Literature DB >> 32055946

Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease.

Jung Hee Son1, Seung Soo Lee2, Yedaun Lee3, Bo-Kyeong Kang4, Yu Sub Sung1, SoRa Jo1, Eunsil Yu5.   

Abstract

OBJECTIVES: To evaluate whether the liver and spleen volumetric indices, measured on portal venous phase CT images, could be used to assess liver fibrosis severity in chronic liver disease.
METHODS: From 2007 to 2017, 558 patients (mean age 48.7 ± 13.1 years; 284 men and 274 women) with chronic liver disease (n = 513) or healthy liver (n = 45) were retrospectively enrolled. The liver volume (sVolL) and spleen volume (sVolS), normalized to body surface area and liver-to-spleen volume ratio (VolL/VolS), were measured on CT images using a deep learning algorithm. The correlation between the volumetric indices and the pathologic liver fibrosis stages combined with the presence of decompensation (F0, F1, F2, F3, F4C [compensated cirrhosis], and F4D [decompensated cirrhosis]) were assessed using Spearman's correlation coefficient. The performance of the volumetric indices in the diagnosis of advanced fibrosis, cirrhosis, and decompensated cirrhosis were evaluated using the area under the receiver operating characteristic curve (AUC).
RESULTS: The sVolS (ρ = 0.47-0.73; p < .001) and VolL/VolS (ρ = -0.77-- 0.48; p < .001) showed significant correlation with liver fibrosis stage in all etiological subgroups (i.e., viral hepatitis, alcoholic and non-alcoholic fatty liver, and autoimmune diseases), while the significant correlation of sVolL was noted only in the viral hepatitis subgroup (ρ = - 0.55; p < .001). To diagnose advanced fibrosis, cirrhosis, and decompensated cirrhosis, the VolL/VolS (AUC 0.82-0.88) and sVolS (AUC 0.82-0.87) significantly outperformed the sVolL (AUC 0.63-0.72; p < .001).
CONCLUSION: The VolL/VolS and sVolS may be used for assessing liver fibrosis severity in chronic liver disease. KEY POINTS: • Volumetric indices of liver and spleen measured on computed tomography images may allow liver fibrosis severity to be assessed in patients with chronic liver disease.

Entities:  

Keywords:  Deep learning; Liver fibrosis; Multidetector computed tomography; Organ volume

Year:  2020        PMID: 32055946     DOI: 10.1007/s00330-020-06665-4

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  10 in total

1.  Immunosuppression and cardiovascular dysfunction in patients with severe versus mild coronavirus disease 2019: a case series.

Authors:  Hejing Bao; Gang Li; Yinhua Fang; Qin Lai; Hehong Bao; Yu Zheng; Yanjun Hu
Journal:  Clin Transl Immunology       Date:  2020-10-01

2.  Diagnostic performance of liver fibrosis assessment by quantification of liver surface nodularity on computed tomography and magnetic resonance imaging: systematic review and meta-analysis.

Authors:  Subin Heo; Dong Wook Kim; Sang Hyun Choi; Seong Woo Kim; Jong Keon Jang
Journal:  Eur Radiol       Date:  2022-01-19       Impact factor: 5.315

3.  Diagnosis of Liver Cirrhosis and Liver Fibrosis by Artificial Intelligence Algorithm-Based Multislice Spiral Computed Tomography.

Authors:  Liexiu Wu; Bo Ning; Jianjun Yang; Yanni Chen; Caihong Zhang; Yun Yan
Journal:  Comput Math Methods Med       Date:  2022-03-15       Impact factor: 2.238

4.  Radiomics analysis of contrast-enhanced CT for staging liver fibrosis: an update for image biomarker.

Authors:  Jincheng Wang; Shengnan Tang; Yingfan Mao; Jin Wu; Shanshan Xu; Qi Yue; Jun Chen; Jian He; Yin Yin
Journal:  Hepatol Int       Date:  2022-03-28       Impact factor: 9.029

5.  Fully automated AI-based splenic segmentation for predicting survival and estimating the risk of hepatic decompensation in TACE patients with HCC.

Authors:  Lukas Müller; Roman Kloeckner; Aline Mähringer-Kunz; Fabian Stoehr; Christoph Düber; Gordon Arnhold; Simon Johannes Gairing; Friedrich Foerster; Arndt Weinmann; Peter Robert Galle; Jens Mittler; Daniel Pinto Dos Santos; Felix Hahn
Journal:  Eur Radiol       Date:  2022-04-08       Impact factor: 7.034

6.  Prognostic value of splenic volume in hepatocellular carcinoma patients receiving transarterial chemoembolization.

Authors:  Hai-Tao Dai; Bin Chen; Ke-Yu Tang; Gui-Yuan Zhang; Chun-Yong Wen; Xian-Hong Xiang; Jian-Yong Yang; Yan Guo; Run Lin; Yong-Hui Huang
Journal:  J Gastrointest Oncol       Date:  2021-06

Review 7.  Noninvasive staging of liver fibrosis: review of current quantitative CT and MRI-based techniques.

Authors:  Won Hyeong Im; Ji Soo Song; Weon Jang
Journal:  Abdom Radiol (NY)       Date:  2021-07-06

8.  Evaluation of a Deep Learning Algorithm for Automated Spleen Segmentation in Patients with Conditions Directly or Indirectly Affecting the Spleen.

Authors:  Aymen Meddeb; Tabea Kossen; Keno K Bressem; Bernd Hamm; Sebastian N Nagel
Journal:  Tomography       Date:  2021-12-13

9.  Liver-to-Spleen Volume Ratio Automatically Measured on CT Predicts Decompensation in Patients with B Viral Compensated Cirrhosis.

Authors:  Ji Hye Kwon; Seung Soo Lee; Jee Seok Yoon; Heung-Il Suk; Yu Sub Sung; Ho Sung Kim; Chul-Min Lee; Kang Mo Kim; So Jung Lee; So Yeon Kim
Journal:  Korean J Radiol       Date:  2021-08-31       Impact factor: 3.500

10.  Nature of the liver volume depending on the gender and age assessing volumetry from a reconstruction of the computed tomography.

Authors:  Kohei Harada; Tomohiro Ishinuki; Yoshiya Ohashi; Takeo Tanaka; Ayaka Chiba; Kanako Numasawa; Tatsuya Imai; Shun Hayasaka; Takahito Tsugiki; Koji Miyanishi; Minoru Nagayama; Ichiro Takemasa; Junji Kato; Toru Mizuguchi
Journal:  PLoS One       Date:  2021-12-08       Impact factor: 3.240

  10 in total

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