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Dreier JP, Lemale CL, Horst V, Major S, Kola V, Schoknecht K, Scheel M, Hartings JA, Vajkoczy P, Wolf S, Woitzik J, Hecht N. Similarities in the Electrographic Patterns of Delayed Cerebral Infarction and Brain Death After Aneurysmal and Traumatic Subarachnoid Hemorrhage. Transl Stroke Res 2024:10.1007/s12975-024-01237-w. [PMID: 38396252 DOI: 10.1007/s12975-024-01237-w] [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: 01/11/2024] [Revised: 02/11/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024]
Abstract
While subarachnoid hemorrhage is the second most common hemorrhagic stroke in epidemiologic studies, the recent DISCHARGE-1 trial has shown that in reality, three-quarters of focal brain damage after subarachnoid hemorrhage is ischemic. Two-fifths of these ischemic infarctions occur early and three-fifths are delayed. The vast majority are cortical infarcts whose pathomorphology corresponds to anemic infarcts. Therefore, we propose in this review that subarachnoid hemorrhage as an ischemic-hemorrhagic stroke is rather a third, separate entity in addition to purely ischemic or hemorrhagic strokes. Cumulative focal brain damage, determined by neuroimaging after the first 2 weeks, is the strongest known predictor of patient outcome half a year after the initial hemorrhage. Because of the unique ability to implant neuromonitoring probes at the brain surface before stroke onset and to perform longitudinal MRI scans before and after stroke, delayed cerebral ischemia is currently the stroke variant in humans whose pathophysiological details are by far the best characterized. Optoelectrodes located directly over newly developing delayed infarcts have shown that, as mechanistic correlates of infarct development, spreading depolarizations trigger (1) spreading ischemia, (2) severe hypoxia, (3) persistent activity depression, and (4) transition from clustered spreading depolarizations to a negative ultraslow potential. Furthermore, traumatic brain injury and subarachnoid hemorrhage are the second and third most common etiologies of brain death during continued systemic circulation. Here, we use examples to illustrate that although the pathophysiological cascades associated with brain death are global, they closely resemble the local cascades associated with the development of delayed cerebral infarcts.
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Affiliation(s)
- Jens P Dreier
- Center for Stroke Research Berlin, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
- Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.
- Einstein Center for Neurosciences Berlin, Berlin, Germany.
| | - Coline L Lemale
- Center for Stroke Research Berlin, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany
- Department of Experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Viktor Horst
- Center for Stroke Research Berlin, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany
- Institute of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Sebastian Major
- Center for Stroke Research Berlin, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany
- Department of Experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Vasilis Kola
- Center for Stroke Research Berlin, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany
| | - Karl Schoknecht
- Medical Faculty, Carl Ludwig Institute for Physiology, University of Leipzig, Leipzig, Germany
| | - Michael Scheel
- Department of Neuroradiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Jed A Hartings
- Department of Neurosurgery, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Peter Vajkoczy
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Stefan Wolf
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Johannes Woitzik
- Department of Neurosurgery, Evangelisches Krankenhaus Oldenburg, University of Oldenburg, Oldenburg, Germany
| | - Nils Hecht
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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Theodorou A, Palaiodimou L, Papagiannopoulou G, Kargiotis O, Psychogios K, Safouris A, Bakola E, Chondrogianni M, Kotsali-Peteinelli V, Melanis K, Tsibonakis A, Andreadou E, Vasilopoulou S, Lachanis S, Velonakis G, Tzavellas E, Tzartos JS, Voumvourakis K, Paraskevas GP, Tsivgoulis G. Clinical Characteristics, Neuroimaging Markers, and Outcomes in Patients with Cerebral Amyloid Angiopathy: A Prospective Cohort Study. J Clin Med 2023; 12:5591. [PMID: 37685658 PMCID: PMC10488273 DOI: 10.3390/jcm12175591] [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: 07/04/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
