Literature DB >> 30627523

Radiomics in head and neck cancer: from exploration to application.

Andrew J Wong1,2, Aasheesh Kanwar1,3, Abdallah S Mohamed1,4, Clifton D Fuller1,5.   

Abstract

In the context of clinical oncology, a fundamental goal of radiomics is the extraction of large amounts of quantitative features whose subsequent analysis can be used for decision support towards personalized and actionable cancer care. Head and neck cancers present a unique set of diagnostic and therapeutic challenges by nature of its complex anatomy and heterogeneity. Radiomics holds the potential to address these barriers, but only if as a collective field we direct future effort towards investigating specific oncologic function and oncologic outcomes, with external validation and collaborative multi-institutional efforts to begin standardizing and refining radiomic signatures. Here we present an overview of radiomic texture analysis methods as well as the software infrastructure, review the developments of radiomics in head and neck cancer applications, discuss unmet challenges, and propose key recommendations for moving the field forward.

Entities:  

Keywords:  Radiomics; head and neck cancer; imaging biomarker; machine learning; texture analysis

Year:  2016        PMID: 30627523      PMCID: PMC6322843          DOI: 10.21037/tcr.2016.07.18

Source DB:  PubMed          Journal:  Transl Cancer Res        ISSN: 2218-676X            Impact factor:   1.241


  24 in total

1.  CT-based Radiomic Signatures for Predicting Histopathologic Features in Head and Neck Squamous Cell Carcinoma.

Authors:  Pritam Mukherjee; Murilo Cintra; Chao Huang; Mu Zhou; Shankuan Zhu; A Dimitrios Colevas; Nancy Fischbein; Olivier Gevaert
Journal:  Radiol Imaging Cancer       Date:  2020-05-15

2.  Radiomics Analysis of PET and CT Components of PET/CT Imaging Integrated with Clinical Parameters: Application to Prognosis for Nasopharyngeal Carcinoma.

Authors:  Wenbing Lv; Qingyu Yuan; Quanshi Wang; Jianhua Ma; Qianjin Feng; Wufan Chen; Arman Rahmim; Lijun Lu
Journal:  Mol Imaging Biol       Date:  2019-10       Impact factor: 3.488

Review 3.  Radiomics: from qualitative to quantitative imaging.

Authors:  William Rogers; Sithin Thulasi Seetha; Turkey A G Refaee; Relinde I Y Lieverse; Renée W Y Granzier; Abdalla Ibrahim; Simon A Keek; Sebastian Sanduleanu; Sergey P Primakov; Manon P L Beuque; Damiënne Marcus; Alexander M A van der Wiel; Fadila Zerka; Cary J G Oberije; Janita E van Timmeren; Henry C Woodruff; Philippe Lambin
Journal:  Br J Radiol       Date:  2020-02-26       Impact factor: 3.039

4.  Magnetic resonance image biomarkers improve differentiation of benign and malignant parotid tumors through diagnostic model analysis.

Authors:  Yuebo Liu; Jiabao Zheng; Jizhi Zhao; Lijiang Yu; Xiaoping Lu; Zhihui Zhu; Chunlan Guo; Tao Zhang
Journal:  Oral Radiol       Date:  2021-01-11       Impact factor: 1.852

5.  Data-Driven Methods for Advancing Precision Oncology.

Authors:  Prema Nedungadi; Akshay Iyer; Georg Gutjahr; Jasmine Bhaskar; Asha B Pillai
Journal:  Curr Pharmacol Rep       Date:  2018-03-06

Review 6.  Diagnostic Utility of Radiomics in Thyroid and Head and Neck Cancers.

Authors:  Maryam Gul; Kimberley-Jane C Bonjoc; David Gorlin; Chi Wah Wong; Amirah Salem; Vincent La; Aleksandr Filippov; Abbas Chaudhry; Muhammad H Imam; Ammar A Chaudhry
Journal:  Front Oncol       Date:  2021-07-07       Impact factor: 6.244

7.  Development and validation of an MRI-based radiomics nomogram for distinguishing Warthin's tumour from pleomorphic adenomas of the parotid gland.

Authors:  Ying-Mei Zheng; Jiao Chen; Qi Xu; Wen-Hui Zhao; Xin-Feng Wang; Ming-Gang Yuan; Zong-Jing Liu; Zeng-Jie Wu; Cheng Dong
Journal:  Dentomaxillofac Radiol       Date:  2021-05-05       Impact factor: 3.525

8.  Evaluating the Effect of Right-Censored End Point Transformation for Radiomic Feature Selection of Data From Patients With Oropharyngeal Cancer.

Authors:  Luka Zdilar; David M Vock; G Elisabeta Marai; Clifton D Fuller; Abdallah S R Mohamed; Hesham Elhalawani; Baher Ahmed Elgohari; Carly Tiras; Austin Miller; Guadalupe Canahuate
Journal:  JCO Clin Cancer Inform       Date:  2018-12

9.  Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer.

Authors:  Martin Vallières; Emily Kay-Rivest; Léo Jean Perrin; Xavier Liem; Christophe Furstoss; Hugo J W L Aerts; Nader Khaouam; Phuc Felix Nguyen-Tan; Chang-Shu Wang; Khalil Sultanem; Jan Seuntjens; Issam El Naqa
Journal:  Sci Rep       Date:  2017-08-31       Impact factor: 4.379

10.  Oropharyngeal cancer patient stratification using random forest based-learning over high-dimensional radiomic features.

Authors:  Harsh Patel; David M Vock; G Elisabeta Marai; Clifton D Fuller; Abdallah S R Mohamed; Guadalupe Canahuate
Journal:  Sci Rep       Date:  2021-07-07       Impact factor: 4.379

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