A Precise Method for Linking Neuroanatomy to Function After Stroke: A Pilot Study

REFERENCES

• Thom T, Haase N, Rosamond W, et al. Heart disease and stroke statistics - 2006 update. A report for the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2006;113:e85–151.
   PubMed Web of Science ®Google Scholar
• Elkins is, Johnston SC. Thirty-year projections for deaths from ischemic stroke in the United States. Stroke. 2003;34:2109–2112.
   PubMed Web of Science ®Google Scholar
• Institute of Medicine Committee on Identifying Pri-ority Areas for Quality Improvement. Priority Areas for National Action: Transforming Health Care Quality. Washington, DC: National Academies Press; 2003.
   Google Scholar
• Chaudhuri G, Harvey RF, Sulton LD, Lamber RW. Computerized tomography head scans as predic-tors of functional outcome of stroke patients. Arch Phys Med Rehabil. 1988;69:496–498.
   PubMed Web of Science ®Google Scholar
• Saeki S, Ogata H, Hachisuka K, Okubo T, Takahashi K, Hoshuyama T. Association between location of the lesion and discharge status of ADL in first stroke patients. Arch Phys Med Rehabil. 1994;75:858–860.
   PubMed Web of Science ®Google Scholar
• Chae J, Zorowitz R. Functional status of cortical and subcortical nonhemorrhagic stroke survivors and the effect of lesion laterality. Am J Phys Med Rehabil. 1998;77:415–420.
   PubMed Web of Science ®Google Scholar
• Beloosesky Y, Streifler JY, Vurstin A, Grinblat J. The importance of brain infarct size and location in pre-dicting outcome after stroke. Age Ageing. 1995;24:515–518.
   PubMed Web of Science ®Google Scholar
• Dromerick A, Reding M. Functional outcomes for patients with hemiparesis, hemihypesthesia, and hemianopsia: Does lesion location matter? Stroke. 1995;26:2023–2026.
   Google Scholar
• Saver IL, Johnston KC, Homer D, Wityk R, Koroshetz WI, Truskowski LL, Haley C. Infarct volume as a surrogate or auxiliary outcome measure in ischemic stroke clinical trials. Stroke. 1999;30:293–298.
   PubMed Web of Science ®Google Scholar
• Schiemanck SK, Kwakkel G, Post MWM, Kappelle LJ, Prevo AJH. Predicting long-term independency in activities of daily living after middle cerebral artery stroke. Stroke. 2006;37:1050–1054.
   PubMed Web of Science ®Google Scholar
• Chen CL, Tang FT, Chen HC, Chung CY, Wong MK. Brain lesion size and location: effects on motor re-covery and functional outcome in stroke patients. Arch Phys Med Rehabil. 2000;81:447–452.
   PubMed Web of Science ®Google Scholar
• Agency for Health Care Policy and Research and the Post-Stroke Rehabilitation Guideline Panel. Post-Stroke Rehabilitation. Rockville, MD: US Department of Health and Human Services; 1995. Report No. 95–0662. Sponsored by the Agency for Healthcare Research and Quality.
   Google Scholar
• Kelly-Hayes M, Robertson JT, Broderick JP, Duncan PW, Hershey LA, Roth EJ, Thies WH, Trombly CA. The American Heart Association Stroke Outcome Classification. Stroke. 1998;29:1274–1280.
   PubMed Web of Science ®Google Scholar
• Duncan PW, Zorowitz R, Bates B, Choi JY, Glasberg JJ, Graham GD, Katz RC., Lam berty K, Reker D. Man-agement of adult stroke rehabilitation care: A clini-cal practice guideline. Stroke. 2005;36:e100–e143.
   PubMed Web of Science ®Google Scholar
• Brott T, Marler JR, Olinger CP, Adams HP, Tomsick T, Barsan WG, Biller J, Eberle R, Hertzberg V, Walker M. Measurements of acute cerebral infarction: le-sion size by computed tomography. Stroke. 1989;20:871–875.
   PubMed Web of Science ®Google Scholar
• Lyden PD, Zweifler R, Mahdavi Z, Lonzo L. A rapid, reliable and valid method for measuring infarct and brain compartment volumes from computed to-mography scans. Stroke. 1994;25:2421–2428.
   PubMed Web of Science ®Google Scholar
• Saunders DE, Clifton AG, Brown MM. Measurement of infarct size using MRI predicts prognosis in middle cerebral artery infarction. Stroke. 1995;26:2272–2276.