Background and purpose: Sporadic cerebral amyloid angiopathy (CAA) is a small vessel disease, resulting from progressive amyloid-β deposition in the media/adventitia of cortical and leptomeningeal arterioles. We sought to assess the prevalence of baseline characteristics, clinical and radiological findings, as well as outcomes among patients with CAA, in the largest study to date conducted in Greece. Methods: Sixty-eight patients fulfilling the Boston Criteria v1.5 for probable/possible CAA were enrolled and followed for at least twelve months. Magnetic Resonance Imaging was used to assess specific neuroimaging markers. Data regarding cerebrospinal fluid biomarker profile and Apolipoprotein-E genotype were collected. Multiple logistic regression analyses were performed to identify predictors of clinical phenotypes. Cox-proportional hazard regression models were used to calculate associations with the risk of recurrent intracerebral hemorrhage (ICH). Results: Focal neurological deficits (75%), cognitive decline (57%), and transient focal neurological episodes (TFNEs; 21%) were the most common clinical manifestations. Hemorrhagic lesions, including lobar cerebral microbleeds (CMBs; 93%), cortical superficial siderosis (cSS; 48%), and lobar ICH (43%) were the most prevalent neuroimaging findings. cSS was independently associated with the likelihood of TFNEs at presentation (OR: 4.504, 95%CI:1.258-19.088), while multiple (>10) lobar CMBs were independently associated with cognitive decline at presentation (OR:5.418, 95%CI:1.316-28.497). cSS emerged as the only risk factor of recurrent ICH (HR:4.238, 95%CI:1.509-11.900) during a median follow-up of 20 months. Conclusions: cSS was independently associated with TFNEs at presentation and ICH recurrence at follow-up, while a higher burden of lobar CMBs with cognitive decline at baseline. These findings highlight the prognostic value of neuroimaging markers, which may influence clinical decision-making.
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Affiliation(s)
- Aikaterini Theodorou
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Lina Palaiodimou
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Georgia Papagiannopoulou
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Odysseas Kargiotis
- Stroke Unit, Metropolitan Hospital, 18547 Piraeus, Greece; (O.K.); (K.P.); (A.S.)
| | - Klearchos Psychogios
- Stroke Unit, Metropolitan Hospital, 18547 Piraeus, Greece; (O.K.); (K.P.); (A.S.)
| | - Apostolos Safouris
- Stroke Unit, Metropolitan Hospital, 18547 Piraeus, Greece; (O.K.); (K.P.); (A.S.)
| | - Eleni Bakola
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Maria Chondrogianni
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Vasiliki Kotsali-Peteinelli
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Konstantinos Melanis
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Athanasios Tsibonakis
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Elissavet Andreadou
- First Department of Neurology, “Eginition” Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (S.V.)
| | - Sofia Vasilopoulou
- First Department of Neurology, “Eginition” Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (S.V.)
| | - Stefanos Lachanis
- Iatropolis Magnetic Resonance Diagnostic Centre, 15231 Athens, Greece;
| | - Georgios Velonakis
- Second Department of Radiology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece;
| | - Elias Tzavellas
- First Department of Psychiatry, “Aiginition” Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece;
| | - John S. Tzartos
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Konstantinos Voumvourakis
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Georgios P. Paraskevas
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
| | - Georgios Tsivgoulis
- Second Department of Neurology, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.T.); (L.P.); (G.P.); (E.B.); (M.C.); (V.K.-P.); (K.M.); (A.T.); (J.S.T.); (K.V.); (G.P.P.)
