Infarct Evolution in a Large Animal Model of Middle Cerebral Artery Occlusion

  • Mohammed Salman ShazeebEmail author
  • Robert M. King
  • Olivia W. Brooks
  • Ajit S. Puri
  • Nils Henninger
  • Johannes Boltze
  • Matthew J. Gounis
Original Article


Mechanical thrombectomy for the treatment of ischemic stroke shows high rates of recanalization; however, some patients still have a poor clinical outcome. A proposed reason for this relates to the fact that the ischemic infarct growth differs significantly between patients. While some patients demonstrate rapid evolution of their infarct core (fast evolvers), others have substantial potentially salvageable penumbral tissue even hours after initial vessel occlusion (slow evolvers). We show that the dog middle cerebral artery occlusion model recapitulates this key aspect of human stroke rendering it a highly desirable model to develop novel multimodal treatments to improve clinical outcomes. Moreover, this model is well suited to develop novel image analysis techniques that allow for improved lesion evolution prediction; we provide proof-of-concept that MRI perfusion-based time-to-peak maps can be utilized to predict the rate of infarct growth as validated by apparent diffusion coefficient-derived lesion maps allowing reliable classification of dogs into fast versus slow evolvers enabling more robust study design for interventional research.


Dog Middle cerebral artery occlusion Infarct growth rate Perfusion MRI Time-to-peak Stroke 


Authors’ Contributions

The concept of study was developed by Matthew Gounis, Nils Henninger, Johannes Boltze, and Ajit Puri. Robert King and Matthew Gounis performed the animal experiments and collected the imaging data. Olivia Brooks performed data analysis. Mohammed Salman Shazeeb developed the image analysis pipeline, performed image analysis, and wrote the manuscript. Robert King also performed image analysis. Mathew Gounis, Nils Henninger, Johannes Boltze, and Robert King made significant edits to the manuscript for intellectual content. All authors read and approved the final manuscript.

Funding Information

Dr. Henninger is supported by K08NS091499 from the National Institute of Neurological Disorders and Stroke (NINDS) of the National Institutes of Health (NIH). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Dr. Gounis has received research support from the NIH, the United States–Israel Binational Science Foundation, Anaconda, Cerenovus, Ceretrieve, Cook Medical, Gentuity, Imperative Care, InNeuroCo, Magneto, Microvention, Medtronic Neurovascular, MIVI Neurosciences, Neuravi, Neurogami, Philips Healthcare, Rapid Medical, Route 92 Medical, Stryker Neurovascular, Syntheon, and the Wyss Institute.

Compliance with Ethical Standards

Conflict of Interest

Dr. Henninger is supported by K08NS091499 from the National Institute of Neurological Disorders and Stroke of the National Institutes of Health (NIH). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Dr. Henninger serves on the advisory board of Omniox, Inc. and serves as consultant to Astrocyte Pharmaceuticals, Inc. Dr. Gounis has been a consultant on a fee-per-hour basis for Cerenovus, Imperative Care, Mivi Neurosciences, Phenox, Route 92 Medical, Stryker Neurovascular; holds stock in Imperative Care and Neurogami; and has received research support from the NIH, the United States–Israel Binational Science Foundation, Anaconda, Cerenovus, Ceretrieve, Cook Medical, Gentuity, Imperative Care, InNeuroCo, Magneto, Microvention, Medtronic Neurovascular, MIVI Neurosciences, Neuravi, Neurogami, Philips Healthcare, Rapid Medical, Route 92 Medical, Stryker Neurovascular, Syntheon, and the Wyss Institute. All authors declare that they have no potential conflicts of interest in regard to the research, authorship, and publication of this paper.

Ethical Approval

All animal research procedures were performed as approved by the Institutional Animal Care and Use Committee (IACUC) of the University of Massachusetts Medical School (Worcester, MA, USA). This article does not contain any studies with human participants performed by any of the authors.


