Deans' stroke musings

Changing stroke rehab and research worldwide now.Time is Brain!Just think of all the trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 493 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It's quite disgusting that this information is not available from every stroke association and doctors group.
My back ground story is here:http://oc1dean.blogspot.com/2010/11/my-background-story_8.html

Tuesday, December 13, 2016

Imaging Selection in Ischemic Stroke: Feasibility of Automated CT-Perfusion Analysis

You better hope you are one of the strokes that meets these cherry picked patients so you can get proper interventions. Real world difficult strokes need not apply for interventions. I would leave no stroke patient hanging with no decent interventions possible. This cherry picking crap is what happens when you don't have stroke survivors running the strategy and research. 
http://wso.sagepub.com/content/10/1/51.full
  1. Bruce C.V. Campbell1,2,*
  2. Nawaf Yassi1
  3. Henry Ma3
  4. Gagan Sharma2
  5. Simon Salinas2
  6. Leonid Churilov3
  7. Atte Meretoja1,3
  8. Mark W. Parsons4
  9. Patricia M. Desmond2
  10. Maarten G. Lansberg5
  11. Geoffrey A. Donnan3
  12. Stephen M. Davis1
  1. 1 Department of Medicine, Royal Melbourne Hospital, Melbourne, Australia
  2. 2 Department of Radiology, Royal Melbourne Hospital, Melbourne, Australia
  3. 3 Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
  4. 4 Priority Research Centre for Brain and Mental Health Research, John Hunter Hospital, University of Newcastle, Newcastle, Australia
  5. 5 Department of Neurology and Neurological Sciences, Stanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA
  1. * Correspondence: Bruce Campbell, Department of Neurology, Royal Melbourne Hospital, Grattan Street, Parkville, VIC 3050, Australia. E-mail: bruce.campbell@mh.org.au

Abstract

Background Advanced imaging may refine patient selection for ischemic stroke treatment but delays to acquire and process the imaging have limited implementation.
Aims We examined the feasibility of imaging selection in clinical practice using fully automated software in the EXTEND trial program.
Methods CTP and perfusion-diffusion MRI data were processed using fully-automated software to generate a yes/no ‘mismatch’ classification that determined eligibility for trial therapies. The technical failure/mismatch classification error rate and time to image and treat with CT vs. MR-based selection were examined.
Results In a consecutive series of 776 patients from five sites over six-months the technical failure rate of CTP acquisition/processing (uninterpretable maps) was 3·4% (26/776, 95%CI 2·2–4·9%). Mismatch classification was overruled by expert review in an additional 9·0% (70/776, 95%CI 7·1–11·3%) due to artifactual ‘perfusion lesion’. In 154 consecutive patients at one site, median additional time to acquire CTP after noncontrast CT was 6·5 min. Subsequent RAPID processing time varied from 3–10 min across 20 trial centers (median 5 min 20 s). In the EXTEND trial, door-to-needle times in patients randomized on the basis of CTP (n = 47) were median 78 min shorter than MRI-selected (n = 16) patients (P < 0·001).
Conclusions Automated CTP-based mismatch selection is rapid, robust in clinical practice, and associated with faster treatment decisions than MRI. This technological advance has the potential to improve the standardization and reproducibility of interpretation of advanced imaging and extend use to practice settings beyond highly specialized academic centers.

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