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European Radiology

, Volume 28, Issue 10, pp 4389–4396 | Cite as

Quantitative parameters of CT texture analysis as potential markers for early prediction of spontaneous intracranial hemorrhage enlargement

  • Qijun Shen
  • Yanna Shan
  • Zhengyu Hu
  • Wenhui Chen
  • Bing Yang
  • Jing Han
  • Yanfang Huang
  • Wen Xu
  • Zhan Feng
Computed Tomography
  • 164 Downloads

Abstract

Objective

To objectively quantify intracranial hematoma (ICH) enlargement by analysing the image texture of head CT scans and to provide objective and quantitative imaging parameters for predicting early hematoma enlargement.

Methods

We retrospectively studied 108 ICH patients with baseline non-contrast computed tomography (NCCT) and 24-h follow-up CT available. Image data were assessed by a chief radiologist and a resident radiologist. Consistency analysis between observers was tested. The patients were divided into training set (75%) and validation set (25%) by stratified sampling. Patients in the training set were dichotomized according to 24-h hematoma expansion ≥ 33%. Using the Laplacian of Gaussian bandpass filter, we chose different anatomical spatial domains ranging from fine texture to coarse texture to obtain a series of derived parameters (mean grayscale intensity, variance, uniformity) in order to quantify and evaluate all data. The parameters were externally validated on validation set.

Results

Significant differences were found between the two groups of patients within variance at V1.0 and in uniformity at U1.0, U1.8 and U2.5. The intraclass correlation coefficients for the texture parameters were between 0.67 and 0.99. The area under the ROC curve between the two groups of ICH cases was between 0.77 and 0.92. The accuracy of validation set by CTTA was 0.59–0.85.

Conclusion

NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement.

Key Points

• Heterogeneity is helpful in predicting ICH enlargement.

• CTTA could play an important role in predicting early ICH enlargement.

• After filtering, fine texture had the best diagnostic performance.

• The histogram-based uniformity parameters can independently predict ICH enlargement.

• CTTA is more objective, more comprehensive, more independently operable, than previous methods.

Keywords

Cerebral hemorrhage/diagnostic imaging Stroke Disease progression Tomography X-ray computed Algorithms 

Abbreviations

APTT

Activated partial prothrombin time

AUC

Area under the ROC curve

BV

Baseline volume

CTA

CT angiography

CTTA

Computed tomography texture analysis

FOV

Field of view

GCS

Glasgow coma scale

ICC

Intraclass correlation coefficient

ICH

Intracranial hematoma

LoG

Laplacian of Gaussian

M

Mean gray-level intensity

MATLAB

Matrix Laboratory

NCCT

Non-contrast computed tomography

NIHSS

National Institutes of Health stroke scale

ROC

Receiver operating characteristic curve

ROI

Region of interest

TTS

Time to scan

U

Uniformity

V

Variance

Notes

Funding

This study has received funding by the Department of Health of Zhejiang Province, China (No. 2017KY051).

This study has received funding by the Department of Health of Zhejiang Province, China (No. 2018KY582).

This study also has received funding by Hangzhou science and Technology Commission, China (No. 164519).

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Zhan Feng.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was not required for this study because of the retrospective nature of the study.

Ethical approval

Institutional review board approval was obtained.

Study subjects or cohorts overlap

Study subjects or cohorts have not been previously reported.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Department of RadiologyHangzhou First People’s HospitalHangzhouChina
  2. 2.Department of RadiologySecond People’s Hospital of Yuhang DistrictHangzhouChina
  3. 3.Department of Radiology, First Affiliated Hospital of College of Medical ScienceZhejiang UniversityHangzhouChina

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