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Marcus A, Mair G, Chen L, Hallett C, Cuervas-Mons CG, Roi D, Rueckert D, Bentley P. Deep learning biomarker of chronometric and biological ischemic stroke lesion age from unenhanced CT. NPJ Digit Med 2024; 7:338. [PMID: 39643604 PMCID: PMC11624201 DOI: 10.1038/s41746-024-01325-z] [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: 07/16/2024] [Accepted: 11/03/2024] [Indexed: 12/09/2024] Open
Abstract
Estimating progression of acute ischemic brain lesions - or biological lesion age - holds huge practical importance for hyperacute stroke management. The current best method for determining lesion age from non-contrast computerised tomography (NCCT), measures Relative Intensity (RI), termed Net Water Uptake (NWU). We optimised lesion age estimation from NCCT using a convolutional neural network - radiomics (CNN-R) model trained upon chronometric lesion age (Onset Time to Scan: OTS), while validating against chronometric and biological lesion age in external datasets (N = 1945). Coefficients of determination (R2) for OTS prediction, using CNN-R, and RI models were 0.58 and 0.32 respectively; while CNN-R estimated OTS showed stronger associations with ischemic core:penumbra ratio, than RI and chronometric, OTS (ρ2 = 0.37, 0.19, 0.11); and with early lesion expansion (regression coefficients >2x for CNN-R versus others) (all comparisons: p < 0.05). Concluding, deep-learning analytics of NCCT lesions is approximately twice as accurate as NWU for estimating chronometric and biological lesion ages.
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Affiliation(s)
- Adam Marcus
- Department of Brain Sciences, Imperial College London, London, UK
| | - Grant Mair
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Liang Chen
- Department of Brain Sciences, Imperial College London, London, UK
| | - Charles Hallett
- Department of Brain Sciences, Imperial College London, London, UK
| | | | - Dylan Roi
- Department of Brain Sciences, Imperial College London, London, UK
| | - Daniel Rueckert
- Department of Computing, Imperial College London, London, UK
- Klinikum rechts der Isar, Technische Universität München, München, Germany
| | - Paul Bentley
- Department of Brain Sciences, Imperial College London, London, UK.
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Winkelmeier L, Heit JJ, Broocks G, Prüter J, Heitkamp C, Schell M, Albers GW, Lansberg MG, Wintermark M, Kemmling A, Stracke CP, Guenego A, Paech D, Fiehler J, Faizy TD. Association between occlusion location, net water uptake and ischemic lesion growth in large vessel anterior circulation strokes. J Cereb Blood Flow Metab 2024; 44:1352-1361. [PMID: 38329032 PMCID: PMC11342730 DOI: 10.1177/0271678x241232193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/28/2023] [Accepted: 01/14/2024] [Indexed: 02/09/2024]
Abstract
Ischemic lesion net water uptake (NWU) represents a quantitative imaging biomarker for cerebral edema in acute ischemic stroke. Data on NWU for distinct occlusion locations remain scarce, but might help to improve the prognostic value of NWU. In this retrospective multicenter cohort study, we compared NWU between patients with proximal large vessel occlusion (pLVO; ICA or proximal M1) and distal large vessel occlusion (dLVO; distal M1 or M2). NWU was quantified by densitometric measurements of the early ischemic region. Arterial collateral status was assessed using the Maas scale. Regression analysis was used to investigate the relationship between occlusion location, NWU and ischemic lesion growth. A total of 685 patients met inclusion criteria. Early ischemic lesion NWU was higher in patients with pLVO compared with dLVO (7.7% vs 3.9%, P < .001). The relationship between occlusion location and NWU was partially mediated by arterial collateral status. NWU was associated with absolute ischemic lesion growth between admission and follow-up imaging (β estimate, 5.50, 95% CI, 3.81-7.19, P < .001). This study establishes a framework for the relationship between occlusion location, arterial collateral status, early ischemic lesion NWU and ischemic lesion growth. Future prognostic thresholds for NWU might be optimized by adjusting for the occlusion location.
