CT WML patterns and the current standard MRI-based visual rating scale.
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Affiliation(s)
- Johanna Pitkänen
- Department of Neurology, University of Helsinki and Helsinki University Hospital, PO Box 302, 00029 HUS, Helsinki, Finland.
| | - Juha Koikkalainen
- Combinostics Ltd., Tampere, Finland and VTT Technical Research Centre of Finland, Tampere, Finland
| | - Tuomas Nieminen
- Combinostics Ltd., Tampere, Finland and VTT Technical Research Centre of Finland, Tampere, Finland
| | - Ivan Marinkovic
- Department of Neurology, University of Helsinki and Helsinki University Hospital, PO Box 302, 00029 HUS, Helsinki, Finland
| | - Sami Curtze
- Department of Neurology, University of Helsinki and Helsinki University Hospital, PO Box 302, 00029 HUS, Helsinki, Finland
| | - Gerli Sibolt
- Department of Neurology, University of Helsinki and Helsinki University Hospital, PO Box 302, 00029 HUS, Helsinki, Finland
| | - Hanna Jokinen
- Department of Neurology, University of Helsinki and Helsinki University Hospital, PO Box 302, 00029 HUS, Helsinki, Finland
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
- Institutes of Neurology and Healthcare Engineering, University College London, London, UK
- NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust and University College London, London, England, UK
| | - Reinhold Schmidt
- Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, Netherlands
| | - Leonardo Pantoni
- L. Sacco Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, Netherlands
| | - Lars-Olof Wahlund
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Antti Korvenoja
- HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Jyrki Lötjönen
- Combinostics Ltd., Tampere, Finland and VTT Technical Research Centre of Finland, Tampere, Finland
| | - Timo Erkinjuntti
- Department of Neurology, University of Helsinki and Helsinki University Hospital, PO Box 302, 00029 HUS, Helsinki, Finland
| | - Susanna Melkas
- Department of Neurology, University of Helsinki and Helsinki University Hospital, PO Box 302, 00029 HUS, Helsinki, Finland
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Timmerman N, Rots ML, van Koeverden ID, Haitjema S, van Laarhoven CJHCM, Vuurens AM, den Ruijter HM, Pasterkamp G, Kappelle LJ, de Kleijn DPV, de Borst GJ. Cerebral Small Vessel Disease in Standard Pre-operative Imaging Reports Is Independently Associated with Increased Risk of Cardiovascular Death Following Carotid Endarterectomy. Eur J Vasc Endovasc Surg 2020; 59:872-880. [PMID: 32331995 DOI: 10.1016/j.ejvs.2020.02.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 12/15/2019] [Accepted: 02/05/2020] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Cerebral white matter lesions (WMLs) and lacunar infarcts are surrogates of cerebral small vessel disease (SVD). WML severity as determined by trained radiologists predicts post-operative stroke or death in patients undergoing carotid endarterectomy (CEA). It is unknown whether routine pre-operative brain imaging reports as part of standard clinical practice also predict short and long term risk of stroke and death after CEA. METHODS Consecutive patients from the Athero-Express biobank study that underwent CEA for symptomatic high degree stenosis between March 2002 and November 2014 were included. Pre-operative brain imaging (computed tomography [CT] or magnetic resonance imaging [MRI]) reports were reviewed for reporting of SVD, defined as WMLs or any lacunar infarcts. The primary outcome was defined as any stroke or any cardiovascular death over three year follow up. The secondary outcome was defined as the 30 day peri-operative risk of stroke or cardiovascular death. RESULTS A total of 1038 patients were included (34% women), of whom 659 (63.5%) had CT images and 379 (36.5%) MRI images available. Of all patients, 697 (67%) had SVD reported by radiologists. Patients with SVD had a higher three year risk of cardiovascular death than those without (6.5% vs. 2.1%, adjusted HR 2.52 [95% CI 1.12-5.67]; p = .026) but no association was observed for the three year risk of stroke (9.0% vs. 6.7%, for patients with SVD vs. those without, adjusted HR 1.24 [95% CI 0.76-2.02]; p = .395). No differences in 30 day peri-operative risk were observed for stroke (4.4% vs. 2.9%, for patients with vs. those without SVD; adjusted HR 1.49 [95% CI 0.73-3.05]; p = .28), and for the combined stroke/cardiovascular death risk (4.4% vs. 3.5%, adjusted HR 1.20 [95% CI 0.61-2.35]; p = .59). CONCLUSION Presence of SVD in pre-operative brain imaging reports can serve as a predictor for the three year risk of cardiovascular death in symptomatic patients undergoing CEA but does not predict peri-operative or long term risk of stroke.
