Literature DB >> 32605628

Texture analysis of MR images to identify the differentiated degree in hepatocellular carcinoma: a retrospective study.

Mengmeng Feng1, Mengchao Zhang2, Yuanqing Liu1, Nan Jiang1, Qian Meng1, Jia Wang3, Ziyun Yao4, Wenjuan Gan4, Hui Dai5,6.   

Abstract

BACKGROUND: To explore the clinical value of texture analysis of MR images (multiphase Gd-EOB-DTPA-enhanced MRI and T2 weighted imaging (T2WI) to identify the differentiated degree of hepatocellular carcinoma (HCC).
METHOD: One hundred four participants were enrolled in this retrospective study. Each participant performed preoperative Gd-EOB-DTPA-enhanced MR scanning. Texture features were analyzed by MaZda, and B11 program was used for data analysis and classification. The diagnosis efficiencies of texture features and conventional imaging features in identifying the differentiated degree of HCC were assessed by receiver operating characteristic analysis. The relationship between texture features and differentiated degree of HCC was evaluated by Spearman's correlation coefficient.
RESULTS: The grey-level co-occurrence matrix -based texture features were most frequently extracted and the nonlinear discriminant analysis was excellent with the misclassification rate ranging from 3.33 to 14.93%. The area under the curve (AUC) of the combined texture features between poorly- and well-differentiated HCC, poorly- and moderately-differentiated HCC, moderately- and well-differentiated HCC was 0.812, 0.879 and 0.808 respectively, while the AUC of tumor size was 0.649, 0.660 and 0.517 respectively. The tumor size was significantly different between poorly- and moderately-HCC (p = 0.014). The COMBINE AUC values were not increased with tumor size combined.
CONCLUSIONS: Texture analysis of Gd-EOB-DTPA-enhanced MRI and T2WI was valuable and might be a promising method in identifying the differentiated degree of HCC. The poorly-differentiated HCC was more heterogeneous than well- and moderately-differentiated HCC.

Entities:  

Keywords:  Differentiated degree; Hepatocellular carcinoma; Texture feature

Year:  2020        PMID: 32605628      PMCID: PMC7325565          DOI: 10.1186/s12885-020-07094-8

Source DB:  PubMed          Journal:  BMC Cancer        ISSN: 1471-2407            Impact factor:   4.430


  34 in total

Review 1.  Should we biopsy each liver mass suspicious for HCC before liver transplantation?--no, please don't.

Authors:  R Stigliano; A K Burroughs
Journal:  J Hepatol       Date:  2005-10       Impact factor: 25.083

2.  MaZda--a software package for image texture analysis.

Authors:  Piotr M Szczypiński; Michał Strzelecki; Andrzej Materka; Artur Klepaczko
Journal:  Comput Methods Programs Biomed       Date:  2008-10-14       Impact factor: 5.428

3.  Edmondson-Steiner grading increases the predictive efficiency of TNM staging for long-term survival of patients with hepatocellular carcinoma after curative resection.

Authors:  Li Zhou; Jing-An Rui; Da-Xiong Ye; Shao-Bin Wang; Shu-Guang Chen; Qiang Qu
Journal:  World J Surg       Date:  2008-08       Impact factor: 3.352

4.  Angiomyolipoma with minimal fat: differentiation from clear cell renal cell carcinoma and papillary renal cell carcinoma by texture analysis on CT images.

Authors:  Lifen Yan; Zaiyi Liu; Guangyi Wang; Yanqi Huang; Yubao Liu; Yuanxin Yu; Changhong Liang
Journal:  Acad Radiol       Date:  2015-05-29       Impact factor: 3.173

5.  MRI features predict survival and molecular markers in diffuse lower-grade gliomas.

Authors:  Hao Zhou; Martin Vallières; Harrison X Bai; Chang Su; Haiyun Tang; Derek Oldridge; Zishu Zhang; Bo Xiao; Weihua Liao; Yongguang Tao; Jianhua Zhou; Paul Zhang; Li Yang
Journal:  Neuro Oncol       Date:  2017-06-01       Impact factor: 12.300

6.  Enhancement patterns of hepatocellular carcinomas on multiphasicmultidetector row CT: comparison with pathological differentiation.

