Book contents
- Textbook of Stroke Medicine
- Textbook of Stroke Medicine
- Copyright page
- Contents
- Contributors
- Preface
- Section 1 Etiology, Pathophysiology, and Imaging
- Chapter 1 Neuropathology and Pathophysiology of Stroke
- Chapter 2 Common Causes of Ischemic Stroke
- Chapter 3 Neuroradiology
- Chapter 4 Imaging for Prediction of Functional Outcome and for Assessment of Recovery
- Chapter 5 Ultrasound in Acute Ischemic Stroke
- Section 2 Clinical Epidemiology and Risk Factors
- Section 3 Diagnostics and Syndromes
- Section 4 Therapeutic Strategies and Neurorehabilitation
- Index
- References
Chapter 3 - Neuroradiology
from Section 1 - Etiology, Pathophysiology, and Imaging
Published online by Cambridge University Press: 16 May 2019
Book contents
- Textbook of Stroke Medicine
- Textbook of Stroke Medicine
- Copyright page
- Contents
- Contributors
- Preface
- Section 1 Etiology, Pathophysiology, and Imaging
- Chapter 1 Neuropathology and Pathophysiology of Stroke
- Chapter 2 Common Causes of Ischemic Stroke
- Chapter 3 Neuroradiology
- Chapter 4 Imaging for Prediction of Functional Outcome and for Assessment of Recovery
- Chapter 5 Ultrasound in Acute Ischemic Stroke
- Section 2 Clinical Epidemiology and Risk Factors
- Section 3 Diagnostics and Syndromes
- Section 4 Therapeutic Strategies and Neurorehabilitation
- Index
- References
- Type
- Chapter
- Information
- Textbook of Stroke Medicine , pp. 50 - 67Publisher: Cambridge University PressPrint publication year: 2019
References
Bill, O, Faouzi, M, Meuli, R, et al. Added value of multimodal computed tomography imaging: analysis of 1994 acute ischaemic strokes. Eur J Neurol 2017; 24: 167–74.CrossRefGoogle ScholarPubMed
Michel, P, Odier, C, Rutgers, M, et al. The Acute STroke Registry and Analysis of Lausanne (ASTRAL): design and baseline analysis of an ischemic stroke registry including acute multimodal imaging. Stroke 2010; 41: 2491–8.Google Scholar
Na, DG, Kim, EY, Ryoo, JW, et al. CT sign of brain swelling without concomitant parenchymal hypoattenuation: comparison with diffusion- and perfusion-weighted MR imaging. Radiology 2005; 235: 986–92.CrossRefGoogle ScholarPubMed
Barber, PA, Demchuk, AM, Zhang, J, Buchan, AM. Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. ASPECTS Study Group. Alberta Stroke Programme Early CT Score. Lancet Lond Engl 2000; 355: 1670–4.Google Scholar
Puetz, V, Dzialowski, I, Hill, MD, Demchuk, AM. The Alberta Stroke Program Early CT Score in clinical practice: what have we learned? Int J Stroke Off J Int Stroke Soc 2009; 4: 354–64.Google ScholarPubMed
Hill, MD, Rowley, HA, Adler, F, et al. Selection of acute ischemic stroke patients for intra-arterial thrombolysis with pro-urokinase by using ASPECTS. Stroke 2003; 34: 1925–31.Google Scholar
Demchuk, AM, Hill, MD, Barber, PA, et al. Importance of early ischemic computed tomography changes using ASPECTS in NINDS rtPA Stroke Study. Stroke 2005; 36: 2110–15.CrossRefGoogle ScholarPubMed
Goyal, M, Menon, BK, van Zwam, WH, et al. Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials. Lancet Lond Engl 2016; 387: 1723–31.Google Scholar
Strbian, D, Engelter, S, Michel, P, et al. Symptomatic intracranial hemorrhage after stroke thrombolysis: the SEDAN score. Ann Neurol 2012; 71: 634–41.Google Scholar