  1. 1.
    Saver JL, Goyal M, Bonafe A, Diener HC, Levy EI, Pereira VM, et al. Stent-retriever thrombectomy after intravenous t-PA vs. t-PA alone in stroke. N Engl J Med. 2015;372(24):2285–95. Scholar
  2. 2.
    Jovin TG, Chamorro A, Cobo E, de Miquel MA, Molina CA, Rovira A, et al. Thrombectomy within 8 hours after symptom onset in ischemic stroke. N Engl J Med. 2015;372(24):2296–306. Scholar
  3. 3.
    Campbell BC, Mitchell PJ, Kleinig TJ, Dewey HM, Churilov L, Yassi N, et al. Endovascular therapy for ischemic stroke with perfusion-imaging selection. N Engl J Med. 2015;372(11):1009–18. Scholar
  4. 4.
    Blanc R, Redjem H, Ciccio G, Smajda S, Desilles JP, Orng E, et al. Predictors of the aspiration component success of a direct aspiration first pass technique (ADAPT) for the endovascular treatment of stroke reperfusion strategy in anterior circulation acute stroke. Stroke. 2017;48(6):1588–93. Scholar
  5. 5.
    Mikati AG, Mandelbaum M, Sapnar S, Puri AS, Silver B, Goddeau RP, Jr. et al.. Impact of leukoaraiosis severity on the association of time to successful reperfusion with 90-day functional outcome after large vessel occlusion stroke. Transl Stroke Res. 2019. doi:
  6. 6.
    Bang OY, Goyal M, Liebeskind DS. Collateral circulation in ischemic stroke: assessment tools and therapeutic strategies. Stroke. 2015;46(11):3302–9. Scholar
  7. 7.
    Shuaib A, Butcher K, Mohammad AA, Saqqur M, Liebeskind DS. Collateral blood vessels in acute ischaemic stroke: a potential therapeutic target. Lancet Neurol. 2011;10(10):909–21. Scholar
  8. 8.
    Winship IR, Armitage GA, Ramakrishnan G, Dong B, Todd KG, Shuaib A. Augmenting collateral blood flow during ischemic stroke via transient aortic occlusion. J Cereb Blood Flow Metab. 2014;34(1):61–71. Scholar
  9. 9.
    Henninger N, Fisher M. Stimulating circle of Willis nerve fibers preserves the diffusion-perfusion mismatch in experimental stroke. Stroke. 2007;38(10):2779–86. Scholar
  10. 10.
    Shin HK, Nishimura M, Jones PB, Ay H, Boas DA, Moskowitz MA, et al. Mild induced hypertension improves blood flow and oxygen metabolism in transient focal cerebral ischemia. Stroke. 2008;39(5):1548–55. Scholar
  11. 11.
    Terpolilli NA, Kim SW, Thal SC, Kataoka H, Zeisig V, Nitzsche B, et al. Inhalation of nitric oxide prevents ischemic brain damage in experimental stroke by selective dilatation of collateral arterioles. Circ Res. 2012;110(5):727–38. Scholar
  12. 12.
    Bratane BT, Cui H, Cook DJ, Bouley J, Tymianski M, Fisher M. Neuroprotection by freezing ischemic penumbra evolution without cerebral blood flow augmentation with a postsynaptic density-95 protein inhibitor. Stroke. 2011;42(11):3265–70. Scholar
  13. 13.
    Hill MD, Martin RH, Mikulis D, Wong JH, Silver FL, Terbrugge KG, et al. Safety and efficacy of NA-1 in patients with iatrogenic stroke after endovascular aneurysm repair (ENACT): a phase 2, randomised, double-blind, placebo-controlled trial. Lancet Neurol. 2012;11(11):942–50. Scholar
  14. 14.
    Sun HS, Doucette TA, Liu Y, Fang Y, Teves L, Aarts M, et al. Effectiveness of PSD95 inhibitors in permanent and transient focal ischemia in the rat. Stroke. 2008;39(9):2544–53. Scholar
  15. 15.