Authors:  J H Lee; J M Lee; S J Kim; J H Baek; S H Yun; K W Kim; J K Han; B I Choi
Journal:  Br J Radiol       Date:  2012-09       Impact factor: 3.039

7.  Recurrent hepatocellular carcinoma after hepatic resection: prognostic factors and long-term outcome.

Authors:  W-T Chen; G-Y Chau; W-Y Lui; S-H Tsay; K-L King; C-C Loong; C-W Wu
Journal:  Eur J Surg Oncol       Date:  2004-05       Impact factor: 4.424

8.  Recurrence of hepatocellular carcinoma after liver transplant: patterns and prognosis.

Authors:  Sasan Roayaie; Jonathan D Schwartz; Max W Sung; Sukru H Emre; Charles M Miller; Gabriel E Gondolesi; Nancy R Krieger; Myron E Schwartz
Journal:  Liver Transpl       Date:  2004-04       Impact factor: 5.799

9.  MRI texture analysis in differentiating luminal A and luminal B breast cancer molecular subtypes - a feasibility study.

Authors:  Kirsi Holli-Helenius; Annukka Salminen; Irina Rinta-Kiikka; Ilkka Koskivuo; Nina Brück; Pia Boström; Riitta Parkkola
Journal:  BMC Med Imaging       Date:  2017-12-29       Impact factor: 1.930

10.  Resectable pancreatic ductal adenocarcinoma: association between preoperative CT texture features and metastatic nodal involvement.

Authors:  Wei Huan Fang; Xu Dong Li; Hui Zhu; Fei Miao; Xiao Hua Qian; Zi Lai Pan; Xiao Zhu Lin
Journal:  Cancer Imaging       Date:  2020-02-10       Impact factor: 3.909

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  5 in total

1.  MRI-Based Radiomic Features Help Identify Lesions and Predict Histopathological Grade of Hepatocellular Carcinoma.

Authors:  Valentina Brancato; Nunzia Garbino; Marco Salvatore; Carlo Cavaliere
Journal:  Diagnostics (Basel)       Date:  2022-04-26

Review 2.  Quantitative magnetic resonance imaging for focal liver lesions: bridging the gap between research and clinical practice.

Authors:  Roberto Cannella; Riccardo Sartoris; Jules Grégory; Lorenzo Garzelli; Valérie Vilgrain; Maxime Ronot; Marco Dioguardi Burgio
Journal:  Br J Radiol       Date:  2021-05-14       Impact factor: 3.629

Review 3.  Progress of MRI Radiomics in Hepatocellular Carcinoma.

Authors:  Xue-Qin Gong; Yun-Yun Tao; Yao-Kun Wu; Ning Liu; Xi Yu; Ran Wang; Jing Zheng; Nian Liu; Xiao-Hua Huang; Jing-Dong Li; Gang Yang; Xiao-Qin Wei; Lin Yang; Xiao-Ming Zhang
Journal:  Front Oncol       Date:  2021-09-20       Impact factor: 6.244

4.  Texture analysis of low-flow vascular malformations in the oral and maxillofacial region: venous malformation vs. lymphatic malformation.

Authors:  Kotaro Ito; Hirotaka Muraoka; Naohisa Hirahara; Eri Sawada; Satoshi Tokunaga; Takashi Kaneda
Journal:  Pol J Radiol       Date:  2022-09-05

5.  Single-Photon Emission Computed Tomography/Computed Tomography Image-Based Radiomics for Discriminating Vertebral Bone Metastases From Benign Bone Lesions in Patients With Tumors.

Authors:  Zhicheng Jin; Fang Zhang; Yizhen Wang; Aijuan Tian; Jianan Zhang; Meiyan Chen; Jing Yu
Journal:  Front Med (Lausanne)       Date:  2022-01-04
  5 in total

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