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Jan 28, 2016 (publication date) through Apr 25, 2024
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Publication Name
World Journal of Radiology
ISSN
1949-8470
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
| For: | Jansen JF, Lu Y, Gupta G, Lee NY, Stambuk HE, Mazaheri Y, Deasy JO, Shukla-Dave A. Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer. World J Radiol 2016; 8(1): 90-97 [PMID: 26834947 DOI: 10.4329/wjr.v8.i1.90] |
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| URL: | https://www.wjgnet.com/1949-8470/full/v8/i1/90.htm |
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Hirotaka Muraoka, Takashi Kaneda, Kotaro Ito, Naohisa Hirahara, Shungo Ichiki, Takumi Kondo. Diagnostic utility of magnetic resonance imaging texture analysis in suppurative osteomyelitis of the mandible. Oral Radiology 2022; 38(4): 601 doi: 10.1007/s11282-022-00595-1
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Hailin Li, Weiyuan Huang, Siwen Wang, Priya S. Balasubramanian, Gang Wu, Mengjie Fang, Xuebin Xie, Jie Zhang, Di Dong, Jie Tian, Feng Chen. Comprehensive integrated analysis of MR and DCE-MR radiomics models for prognostic prediction in nasopharyngeal carcinoma. Visual Computing for Industry, Biomedicine, and Art 2023; 6(1) doi: 10.1186/s42492-023-00149-0
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| 14 |
Yue Cao, Madhava Aryal, Pin Li, Choonik Lee, Matthew Schipper, Peter G. Hawkins, Christina Chapman, Dawn Owen, Aleksandar F. Dragovic, Paul Swiecicki, Keith Casper, Francis Worden, Theodore S. Lawrence, Avraham Eisbruch, Michelle Mierzwa. Predictive Values of MRI and PET Derived Quantitative Parameters for Patterns of Failure in Both p16+ and p16– High Risk Head and Neck Cancer. Frontiers in Oncology 2019; 9 doi: 10.3389/fonc.2019.01118
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| 15 |
Amit Jethanandani, Timothy A. Lin, Stefania Volpe, Hesham Elhalawani, Abdallah S. R. Mohamed, Pei Yang, Clifton D. Fuller. Exploring Applications of Radiomics in Magnetic Resonance Imaging of Head and Neck Cancer: A Systematic Review. Frontiers in Oncology 2018; 8 doi: 10.3389/fonc.2018.00131
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| 16 |
Cosimo Nardi, Maddalena Tomei, Michele Pietragalla, Linda Calistri, Nicholas Landini, Pierluigi Bonomo, Giuditta Mannelli, Francesco Mungai, Luigi Bonasera, Stefano Colagrande. Texture analysis in the characterization of parotid salivary gland lesions: A study on MR diffusion weighted imaging. European Journal of Radiology 2021; 136: 109529 doi: 10.1016/j.ejrad.2021.109529
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| 17 |
Roland M. Martens, Daniel P. Noij, Meedie Ali, Thomas Koopman, J. Tim Marcus, Marije R. Vergeer, Henrica de Vet, Marcus C. de Jong, C. René Leemans, Otto S. Hoekstra, Remco de Bree, Pim de Graaf, Ronald Boellaard, Jonas A. Castelijns. Functional imaging early during (chemo)radiotherapy for response prediction in head and neck squamous cell carcinoma; a systematic review. Oral Oncology 2019; 88: 75 doi: 10.1016/j.oraloncology.2018.11.005
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| 18 |
Huan‐ling Guo, Li‐da Chen, Wei Li, Jin‐yu Liang, Jian‐chao Zhang, Xin Li, Xiao‐yan Xie, Ming‐de Lu, Ming Kuang, Wei Wang. Ultrasomics for Early Evaluation of the Tumor Response to MicroRNA‐122 in a Nude Mouse Hepatocellular Carcinoma Model. Journal of Ultrasound in Medicine 2020; 39(1): 61 doi: 10.1002/jum.15071
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| 19 |
H. Kuno, M.M. Qureshi, M.N. Chapman, B. Li, V.C. Andreu-Arasa, K. Onoue, M.T. Truong, O. Sakai. CT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with Chemoradiotherapy. American Journal of Neuroradiology 2017; 38(12): 2334 doi: 10.3174/ajnr.A5407
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| 20 |
Jiliang Ren, Ying Yuan, Yiqian Shi, Xiaofeng Tao. Tumor heterogeneity in oral and oropharyngeal squamous cell carcinoma assessed by texture analysis of CT and conventional MRI: a potential marker of overall survival. Acta Radiologica 2019; 60(10): 1273 doi: 10.1177/0284185119825487
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| 21 |
Abhishek Mahajan, Ankita Ahuja, Nilesh Sable, Hilda E. Stambuk. Imaging in oral cancers: A comprehensive review. Oral Oncology 2020; 104: 104658 doi: 10.1016/j.oraloncology.2020.104658
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| 22 |