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Affiliation(s)
- Laurens Winkelmeier
- Department of Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jeremy J Heit
- Department of Neuroradiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Gabriel Broocks
- Department of Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Julia Prüter
- Department of Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Heitkamp
- Department of Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Maximilian Schell
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gregory W Albers
- Department of Neurology, Stanford University School of Medicine, Stanford, CA, USA
| | - Maarten G Lansberg
- Department of Neurology, Stanford University School of Medicine, Stanford, CA, USA
| | - Max Wintermark
- Department of Neuroradiology, MD Anderson, Houston, Texas, USA
| | - André Kemmling
- Department of Neuroradiology, University Marburg, Marburg, Germany
| | | | - Adrien Guenego
- Department of Neuroradiology, Erasme Medical Center, Brussels, Belgium
| | - Daniel Paech
- Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Jens Fiehler
- Department of Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias D Faizy
- Department of Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Wu H, Shi J, Sun X, Lu M, Liao A, Li Y, Xiao L, Zhou C, Dong W, Geng Z, Yuan L, Guo R, Chen M, Cheng X, Zhu W. Predictive effect of net water uptake on futile recanalisation in patients with acute large-vessel occlusion stroke. Clin Radiol 2024; 79:e599-e606. [PMID: 38310056 DOI: 10.1016/j.crad.2024.01.009] [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: 05/19/2023] [Revised: 12/03/2023] [Accepted: 01/06/2024] [Indexed: 02/05/2024]
Abstract
AIM To determine whether net water uptake (NWU) based on automated software evaluation could predict futile recanalisation in patients with acute anterior circulation large-vessel occlusion (LVO). MATERIALS AND METHODS Patients with acute anterior circulation LVO undergoing mechanical thrombectomy in Jinling Hospital were evaluated retrospectively. NWU and other baseline data were evaluated by performing univariate and multivariate analyses. The primary endpoint was 90-day modified Rankin scale score ≥3. A nomogram to predict poor clinical outcomes was developed based on multivariate logistic regression analysis. RESULTS Overall, 135 patients who underwent thrombectomy with a TICI grade ≥2b were enrolled. In multivariate logistic regression analysis, the following factors were identified as independent predictors of futile recanalisation: age (odds ratio [OR]: 1.055, 95 % confidence interval [CI]: 1.004-1.110, p=0.035), female (OR: 0.289, 95 % CI: 0.098-0.850, p=0.024), hypertension (OR: 3.182, 95 % CI: 1.160-8.728, p=0.025), high blood glucose level (OR: 1.36, 95 % CI: 1.087-1.701, p=0.007), admission National Institutes of Health Stroke Scale score (OR: 1.082, 95 % CI: 1.003-1.168, p=0.043), and NWU (OR: 1.312, 95 % CI: 1.038-1.659, p=0.023). CONCLUSIONS NWU based on Alberta Stroke Program Early Computed Tomography (CT) Score (ASPECTS) could be used to predict the occurrence of futile recanalisation in patients with acute anterior circulation LVO ischaemic stroke.
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Affiliation(s)
- H Wu
- Department of Neurology, Third People's Hospital of Yancheng, Yancheng 224001, Jiangsu, China; Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Nanjing 210002, Jiangsu, China
| | - J Shi
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu, China
| | - X Sun
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Nanjing 210002, Jiangsu, China
| | - M Lu
- Department of Neurology, Jinling Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - A Liao
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Nanjing 210002, Jiangsu, China
| | - Y Li
- Department of Neurology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, Jiangsu, China
| | - L Xiao
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Nanjing 210002, Jiangsu, China
| | - C Zhou
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu, China
| | - W Dong
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Nanjing 210002, Jiangsu, China
| | - Z Geng
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Nanjing 210002, Jiangsu, China
| | - L Yuan
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Nanjing 210002, Jiangsu, China
| | - R Guo
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Nanjing 210002, Jiangsu, China
| | - M Chen
- Department of Neurology, Third People's Hospital of Yancheng, Yancheng 224001, Jiangsu, China
| | - X Cheng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu, China.
| | - W Zhu
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Nanjing 210002, Jiangsu, China.
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Pham J, Ng FC. Novel advanced imaging techniques for cerebral oedema. Front Neurol 2024; 15:1321424. [PMID: 38356883 PMCID: PMC10865379 DOI: 10.3389/fneur.2024.1321424] [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: 10/14/2023] [Accepted: 01/09/2024] [Indexed: 02/16/2024] Open
Abstract
Cerebral oedema following acute ischemic infarction has been correlated with poor functional outcomes and is the driving mechanism of malignant infarction. Measurements of midline shift and qualitative assessment for herniation are currently the main CT indicators for cerebral oedema but have limited sensitivity for small cortical infarcts and are typically a delayed sign. In contrast, diffusion-weighted (DWI) or T2-weighted magnetic resonance imaging (MRI) are highly sensitive but are significantly less accessible. Due to the need for early quantification of cerebral oedema, several novel imaging biomarkers have been proposed. Based on neuroanatomical shift secondary to space-occupying oedema, measures such as relative hemispheric volume and cerebrospinal fluid displacement are correlated with poor outcomes. In contrast, other imaging biometrics, such as net water uptake, T2 relaxometry and blood brain barrier permeability, reflect intrinsic tissue changes from the influx of fluid into the ischemic region. This review aims to discuss quantification of cerebral oedema using current and developing advanced imaging techniques, and their role in predicting clinical outcomes.
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Affiliation(s)
- Jenny Pham
- Department of Radiology, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Felix C. Ng
- Department of Neurology, Royal Melbourne Hospital, Parkville, VIC, Australia
- Department of Neurology, Austin Health, Heidelberg, VIC, Australia
- Department of Medicine at Royal Melbourne Hospital, Melbourne Brain Centre, University of Melbourne, Parkville, VIC, Australia
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