    Fisher M, Saver JL. Future directions of acute ischaemic stroke therapy. Lancet Neurol. 2015;14(7):758–67. Scholar
  16. 16.
    Bacigaluppi M, Comi G, Hermann DM. Animal models of ischemic stroke. Part two: modeling cerebral ischemia. Open Neurol J. 2010;4:34–8. Scholar
  17. 17.
    Jahan R, Stewart D, Vinters HV, Yong W, Vinuela F, Vandeberg P, et al. Middle cerebral artery occlusion in the rabbit using selective angiography: application for assessment of thrombolysis. Stroke. 2008;39(5):1613–5. Scholar
  18. 18.
    Wey HY, Kroma GM, Li J, Leland MM, Jones L, Duong TQ. MRI of perfusion-diffusion mismatch in non-human primate (baboon) stroke: a preliminary report. Open Neuroimaging J. 2011;5:147–52. Scholar
  19. 19.
    Zhang X, Tong F, Li CX, Yan Y, Kempf D, Nair G, et al. Temporal evolution of ischemic lesions in nonhuman primates: a diffusion and perfusion MRI study. PLoS One. 2015;10(2):e0117290. Scholar
  20. 20.
    Hill NC, Millikan CH, Wakim KG, Sayre GP. Studies in cerebrovascular disease. VII. Experimental production of cerebral infarction by intracarotid injection of homologous blood clot: preliminary report. Mayo Clin Proc. 1955;30(26):625–33.Google Scholar
  21. 21.
    Molinari GF. Experimental cerebral infarction. I. Selective segmental occlusion of intracranial arteries in the dog. Stroke. 1970;1(4):224–31.CrossRefGoogle Scholar
  22. 22.
    Rink C, Christoforidis G, Abduljalil A, Kontzialis M, Bergdall V, Roy S, et al. Minimally invasive neuroradiologic model of preclinical transient middle cerebral artery occlusion in canines. Proc Natl Acad Sci U S A. 2008;105(37):14100–5. Scholar
  23. 23.
    Purdy PD, Devous MD Sr, Batjer HH, White CL 3rd, Meyer Y, Samson DS. Microfibrillar collagen model of canine cerebral infarction. Stroke. 1989;20(10):1361–7.CrossRefGoogle Scholar
  24. 24.
    Harris AD, Kosior JC, Ryder RC, Andersen LB, Hu WY, Hudon M, et al. MRI of ischemic stroke in canines: applications for monitoring intraarterial thrombolysis. J Magn Reson Imaging. 2007;26(6):1421–8. Scholar
  25. 25.
    Shaibani A, Khawar S, Shin W, Cashen TA, Schirf B, Rohany M, et al. First results in an MR imaging—compatible canine model of acute stroke. AJNR Am J Neuroradiol. 2006;27(8):1788–93.PubMedGoogle Scholar
  26. 26.
    Ahmed AS, Zellerhoff M, Strother CM, Pulfer KA, Redel T, Deuerling-Zheng Y, et al. C-arm CT measurement of cerebral blood volume: an experimental study in canines. AJNR Am J Neuroradiol. 2009;30(5):917–22.CrossRefGoogle Scholar
  27. 27.
    van der Bom IMJ, Mehra M, Walvick RP, Chueh J-Y, Gounis MJ. Quantitative evaluation of c-arm CT CBV in a canine model of ischemic stroke. AJNR Am J Neuroradiol. 2011;33:353–8.PubMedGoogle Scholar
  28. 28.
    Brooks OW, King RM, Nossek E, Marosfoi M, Caroff J, Chueh JY et al.. A canine model of mechanical thrombectomy in stroke. J Neurointerv Surg. 2019. doi:
  29. 29.
    Anderson WD, Kubicek W. The vertebral-basilar system of dog in relation to man and other mammals. Am J Anat. 1971;132(2):179–88. Scholar
  30. 30.
    Wells AJ, Vink R, Blumbergs PC, Brophy BP, Helps SC, Knox SJ, et al. A surgical model of permanent and transient middle cerebral artery stroke in the sheep. PLoS One. 2012;7(7):e42157. Scholar