   PubMed Web of Science ®Google Scholar
• van der Worp HB, Claus S, Bar PR, Ramos LM, Algra A, van Gijn J, Kappelle U. Reproducibility of mea-surements of cerebral infarct volume on CT scans. Stroke. 2001;32:424–430.
   PubMed Web of Science ®Google Scholar
• Hoffman T, McKenna K. Prediction of outcome after stroke: implications for clinical practice. Phys Occup Ther Geriatr. 2001;19:53–75.
   Google Scholar
• Jongbloed L. Prediction of function after stroke: a critical review. Stroke. 1986;17:765–776.
   PubMed Web of Science ®Google Scholar
• Kwakkel G, Wagenaar RC, Kollen GJ, Lankhorst Gl. Predicting disability in stroke: a critical review of the literature. Age Ageing. 1996;25:479–489.
   PubMed Web of Science ®Google Scholar
• Tatu L, Moulin T, Bogousslavsky J, Duvernoy H. Arterial territories of human brain. In: J Bogousslavsky, Caplan LR, eds. Stroke Syndromes. Cambridge, UK: Cambridge University Press; 2001:375–404.
   Google Scholar
• Brott T, Adams HP, Olinger CP, et al. Measurements of acute cerebral infarction: a clinical examination scale. Stroke. 1989;20:864–870.
   PubMed Web of Science ®Google Scholar
• Frankel MR, Morgenstern LB, Kwiatkowski T, Lu M, Tilley BC, Broderick JP, Libman R, Levine SR, Brott T. Predicting prognosis after stroke: a placebo group analysis from the National Institute of Neurological Disorders and Stroke rt-PA Stroke Trial. Neurology. 2000;55:952–959.
   PubMed Web of Science ®Google Scholar
• Holm MB, Rogers JC. Functional assessment: the Performance Assessment of Self-Care Skills (PASS). In: Hemphill BJ, ed. Assessments in Occupational Therapy Mental Health: An Integrative Approach. Thorofare, NJ: Slack, Inc; 1999:117–124.
   Google Scholar
• Kass G. An exploratory technique for investigating large quantities of categorical data. App! Statistics. 1980;29:119–127.
   Google Scholar
• Biggs D, de Ville B, Suen B. A method of choosing multiway partitions for classification and decision trees. J Appl Statistics. 1991;18:49–62.
   Google Scholar
• Skidmore ER, Rogers JC, Chandler LS, Holm MB. Developing empirical models to enhance stroke re-habilitation. Disabil Rehabil. 2006;28:1027–1034.
   PubMed Web of Science ®Google Scholar
• Skidmore ER, Rogers JC, Chandler LS, Holm MB. Dynamic interactions between impairment and ac-tivity after stroke: examining the utility of decision analysis methods. Clin Rehabil. 2006;20:523–535.
   PubMed Web of Science ®Google Scholar
• Berman SA, Hayman LA, Hinck VC. Correlation of CT cerebral vascular territories with function: 3. midddle cerebral artery. Am J Roentgenol. 1984;142:1035–1040.
   PubMed Web of Science ®Google Scholar
• Kandel ER, Schwartz JFI, Jessell TM, eds. Principles of Neural Science. 4th ed. New York: McGraw-Hill; 2000.
   Google Scholar
• van de Port I, Kwakkel G, van Wijk I, Lindeman E. Susceptibility to deterioration of mobility long-term after stroke: a prospective cohort study. Stroke. 2006;37:167–171.
   PubMed Web of Science ®Google Scholar
• Sands L, Yaffe K, Covinsky K, Chren M, Counsell C, Palmer R, Fortinksy R, Landefeld C. Cognitive screening predicts magnitude of functional recovery from admission to 3 months after discharge in hos-pitalized elders. I Gerontol. 2003;58:37–45.
   Google Scholar
• Talairach J, Tournoux P. Co-planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional Sys-tem - An Approach to Cerebral Imaging. New York: Thieme Medical Publishers; 1988.
   Google Scholar
• Mazziotta JC, Toga AW, Evans A, Fox P, Lancaster J. A probablistic atlas of the human brain: theory and rationale for its development. Neurolmage. 1995;2:89–101.
   PubMed Web of Science ®Google Scholar
• Evans AC, Collins DL, Milner B. An MRI-based ster-eotactic atlas from 250 young normal subjects. Soc Neurosci. 1992;18:408.
   Google Scholar
• Evans AC, Collins DL, Mills SR, Brown ED, Kelly RL, Peters TM. 3D statistical neuroanatomical models from 305 MRI volumes. Proc IEEE-Nuclear Sci Symp Med Imaging Conf. 1993;1813–1817.
   Google Scholar