Nezu, T, Koga, M, Nakagawara, J, et al. Early ischemic change on CT versus diffusion-weighted imaging for patients with stroke receiving intravenous recombinant tissue-type plasminogen activator therapy: stroke acute management with urgent risk-factor assessment and improvement (SAMURAI) rt-PA registry. Stroke 2011; 42: 2196–200.Google Scholar
Latchaw, RE, Yonas, H, Hunter, GJ, et al. Guidelines and recommendations for perfusion imaging in cerebral ischemia: a scientific statement for healthcare professionals by the writing group on perfusion imaging, from the Council on Cardiovascular Radiology of the American Heart Association. Stroke 2003; 34: 1084–104.CrossRefGoogle Scholar
Wintermark, M, Reichhart, M, Thiran, J-P, et al. Prognostic accuracy of cerebral blood flow measurement by perfusion computed tomography, at the time of emergency room admission, in acute stroke patients. Ann Neurol 2002; 51: 417–32.CrossRefGoogle ScholarPubMed
Koenig, M, Kraus, M, Theek, C, et al. Quantitative assessment of the ischemic brain by means of perfusion-related parameters derived from perfusion CT. Stroke 2001; 32: 431–7.Google Scholar
Eastwood, JD, Lev, MH, Azhari, T, et al. CT perfusion scanning with deconvolution analysis: pilot study in patients with acute middle cerebral artery stroke. Radiology 2002; 222: 227–36.Google Scholar
Murphy, BD, Fox, AJ, Lee, DH, et al. White matter thresholds for ischemic penumbra and infarct core in patients with acute stroke: CT perfusion study. Radiology 2008; 247: 818–25.Google Scholar
Wintermark, M, Fischbein, NJ, Smith, WS, et al. Accuracy of dynamic perfusion CT with deconvolution in detecting acute hemispheric stroke. AJNR Am J Neuroradiol 2005; 26: 104–12.Google Scholar
Youn, SW, Kim, JH, Weon, Y-C, et al. Perfusion CT of the brain using 40-mm-wide detector and toggling table technique for initial imaging of acute stroke. AJR Am J Roentgenol 2008; 191: W120–6.Google Scholar
Wintermark, M, Flanders, AE, Velthuis, B, et al. Perfusion-CT assessment of infarct core and penumbra: receiver operating characteristic curve analysis in 130 patients suspected of acute hemispheric stroke. Stroke 2006; 37: 979–85.CrossRefGoogle ScholarPubMed
Bivard, A, Spratt, N, Levi, C, Parsons, M. Perfusion computer tomography: imaging and clinical validation in acute ischaemic stroke. Brain J Neurol 2011; 134: 3408–16.CrossRefGoogle ScholarPubMed
Campbell, BCV, Christensen, S, Levi, CR, et al. Cerebral blood flow is the optimal CT perfusion parameter for assessing infarct core. Stroke 2011; 42: 3435–40.Google Scholar
Bivard, A, Kleinig, T, Miteff, F, et al. Ischemic core thresholds change with time to reperfusion: a case control study. Ann Neurol 2017; 82: 995–1003.CrossRefGoogle ScholarPubMed
Dehkharghani, S, Bammer, R, Straka, M, et al. Performance and predictive value of a user-independent platform for CT perfusion analysis: threshold-derived automated systems outperform examiner-driven approaches in outcome prediction of acute ischemic stroke. AJNR Am J Neuroradiol 2015; 36: 1419–25.Google Scholar
Austein, F, Riedel, C, Kerby, T, et al. Comparison of perfusion CT software to predict the final infarct volume after thrombectomy. Stroke 2016; 47: 2311–17.Google Scholar
Demeestere, J, Garcia-Esperon, C, Garcia-Bermejo, P, et al. Evaluation of hyperacute infarct volume using ASPECTS and brain CT perfusion core volume. Neurology 2017; 88: 2248–53.Google Scholar
Meyer, IA, Cereda, CW, Correia, PN, et al. Factors associated with focal computed tomographic perfusion abnormalities in supratentorial transient ischemic attacks. Stroke 2018; 49: 68–75.CrossRefGoogle ScholarPubMed
