Evidence map›Paper›PMID 18635616›Full record

ArticleAJNR. American journal of neuroradiology2008

Dynamic perfusion CT assessment of the blood-brain barrier permeability: first pass versus delayed acquisition.

J W Dankbaar, J Hom, T Schneider, S-C Cheng, B C Lau, I van der Schaaf, S Virmani, S Pohlman, W P Dillon, M Wintermark

Open access · hybridAbstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Multimodality imaging of blood-brain barrier impairment during epileptogenesis.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2017
    Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Observational
  15. Drug delivery to the ischemic brain.Advances in pharmacology (San Diego, Calif.) · 2014
    Review
  16. A fast nonlinear regression method for estimating permeability in CT perfusion imaging.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2013
    Article
  17. Article
  18. Cerebral microdialysis in clinical studies of drugs: pharmacokinetic applications.Journal of pharmacokinetics and pharmacodynamics · 2013
    Review
  19. Quantification of blood-to-brain transfer rate in multiple sclerosis.Multiple sclerosis and related disorders · 2013
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 3 countries.

J W DankbaarDepartment of Radiology, Neuroradiology Section, University of California, San Francisco, San Francisco, CA 94143-0628, USA.
J Hom
T Schneider
S-C Cheng
B C Lau
I van der Schaaf
S Virmani
S Pohlman
W P Dillon
M Wintermark
University of California, San Francisco · USPhilips (Finland) · FIUniversity Medical Center · USUniversity Medical Center Utrecht · NL

Funding

CTSA: K12 COMPONENTKL2RR024130 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOHNSTON, S. CLAIBORNE · 2006 to 2011
$19.3M
NCRR NIH HHS KL2 RR024130
6 · The paper itself

Abstract

background and purposeThe Patlak model has been applied to first-pass perfusion CT (PCT) data to extract information on blood-brain barrier permeability (BBBP) to predict hemorrhagic transformation in patients with acute stroke. However, the Patlak model was originally described for the delayed steady-state phase of contrast circulation. The goal of this study was to assess whether the first pass or the delayed phase of a contrast bolus injection better respects the assumptions of the Patlak model for the assessment of BBBP in patients with acute stroke by using PCT. MATERIALS AND

methodsWe retrospectively identified 125 consecutive patients (29 with acute hemispheric stroke and 96 without) who underwent a PCT study by using a prolonged acquisition time up to 3 minutes. The Patlak model was applied to calculate BBBP in ischemic and nonischemic brain tissue. Linear regression of the Patlak plot was performed separately for the first pass and for the delayed phase of the contrast bolus injection. Patlak linear regression models for the first pass and the delayed phase were compared in terms of their respective square root mean squared errors (square root MSE) and correlation coefficients (R) by using generalized estimating equations with robust variance estimation.

resultsBBBP values calculated from the first pass were significantly higher than those from the delayed phase, both in nonischemic brain tissue (2.81 mL x 100 g(-1) x min(-1) for the first pass versus 1.05 mL x 100 g(-1) x min(-1) for the delayed phase, P < .001) and in ischemic tissue (7.63 mL x 100 g(-1) x min(-1) for the first pass versus 1.31 mL x 100 g(-1) x min(-1) for the delayed phase, P < .001). Compared with regression models from the first pass, Patlak regression models obtained from the delayed data were of better quality, showing significantly lower square root MSE and higher R.

conclusionOnly the delayed phase of PCT acquisition respects the assumptions of linearity of the Patlak model in patients with and without stroke.

Indexed as

AgedAged, 80 and overBlood-Brain BarrierCapillary PermeabilityCerebral AngiographyCerebral HemorrhageCerebral InfarctionComputer GraphicsContrast MediaFemaleHumansImage EnhancementImage Processing, Computer-AssistedIohexolMaleMiddle AgedContrast MediaIohexol

Identifiers

PMID18635616
PMCPMC8118760
OpenAlexW2134657255

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.