  31. 31.
    Boltze J, Forschler A, Nitzsche B, Waldmin D, Hoffmann A, Boltze CM, et al. Permanent middle cerebral artery occlusion in sheep: a novel large animal model of focal cerebral ischemia. J Cereb Blood Flow Metab. 2008;28(12):1951–64. Scholar
  32. 32.
    Platt SR, Holmes SP, Howerth EW, Duberstein KJJ, Dove CR, Kinder HA, et al. Development and characterization of a Yucatan miniature biomedical pig permanent middle cerebral artery occlusion stroke model. Exp Transl Stroke Med. 2014;6(1):5. Scholar
  33. 33.
    Mehra M, Henninger N, Hirsch JA, Chueh J, Wakhloo AK, Gounis MJ. Preclinical acute ischemic stroke modeling. J Neurointerv Surg. 2012;4(4):307–13. Scholar
  34. 34.
    Herrmann AM, Meckel S, Gounis MJ, Kringe L, Motschall E, Mulling C, et al. Large animals in neurointerventional research: a systematic review on models, techniques and their application in endovascular procedures for stroke, aneurysms and vascular malformations. J Cereb Blood Flow Metab. 2019;39(3):375–94. Scholar
  35. 35.
    Kang BT, Lee JH, Jung DI, Park C, Gu SH, Jeon HW, et al. Canine model of ischemic stroke with permanent middle cerebral artery occlusion: clinical and histopathological findings. J Vet Sci. 2007;8(4):369–76.CrossRefGoogle Scholar
  36. 36.
    Harris AD, Kosior RK, Chen HS, Andersen LB, Frayne R. Evolution of hyperacute stroke over 6 hours using serial MR perfusion and diffusion maps. J Magn Reson Imaging. 2009;29(6):1262–70. Scholar
  37. 37.
    Christoforidis GA, Vakil P, Ansari SA, Dehkordi FH, Carroll TJ. Impact of pial collaterals on infarct growth rate in experimental acute ischemic stroke. AJNR Am J Neuroradiol. 2017;38(2):270–5. Scholar
  38. 38.
    Rocha M, Jovin TG. Fast versus slow progressors of infarct growth in large vessel occlusion stroke: clinical and research implications. Stroke. 2017;48(9):2621–7. Scholar
  39. 39.
    Wheeler HM, Mlynash M, Inoue M, Tipirnini A, Liggins J, Bammer R, et al. The growth rate of early DWI lesions is highly variable and associated with penumbral salvage and clinical outcomes following endovascular reperfusion. Int J Stroke. 2015;10(5):723–9. Scholar
  40. 40.
    Ribo M, Molina CA, Cobo E, Cerda N, Tomasello A, Quesada H, et al. Association between time to reperfusion and outcome is primarily driven by the time from imaging to reperfusion. Stroke. 2016;47(4):999–1004. Scholar
  41. 41.
    Copen WA, Rezai Gharai L, Barak ER, Schwamm LH, Wu O, Kamalian S, et al. Existence of the diffusion-perfusion mismatch within 24 hours after onset of acute stroke: dependence on proximal arterial occlusion. Radiology. 2009;250(3):878–86. Scholar
  42. 42.
    Marchal G, Beaudouin V, Rioux P, de la Sayette V, Le Doze F, Viader F, et al. Prolonged persistence of substantial volumes of potentially viable brain tissue after stroke: a correlative PET-CT study with voxel-based data analysis. Stroke. 1996;27(4):599–606.CrossRefGoogle Scholar
  43. 43.
    Schellinger PD, Jansen O, Fiebach JB, Heiland S, Steiner T, Schwab S, et al. Monitoring intravenous recombinant tissue plasminogen activator thrombolysis for acute ischemic stroke with diffusion and perfusion MRI. Stroke. 2000;31(6):1318–28.CrossRefGoogle Scholar