- Department of Neurology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
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Fandler-Höfler S, Obergottsberger L, Ambler G, Eppinger S, Wünsch G, Kneihsl M, Seiffge D, Banerjee G, Wilson D, Nash P, Jäger HR, Enzinger C, Werring DJ, Gattringer T. Association of the Presence and Pattern of MRI Markers of Cerebral Small Vessel Disease With Recurrent Intracerebral Hemorrhage. Neurology 2023; 101:e794-e804. [PMID: 37349111 PMCID: PMC10449438 DOI: 10.1212/wnl.0000000000207510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 04/24/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Assessing the risk of recurrent intracerebral hemorrhage (ICH) is of high clinical importance. MRI-based cerebral small vessel disease (SVD) markers may help establish ICH etiologic subtypes (including cryptogenic ICH) relevant for recurrence risk. METHODS We investigated the risk of recurrent ICH in a large cohort of consecutive ICH survivors with available MRI at baseline. Patients with macrovascular, structural, or other identified secondary causes (other than SVD) were excluded. Based on MRI findings, ICH etiology was defined as probable cerebral amyloid angiopathy (CAA) according to the Boston 2.0 criteria, arteriolosclerosis (nonlobar ICH and additional markers of arteriolosclerosis, absent lobar hemorrhagic lesions), mixed SVD (mixed deep and lobar hemorrhagic changes), or cryptogenic ICH (no MRI markers of SVD). Recurrent ICH was determined using electronic health records and confirmed by neuroimaging. Data from an independent multicenter cohort (CROMIS-2 ICH) were used to confirm core findings. RESULTS Of 443 patients with ICH (mean age 67 ± 13 years, 41% female), ICH etiology was mixed SVD in 36.7%, arteriolosclerosis in 23.6%, CAA in 23.0%, and cryptogenic ICH in 16.7%. During a median follow-up period of 5.7 years (interquartile range 2.9-10.0, 2,682 patient-years), recurrent ICH was found in 59 individual patients (13.3%). The highest recurrence rate per 100 person-years was detected in patients with CAA (8.5, 95% CI 6.1-11.7), followed by that in those with mixed SVD (1.8, 95% CI 1.1-2.9) and arteriolosclerosis (0.6, 95% CI 0.3-1.5). No recurrent ICH occurred in patients with cryptogenic ICH during 510 person-years follow-up (97.5% CI 0-0.7); this finding was confirmed in an independent cohort (CROMIS-2 ICH, n = 216), in which also there was no recurrence in patients with cryptogenic ICH. In patients with CAA, cortical superficial siderosis was the imaging feature strongest related to ICH recurrence (hazard ratio 5.7, 95% CI 2.4-13.6). DISCUSSION MRI-based etiologic subtypes are helpful in determining the recurrence risk of ICH; while the highest recurrence risk was found in CAA, recurrence risk was low for arteriolosclerosis and negligible for cryptogenic ICH.
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Affiliation(s)
- Simon Fandler-Höfler
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Lena Obergottsberger
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Gareth Ambler
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Sebastian Eppinger
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Gerit Wünsch
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Markus Kneihsl
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - David Seiffge
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Gargi Banerjee
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Duncan Wilson
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Philip Nash
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Hans Rudolf Jäger
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Christian Enzinger
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - David J Werring
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom
| | - Thomas Gattringer
- From the Department of Neurology (S.F.-H., L.O., S.E., M.K., C.E., T.G.), Medical University of Graz, Austria; Stroke Research Centre (S.F.-H., D.S., G.B., D. Wilson, P.N., D. Werring), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology; Department of Statistical Science (G.A.), University College London, United Kingdom; Division of Neuroradiology, Vascular and Interventional Radiology (S.E., M.K., T.G.), Department of Radiology; Institute for Medical Informatics, Statistics and Documentation (G.W.), Medical University of Graz, Austria; Department of Neurology (D.S.), University Hospital Bern, Inselspital, University of Bern, Switzerland; and Neuroradiological Academic Unit (H.R.J.), Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, United Kingdom.
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Thotamgari SR, Babbili A, Bucchanolla P, Thakkar S, Patel HP, Spaseski MB, Graff-Radford J, Rabinstein AA, Asad ZUA, Asirvatham SJ, Holmes DR, Deshmukh A, DeSimone CV. Impact of Atrial Fibrillation on Outcomes in Patients Hospitalized With Nontraumatic Intracerebral Hemorrhage. Mayo Clin Proc Innov Qual Outcomes 2023; 7:222-230. [PMID: 37304065 PMCID: PMC10250577 DOI: 10.1016/j.mayocpiqo.2023.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023] Open
Abstract
Objective To assess the effect of atrial fibrillation (AF) on outcomes in hospitalizations for non-traumatic intracerebral hemorrhage (ICH). Patients and Methods We queried the National Inpatient Sample database between January 1, 2016, and December 31, 2019, to identify hospitalizations with an index diagnosis of non-traumatic ICH using ICD-10 code I61. The cohort was divided into patients with and without AF. Propensity score matching was used to balance the covariates between AF and non-AF groups. Logistic regression was used to analyze the association. All statistical analyses were performed using weighted values. Results Our cohort included 292,725 hospitalizations with a primary discharge diagnosis of non-traumatic ICH. From this group, 59,005 (20%) recorded a concurrent diagnosis of AF, and 46% of these patients with AF were taking anticoagulants. Patients with AF reported a higher Elixhauser comorbidity index (19.8±6.0 vs 16.6±6.4; P<.001) before propensity matching. After propensity matching, the multivariate analysis reported that AF (aOR, 2.34; 95% CI, 2.26-2.42; P<.001) and anticoagulation drug use (aOR, 1.32; 95% CI, 1.28-1.37; P<.001) were independently associated with all-cause in-hospital mortality. Moreover, AF was significantly associated with respiratory failure requiring mechanical ventilation (odds ratio, 1.57; 95% CI, 1.52-1.62; P<.001) and acute heart failure (odds ratio, 1.26; 95% CI, 1.19-1.33; P<.001) compared with the absence of AF. Conclusion These data suggest that non-traumatic ICH hospitalizations with coexistent AF are associated with worse in-hospital outcomes such as higher mortality and acute heart failure.
