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

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. We retrospectively studied 108 ICH patients with baseline non-contrast computed tomo...

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Veröffentlicht in:European radiology 2018-10, Vol.28 (10), p.4389-4396
Hauptverfasser: Shen, Qijun, Shan, Yanna, Hu, Zhengyu, Chen, Wenhui, Yang, Bing, Han, Jing, Huang, Yanfang, Xu, Wen, Feng, Zhan
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container_issue 10
container_start_page 4389
container_title European radiology
container_volume 28
creator Shen, Qijun
Shan, Yanna
Hu, Zhengyu
Chen, Wenhui
Yang, Bing
Han, Jing
Huang, Yanfang
Xu, Wen
Feng, Zhan
description 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. 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. Significant differences were found between the two groups of patients within variance at V and in uniformity at U , U and U . 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. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • 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.
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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. Significant differences were found between the two groups of patients within variance at V and in uniformity at U , U and U . 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. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • 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.</description><identifier>ISSN: 0938-7994</identifier><identifier>EISSN: 1432-1084</identifier><identifier>DOI: 10.1007/s00330-018-5364-8</identifier><identifier>PMID: 29713780</identifier><language>eng</language><publisher>Germany: Springer Nature B.V</publisher><subject>Adult ; Aged ; Algorithms ; Bandpass filters ; Computed tomography ; Computed Tomography Angiography - methods ; Correlation coefficients ; Diagnostic systems ; Disease Progression ; Early Diagnosis ; Enlargement ; Expansion ; Female ; Glasgow Coma Scale ; Hematoma ; Hematoma - diagnostic imaging ; Hematoma - pathology ; Hemorrhage ; Heterogeneity ; Hospitals ; Humans ; Image contrast ; Intracranial Hemorrhages - diagnostic imaging ; Intracranial Hemorrhages - pathology ; Laboratories ; Male ; Medical diagnosis ; Medical imaging ; Middle Aged ; Parameters ; Patients ; Predictions ; Radiographic Image Interpretation, Computer-Assisted ; Retrospective Studies ; ROC Curve ; Stroke ; Texture ; Tomography ; Training</subject><ispartof>European radiology, 2018-10, Vol.28 (10), p.4389-4396</ispartof><rights>European Radiology is a copyright of Springer, (2018). 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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. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • 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.</description><subject>Adult</subject><subject>Aged</subject><subject>Algorithms</subject><subject>Bandpass filters</subject><subject>Computed tomography</subject><subject>Computed Tomography Angiography - methods</subject><subject>Correlation coefficients</subject><subject>Diagnostic systems</subject><subject>Disease Progression</subject><subject>Early Diagnosis</subject><subject>Enlargement</subject><subject>Expansion</subject><subject>Female</subject><subject>Glasgow Coma Scale</subject><subject>Hematoma</subject><subject>Hematoma - diagnostic imaging</subject><subject>Hematoma - pathology</subject><subject>Hemorrhage</subject><subject>Heterogeneity</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Image contrast</subject><subject>Intracranial Hemorrhages - diagnostic imaging</subject><subject>Intracranial Hemorrhages - pathology</subject><subject>Laboratories</subject><subject>Male</subject><subject>Medical diagnosis</subject><subject>Medical imaging</subject><subject>Middle Aged</subject><subject>Parameters</subject><subject>Patients</subject><subject>Predictions</subject><subject>Radiographic Image Interpretation, Computer-Assisted</subject><subject>Retrospective Studies</subject><subject>ROC Curve</subject><subject>Stroke</subject><subject>Texture</subject><subject>Tomography</subject><subject>Training</subject><issn>0938-7994</issn><issn>1432-1084</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNpdkMtOwzAQRS0EoqXwAWyQJTZsAn4Rx0tU8ZIqIaSyribupKQkcbAdRH-Br8aFsmE1m3Ov7hxCTjm75Izpq8CYlCxjvMiuZa6yYo-MuZIi46xQ-2TMjCwybYwakaMQ1owxw5U-JCNhNJe6YGPy9TxAF-sIsf5A2oOHFiP6QF1Fp3Ma8TMOHil00GxCHSgE2ruIKQINbcG_JbZyniL4ZkN7j8vaxtp123zoXRehQzcEWnfRg_XQbXOv2DrvX2GFFLsG_Arb1HhMDipoAp7s7oS83N3Opw_Z7On-cXozy3ohTcxKBUwrLJFJYzXmpS54-leUrFwaKFBai1JYJSvIkySb58qgyXkFS0BhtZyQi9_e3rv3AUNctHWw2DS_UxciSZWFFtcqoef_0LUbfHLxQ4mca8231NmOGsoWl4ve18nMZvFnWX4DtzyC1w</recordid><startdate>201810</startdate><enddate>201810</enddate><creator>Shen, Qijun</creator><creator>Shan, Yanna</creator><creator>Hu, Zhengyu</creator><creator>Chen, Wenhui</creator><creator>Yang, Bing</creator><creator>Han, Jing</creator><creator>Huang, Yanfang</creator><creator>Xu, Wen</creator><creator>Feng, Zhan</creator><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>3V.</scope><scope>7QO</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9496-4211</orcidid></search><sort><creationdate>201810</creationdate><title>Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement</title><author>Shen, Qijun ; 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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. Significant differences were found between the two groups of patients within variance at V and in uniformity at U , U and U . 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. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • 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.</abstract><cop>Germany</cop><pub>Springer Nature B.V</pub><pmid>29713780</pmid><doi>10.1007/s00330-018-5364-8</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-9496-4211</orcidid></addata></record>
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subjects Adult
Aged
Algorithms
Bandpass filters
Computed tomography
Computed Tomography Angiography - methods
Correlation coefficients
Diagnostic systems
Disease Progression
Early Diagnosis
Enlargement
Expansion
Female
Glasgow Coma Scale
Hematoma
Hematoma - diagnostic imaging
Hematoma - pathology
Hemorrhage
Heterogeneity
Hospitals
Humans
Image contrast
Intracranial Hemorrhages - diagnostic imaging
Intracranial Hemorrhages - pathology
Laboratories
Male
Medical diagnosis
Medical imaging
Middle Aged
Parameters
Patients
Predictions
Radiographic Image Interpretation, Computer-Assisted
Retrospective Studies
ROC Curve
Stroke
Texture
Tomography
Training
title Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement
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