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BMC Medical Imaging

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Open Access 01-12-2017 | Research article

Texture-based classification of different single liver lesion based on SPAIR T2W MRI images

Authors: Zhenjiang Li, Yu Mao, Wei Huang, Hongsheng Li, Jian Zhu, Wanhu Li, Baosheng Li

Published in: BMC Medical Imaging | Issue 1/2017

Abstract

Background

To assess the feasibility of texture analysis (TA) based on spectral attenuated inversion-recovery T2 weighted magnetic resonance imaging (SPAIR T2W-MRI) for the classification of hepatic hemangioma (HH), hepatic metastases (HM) and hepatocellular carcinoma (HCC).

Methods

The SPAIR T2W-MRI data of 162 patients with HH (n=55), HM (n=67) and HCC (n=40) were retrospectively analyzed. We used two independent cohorts for training (n = 112 patients) and validation (n = 50 patients). The TA was performed and textual parameters derived from the gray level co-occurrence matrix (GLCM), gray level gradient co-occurrence matrix (GLGCM), gray-level run-length matrix (GLRLM), Gabor wavelet transform (GWTF), intensity-size-zone matrix (ISZM), and histogram features were calculated. The capacity of each parameter to classify three types of single liver lesions was assessed using the Kruskal-Wallis test. Specificity and sensitivity for each of the studied parameters were derived using ROC curves. Four supervised classification algorithms were trained with the most influential textural features in the classification of tumor types. The test datasets validated the reliability of the models.

Results

The texture analyses showed that the HH versus HM, HM versus HCC, and HH versus HCC could be differentiated by 9, 16 and 10 feature parameters, respectively. The model’s misclassification rates were 11.7, 9.6 and 9.7% respectively. No texture feature was able to adequately distinguish among the three types of single liver lesions at the same time. The BP-ANN model had better predictive ability.

Conclusion

Texture features of SPAIR T2W-MRI can classify the three types of single liver lesions (HH, HM and HCC) and may serve as an adjunct tool for accurate diagnosis of these diseases.

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Title: Texture-based classification of different single liver lesion based on SPAIR T2W MRI images
Authors: Zhenjiang Li
Yu Mao
Wei Huang
Hongsheng Li
Jian Zhu
Wanhu Li
Baosheng Li
Publication date: 01-12-2017
Publisher: BioMed Central
Published in: BMC Medical Imaging / Issue 1/2017
Electronic ISSN: 1471-2342
DOI: https://doi.org/10.1186/s12880-017-0212-x

At a glance: The STEP trials

Springer Medicine

Texture-based classification of different single liver lesion based on SPAIR T2W MRI images

Abstract

Background

Methods

Results

Conclusion

At a glance: The STEP trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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