Gelfand, JM, Wintermark, M, Josephson, SA. Cerebral perfusion-CT patterns following seizure. Eur J Neurol 2010; 17: 594–601.CrossRefGoogle ScholarPubMed
Koome, M, Churilov, L, Chen, Z, et al. Computed tomography perfusion as a diagnostic tool for seizures after ischemic stroke. Neuroradiology 2016; 58: 577–84.Google Scholar
Gonzalez-Delgado, M, Michel, P, Reichhart, M, et al. The significance of focal hypoperfusion during migraine with aura (abstract). Stroke 2005; 36: 444.Google Scholar
Furtado, AD, Smith, WS, Koroshetz, W, et al. Perfusion CT imaging follows clinical severity in left hemispheric strokes. Eur Neurol 2008; 60: 244–52.Google Scholar
Pallesen, L-P, Lambrou, D, Eskandari, A, et al. Perfusion computed tomography in posterior circulation stroke: predictors and prognostic implications of focal hypoperfusion. Eur J Neurol 2018; 25: 725–31.Google Scholar
Zhu, G, Michel, P, Aghaebrahim, A, et al. Computed tomography workup of patients suspected of acute ischemic stroke: perfusion computed tomography adds value compared with clinical evaluation, noncontrast computed tomography, and computed tomography angiogram in terms of predicting outcome. Stroke 2013; 44: 1049–55.Google Scholar
Zhu, G, Michel, P, Aghaebrahim, A, et al. Prediction of recanalization trumps prediction of tissue fate: the penumbra: a dual-edged sword. Stroke 2013; 44: 1014–19.CrossRefGoogle ScholarPubMed
Silvennoinen, HM, Hamberg, LM, Lindsberg, PJ, Valanne, L, Hunter, GJ. CT perfusion identifies increased salvage of tissue in patients receiving intravenous recombinant tissue plasminogen activator within 3 hours of stroke onset. AJNR Am J Neuroradiol 2008; 29: 1118–23.Google Scholar
Psychogios, M-N, Schramm, P, Frölich, AM, et al. Alberta Stroke Program Early CT Scale evaluation of multimodal computed tomography in predicting clinical outcomes of stroke patients treated with aspiration thrombectomy. Stroke 2013; 44: 2188–93.CrossRefGoogle ScholarPubMed
Lansberg, MG, Christensen, S, Kemp, S, et al. Computed tomographic perfusion to predict response to recanalization in ischemic stroke. Ann Neurol 2017; 81: 849–56.Google Scholar
Borst, J, Berkhemer, OA, Roos, YBWEM, et al. Value of computed tomographic perfusion-based patient selection for intra-arterial acute ischemic stroke treatment. Stroke 2015; 46: 3375–82.Google Scholar
Campbell, BCV, Mitchell, PJ, Kleinig, TJ, et al. Endovascular therapy for ischemic stroke with perfusion-imaging selection. N Engl J Med 2015; 372: 1009–18.Google Scholar
Nogueira, RG, Jadhav, AP, Haussen, DC, et al. Thrombectomy 6 to 24 hours after stroke with a mismatch between deficit and infarct. N Engl J Med 2018; 378: 11–21.Google Scholar
Albers, GW, Marks, MP, Kemp, S, et al. Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging. N Engl J Med 2018; 378: 708–18.CrossRefGoogle ScholarPubMed
Tsetsou, S, Amiguet, M, Eskandari, A, et al. Severe cerebral hypovolemia on perfusion CT and lower body weight are associated with parenchymal haemorrhage after thrombolysis. Neuroradiology 2017; 59: 23–9.Google Scholar
Hermitte, L, Cho, T-H, Ozenne, B, et al. Very low cerebral blood volume predicts parenchymal hematoma in acute ischemic stroke. Stroke 2013; 44: 2318–20.Google Scholar