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Affiliation(s)
| | - Akhilesh Babbili
- Department of Internal Medicine, Louisiana State University Health, Shreveport
| | | | | | - Harsh P. Patel
- Division of Cardiology, Southern Illinois University, Springfield, IL
| | - Maja B. Spaseski
- Department of Internal Medicine, Weiss Memorial Hospital, Chicago, IL
| | | | | | - Zain Ul Abideen Asad
- Department of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City
| | | | - David R. Holmes
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
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Li YL, Chen C, Zhang LJ, Zheng YN, Lv XN, Zhao LB, Li Q, Lv FJ. Prediction of Early Perihematomal Edema Expansion Based on Noncontrast Computed Tomography Radiomics and Machine Learning in Intracerebral Hemorrhage. World Neurosurg 2023; 175:e264-e270. [PMID: 36958717 DOI: 10.1016/j.wneu.2023.03.066] [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: 02/03/2023] [Revised: 03/15/2023] [Accepted: 03/16/2023] [Indexed: 03/25/2023]
Abstract
OBJECTIVES To investigate the predictive value of noncontrast computed tomography (NCCT) models based on radiomics features and machine learning for early perihematomal edema (PHE) expansion in patients with spontaneous intracerebral hemorrhage (ICH). METHODS We retrospectively reviewed NCCT data from 214 patients with spontaneous ICH. All radiomics features were extracted from volume of interest of hematomas on admission scans. A total of 8 machine learning methods were applied for constructing models in the training and the test set. Receiver operating characteristic analysis and the areas under the curve were used to evaluate the predictive value. RESULTS A total of 23 features were finally selected to establish models of early PHE expansion after feature screening. Patients were randomly assigned into training (n = 171) and test (n = 43) sets. The accuracy, sensitivity, and specificity in the test set were 72.1%, 90.0%, and 66.7% for the support vector machine model; 79.1%, 70.0%, and 84.4% for the k-nearest neighbor model; 88.4%, 90.0%, and 87.9% for the logistic regression model; 74.4%, 90.0%, and 69.7% for the extra tree model; 74.4%, 90.0%, and 69.7% for the extreme gradient boosting model; 83.7%, 100%, and 78.8% for the multilayer perceptron (MLP) model; 72.1%, 100%, and 65.6% for the light gradient boosting machine model; and 60.5%, 90.0%, and 53.1% for the random forest model, respectively. CONCLUSIONS The MLP model seemed to be the best model for prediction of PHE expansion in patients with ICH. NCCT models based on radiomics features and machine learning could predict early PHE expansion and improve the discrimination of identify spontaneous intracerebral hemorrhage patients at risk of early PHE expansion.
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Affiliation(s)
- Yu-Lun Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Chu Chen
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li-Juan Zhang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yi-Neng Zheng
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xin-Ni Lv
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li-Bo Zhao
- Chongqing Key Laboratory of Cerebrovascular Disease Research, Chongqing, China; Department of Neurology, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Qi Li
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China; Chongqing Key Laboratory of Cerebrovascular Disease Research, Chongqing, China.