Jacobus F. A. Jansen, Gerhard S. Drenthen. Editorial for “MRI‐Based Back Propagation Neural Network Model as a Powerful Tool for Predicting the Response to Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma”. Journal of Magnetic Resonance Imaging 2022; 56(2): 560 doi: 10.1002/jmri.28049
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| 23 |
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. Diagnostic Utility of Radiomics in Thyroid and Head and Neck Cancers. Frontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.639326
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| 24 |
Mario Tortora, Laura Gemini, Alessandra Scaravilli, Lorenzo Ugga, Andrea Ponsiglione, Arnaldo Stanzione, Felice D’Arco, Gennaro D’Anna, Renato Cuocolo. Radiomics Applications in Head and Neck Tumor Imaging: A Narrative Review. Cancers 2023; 15(4): 1174 doi: 10.3390/cancers15041174
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| 25 |
Francesca Gallivanone, Marta Maria Panzeri, Carla Canevari, Claudio Losio, Luigi Gianolli, Francesco De Cobelli, Isabella Castiglioni. Biomarkers from in vivo molecular imaging of breast cancer: pretreatment 18F-FDG PET predicts patient prognosis, and pretreatment DWI-MR predicts response to neoadjuvant chemotherapy. Magnetic Resonance Materials in Physics, Biology and Medicine 2017; 30(4): 359 doi: 10.1007/s10334-017-0610-7
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| 26 |
S. Sun, P.A. Bonaffini, S. Nougaret, L. Fournier, A. Dohan, J. Chong, J. Smith, H. Addley, C. Reinhold. How to differentiate uterine leiomyosarcoma from leiomyoma with imaging. Diagnostic and Interventional Imaging 2019; 100(10): 619 doi: 10.1016/j.diii.2019.07.007
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Wen-zhu Li, Gang Wu, Tian-sheng Li, Gan-mian Dai, Yu-ting Liao, Qian-yu Yang, Feng Chen, Wei-yuan Huang. Dynamic contrast-enhanced magnetic resonance imaging-based radiomics for the prediction of progression-free survival in advanced nasopharyngeal carcinoma. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.955866
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| 28 |
Yen Hui Ong, Weihui Zheng, Pek Lan Khong, Qianqian Ni. Application of radiogenomics in head and neck cancer: A new tool toward diagnosis and therapy. iRADIOLOGY 2024; 2(2): 113 doi: 10.1002/ird3.61
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| 29 |
James C. Korte, Carlos Cardenas, Nicholas Hardcastle, Tomas Kron, Jihong Wang, Houda Bahig, Baher Elgohari, Rachel Ger, Laurence Court, Clifton D. Fuller, Sweet Ping Ng. Radiomics feature stability of open-source software evaluated on apparent diffusion coefficient maps in head and neck cancer. Scientific Reports 2021; 11(1) doi: 10.1038/s41598-021-96600-4
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| 30 |
Amrita Guha, Steve Connor, Mustafa Anjari, Harish Naik, Musib Siddiqui, Gary Cook, Vicky Goh. Radiomic analysis for response assessment in advanced head and neck cancers, a distant dream or an inevitable reality? A systematic review of the current level of evidence. The British Journal of Radiology 2020; 93(1106): 20190496 doi: 10.1259/bjr.20190496
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| 31 |
Noriyuki Fujima, Akihiro Homma, Taisuke Harada, Yukie Shimizu, Khin Khin Tha, Satoshi Kano, Takatsugu Mizumachi, Ruijiang Li, Kohsuke Kudo, Hiroki Shirato. The utility of MRI histogram and texture analysis for the prediction of histological diagnosis in head and neck malignancies. Cancer Imaging 2019; 19(1) doi: 10.1186/s40644-019-0193-9
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Hans-Jonas Meyer, Gordian Hamerla, Anne Kathrin Höhn, Alexey Surov. CT Texture Analysis—Correlations With Histopathology Parameters in Head and Neck Squamous Cell Carcinomas. Frontiers in Oncology 2019; 9 doi: 10.3389/fonc.2019.00444
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Elisa Scalco, Simona Marzi, Giuseppe Sanguineti, Antonello Vidiri, Giovanna Rizzo. Characterization of cervical lymph-nodes using a multi-parametric and multi-modal approach for an early prediction of tumor response to chemo-radiotherapy. Physica Medica 2016; 32(12): 1672 doi: 10.1016/j.ejmp.2016.09.003
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Kasia Owczarczyk, Davide Prezzi, Matthew Cascino, Robert Kozarski, Andrew Gaya, Muhammad Siddique, Gary J. Cook, Rob Glynne-Jones, Vicky Goh. MRI heterogeneity analysis for prediction of recurrence and disease free survival in anal cancer. Radiotherapy and Oncology 2019; 134: 119 doi: 10.1016/j.radonc.2019.01.022
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