Minnerup, J, Wersching, H, Ringelstein, EB, et al. Prediction of malignant middle cerebral artery infarction using computed tomography-based intracranial volume reserve measurements. Stroke 2011; 42: 3403–9.CrossRefGoogle ScholarPubMed
Bektas, H, Wu, T-C, Kasam, M, et al. Increased blood–brain barrier permeability on perfusion CT might predict malignant middle cerebral artery infarction. Stroke 2010; 41: 2539–44.Google Scholar
Rotzinger, DC, Mosimann, PJ, Meuli, RA, Maeder, P, Michel, P. Site and rate of occlusive disease in cervicocerebral arteries: a CT angiography study of 2209 patients with acute ischemic stroke. AJNR Am J Neuroradiol 2017; 38: 868–74.Google Scholar
Bash, S, Villablanca, JP, Jahan, R, et al. Intracranial vascular stenosis and occlusive disease: evaluation with CT angiography, MR angiography, and digital subtraction angiography. AJNR Am J Neuroradiol 2005; 26: 1012–21.Google Scholar
Knauth, M, von Kummer, R, Jansen, O, et al. Potential of CT angiography in acute ischemic stroke. AJNR Am J Neuroradiol 1997; 18: 1001–10.Google Scholar
Riedel, CH, Zimmermann, P, Jensen-Kondering, U, et al. The importance of size: successful recanalization by intravenous thrombolysis in acute anterior stroke depends on thrombus length. Stroke 2011; 42: 1775–7.CrossRefGoogle ScholarPubMed
Riedel, CH, Yoo, AJ. Clot characterization by noncontrast CT to predict IV tPA failure. AJNR Am J Neuroradiol 2012; 33: E63; author reply E64.CrossRefGoogle ScholarPubMed
Puetz, V, Dzialowski, I, Hill, MD, et al. Intracranial thrombus extent predicts clinical outcome, final infarct size and hemorrhagic transformation in ischemic stroke: the clot burden score. Int J Stroke Off J Int Stroke Soc 2008; 3: 230–6.Google ScholarPubMed
Medlin, F, Amiguet, M, Vanacker, P, Michel, P. Influence of arterial occlusion on outcome after intravenous thrombolysis for acute ischemic stroke. Stroke 2015; 46: 126–31.Google Scholar
Smith, WS, Schwab, S. Advances in stroke: critical care and emergency medicine. Stroke 2012; 43: 308–9.Google Scholar
González, RG, Lev, MH, Goldmacher, GV, et al. Improved outcome prediction using CT angiography in addition to standard ischemic stroke assessment: results from the STOPStroke study. PloS One 2012; 7: e30352.Google Scholar
Tan, IYL, Demchuk, AM, Hopyan, J, et al. CT angiography clot burden score and collateral score: correlation with clinical and radiologic outcomes in acute middle cerebral artery infarct. AJNR Am J Neuroradiol 2009; 30: 525–31.Google Scholar
Saarinen, JT, Sillanpää, N, Rusanen, H, et al. The mid-M1 segment of the middle cerebral artery is a cutoff clot location for good outcome in intravenous thrombolysis. Eur J Neurol 2012; 19: 1121–7.Google Scholar
Menon, BK, Smith, EE, Modi, J, et al. Regional leptomeningeal score on CT angiography predicts clinical and imaging outcomes in patients with acute anterior circulation occlusions. AJNR Am J Neuroradiol 2011; 32: 1640–5.CrossRefGoogle Scholar
Tan, JC, Dillon, WP, Liu, S, et al. Systematic comparison of perfusion-CT and CT-angiography in acute stroke patients. Ann Neurol 2007; 61: 533–43.CrossRefGoogle ScholarPubMed
Miteff, F, Levi, CR, Bateman, GA, et al. The independent predictive utility of computed tomography angiographic collateral status in acute ischaemic stroke. Brain J Neurol 2009; 132: 2231–8.Google Scholar
Angermaier, A, Langner, S, Kirsch, M, et al. CT-angiographic collateralization predicts final infarct volume after intra-arterial thrombolysis for acute anterior circulation ischemic stroke. Cerebrovasc Dis Basel Switz 2011; 31: 177–84.Google Scholar
