Literature DB >> 28813195

Prediction of Therapeutic Response of Hepatocellular Carcinoma to Transcatheter Arterial Chemoembolization Based on Pretherapeutic Dynamic CT and Textural Findings.

Hyun Jeong Park1, Jung Hoon Kim2, Seo-Youn Choi3, Eun Sun Lee1, Sang Joon Park4, Jae Young Byun5, Byung Ihn Choi1.   

Abstract

OBJECTIVE: The objective of our study was to assess the value of CT texture analysis for prediction of therapeutic response of hepatocellular carcinoma (HCC) to transcatheter arterial chemoembolization (TACE) with pretherapeutic dynamic CT.
MATERIALS AND METHODS: We retrospectively analyzed 132 HCCs in 96 patients treated with TACE who underwent dynamic CT before initial TACE. Imaging findings and arterial enhancement ratios were analyzed. All HCCs were manually segmented, and their texture features were quantitatively extracted using in-house software. CT texture was quantified with 2D and 3D analysis. HCCs were classified as with and without complete response (CR) according to modified Response Evaluation Criteria in Solid Tumors. Predictive factors for CR were assessed with multivariate analysis. Radiologic responses were correlated with time to progression (TTP).
RESULTS: Of the 132 HCCs, CR was achieved in 75 (56.8%). Tumor size, subjective arterial tumor attenuation, and arterial enhancement ratios were significantly associated with CR. On 2D and 3D analysis, tumors with CR showed significantly lower homogeneity and higher mean attenuation, gray-level co-occurrence matrix (GLCM) moments, and CT number percentiles (p < 0.05). On multivariate analysis, higher subjective tumor attenuation (adjusted odds ratio [OR] = 23.35), arterial enhancement ratio (OR = 14.07), GLCM moments (OR = 6.57), smaller tumor size (OR = 17.26), and lower homogeneity (OR = 0.69) were significant predictors of CR compared with incomplete response (p < 0.05). Median survival value for TTP was significantly longer in tumors with CR (p < 0.001).
CONCLUSION: Pretherapeutic dynamic CT texture analysis can be valuable to predict CR of HCC to TACE. Higher arterial enhancement and GLCM moments, lower homogeneity, and smaller tumor size are significant predictors of CR after TACE.

Entities:  

Keywords:  CT; hepatocellular carcinoma; texture analysis; transcatheter arterial chemoembolization (TACE)

Mesh:

Year:  2017        PMID: 28813195     DOI: 10.2214/AJR.16.17398

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  24 in total

1.  Imaging prediction of nonalcoholic steatohepatitis using computed tomography texture analysis.

Authors:  Shotaro Naganawa; Kenichiro Enooku; Ryosuke Tateishi; Hiroyuki Akai; Koichiro Yasaka; Junji Shibahara; Tetsuo Ushiku; Osamu Abe; Kuni Ohtomo; Shigeru Kiryu
Journal:  Eur Radiol       Date:  2018-02-05       Impact factor: 5.315

2.  Harmonization of radiomic feature distributions: impact on classification of hepatic tissue in CT imaging.

Authors:  Hubert Beaumont; Antoine Iannessi; Anne-Sophie Bertrand; Jean Michel Cucchi; Olivier Lucidarme
Journal:  Eur Radiol       Date:  2021-01-18       Impact factor: 5.315

Review 3.  Radiomics of hepatocellular carcinoma.

Authors:  Sara Lewis; Stefanie Hectors; Bachir Taouli
Journal:  Abdom Radiol (NY)       Date:  2021-01

4.  Tumor Vascular Networks Depicted in Contrast-Enhanced Ultrasound Images as a Predictor for Transarterial Chemoembolization Treatment Response.

Authors:  Ipek Oezdemir; Corrine E Wessner; Colette Shaw; John R Eisenbrey; Kenneth Hoyt
Journal:  Ultrasound Med Biol       Date:  2020-06-16       Impact factor: 2.998

Review 5.  Radiomics of hepatocellular carcinoma: promising roles in patient selection, prediction, and assessment of treatment response.

Authors:  Amir A Borhani; Roberta Catania; Yuri S Velichko; Stefanie Hectors; Bachir Taouli; Sara Lewis
Journal:  Abdom Radiol (NY)       Date:  2021-04-23

6.  Texture analysis on gadoxetic acid enhanced-MRI for predicting Ki-67 status in hepatocellular carcinoma: A prospective study.

Authors:  Zheng Ye; Hanyu Jiang; Jie Chen; Xijiao Liu; Yi Wei; Chunchao Xia; Ting Duan; Likun Cao; Zhen Zhang; Bin Song
Journal:  Chin J Cancer Res       Date:  2019-10       Impact factor: 5.087

7.  A machine learning model to predict hepatocellular carcinoma response to transcatheter arterial chemoembolization.

Authors:  Ali Morshid; Khaled M Elsayes; Ahmed M Khalaf; Mohab M Elmohr; Justin Yu; Ahmed O Kaseb; Manal Hassan; Armeen Mahvash; Zhihui Wang; John D Hazle; David Fuentes
Journal:  Radiol Artif Intell       Date:  2019-09-25

Review 8.  Advanced analytics and artificial intelligence in gastrointestinal cancer: a systematic review of radiomics predicting response to treatment.

Authors:  Nina J Wesdorp; Tessa Hellingman; Elise P Jansma; Jan-Hein T M van Waesberghe; Ronald Boellaard; Cornelis J A Punt; Joost Huiskens; Geert Kazemier
Journal:  Eur J Nucl Med Mol Imaging       Date:  2020-12-16       Impact factor: 9.236

9.  Response prediction of hepatocellular carcinoma undergoing transcatheter arterial chemoembolization: unlocking the potential of CT texture analysis through nested decision tree models.

Authors:  Jan Vosshenrich; Christoph J Zech; Tobias Heye; Tuyana Boldanova; Geoffrey Fucile; Stefan Wieland; Markus H Heim; Daniel T Boll
Journal:  Eur Radiol       Date:  2020-12-03       Impact factor: 5.315

10.  Radiomic analysis of MRI to Predict Sustained Complete Response after Radiofrequency Ablation in Patients with Hepatocellular Carcinoma - A Pilot Study.

Authors:  Natally Horvat; Jose de Arimateia B Araujo-Filho; Antonildes N Assuncao-Jr; Felipe Augusto de M Machado; John A Sims; Camila Carlos Tavares Rocha; Brunna Clemente Oliveira; Joao Vicente Horvat; Claudia Maccali; Anna Luísa Boschiroli Lamanna Puga; Aline Lopes Chagas; Marcos Roberto Menezes; Giovanni Guido Cerri
Journal:  Clinics (Sao Paulo)       Date:  2021-07-16       Impact factor: 2.365

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