  44. 44.
    Wu O, Koroshetz WJ, Ostergaard L, Buonanno FS, Copen WA, Gonzalez RG, et al. Predicting tissue outcome in acute human cerebral ischemia using combined diffusion- and perfusion-weighted MR imaging. Stroke. 2001;32(4):933–42.CrossRefGoogle Scholar
  45. 45.
    Ostergaard L, Sorensen AG, Chesler DA, Weisskoff RM, Koroshetz WJ, Wu O, et al. Combined diffusion-weighted and perfusion-weighted flow heterogeneity magnetic resonance imaging in acute stroke. Stroke. 2000;31(5):1097–103.CrossRefGoogle Scholar
  46. 46.
    Schaefer PW, Hunter GJ, He J, Hamberg LM, Sorensen AG, Schwamm LH, et al. Predicting cerebral ischemic infarct volume with diffusion and perfusion MR imaging. AJNR Am J Neuroradiol. 2002;23(10):1785–94.PubMedGoogle Scholar
  47. 47.
    Wheeler HM, Mlynash M, Inoue M, Tipirneni A, Liggins J, Zaharchuk G, et al. Early diffusion-weighted imaging and perfusion-weighted imaging lesion volumes forecast final infarct size in DEFUSE 2. Stroke. 2013;44(3):681–5. Scholar
  48. 48.
    Olivot JM, Mlynash M, Thijs VN, Purushotham A, Kemp S, Lansberg MG, et al. Geography, structure, and evolution of diffusion and perfusion lesions in Diffusion and perfusion imaging Evaluation For Understanding Stroke Evolution (DEFUSE). Stroke. 2009;40(10):3245–51. Scholar
  49. 49.
    Rordorf G, Koroshetz WJ, Copen WA, Cramer SC, Schaefer PW, Budzik RF Jr, et al. Regional ischemia and ischemic injury in patients with acute middle cerebral artery stroke as defined by early diffusion-weighted and perfusion-weighted MRI. Stroke. 1998;29(5):939–43.CrossRefGoogle Scholar
  50. 50.
    Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161(2):401–7. Scholar
  51. 51.
    Wesbey GE, Moseley ME, Ehman RL. Translational molecular self-diffusion in magnetic resonance imaging. II. Measurement of the self-diffusion coefficient. Investig Radiol. 1984;19(6):491–8.CrossRefGoogle Scholar
  52. 52.
    Moseley ME, Cohen Y, Mintorovitch J, Chileuitt L, Shimizu H, Kucharczyk J, et al. Early detection of regional cerebral ischemia in cats: comparison of diffusion- and T2-weighted MRI and spectroscopy. Magn Reson Med. 1990;14(2):330–46.CrossRefGoogle Scholar
  53. 53.
    Copen WA, Schaefer PW, Wu O. MR perfusion imaging in acute ischemic stroke. Neuroimaging Clin N Am. 2011;21(2):259–83. Scholar
  54. 54.
    Neumann-Haefelin T, Wittsack HJ, Wenserski F, Siebler M, Seitz RJ, Modder U, et al. Diffusion- and perfusion-weighted MRI. The DWI/PWI mismatch region in acute stroke. Stroke. 1999;30(8):1591–7.CrossRefGoogle Scholar
  55. 55.
    Albers GW. Expanding the window for thrombolytic therapy in acute stroke. The potential role of acute MRI for patient selection. Stroke. 1999;30(10):2230–7.CrossRefGoogle Scholar
  56. 56.
    Rivers CS, Wardlaw JM, Armitage PA, Bastin ME, Carpenter TK, Cvoro V, et al. Do acute diffusion- and perfusion-weighted MRI lesions identify final infarct volume in ischemic stroke? Stroke. 2006;37(1):98–104. Scholar
  57. 57.
    Takasawa M, Jones PS, Guadagno JV, Christensen S, Fryer TD, Harding S, et al. How reliable is perfusion MR in acute stroke? Validation and determination of the penumbra threshold against quantitative PET. Stroke. 2008;39(3):870–7. Scholar