Goyal, M, Demchuk, AM, Menon, BK, et al. Randomized assessment of rapid endovascular treatment of ischemic stroke. N Engl J Med 2015; 372: 1019–30.Google Scholar
Schramm, P, Schellinger, PD, Fiebach, JB, et al. Comparison of CT and CT angiography source images with diffusion-weighted imaging in patients with acute stroke within 6 hours after onset. Stroke 2002; 33: 2426–32.Google Scholar
Lev, MH, Segal, AZ, Farkas, J, et al. Utility of perfusion-weighted CT imaging in acute middle cerebral artery stroke treated with intra-arterial thrombolysis: prediction of final infarct volume and clinical outcome. Stroke 2001; 32: 2021–8.Google Scholar
Puetz, V, Sylaja, PN, Hill, MD, et al. CT angiography source images predict final infarct extent in patients with basilar artery occlusion. AJNR Am J Neuroradiol 2009; 30: 1877–83.Google Scholar
Demchuk, AM, Dowlatshahi, D, Rodriguez-Luna, D, et al. Prediction of haematoma growth and outcome in patients with intracerebral haemorrhage using the CT-angiography spot sign (PREDICT): a prospective observational study. Lancet Neurol 2012; 11: 307–14.Google Scholar
Fainardi, E, Borrelli, M, Saletti, A, et al. CT perfusion mapping of hemodynamic disturbances associated to acute spontaneous intracerebral hemorrhage. Neuroradiology 2008; 50: 729–40.Google Scholar
Fiebach, JB, Schellinger, PD, Jansen, O, et al. CT and diffusion-weighted MR imaging in randomized order: diffusion-weighted imaging results in higher accuracy and lower interrater variability in the diagnosis of hyperacute ischemic stroke. Stroke 2002; 33: 2206–10.Google Scholar
Chalela, JA, Kidwell, CS, Nentwich, LM, et al. Magnetic resonance imaging and computed tomography in emergency assessment of patients with suspected acute stroke: a prospective comparison. Lancet Lond Engl 2007; 369: 293–8.Google Scholar
von Kummer, R, Bourquain, H, Bastianello, S, et al. Early prediction of irreversible brain damage after ischemic stroke at CT. Radiology 2001; 219: 95–100.Google Scholar
Sedlaczek, O, Hirsch, JG, Grips, E, et al. Detection of delayed focal MR changes in the lateral hippocampus in transient global amnesia. Neurology 2004; 62: 2165–70.Google Scholar
Chatzikonstantinou, A, Gass, A, Förster, A, Hennerici, MG, Szabo, K. Features of acute DWI abnormalities related to status epilepticus. Epilepsy Res 2011; 97: 45–51.Google Scholar
Eisele, P, Szabo, K, Griebe, M, et al. Reduced diffusion in a subset of acute MS lesions: a serial multiparametric MRI study. AJNR Am J Neuroradiol 2012; 33: 1369–73.Google Scholar
Ma, L, Gao, P-Y, Lin, Y, et al. Can baseline magnetic resonance angiography (MRA) status become a foremost factor in selecting optimal acute stroke patients for recombinant tissue plasminogen activator (rt-PA) thrombolysis beyond 3 hours? Neurol Res 2009; 31: 355–61.Google Scholar
Chemmanam, T, Campbell, BCV, Christensen, S, et al. Ischemic diffusion lesion reversal is uncommon and rarely alters perfusion-diffusion mismatch. Neurology 2010; 75: 1040–7.Google Scholar
Fiehler, J, Knudsen, K, Kucinski, T, et al. Predictors of apparent diffusion coefficient normalization in stroke patients. Stroke 2004; 35: 514–19.Google Scholar
Yoo, AJ, Barak, ER, Copen, WA, et al. Combining acute diffusion-weighted imaging and mean transmit time lesion volumes with National Institutes of Health Stroke Scale Score improves the prediction of acute stroke outcome. Stroke 2010; 41: 1728–35.Google Scholar
