Classification of hepatocellular carcinoma and intrahepatic cholangiocarcinoma based on multi-phase CT scans

Abstract

Liver and bile duct cancers are leading causes of worldwide cancer death. The most common ones are hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). Influencing factors and prognosis of HCC and ICC are different. Precise classification of these two liver cancers is essential for treatment and prevention plans. The aim of this study is to develop a machine-based method that differentiates between the two types of liver cancers from multi-phase abdominal computerized tomography (CT) scans. The proposed method consists of two major steps. In the first step, the liver is segmented from the original images using a convolutional neural network model, together with task-specific pre-processing and post-processing techniques. In the second step, by looking at the intensity histograms of the segmented images, we extract features from regions that are discriminating between HCC and ICC, and use them as an input for classification using support vector machine model. By testing on a dataset of labeled multi-phase CT scans provided by Maharaj Nakorn Chiang Mai Hospital, Thailand, we have obtained 88% in classification accuracy. Our proposed method has a great potential in helping radiologists diagnosing liver cancer.

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Acknowledgments

We would like to thank Chiang Mai University, Thailand, for financial support and computing resources.

Funding

This study was funded by Faculty of Medicine, Chiang Mai University, Thailand.

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Correspondence to Papangkorn Inkeaw.

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The authors declare that they have no competing interests.

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This study was approved and monitored by the Ethics Committee of Faculty of Medicine, Chiang Mai University, Thailand.

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Author contributions

Conceptualization: Donlapark Pornnopparath, Papangkorn Inkeaw. Methodology: Donlapark Pornnopparath, Papangkorn Inkeaw. Software: Donlapark Pornnopparath, Papangkorn Inkeaw. Validation: Donlapark Pornnopparath, Papangkorn Inkeaw. Formal analysis: Donlapark Pornnopparath, Papangkorn Inkeaw. Investigation: Donlapark Pornnopparath, Papangkorn Inkeaw. Data curation: Donlapark Pornnopparath, Patumrat Sripan, Nakarin Inmutto. Writing—original draft: Donlapark Pornnopparath, Papangkorn Inkeaw, Patumrat Sripan. Writing—review and editing: Jeerayut Chaijaruwanich, Patrinee Traisathit, Nakarin Inmutto, Wittanee Na Chiangmai, Donsuk Pongnikorn, Imjai Chitapanarux. Visualization: Donlapark Pornnopparath, Papangkorn Inkeaw. Supervision: Jeerayut Chaijaruwanich, Patrinee Traisathit, Imjai Chitapanarux. Project administration: Nakarin Inmutto. Funding acquisition: Nakarin Inmutto.

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Ponnoprat, D., Inkeaw, P., Chaijaruwanich, J. et al. Classification of hepatocellular carcinoma and intrahepatic cholangiocarcinoma based on multi-phase CT scans. Med Biol Eng Comput 58, 2497–2515 (2020). https://doi.org/10.1007/s11517-020-02229-2

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Keywords

  • Classification
  • Machine learning
  • Image processing
  • Liver neoplasms
  • Tomography