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Semi-automatic measurement of intracranial hemorrhage growth on non-contrast CT

Authors
 Kevin J Chung  ;  Hulin Kuang  ;  Alyssa Federico  ;  Hyun Seok Choi  ;  Linda Kasickova  ;  Abdulaziz Sulaiman Al Sultan  ;  MacKenzie Horn  ;  Mark Crowther  ;  Stuart J Connolly  ;  Patrick Yue  ;  John T Curnutte  ;  Andrew M Demchuk  ;  Bijoy K Menon  ;  Wu Qiu 
Citation
 INTERNATIONAL JOURNAL OF STROKE, Vol.16(2) : 192-199, 2021-02 
Journal Title
INTERNATIONAL JOURNAL OF STROKE
ISSN
 1747-4930 
Issue Date
2021-02
MeSH
Head ; Humans ; Intracranial Hemorrhages / diagnostic imaging ; Reproducibility of Results ; Stroke* / diagnostic imaging ; Tomography, X-Ray Computed
Keywords
Intracranial hemorrhage segmentation ; convex optimization ; max-flow algorithm ; non-contrast CT ; stroke
Abstract
Background: Manual segmentations of intracranial hemorrhage on non-contrast CT images are the gold-standard in measuring hematoma growth but are prone to rater variability.

Aims: We demonstrate that a convex optimization-based interactive segmentation approach can accurately and reliably measure intracranial hemorrhage growth.

Methods: Baseline and 16-h follow-up head non-contrast CT images of 46 subjects presenting with intracranial hemorrhage were selected randomly from the ANNEXA-4 trial imaging database. Three users semi-automatically segmented intracranial hemorrhage to measure hematoma volume for each timepoint using our proposed method. Segmentation accuracy was quantitatively evaluated compared to manual segmentations by using Dice similarity coefficient, Pearson correlation, and Bland-Altman analysis. Intra- and inter-rater reliability of the Dice similarity coefficient and intracranial hemorrhage volumes and volume change were assessed by the intraclass correlation coefficient and minimum detectable change.

Results: Among the three users, the mean Dice similarity coefficient, Pearson correlation, and mean difference ranged from 76.79% to 79.76%, 0.970 to 0.980 (p < 0.001), and -1.5 to -0.4 ml, respectively, for all intracranial hemorrhage segmentations. Inter-rater intraclass correlation coefficients between the three users for Dice similarity coefficient and intracranial hemorrhage volume were 0.846 and 0.962, respectively, and the corresponding minimum detectable change was 2.51 ml. Inter-rater intraclass correlation coefficient for intracranial hemorrhage volume change ranged from 0.915 to 0.958 for each user compared to manual measurements, resulting in an minimum detectable change range of 2.14 to 4.26 ml.

Conclusions: We spatially and volumetrically validate a novel interactive segmentation method for delineating intracranial hemorrhage on head non-contrast CT images. Good spatial overlap, excellent volume correlation, and good repeatability suggest its usefulness for measuring intracranial hemorrhage volume and volume change on non-contrast CT images.
Full Text
https://journals.sagepub.com/doi/10.1177/1747493019895704
DOI
10.1177/1747493019895704
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Choi, Hyun Seok(최현석) ORCID logo https://orcid.org/0000-0003-4999-8513
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/191052
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