Parsons, MW, Christensen, S, McElduff, P, et al. Pretreatment diffusion- and perfusion-MR lesion volumes have a crucial influence on clinical response to stroke thrombolysis. J Cereb Blood Flow Metab 2010; 30: 1214–25.Google Scholar
Mlynash, M, Lansberg, MG, De Silva, DA, et al. Refining the definition of the malignant profile: insights from the DEFUSE-EPITHET pooled data set. Stroke 2011; 42: 1270–5.Google Scholar
Thomalla, G, Cheng, B, Ebinger, M, et al. DWI-FLAIR mismatch for the identification of patients with acute ischaemic stroke within 4·5 h of symptom onset (PRE-FLAIR): a multicentre observational study. Lancet Neurol 2011; 10: 978–86.Google Scholar
Mackey, J, Kleindorfer, D, Sucharew, H, et al. Population-based study of wake-up strokes. Neurology 2011; 76: 1662–7.Google Scholar
Thomalla, G, Simonsen, CZ, Boutitie, F, et al. MRI-guided thrombolysis for stroke with unknown time of onset. N Engl J Med 2018; 379: 611–22.Google Scholar
Fiebach, JB, Al-Rawi, Y, Wintermark, M, et al. Vascular occlusion enables selecting acute ischemic stroke patients for treatment with desmoteplase. Stroke 2012; 43: 1561–6.Google Scholar
Fiehler, J, Knudsen, K, Thomalla, G, et al. Vascular occlusion sites determine differences in lesion growth from early apparent diffusion coefficient lesion to final infarct. AJNR Am J Neuroradiol 2005; 26: 1056–61.Google Scholar
Schellinger, PD, Chalela, JA, Kang, D-W, Latour, LL, Warach, S. Diagnostic and prognostic value of early MR imaging vessel signs in hyperacute stroke patients imaged <3 hours and treated with recombinant tissue plasminogen activator. AJNR Am J Neuroradiol 2005; 26: 618–24.Google Scholar
Galinovic, I, Ostwaldt, A-C, Soemmer, C, et al. Search for a map and threshold in perfusion MRI to accurately predict tissue fate: a protocol for assessing lesion growth in patients with persistent vessel occlusion. Cerebrovasc Dis Basel Switz 2011; 32: 186–93.Google Scholar
Rovira, A, Orellana, P, Alvarez-Sabín, J, et al. Hyperacute ischemic stroke: middle cerebral artery susceptibility sign at echo-planar gradient-echo MR imaging. Radiology 2004; 232: 466–73.Google Scholar
Thomalla, G, Schwark, C, Sobesky, J, et al. Outcome and symptomatic bleeding complications of intravenous thrombolysis within 6 hours in MRI-selected stroke patients: comparison of a German multicenter study with the pooled data of ATLANTIS, ECASS, and NINDS tPA trials. Stroke 2006; 37: 852–8.Google Scholar
Hacke, W, Albers, G, Al-Rawi, Y, et al. The Desmoteplase in Acute Ischemic Stroke Trial (DIAS): a phase II MRI-based 9-hour window acute stroke thrombolysis trial with intravenous desmoteplase. Stroke 2005; 36: 66–73.Google Scholar
Butcher, K, Parsons, M, Allport, L, et al. Rapid assessment of perfusion-diffusion mismatch. Stroke 2008; 39: 75–81.Google Scholar
Albers, GW, Thijs, VN, Wechsler, L, et al. Magnetic resonance imaging profiles predict clinical response to early reperfusion: the diffusion and perfusion imaging evaluation for understanding stroke evolution (DEFUSE) study. Ann Neurol 2006; 60: 508–17.CrossRefGoogle ScholarPubMed
Davis, SM, Donnan, GA, Parsons, MW, et al. Effects of alteplase beyond 3 h after stroke in the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET): a placebo-controlled randomised trial. Lancet Neurol 2008; 7: 299–309.Google Scholar