| | - Fa-Jin Lv
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
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Li YL, Zheng YN, Zhang LJ, Li ZQ, Deng L, Lv XN, Li Q, Lv FJ. Comparison of different noncontrast computed tomographic markers for predicting early perihematomal edema expansion in patients with intracerebral hemorrhage. J Clin Neurosci 2023; 112:1-5. [PMID: 37011516 DOI: 10.1016/j.jocn.2023.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/06/2023] [Accepted: 03/09/2023] [Indexed: 04/04/2023]
Abstract
OBJECTIVES Noncontrast computed tomography (NCCT) imaging markers are associated with early perihematomal edema (PHE) growth. The aim of this study was to compare the predictive value of different NCCT markers in predicting early PHE expansion. METHODS ICH patients who underwent baseline CT scan within 6 h of symptoms onset and follow-up CT scan within 36 h between July 2011 and March 2017 were included in this study. The predictive value of hypodensity, satellite sign, heterogeneous density, irregular shape, blend sign, black hole sign, island sign and expansion-prone hematoma for early perihematomal edema expansion were assessed, separately. RESULTS 214 patients were included in our final analysis. After adjusting for ICH characteristics, hypodensity, blend sign, island sign and expansion-prone hematoma are still predictors of early perihematomal edema expansion in multivariable logistics regression analysis (all P < 0.05). The area under the receiver operating characteristic (ROC) curve of expansion-prone hematoma was significantly larger than the area under the ROC curve of hypodensity, blend sign and island sign in predicting PHE expansion (P = 0.003, P < 0.001 and P = 0.002, respectively). CONCLUSION Compared with single NCCT imaging markers, expansion-prone hematoma seems to be optimal predictor for early PHE expansion than any single NCCT imaging marker.
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Can novel CT-and MR-based neuroimaging biomarkers further improve the etiological diagnosis of lobar intra-cerebral hemorrhage? J Neurol 2023; 270:582-588. [PMID: 36307736 DOI: 10.1007/s00415-022-11434-y] [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: 06/27/2022] [Revised: 10/17/2022] [Accepted: 10/18/2022] [Indexed: 01/07/2023]
Abstract
Lobar hematomas represent around half of all supratentorial hemorrhages and have high mortality and morbidity. Their management depends on the underlying cause. Apart from local causes such as vascular malformation, which are rare and can usually be easily excluded thanks to imaging, the vast majority of lobar hematomas equally frequently result from either hypertensive arteriolopathy (HA) or cerebral amyloid angiopathy (CAA). Distinguishing between CAA and HA is important for prognostication (risk of recurrence nearly sevenfold higher in the former), for decision-making regarding, e.g., antithrombotic therapies (for other indications) and for clinical trials of new therapies. Currently, a non-invasive diagnosis of probable CAA can be made using the MR-based modified Boston criteria, which have excellent specificity but moderate sensitivity against histopathological reference, leading to the clinically largely irrelevant diagnosis of "possible CAA". Furthermore, the Boston criteria cannot be applied when both lobar and deep MRI hemorrhagic markers are present, a not uncommon situation. Here we propose to test whether new CT and MR-based imaging biomarkers, namely finger-like projections of the hematoma and adjacent subarachnoid hemorrhage on acute-stage CT or MRI, and remote punctate diffusion-weighted imaging ischemic lesions on acute or subacute-stage MRI, have the potential to improve the performance of the Boston criteria. Furthermore, we also propose to test whether clinical-radiological biomarkers may also allow a positive diagnosis of HA to be made in lobar hematomas, which, if feasible, would not only further reduce the prevalence of "possible CAA" but also permit a diagnosis of HA and/or CAA to be made in the presence of mixed deep and lobar MRI hemorrhagic markers.