  58. 58.
    Baird AE, Lovblad KO, Dashe JF, Connor A, Burzynski C, Schlaug G, et al. Clinical correlations of diffusion and perfusion lesion volumes in acute ischemic stroke. Cerebrovasc Dis. 2000;10(6):441–8. Scholar
  59. 59.
    Barber PA, Parsons MW, Desmond PM, Bennett DA, Donnan GA, Tress BM, et al. The use of PWI and DWI measures in the design of “proof-of-concept” stroke trials. J Neuroimaging. 2004;14(2):123–32.CrossRefGoogle Scholar
  60. 60.
    Butcher K, Parsons M, Baird T, Barber A, Donnan G, Desmond P, et al. Perfusion thresholds in acute stroke thrombolysis. Stroke. 2003;34(9):2159–64. Scholar
  61. 61.
    Parsons MW, Barber PA, Chalk J, Darby DG, Rose S, Desmond PM, et al. Diffusion- and perfusion-weighted MRI response to thrombolysis in stroke. Ann Neurol. 2002;51(1):28–37.CrossRefGoogle Scholar
  62. 62.
    Parsons MW, Yang Q, Barber PA, Darby DG, Desmond PM, Gerraty RP, et al. Perfusion magnetic resonance imaging maps in hyperacute stroke: relative cerebral blood flow most accurately identifies tissue destined to infarct. Stroke. 2001;32(7):1581–7.CrossRefGoogle Scholar
  63. 63.
    Rohl L, Geday J, Ostergaard L, Simonsen CZ, Vestergaard-Poulsen P, Andersen G, et al. Correlation between diffusion- and perfusion-weighted MRI and neurological deficit measured by the Scandinavian Stroke Scale and Barthel Index in hyperacute subcortical stroke (< or = 6 hours). Cerebrovasc Dis. 2001;12(3):203–13. Scholar
  64. 64.
    Rohl L, Ostergaard L, Simonsen CZ, Vestergaard-Poulsen P, Andersen G, Sakoh M, et al. Viability thresholds of ischemic penumbra of hyperacute stroke defined by perfusion-weighted MRI and apparent diffusion coefficient. Stroke. 2001;32(5):1140–6.CrossRefGoogle Scholar
  65. 65.
    Rose SE, Chalk JB, Griffin MP, Janke AL, Chen F, McLachan GJ, et al. MRI based diffusion and perfusion predictive model to estimate stroke evolution. Magn Reson Imaging. 2001;19(8):1043–53.CrossRefGoogle Scholar
  66. 66.
    Rose SE, Janke AL, Griffin M, Finnigan S, Chalk JB. Improved prediction of final infarct volume using bolus delay-corrected perfusion-weighted MRI: implications for the ischemic penumbra. Stroke. 2004;35(11):2466–71. Scholar
  67. 67.
    Ueda T, Yuh WT, Maley JE, Quets JP, Hahn PY, Magnotta VA. Outcome of acute ischemic lesions evaluated by diffusion and perfusion MR imaging. AJNR Am J Neuroradiol. 1999;20(6):983–9.PubMedGoogle Scholar
  68. 68.
    Yoo AJ, Verduzco LA, Schaefer PW, Hirsch JA, Rabinov JD, Gonzalez RG. MRI-based selection for intra-arterial stroke therapy: value of pretreatment diffusion-weighted imaging lesion volume in selecting patients with acute stroke who will benefit from early recanalization. Stroke. 2009;40(6):2046–54. Scholar
  69. 69.
    Mlynash M, Lansberg MG, De Silva DA, Lee J, Christensen S, Straka M, et al. Refining the definition of the malignant profile: insights from the DEFUSE-EPITHET pooled data set. Stroke. 2011;42(5):1270–5. Scholar
  70. 70.
    Kakuda W, Lansberg MG, Thijs VN, Kemp SM, Bammer R, Wechsler LR, et al. Optimal definition for PWI/DWI mismatch in acute ischemic stroke patients. J Cereb Blood Flow Metab. 2008;28(5):887–91. Scholar
  71. 71.
