Literature DB >> 31838472

Comparison of ABC Methods with Computerized Estimates of Intracerebral Hemorrhage Volume: The INTERACT2 Study.

Candice Delcourt1,2,3, Cheryl Carcel1,2, Danni Zheng1,2, Shoichiro Sato1,4, Hisatomi Arima1,5, Sonu Bhaskar2,6,7, Pierre Janin2,8, Rustam Al-Shahi Salman9, Yongjun Cao10, Shihong Zhang11, Emma Heeley12, Leo Davies2,3, John Chalmers1, Craig S Anderson13,14,15.   

Abstract

BACKGROUND AND
PURPOSE: Hematoma volume is a key determinant of outcome in acute intracerebral hemorrhage (ICH). We aimed to compare estimates of ICH volume between simple (ABC/2, length, width, and height) and gold standard planimetric software approaches.
METHODS: Data are from the second Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial (INTERACT2). Multivariable linear regression was used to compare ICH volumes on baseline CT scans using the ABC/2, modified ABC/2 (mABC/2), and MIStar software. Other aspects of ICH morphology examined included location, irregularity, heterogeneity, intraventricular and subarachnoid hemorrhage extension (SAH) of hematoma, and associated white matter lesions and brain atrophy.
RESULTS: In 2,084 patients with manual and semiautomated measurements, median (IQR) ICH volumes for each approach were: ABC/2 11.1 (5.11-20.88 mL), mABC/2 7.8 (3.88-14.11 mL), and MIStar 10.7 (5.59-18.66 mL). Median differences between ABC/2 and MIStar, and mABC/2 and MIStar were 0.34 (-1.01 to 2.96) and -2.4 (-4.95 to -0.7416), respectively. Hematoma volumes differed significantly with irregular shape (ABC/2 and MIStar, p < 0.001; mABC/2 and MIStar, p = 0.007) and larger volumes (mABC/2 and MIStar, p < 0.001; ABC/2 and MIStar, p = 0.07). ICH with SAH showed a significant discrepancy between ABC/2 and MIStar (p < 0.001).
CONCLUSIONS: Overall, ABC/2 performs better than mABC/2 in estimating ICH volume. The largest discrepancies were evidenced against automated software for irregular-shaped and large ICH with SAH, but the clinical significance of this is uncertain.
© 2019 The Author(s) Published by S. Karger AG, Basel.

Entities:  

Keywords:  Hematoma size; Imaging, stroke; Intracerebral hemorrhage; Stroke outcome measures

Mesh:

Year:  2019        PMID: 31838472      PMCID: PMC6940457          DOI: 10.1159/000504531

Source DB:  PubMed          Journal:  Cerebrovasc Dis Extra        ISSN: 1664-5456


  17 in total

1.  The second (main) phase of an open, randomised, multicentre study to investigate the effectiveness of an intensive blood pressure reduction in acute cerebral haemorrhage trial (INTERACT2).

Authors:  C Delcourt; Y Huang; J Wang; E Heeley; R Lindley; C Stapf; C Tzourio; H Arima; M Parsons; J Sun; B Neal; J Chalmers; C Anderson
Journal:  Int J Stroke       Date:  2010-04       Impact factor: 5.266

2.  Factors affecting the prognosis in thalamic hemorrhage.

Authors:  R Kwak; S Kadoya; T Suzuki
Journal:  Stroke       Date:  1983 Jul-Aug       Impact factor: 7.914

Review 3.  Worldwide stroke incidence and early case fatality reported in 56 population-based studies: a systematic review.

Authors:  Valery L Feigin; Carlene M M Lawes; Derrick A Bennett; Suzanne L Barker-Collo; Varsha Parag
Journal:  Lancet Neurol       Date:  2009-02-21       Impact factor: 44.182

4.  Rapid blood-pressure lowering in patients with acute intracerebral hemorrhage.

Authors:  Craig S Anderson; Emma Heeley; Yining Huang; Jiguang Wang; Christian Stapf; Candice Delcourt; Richard Lindley; Thompson Robinson; Pablo Lavados; Bruce Neal; Jun Hata; Hisatomi Arima; Mark Parsons; Yuechun Li; Jinchao Wang; Stephane Heritier; Qiang Li; Mark Woodward; R John Simes; Stephen M Davis; John Chalmers
Journal:  N Engl J Med       Date:  2013-05-29       Impact factor: 91.245

5.  Ultra-early evaluation of intracerebral hemorrhage.

Authors:  J P Broderick; T G Brott; T Tomsick; W Barsan; J Spilker
Journal:  J Neurosurg       Date:  1990-02       Impact factor: 5.115

6.  Relationship between white-matter hyperintensities and hematoma volume and growth in patients with intracerebral hemorrhage.

Authors:  Min Lou; Adel Al-Hazzani; Richard P Goddeau; Vera Novak; Magdy Selim
Journal:  Stroke       Date:  2009-11-19       Impact factor: 7.914

7.  Grading white matter lesions on CT and MRI: a simple scale.

Authors:  J C van Swieten; A Hijdra; P J Koudstaal; J van Gijn
Journal:  J Neurol Neurosurg Psychiatry       Date:  1990-12       Impact factor: 10.154

8.  Comparison of hematoma shape and volume estimates in warfarin versus non-warfarin-related intracerebral hemorrhage.

Authors:  Kevin N Sheth; Tracy A Cushing; Lauren Wendell; Michael H Lev; Javier M Romero; Kristin Schwab; Eric E Smith; Steven M Greenberg; Jonathan Rosand; Joshua N Goldstein
Journal:  Neurocrit Care       Date:  2010-02       Impact factor: 3.210

9.  Computer-assisted volumetric analysis compared with ABC/2 method for assessing warfarin-related intracranial hemorrhage volumes.

Authors:  William D Freeman; Kevin M Barrett; Joseph M Bestic; James F Meschia; Daniel F Broderick; Thomas G Brott
Journal:  Neurocrit Care       Date:  2008       Impact factor: 3.210

10.  Software output from semi-automated planimetry can underestimate intracerebral haemorrhage and peri-haematomal oedema volumes by up to 41.

Authors:  Teddy Y Wu; Oluwaseun Sobowale; Robert Hurford; Gagan Sharma; Søren Christensen; Nawaf Yassi; Turgut Tatlisumak; Patricia M Desmond; Bruce C V Campbell; Stephen M Davis; Adrian R Parry-Jones; Atte Meretoja
Journal:  Neuroradiology       Date:  2016-07-05       Impact factor: 2.804

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  1 in total

1.  A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT.

Authors:  Ali Arab; Betty Chinda; George Medvedev; William Siu; Hui Guo; Tao Gu; Sylvain Moreno; Ghassan Hamarneh; Martin Ester; Xiaowei Song
Journal:  Sci Rep       Date:  2020-11-09       Impact factor: 4.379

  1 in total

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