Literature DB >> 33891149

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

Amir A Borhani1, Roberta Catania2, Yuri S Velichko2, Stefanie Hectors3,4, Bachir Taouli3,4, Sara Lewis3,4.   

Abstract

Radiomics refers to the process of conversion of conventional medical images into quantifiable data ("features") which can be further mined to reveal complex patterns and relationships between the voxels in the image. These high throughput features can potentially reflect the histology of biologic tissues at macroscopic and microscopic levels. Several studies have investigated radiomics of hepatocellular carcinoma (HCC) before and after treatment. HCC is a heterogeneous disease with diverse phenotypical and genotypical landscape. Due to this inherent heterogeneity, HCC lesions can manifest variable aggressiveness with different response to treatment options, including the newer targeted therapies. Hence, radiomics can be used as a potential tool to enable patient selection for therapies and to predict response to treatments and outcome. Additionally, radiomics may serve as a tool for earlier and more efficient assessment of response to treatment. Radiomics, radiogenomics, and radio-immunoprofiling and their potential roles in management of patients with HCC will be discussed and critically reviewed in this article.

Entities:  

Keywords:  Hepatocellular carcinoma; Oncology; Radiogenomics; Radiomics

Year:  2021        PMID: 33891149     DOI: 10.1007/s00261-021-03085-w

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  63 in total

1.  LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity.

Authors:  Christophe Nioche; Fanny Orlhac; Sarah Boughdad; Sylvain Reuzé; Jessica Goya-Outi; Charlotte Robert; Claire Pellot-Barakat; Michael Soussan; Frédérique Frouin; Irène Buvat
Journal:  Cancer Res       Date:  2018-06-29       Impact factor: 12.701

2.  IBEX: an open infrastructure software platform to facilitate collaborative work in radiomics.

Authors:  Lifei Zhang; David V Fried; Xenia J Fave; Luke A Hunter; Jinzhong Yang; Laurence E Court
Journal:  Med Phys       Date:  2015-03       Impact factor: 4.071

3.  New strategies in hepatocellular carcinoma: genomic prognostic markers.

Authors:  Augusto Villanueva; Yujin Hoshida; Sara Toffanin; Anja Lachenmayer; Clara Alsinet; Radoslav Savic; Helena Cornella; Josep M Llovet
Journal:  Clin Cancer Res       Date:  2010-08-16       Impact factor: 12.531

4.  Landscape of immune microenvironment in hepatocellular carcinoma and its additional impact on histological and molecular classification.

Authors:  Yutaka Kurebayashi; Hidenori Ojima; Hanako Tsujikawa; Naoto Kubota; Junki Maehara; Yuta Abe; Minoru Kitago; Masahiro Shinoda; Yuko Kitagawa; Michiie Sakamoto
Journal:  Hepatology       Date:  2018-07-25       Impact factor: 17.425

5.  Computational Radiomics System to Decode the Radiographic Phenotype.

Authors:  Joost J M van Griethuysen; Andriy Fedorov; Chintan Parmar; Ahmed Hosny; Nicole Aucoin; Vivek Narayan; Regina G H Beets-Tan; Jean-Christophe Fillion-Robin; Steve Pieper; Hugo J W L Aerts
Journal:  Cancer Res       Date:  2017-11-01       Impact factor: 12.701

6.  Immunological and molecular correlates of disease recurrence after liver resection for hepatocellular carcinoma.

Authors:  Elisabetta Cariani; Massimo Pilli; Alessandro Zerbini; Cristina Rota; Andrea Olivani; Guido Pelosi; Claudia Schianchi; Paolo Soliani; Nicoletta Campanini; Enrico Maria Silini; Tommaso Trenti; Carlo Ferrari; Gabriele Missale
Journal:  PLoS One       Date:  2012-03-02       Impact factor: 3.240

7.  RaCaT: An open source and easy to use radiomics calculator tool.

Authors:  Elisabeth Pfaehler; Alex Zwanenburg; Johan R de Jong; Ronald Boellaard
Journal:  PLoS One       Date:  2019-02-20       Impact factor: 3.240

8.  Radiomics: Images Are More than Pictures, They Are Data.

Authors:  Robert J Gillies; Paul E Kinahan; Hedvig Hricak
Journal:  Radiology       Date:  2015-11-18       Impact factor: 11.105

Review 9.  The biology of Hepatocellular carcinoma: implications for genomic and immune therapies.

Authors:  Galina Khemlina; Sadakatsu Ikeda; Razelle Kurzrock
Journal:  Mol Cancer       Date:  2017-08-30       Impact factor: 27.401

10.  Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing.

Authors:  Grzegorz Chlebus; Andrea Schenk; Jan Hendrik Moltz; Bram van Ginneken; Horst Karl Hahn; Hans Meine
Journal:  Sci Rep       Date:  2018-10-19       Impact factor: 4.379

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  3 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

2.  An update on radiomics techniques in primary liver cancers.

Authors:  Vincenza Granata; Roberta Fusco; Sergio Venazio Setola; Igino Simonetti; Diletta Cozzi; Giulia Grazzini; Francesca Grassi; Andrea Belli; Vittorio Miele; Francesco Izzo; Antonella Petrillo
Journal:  Infect Agent Cancer       Date:  2022-03-04       Impact factor: 2.965

3.  CT-Based Radiomics Analysis to Predict Histopathological Outcomes Following Liver Resection in Colorectal Liver Metastases.

Authors:  Vincenza Granata; Roberta Fusco; Sergio Venanzio Setola; Federica De Muzio; Federica Dell' Aversana; Carmen Cutolo; Lorenzo Faggioni; Vittorio Miele; Francesco Izzo; Antonella Petrillo
Journal:  Cancers (Basel)       Date:  2022-03-24       Impact factor: 6.639

  3 in total

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