Literature DB >> 26670321

Early quantitative CT perfusion parameters variation for prediction of delayed cerebral ischemia following aneurysmal subarachnoid hemorrhage.

Christine Rodriguez-Régent1, Monia Hafsa1, Guillaume Turc2, Wagih Ben Hassen1, Myriam Edjlali1, Alain Sermet3, Nathalie Laquay3, Denis Trystram1, Fawaz Al-Shareef1, Jean-Francois Meder1, Bertrand Devaux4, Catherine Oppenheim1, Olivier Naggara5.   

Abstract

OBJECTIVES: To prospectively evaluate the predictive value of cerebral perfusion-computerized tomography (CTP) parameters variation between day0 and day4 after aneurysmal subarachnoid haemorrhage (aSAH).
METHODS: Mean transit time (MTT) and cerebral blood flow (CBF) values were compared between patients with delayed cerebral ischemia (DCI+ group) and patients without DCI (DCI- group) for previously published optimal cutoff values and for variations of MTTMTT) and of CBF (ΔCBF) values between day0 and day4. DCI+ was defined as a cerebral infarction on 3-months follow-up MRI.
RESULTS: Among 47 included patients, 10 suffered DCI+. Published optimal cutoff values did not predict DCI, either at day0 or at day4. Conversely, ΔMTT and ΔCBF significantly differed between the DCI+ and DCI- groups, with optimal ΔMTT and ΔCBF values of 0.91 seconds (83.9 % sensitivity, 79.5 % specificity, AUC 0.84) and -7.6 mL/100 g/min (100 % sensitivity, 71.4 % specificity, AUC 0.86), respectively. In multivariate analysis, ΔCBF (OR = 1.91, IC95% 1.13-3.23 per each 20 % decrease of ΔCBF) and ΔMTT values (OR = 14.70, IC95% 4.85-44.52 per each 20 % increase of ΔMTT) were independent predictors of DCI.
CONCLUSIONS: Assessment of MTT and CBF value variations between day0 and day4 may serve as an early imaging surrogate for prediction of DCI in aSAH. KEY POINTS: • CT perfusion values are an imaging surrogate for prediction of DCI. • Early variations (day0-day4) after aneurysmal subarachnoid haemorrhage predicted DCI. • A CBF decrease of 7.6 mL/min/100 g predicted DCI with 100 % sensitivity. • An MTT increase of 0.91 seconds predicted DCI with 83.9 % sensitivity. • DCI risk multiplied by 2 per 20 % ΔCBF decrease and by 15 per 20 % ΔMTT increase.

Entities:  

Keywords:  CT perfusion; Cerebral vasospasm; Delayed cerebral ischemia; Prediction; Subarachnoid haemorrhage

Mesh:

Year:  2015        PMID: 26670321     DOI: 10.1007/s00330-015-4135-z

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  26 in total

1.  Radiation-induced temporary hair loss as a radiation damage only occurring in patients who had the combination of MDCT and DSA.

Authors:  Yoshimasa Imanishi; Atsushi Fukui; Hiroshi Niimi; Daisuke Itoh; Kyouko Nozaki; Shunsuke Nakaji; Kumiko Ishizuka; Hitoshi Tabata; Yu Furuya; Masahiko Uzura; Hideto Takahama; Suzuo Hashizume; Shiro Arima; Yasuo Nakajima
Journal:  Eur Radiol       Date:  2004-09-04       Impact factor: 5.315

Review 2.  Subarachnoid haemorrhage.

Authors:  Jan van Gijn; Richard S Kerr; Gabriel J E Rinkel
Journal:  Lancet       Date:  2007-01-27       Impact factor: 79.321

3.  CT perfusion scanning with deconvolution analysis: pilot study in patients with acute middle cerebral artery stroke.

Authors:  James D Eastwood; Michael H Lev; Tarek Azhari; Ting-Yim Lee; Daniel P Barboriak; David M Delong; Clemens Fitzek; Michael Herzau; Max Wintermark; Reto Meuli; David Brazier; James M Provenzale
Journal:  Radiology       Date:  2002-01       Impact factor: 11.105

4.  Diagnostic threshold values of cerebral perfusion measured with computed tomography for delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage.

Authors:  Jan Willem Dankbaar; Nicolien Karen de Rooij; Mienke Rijsdijk; Birgitta K Velthuis; Catharine J M Frijns; Gabriel J E Rinkel; Irene C van der Schaaf
Journal:  Stroke       Date:  2010-08-05       Impact factor: 7.914

5.  Assessment of the accuracy of a Bayesian estimation algorithm for perfusion CT by using a digital phantom.

Authors:  Makoto Sasaki; Kohsuke Kudo; Timothé Boutelier; Fabrice Pautot; Soren Christensen; Ikuko Uwano; Jonathan Goodwin; Satomi Higuchi; Kenji Ito; Fumio Yamashita
Journal:  Neuroradiology       Date:  2013-07-14       Impact factor: 2.804

6.  Acute stroke: a comparison of different CT perfusion algorithms and validation of ischaemic lesions by follow-up imaging.

