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Automated fibrosis phenotyping of liver tissue from non-tumor lesions of patients with and without hepatocellular carcinoma after liver transplantation for non-alcoholic fatty liver disease

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Abstract

Background

Fibrosis is the most important pathological feature in predicting development of Hepatocellular carcinoma (HCC). However, the incidence rate of HCC in patients with non-alcoholic fatty liver disease (NAFLD) is relatively low. We evaluated phenotypic histological features to differentiate HCC from non-HCC in patients with non-tumor lesions of cirrhotic livers.

Methods

Seventeen patients with NAFLD who underwent liver transplantation were enrolled. FibroNest was used to quantify histological phenotypes of non-tumor fibrosis lesions. Quantification included collagen content and structure traits, fiber morphometric traits, and fibrosis architecture traits. Each trait was described by up to seven quantitative fibrosis traits (qFTs). Among the qFTs measured in each specimen, those that described most of the variability between consecutive groups were automatically detected and combined into a normalized Phenotypic Composite Fibrosis Score (Ph-CFS). We trained FibroNest to identify the principal traits that differentiate HCC from non-HCC.

Results

HCC was found in 8 cases and non-HCC in 9 cases. The Ph-CFS significantly differentiated HCC from non-HCC (4.6 vs. 5.9, p < 0.05). Individual qFTs for morphometric features including collagen fiber length, width, perimeter, and area denoted significant differences between HCC and non-HCC. The Ph-CFS could be used to distinguish HCC (Ph-FCS < 5.0) from non-HCC (Ph-FCS ≥ 5.0) with 75% sensitivity and 100% specificity.

Conclusion

In patients who underwent liver transplantation, fibrotic histological phenotypes in non-tumor lesions appeared to be different between HCC and non-HCC. Phenotypic analysis of collagen in non-tumor lesions might be an effective and automated method to distinguish HCC from non-HCC on histopathology imaging.

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Data availability

On reasonable request, derived data supporting the findings of this study are available from the corresponding author.

Abbreviations

LT:

Liver transplantation

qFT:

Quantitative fibrosis trait

Ph-CFS:

Phenotypic composite fibrosis score

HbA1c:

Glycated hemoglobin A1c

BMI:

Body mass index

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Funding

This work was supported by JSPS KAKENHI Grant Number 21K07916.

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Authors and Affiliations

  1. Department of Gastroenterology and Hepatology, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki, 852-8501, Japan

    Yutaka Nakamura, Hisamitsu Miyaaki, Satoshi Miuma, Yuko Akazawa, Masanori Fukusima, Ryu Sasaki, Masafumi Haraguchi & Kazuhiko Nakao

  2. Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan

    Akihiko Soyama, Masaaki Hidaka & Susumu Eguchi

Authors
  1. Yutaka Nakamura
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  2. Hisamitsu Miyaaki
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  4. Yuko Akazawa
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  5. Masanori Fukusima
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  6. Ryu Sasaki
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  11. Kazuhiko Nakao
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Contributions

YN and HM were contributed to the conception design of the study. YN and HM wrote original manuscript. YN, HM, SM, YA, RS, MH, MF, AS, MH, SE and KN were contributed collecting data. YN and ON analyzed data. MH, SE, and KN supervised the study.

Corresponding author

Correspondence to Hisamitsu Miyaaki.

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Conflict of interest

The authors: Yutaka Nakamura, Hisamitsu Miyaaki, Satoshi Miuma, Yuko Akazawa, Masanori Fukusima, Ryu Sasaki, Masafumi Haraguchi, Akihiko Soyama, Masaaki Hidaka, Susumu Eguchi, and Kazuhiko Nakao declare that they have no conflicts to declare.

Animal research (ethics)

It is not applicable.

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Informed consent was obtained in the form of opt-out on the web-site. Those who rejected were excluded.

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It is not applicable.

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It is not applicable.

Ethical approval

This study was conducted in accordance with the 1964 Helsinki declaration and was approved by the Research Ethics Committee of Nagasaki University Hospital (Approval No. 2032316).

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Supplementary Information

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12072_2022_10340_MOESM1_ESM.tif

Supplementary file1 Supplemental Figure1; FibroNest™ quantitative digital pathology platform (PharmaNest, Princeton, NJ) can quantify the histological phenotype of fibrosis, including collagen amount and structure (12 traits), the morphometric traits of collagen fibers (13 traits), and architecture of fibrosis (7 traits). Each trait is best described by its statistical distribution across tissues in the form of a histogram. The resulting histogram of each characteristic is described by quantitative fibrosis traits (qFTs) to account for mean, variance, distortion, and progression. Among the 350 qFTs measured in each tissue, the qFTs that describe most of the variability between the groups (principal qFTs). Continuous variables Phenotypic Fibrosis Composite Scores, Phenotypic Heat Chart, and Traits Trajectories can be represented (TIF 354 KB)

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Nakamura, Y., Miyaaki, H., Miuma, S. et al. Automated fibrosis phenotyping of liver tissue from non-tumor lesions of patients with and without hepatocellular carcinoma after liver transplantation for non-alcoholic fatty liver disease. Hepatol Int 16, 555–561 (2022). https://doi.org/10.1007/s12072-022-10340-9

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  • DOI: https://doi.org/10.1007/s12072-022-10340-9

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