    Kim S, Kang M, Choi S, Kim DW. Mismatch of delayed perfusion volume between TTP and Tmax map of perfusion MRI. Clin Imaging. 2016;40(1):63–7. Scholar
  72. 72.
    Thomalla GJ, Kucinski T, Schoder V, Fiehler J, Knab R, Zeumer H, et al. Prediction of malignant middle cerebral artery infarction by early perfusion- and diffusion-weighted magnetic resonance imaging. Stroke. 2003;34(8):1892–9. Scholar
  73. 73.
    Wouters A, Christensen S, Straka M, Mlynash M, Liggins J, Bammer R, et al. A comparison of relative time to peak and Tmax for mismatch-based patient selection. Front Neurol. 2017;8:539. Scholar
  74. 74.
    Zaro-Weber O, Moeller-Hartmann W, Siegmund D, Kandziora A, Schuster A, Heiss WD, et al. MRI-based mismatch detection in acute ischemic stroke: optimal PWI maps and thresholds validated with PET. J Cereb Blood Flow Metab. 2017;37(9):3176–83. Scholar
  75. 75.
    Sobesky J, Zaro Weber O, Lehnhardt FG, Hesselmann V, Thiel A, Dohmen C, et al. Which time-to-peak threshold best identifies penumbral flow? A comparison of perfusion-weighted magnetic resonance imaging and positron emission tomography in acute ischemic stroke. Stroke. 2004;35(12):2843–7. Scholar
  76. 76.
    Reimer J, Montag C, Schuster A, Moeller-Hartmann W, Sobesky J, Heiss WD, et al. Is perfusion MRI without deconvolution reliable for mismatch detection in acute stroke? Validation with 15O-positron emission tomography. Cerebrovasc Dis. 2018;46(1–2):16–23. Scholar
  77. 77.
    Ogata T, Nagakane Y, Christensen S, Ma H, Campbell BC, Churilov L, et al. A topographic study of the evolution of the MR DWI/PWI mismatch pattern and its clinical impact: a study by the EPITHET and DEFUSE investigators. Stroke. 2011;42(6):1596–601. Scholar
  78. 78.
    Lansberg MG, Straka M, Kemp S, Mlynash M, Wechsler LR, Jovin TG, et al. MRI profile and response to endovascular reperfusion after stroke (DEFUSE 2): a prospective cohort study. Lancet Neurol. 2012;11(10):860–7. Scholar
  79. 79.
    Short CE. Principles & practice of veterinary anesthesia. Williams & Wilkins; 1987.Google Scholar
  80. 80.
    Bratane BT, Bastan B, Fisher M, Bouley J, Henninger N. Ischemic lesion volume determination on diffusion weighted images vs. apparent diffusion coefficient maps. Brain Res. 2009;1279:182–8. Scholar
  81. 81.
    Kang BT, Jang DP, Gu SH, Lee JH, Jung DI, Lim CY, et al. MRI features in a canine model of ischemic stroke: correlation between lesion volume and neurobehavioral status during the subacute stage. Comp Med. 2009;59(5):459–64.PubMedPubMedCentralGoogle Scholar
  82. 82.
    Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175–91.CrossRefGoogle Scholar
  83. 83.
    Jahng GH, Li KL, Ostergaard L, Calamante F. Perfusion magnetic resonance imaging: a comprehensive update on principles and techniques. Korean J Radiol. 2014;15(5):554–77. Scholar
  84. 84.
    Calamante F, Thomas DL, Pell GS, Wiersma J, Turner R. Measuring cerebral blood flow using magnetic resonance imaging techniques. J Cereb Blood Flow Metab. 1999;19(7):701–35. Scholar
  85. 85.
    Perthen JE, Calamante F, Gadian DG, Connelly A. Is quantification of bolus tracking MRI reliable without deconvolution? Magn Reson Med. 2002;47(1):61–7.CrossRefGoogle Scholar
  86. 86.