Authors:  Benjamin Abels; J Pablo Villablanca; Bernd F Tomandl; Michael Uder; Michael M Lell
Journal:  Eur Radiol       Date:  2012-06-21       Impact factor: 5.315

7.  Impact of cerebral microcirculatory changes on cerebral blood flow during cerebral vasospasm after aneurysmal subarachnoid hemorrhage.

Authors:  H Ohkuma; H Manabe; M Tanaka; S Suzuki
Journal:  Stroke       Date:  2000-07       Impact factor: 7.914

8.  CT perfusion-derived mean transit time predicts early mortality and delayed vasospasm after experimental subarachnoid hemorrhage.

Authors:  A M Laslo; J D Eastwood; P Pakkiri; F Chen; T Y Lee
Journal:  AJNR Am J Neuroradiol       Date:  2007-10-26       Impact factor: 3.825

9.  Predictors of cerebral infarction in aneurysmal subarachnoid hemorrhage.

Authors:  Alejandro A Rabinstein; Jonathan A Friedman; Stephen D Weigand; Robyn L McClelland; Jimmy R Fulgham; Edward M Manno; John L D Atkinson; Eelco F M Wijdicks
Journal:  Stroke       Date:  2004-06-24       Impact factor: 7.914

10.  Whole brain CT perfusion in acute anterior circulation ischemia: coverage size matters.

Authors:  B J Emmer; M Rijkee; J M Niesten; M J H Wermer; B K Velthuis; M A A van Walderveen
Journal:  Neuroradiology       Date:  2014-09-17       Impact factor: 2.804

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  11 in total

1.  Defining cutoff values for early prediction of delayed cerebral ischemia after subarachnoid hemorrhage by CT perfusion.

Authors:  Vesna Malinova; Ioannis Tsogkas; Daniel Behme; Veit Rohde; Marios Nikos Psychogios; Dorothee Mielke
Journal:  Neurosurg Rev       Date:  2019-02-02       Impact factor: 3.042

2.  Prediction of outcome after aneurysmal subarachnoid haemorrhage using data from patient admission.

Authors:  Christian Rubbert; Kaustubh R Patil; Kerim Beseoglu; Christian Mathys; Rebecca May; Marius G Kaschner; Benjamin Sigl; Nikolas A Teichert; Johannes Boos; Bernd Turowski; Julian Caspers
Journal:  Eur Radiol       Date:  2018-06-12       Impact factor: 5.315

3.  Computed tomography perfusion as a predictor of delayed cerebral ischemia and functional outcome in spontaneous subarachnoid hemorrhage: A single center experience.

Authors:  Isabel Fragata; Marta Alves; Ana Luísa Papoila; Ana Paiva Nunes; Patrícia Ferreira; Mariana Diogo; Nuno Canto-Moreira; Patrícia Canhão
Journal:  Neuroradiol J       Date:  2019-02-19

4.  Radiological scales predicting delayed cerebral ischemia in subarachnoid hemorrhage: systematic review and meta-analysis.

Authors:  Wessel E van der Steen; Eva L Leemans; René van den Berg; Yvo B W E M Roos; Henk A Marquering; Dagmar Verbaan; Charles B L M Majoie
Journal:  Neuroradiology       Date:  2019-01-28       Impact factor: 2.804

Review 5.  The value of early CT perfusion parameters for predicting delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis.

Authors:  Heze Han; Yu Chen; Runting Li; Fa Lin; Junlin Lu; Xiaolin Chen; Shuo Wang
Journal:  Neurosurg Rev       Date:  2022-04-04       Impact factor: 2.800

6.  Prospective Multicenter Study of Changes in MTT after Aneurysmal SAH and Relationship to Delayed Cerebral Ischemia in Patients with Good- and Poor-Grade Admission Status.

Authors:  A Murphy; T-Y Lee; T R Marotta; J Spears; R L Macdonald; R I Aviv; A Baker; A Bharatha
Journal:  AJNR Am J Neuroradiol       Date:  2018-10-18       Impact factor: 3.825

7.  Magnetic Resonance Imaging in Aneurysmal Subarachnoid Hemorrhage: Current Evidence and Future Directions.

Authors:  Sarah E Nelson; Haris I Sair; Robert D Stevens
Journal:  Neurocrit Care       Date:  2018-10       Impact factor: 3.210

8.  TNF-R1 Correlates with Cerebral Perfusion and Acute Ischemia Following Subarachnoid Hemorrhage.

Authors:  Isabel Fragata; Alejandro Bustamante; Ana Penalba; Patrícia Ferreira; Ana Paiva Nunes; Patrícia Canhão; Joan Montaner
Journal:  Neurocrit Care       Date:  2020-08-20       Impact factor: 3.210

9.  Feasibility of FDCT Early Brain Parenchymal Blood Volume Maps in Predicting Short-Term Prognosis in Patients With Aneurysmal Subarachnoid Hemorrhage.

Authors:  Lili Wen; Longjiang Zhou; Qi Wu; Xiaoming Zhou; Xin Zhang
Journal:  Front Neurol       Date:  2022-07-14       Impact factor: 4.086

10.  Prediction and Risk Assessment Models for Subarachnoid Hemorrhage: A Systematic Review on Case Studies.

Authors:  Jewel Sengupta; Robertas Alzbutas
Journal:  Biomed Res Int       Date:  2022-01-27       Impact factor: 3.411

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