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Malhotra K, Theodorou A, Katsanos AH, Zompola C, Shoamanesh A, Boviatsis E, Paraskevas GP, Spilioti M, Cordonnier C, Werring DJ, Alexandrov AV, Tsivgoulis G. Prevalence of Clinical and Neuroimaging Markers in Cerebral Amyloid Angiopathy: A Systematic Review and Meta-Analysis. Stroke 2022; 53:1944-1953. [PMID: 35264008 DOI: 10.1161/strokeaha.121.035836] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Limited data exist regarding the prevalence of clinical and neuroimaging manifestations among patients diagnosed with cerebral amyloid angiopathy (CAA). We sought to determine the prevalence of clinical phenotypes and radiological markers in patients with CAA. METHODS Systematic review and meta-analysis of studies including patients with CAA was conducted to primarily assess the prevalence of clinical phenotypes and neuroimaging markers as available in the included studies. Sensitivity analyses were performed based on the (1) retrospective or prospective study design and (2) probable or unspecified CAA status. We pooled the prevalence rates using random-effects models and assessed the heterogeneity using the Cochran Q and I2 statistics. RESULTS We identified 12 prospective and 34 retrospective studies including 7159 patients with CAA. The pooled prevalence rates were cerebral microbleeds (52% [95% CI, 43%-60%]; I2=93%), cortical superficial siderosis (49% [95% CI, 38%-59%]; I2=95%), dementia or mild cognitive impairment (50% [95% CI, 35%-65%]; I2=97%), intracerebral hemorrhage (ICH; 44% [95% CI, 27%-61%]; I2=98%), transient focal neurological episodes (48%; 10 studies [95% CI, 29%-67%]; I2=97%), lacunar infarcts (30% [95% CI, 25%-36%]; I2=78%), high grades of perivascular spaces located in centrum semiovale (56% [95% CI, 44%-67%]; I2=88%) and basal ganglia (21% [95% CI, 2%-51%]; I2=98%), and white matter hyperintensities with moderate or severe Fazekas score (53% [95% CI, 40%-65%]; I2=91%). The only neuroimaging marker that was associated with higher odds of recurrent ICH was cortical superficial siderosis (odds ratio, 1.57 [95% CI, 1.01-2.46]; I2=47%). Sensitivity analyses demonstrated a higher prevalence of ICH (53% versus 16%; P=0.03) and transient focal neurological episodes (57% versus 17%; P=0.03) among retrospective studies compared with prospective studies. No difference was documented between the prevalence rates based on the CAA status. CONCLUSIONS Approximately one-half of hospital-based cohort of CAA patients was observed to have cerebral microbleeds, cortical superficial siderosis, mild cognitive impairment, dementia, ICH, or transient focal neurological episodes. Cortical superficial siderosis was the only neuroimaging marker that was associated with higher odds of ICH recurrence. Future population-based studies among well-defined CAA cohorts are warranted to corroborate our findings.
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Affiliation(s)
- Konark Malhotra
- Department of Neurology, Allegheny Health Network, Pittsburgh, PA (K.M.)
| | - Aikaterini Theodorou
- Second Department of Neurology, National and Kapodistrian University of Athens, "Attikon" University Hospital, Greece. (A.T., A.H.K., C.Z., G.P.P., G.T.)
| | - Aristeidis H Katsanos
- Second Department of Neurology, National and Kapodistrian University of Athens, "Attikon" University Hospital, Greece. (A.T., A.H.K., C.Z., G.P.P., G.T.).,Department of Neurology, McMaster University/Population Health Research Institute, Hamilton, Canada (A.H.K., A.S.)
| | - Christina Zompola
- Second Department of Neurology, National and Kapodistrian University of Athens, "Attikon" University Hospital, Greece. (A.T., A.H.K., C.Z., G.P.P., G.T.)
| | - Ashkan Shoamanesh
- Department of Neurology, McMaster University/Population Health Research Institute, Hamilton, Canada (A.H.K., A.S.)
| | - Efstathios Boviatsis
- Department of Neurosurgery, National and Kapodistrian University of Athens, "Attikon" University Hospital, Greece. (E.B.)
| | - George P Paraskevas
- Second Department of Neurology, National and Kapodistrian University of Athens, "Attikon" University Hospital, Greece. (A.T., A.H.K., C.Z., G.P.P., G.T.)
| | - Martha Spilioti
- First Department of Neurology, AHEPA General Hospital, Aristotle University of Thessaloniki, Greece (M.S.)
| | - Charlotte Cordonnier
- University Lille, Inserm, CHU Lille, U1172, LilNCog, Lille Neuroscience and Cognition, France (C.C.)
| | - David J Werring
- Stroke Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom (D.J.W.)
| | - Andrei V Alexandrov
- Department of Neurology, University of Tennessee Health Science Center, Memphis (A.V.A., G.T.)
| | - Georgios Tsivgoulis
- Second Department of Neurology, National and Kapodistrian University of Athens, "Attikon" University Hospital, Greece. (A.T., A.H.K., C.Z., G.P.P., G.T.).,Department of Neurology, University of Tennessee Health Science Center, Memphis (A.V.A., G.T.)
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