    Christensen S, Mouridsen K, Wu O, Hjort N, Karstoft H, Thomalla G, et al. Comparison of 10 perfusion MRI parameters in 97 sub-6-hour stroke patients using voxel-based receiver operating characteristics analysis. Stroke. 2009;40(6):2055–61. Scholar
  87. 87.
    Calamante F. Arterial input function in perfusion MRI: a comprehensive review. Prog Nucl Magn Reson Spectrosc. 2013;74:1–32. Scholar
  88. 88.
    Motta M, Ramadan A, Hillis AE, Gottesman RF, Leigh R. Diffusion-perfusion mismatch: an opportunity for improvement in cortical function. Front Neurol. 2014;5:280. Scholar
  89. 89.
    Wittsack HJ, Ritzl A, Fink GR, Wenserski F, Siebler M, Seitz RJ, et al. MR imaging in acute stroke: diffusion-weighted and perfusion imaging parameters for predicting infarct size. Radiology. 2002;222(2):397–403. Scholar
  90. 90.
    Grandin CB, Duprez TP, Smith AM, Oppenheim C, Peeters A, Robert AR, et al. Which MR-derived perfusion parameters are the best predictors of infarct growth in hyperacute stroke? Comparative study between relative and quantitative measurements. Radiology. 2002;223(2):361–70. Scholar
  91. 91.
    Drier A, Tourdias T, Attal Y, Sibon I, Mutlu G, Lehericy S, et al. Prediction of subacute infarct size in acute middle cerebral artery stroke: comparison of perfusion-weighted imaging and apparent diffusion coefficient maps. Radiology. 2012;265(2):511–7. Scholar
  92. 92.
    Zaro-Weber O, Moeller-Hartmann W, Heiss WD, Sobesky J. MRI perfusion maps in acute stroke validated with 15O-water positron emission tomography. Stroke. 2010;41(3):443–9. Scholar
  93. 93.
    Werner P, Saur D, Zeisig V, Ettrich B, Patt M, Sattler B, et al. Simultaneous PET/MRI in stroke: a case series. J Cereb Blood Flow Metab. 2015;35(9):1421–5. Scholar
  94. 94.
    Martel AL, Allder SJ, Delay GS, Morgan PS, Moody AA. Perfusion MRI of infarcted and noninfarcted brain tissue in stroke: a comparison of conventional hemodynamic imaging and factor analysis of dynamic studies. Investig Radiol. 2001;36(7):378–85.CrossRefGoogle Scholar
  95. 95.
    Hartmann A, Driesen A, Lautenschlager IE, Scholz VB, Schmidt MJ. Quantitative analysis of brain perfusion in healthy dogs by means of magnetic resonance imaging. Am J Vet Res. 2016;77(11):1227–35. Scholar
  96. 96.
    Meijs M, Christensen S, Lansberg MG, Albers GW, Calamante F. Analysis of perfusion MRI in stroke: to deconvolve, or not to deconvolve. Magn Reson Med. 2016;76(4):1282–90. Scholar

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Authors and Affiliations

  1. 1.New England Center for Stroke Research, Department of RadiologyUniversity of Massachusetts Medical SchoolWorcesterUSA
  2. 2.Image Processing and Analysis Core, Department of RadiologyUniversity of Massachusetts Medical SchoolWorcesterUSA
  3. 3.Department of Biomedical EngineeringWorcester Polytechnic InstituteWorcesterUSA
  4. 4.St. George’s University School of MedicineSt. George’sGrenada
  5. 5.Department of NeurologyUniversity of Massachusetts Medical SchoolWorcesterUSA
  6. 6.Department of PsychiatryUniversity of Massachusetts Medical SchoolWorcesterUSA
  7. 7.School of Life SciencesUniversity of WarwickCoventryUK

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