Warach, SJ, Luby, M, Albers, GW, et al. Acute stroke imaging research roadmap III imaging selection and outcomes in acute stroke reperfusion clinical trials: consensus recommendations and further research priorities. Stroke 2016; 47: 1389–98.Google Scholar
Nagakane, Y, Christensen, S, Brekenfeld, C, et al. EPITHET: positive result after reanalysis using baseline diffusion-weighted imaging/perfusion-weighted imaging co-registration. Stroke 2011; 42: 59–64.Google Scholar
Lansberg, MG, Straka, M, Kemp, S, et al. MRI profile and response to endovascular reperfusion after stroke (DEFUSE 2): a prospective cohort study. Lancet Neurol 2012; 11: 860–7.Google Scholar
Kidwell, CS, Alger, JR, Saver, JL. Beyond mismatch: evolving paradigms in imaging the ischemic penumbra with multimodal magnetic resonance imaging. Stroke 2003; 34: 2729–35.Google Scholar
Kucinski, T, Naumann, D, Knab, R, et al. Tissue at risk is overestimated in perfusion-weighted imaging: MR imaging in acute stroke patients without vessel recanalization. AJNR Am J Neuroradiol 2005; 26: 815–19.Google Scholar
Zaharchuk, G, El Mogy, IS, Fischbein, NJ, Albers, GW. Comparison of arterial spin labeling and bolus perfusion-weighted imaging for detecting mismatch in acute stroke. Stroke 2012; 43: 1843–8.Google ScholarPubMed
Bokkers, RPH, Hernandez, DA, Merino, JG, et al. Whole-brain arterial spin labeling perfusion MRI in patients with acute stroke. Stroke 2012; 43: 1290–4.Google Scholar
Niibo, T, Ohta, H, Yonenaga, K, et al. Arterial spin-labeled perfusion imaging to predict mismatch in acute ischemic stroke. Stroke 2013; 44: 2601–3.Google Scholar
Kidwell, CS, Chalela, JA, Saver, JL, et al. Comparison of MRI and CT for detection of acute intracerebral hemorrhage. JAMA 2004; 292: 1823–30.Google Scholar
Fiehler, J. Cerebral microbleeds: old leaks and new haemorrhages. Int J Stroke 2006; 1: 122–30.CrossRefGoogle ScholarPubMed
Fiehler, J, Albers, GW, Boulanger, J-M, et al. Bleeding risk analysis in stroke imaging before thrombolysis (BRASIL): pooled analysis of T2*-weighted magnetic resonance imaging data from 570 patients. Stroke 2007; 38: 2738–44.Google Scholar
Tanikawa, M, Mase, M, Yamada, K, et al. Surgical treatment of chronic subdural hematoma based on intrahematomal membrane structure on MRI. Acta Neurochir (Wien) 2001; 143: 613–18; discussion 618–19.Google Scholar
Wiesmann, M, Mayer, TE, Yousry, I, et al. Detection of hyperacute subarachnoid hemorrhage of the brain by using magnetic resonance imaging. J Neurosurg 2002; 96: 684–9.Google Scholar
Baird, AE, Benfield, A, Schlaug, G, et al. Enlargement of human cerebral ischemic lesion volumes measured by diffusion-weighted magnetic resonance imaging. Ann Neurol 1997; 41: 581–9.Google Scholar
Schaefer, PW, Barak, ER, Kamalian, S, et al. Quantitative assessment of core/penumbra mismatch in acute stroke: CT and MR perfusion imaging are strongly correlated when sufficient brain volume is imaged. Stroke 2008; 39: 2986–92.Google Scholar
Wintermark, M, Reichhart, M, Cuisenaire, O, et al. Comparison of admission perfusion computed tomography and qualitative diffusion- and perfusion-weighted magnetic resonance imaging in acute stroke patients. Stroke 2002; 33: 2025–31.Google Scholar
Wintermark, M, Meuli, R, Browaeys, P, et al. Comparison of CT perfusion and angiography and MRI in selecting stroke patients for acute treatment. Neurology 2007; 68: 694–7.Google Scholar
