Literature DB >> 28461281

Interrater Agreement in the Radiologic Characterization of Ruptured Intracranial Aneurysms Based on Computed Tomography Angiography.

Nicolai Maldaner1, Martin N Stienen2, Philippe Bijlenga3, Davide Croci4, Daniel W Zumofen5, Donato Dalonzo6, Serge Marbacher6, Rodolfo Maduri7, Roy Thomas Daniel7, Carlo Serra8, Giuseppe Esposito8, Marian Christoph Neidert8, Oliver Bozinov8, Luca Regli8, Jan-Karl Burkhardt8.   

Abstract

OBJECTIVE: To determine interrater agreement in the initial radiologic characterization of ruptured intracranial aneurysms based on computed tomography angiography (CTA) with special emphasis on the rater's level of experience.
METHODS: One junior and one senior rater of 5 high-volume neurovascular tertiary centers evaluated anonymized CTA images of 30 consecutive patients with aneurysmal subarachnoid hemorrhage. Each rater described location, side, size, and morphology in a standardized manner. Interrater variability was analyzed using intraclass correlation and Fleiss' kappa analysis.
RESULTS: There was a high level of agreement for location (κ = 0.76, 95% confidence interval [CI] 0.74-0.79), side (κ = 0.95, CI 0.91-0.99), maximum diameter (intraclass correlation coefficient [ICC] 0.81, CI 0.70-0.90), and dome (ICC 0.78, CI 0.66-0.88) of intracranial aneurysms. In contrast, a lower level of agreement was observed for aneurysms' neck diameter (ICC 0.39, CI 0.28-0.58), the presence of multiple aneurysms (κ = 0.35, CI 0.30-0.40), and aneurysm morphology (blister κ = 0.11, CI -0.05 to 0.07; fusiform κ = 0.54, CI 0.48-0.60; multilobular, κ = 0.39 CI 0.33-0.45). The interrater agreement in the senior rater group was greater than in the junior rater group.
CONCLUSIONS: Interrater agreement confirms the benefit of CTA as initial diagnostic imaging in ruptured intracranial aneurysms but not for aneurysm morphology and presence of multiple aneurysms. A trend towards greater interrater agreement between more experienced raters was noticed.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aneurysm morphology; Computed tomography angiography; Interrater agreement; Interrater reliability; Neurovascular imaging; Subarachnoid hemorrhage

Mesh:

Year:  2017        PMID: 28461281     DOI: 10.1016/j.wneu.2017.04.131

Source DB:  PubMed          Journal:  World Neurosurg        ISSN: 1878-8750            Impact factor:   2.104


  6 in total

Review 1.  Artificial Intelligence in the Management of Intracranial Aneurysms: Current Status and Future Perspectives.

Authors:  Z Shi; B Hu; U J Schoepf; R H Savage; D M Dargis; C W Pan; X L Li; Q Q Ni; G M Lu; L J Zhang
Journal:  AJNR Am J Neuroradiol       Date:  2020-03-12       Impact factor: 3.825

2.  Computer-Assisted Three-Dimensional Morphology Evaluation of Intracranial Aneurysms.

Authors:  Hamidreza Rajabzadeh-Oghaz; Nicole Varble; Hussain Shallwani; Vincent M Tutino; Ashkan Mowla; Hakeem J Shakir; Kunal Vakharia; Gursant S Atwal; Adnan H Siddiqui; Jason M Davies; Hui Meng
Journal:  World Neurosurg       Date:  2018-08-01       Impact factor: 2.104

3.  Deep Learning-Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model.

Authors:  Allison Park; Chris Chute; Pranav Rajpurkar; Joe Lou; Robyn L Ball; Katie Shpanskaya; Rashad Jabarkheel; Lily H Kim; Emily McKenna; Joe Tseng; Jason Ni; Fidaa Wishah; Fred Wittber; David S Hong; Thomas J Wilson; Safwan Halabi; Sanjay Basu; Bhavik N Patel; Matthew P Lungren; Andrew Y Ng; Kristen W Yeom
Journal:  JAMA Netw Open       Date:  2019-06-05

4.  A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images.

Authors:  Zhao Shi; Chongchang Miao; U Joseph Schoepf; Rock H Savage; Danielle M Dargis; Chengwei Pan; Xue Chai; Xiu Li Li; Shuang Xia; Xin Zhang; Yan Gu; Yonggang Zhang; Bin Hu; Wenda Xu; Changsheng Zhou; Song Luo; Hao Wang; Li Mao; Kongming Liang; Lili Wen; Longjiang Zhou; Yizhou Yu; Guang Ming Lu; Long Jiang Zhang
Journal:  Nat Commun       Date:  2020-11-30       Impact factor: 14.919

5.  Reliability and accuracy assessment of morphometric measurements obtained with software for three-dimensional reconstruction of brain aneurysms relative to cerebral angiography measures.

Authors:  Pablo M Munarriz; Eduardo Bárcena; Jose F Alén; Ana M Castaño-Leon; Igor Paredes; Luis Miguel Moreno-Gómez; Daniel García-Pérez; Luis Jiménez-Roldán; Pedro A Gómez; Alfonso Lagares
Journal:  Interv Neuroradiol       Date:  2020-09-30       Impact factor: 1.610

6.  Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage.

Authors:  Lenhard Pennig; Ulrike Cornelia Isabel Hoyer; Alexandra Krauskopf; Rahil Shahzad; Stephanie T Jünger; Frank Thiele; Kai Roman Laukamp; Jan-Peter Grunz; Michael Perkuhn; Marc Schlamann; Christoph Kabbasch; Jan Borggrefe; Lukas Goertz
Journal:  Neuroradiology       Date:  2021-04-10       Impact factor: 2.804

  6 in total

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