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Affiliation(s)
- Nathalie Timmerman
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Marjolijn L Rots
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Ian D van Koeverden
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Saskia Haitjema
- Laboratory of Clinical Chemistry and Haematology, Division Laboratories and Pharmacy, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Constance J H C M van Laarhoven
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Annemiek M Vuurens
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Gerard Pasterkamp
- Laboratory of Clinical Chemistry and Haematology, Division Laboratories and Pharmacy, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - L Jaap Kappelle
- Department of Neurology, University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Dominique P V de Kleijn
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Gert J de Borst
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands.
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Oksala NK, Lindström I, Khan N, Pihlajaniemi VJ, Lyytikäinen LP, Pienimäki JP, Hernesniemi J. Pre-Operative Masseter Area is an Independent Predictor of Long-Term Survival after Carotid Endarterectomy. Eur J Vasc Endovasc Surg 2019; 57:331-338. [DOI: 10.1016/j.ejvs.2018.11.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2018] [Accepted: 11/18/2018] [Indexed: 01/09/2023]
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Yu C, Han X, Zhang XL, Yu B, Dong Q. Long-term effects of white matter changes on the risk of stroke recurrence after carotid artery stenting in patients with symptomatic carotid artery stenosis. J Neurol Sci 2016; 369:11-14. [PMID: 27653857 DOI: 10.1016/j.jns.2016.07.062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Revised: 07/11/2016] [Accepted: 07/27/2016] [Indexed: 11/29/2022]
Abstract
INTRODUCTION Cerebral white matter changes (WMC) are associated with increased 30-day perioperative risk of stroke in patients undergoing carotid artery stenting (CAS). However, there is no data showing their impact on postoperative long-term stroke recurrence or survival. It remains unknown whether this effect is independent of classic cardiovascular risk factors or not. We tried to assess the effects of WMC on long-term stroke recurrence after CAS in patients with symptomatic carotid stenosis. METHODS A database of patients with symptomatic carotid stenosis who had undergone CAS was sampled in a single Chinese medical center from 2007 to 2014. Copies of baseline brain imaging were analyzed by two investigators to evaluate the severity of WMC. We analyzed the association between WMC and stroke recurrence after CAS by reviewing case histories and conducting telephone interviews, with a mean follow-up time of 28months. RESULTS 107 patients with an average age of 66years fulfilled the inclusion criteria, of which 70 were examined with CT and the remainder by MRI. In our cohort, 91.6% of the participants were male. There were 29 patients with diffuse WMC. In univariate analysis, patients with diffuse WMC had more contralateral occlusion than those with non-diffuse WMC. In patients with diffuse WMC, more stroke recurrences were observed compared with those with non-diffuse WMC (hazard ratio [HR] 3.516; 95% CI 1.176, 10.510, P=0.024). CONCLUSIONS In patients with symptomatic carotid artery stenosis, diffuse WMC were a risk factor for stroke recurrences after CAS. Larger studies are warranted to confirm this finding and explore the potential clinical impact of WMC so as to better determine treatment strategies for patients with symptomatic carotid artery stenosis.
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Affiliation(s)
- Chun Yu
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Xiang Han
- Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China.
| | - Xiao Long Zhang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Bo Yu
- Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Qiang Dong
- Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China.
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