Dani, KA, Thomas, RGR, Chappell, FM, et al. Computed tomography and magnetic resonance perfusion imaging in ischemic stroke: definitions and thresholds. Ann Neurol 2011; 70: 384–401.Google Scholar
Wintermark, M, Maeder, P, Thiran, JP, Schnyder, P, Meuli, R. Quantitative assessment of regional cerebral blood flows by perfusion CT studies at low injection rates: a critical review of the underlying theoretical models. Eur Radiol 2001; 11: 1220–30.Google Scholar
Liu, Y, Karonen, JO, Vanninen, RL, et al. Acute ischemic stroke: predictive value of 2D phase-contrast MR angiography – serial study with combined diffusion and perfusion MR imaging. Radiology 2004; 231: 517–27.Google Scholar
Schievink, WI. Spontaneous dissection of the carotid and vertebral arteries. N Engl J Med 2001; 344: 898–906.Google Scholar
Lev, MH, Koroshetz, WJ, Schwamm, LH, Gonzalez, RG. CT or MRI for imaging patients with acute stroke: visualization of “tissue at risk”? Stroke 2002; 33: 2736–7.Google Scholar
Mnyusiwalla, A, Aviv, RI, Symons, SP. Radiation dose from multidetector row CT imaging for acute stroke. Neuroradiology 2009; 51: 635–40.Google Scholar
Smith-Bindman, R, Lipson, J, Marcus, R, et al. Radiation dose associated with common computed tomography examinations and the associated lifetime attributable risk of cancer. Arch Intern Med 2009; 169: 2078–86.Google Scholar
Aulicky, P, Mikulík, R, Goldemund, D, et al. Safety of performing CT angiography in stroke patients treated with intravenous thrombolysis. J Neurol Neurosurg Psychiatry 2010; 81: 783–7.Google Scholar
Thomsen, HS, European Society of Urogenital Radiology (ESUR). ESUR guideline: gadolinium-based contrast media and nephrogenic systemic fibrosis. Eur Radiol 2007; 17: 2692–6.Google Scholar
Mortimer, AM, Simpson, E, Bradley, MD, Renowden, SA. Computed tomography angiography in hyperacute ischemic stroke: prognostic implications and role in decision-making. Stroke 2013; 44: 1480–8.Google Scholar
Kidwell, CS, Jahan, R, Gornbein, J, et al. A trial of imaging selection and endovascular treatment for ischemic stroke. N Engl J Med 2013; 368: 914–23.Google Scholar
Ogata, T, Christensen, S, Nagakane, Y, et al. The effects of alteplase 3 to 6 hours after stroke in the EPITHET-DEFUSE combined dataset: post hoc case-control study. Stroke 2013; 44: 87–93.CrossRefGoogle ScholarPubMed
Sztriha, LK, Manawadu, D, Jarosz, J, Keep, J, Kalra, L. Safety and clinical outcome of thrombolysis in ischaemic stroke using a perfusion CT mismatch between 3 and 6 hours. PloS One 2011; 6: e25796.Google Scholar
Obach, V, Oleaga, L, Urra, X, et al. Multimodal CT-assisted thrombolysis in patients with acute stroke: a cohort study. Stroke 2011; 42: 1129–31.Google Scholar
Hassan, AE, Zacharatos, H, Rodriguez, GJ, et al. A comparison of computed tomography perfusion-guided and time-guided endovascular treatments for patients with acute ischemic stroke. Stroke 2010; 41: 1673–8.Google Scholar
Warach, S, Al-Rawi, Y, Furlan, AJ, et al. Refinement of the magnetic resonance diffusion-perfusion mismatch concept for thrombolytic patient selection: insights from the desmoteplase in acute stroke trials. Stroke 2012; 43: 2313–18.Google Scholar
Saver, JL, Goyal, M, van der Lugt, A, et al. Time to treatment with endovascular thrombectomy and outcomes from ischemic stroke: a meta-analysis. JAMA 2016; 316: 1279–88.CrossRefGoogle ScholarPubMed