Identification of the most significant magnetic resonance imaging (MRI) radiomic features in oncological patients with vertebral bone marrow metastatic disease: a feasibility study-Reference-Cited by-同舟云学术

Identification of the most significant magnetic resonance imaging (MRI) radiomic features in oncological patients with vertebral bone marrow metastatic disease: a feasibility study

Published:2018-09-06 Issue:1 Volume:124 Page:50-57
ISSN:0033-8362
Container-title:La radiologia medica
language:en
Short-container-title:Radiol med

Author:

Filograna Laura,Lenkowicz Jacopo,Cellini Francesco,Dinapoli Nicola,Manfrida Stefania,Magarelli Nicola,Leone Antonio,Colosimo Cesare,Valentini Vincenzo

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

http://link.springer.com/article/10.1007/s11547-018-0935-y/fulltext.html

Reference21 articles.

1. Coleman RE (2001) Metastatic bone disease: clinical features, pathophysiology and treatment strategies. Cancer Treat Rev 27(3):165–176

2. Coleman RE (2006) Clinical features of metastatic bone disease and risk of skeletal morbidity. Clin Cancer Res 12(20 Pt 2):6243s–6249s

3. Kumar V, Gu Y, Basu S et al (2012) Radiomics: the process and the challenges. Magn Reson Imaging 30(9):1234–1248

4. Lambin P, Rios-Velazquez E, Leijenaar R et al (2012) Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 48(4):441–446

5. Ravanelli M, Farina D, Morassi M, Roca E, Cavalleri G, Tassi G, Maroldi R (2013) Texture analysis of advanced non-small cell lung cancer (nsclc) on contrast-enhanced computed tomography: prediction of the response to the first-line chemotherapy. Eur Radiol 23(12):3450–3455

Cited by 43 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial intelligence in skeletal metastasis imaging;Computational and Structural Biotechnology Journal;2024-12

2. Novel MRI scoring system to assess osseous malignancy in soft tissue sarcoma patients following radiotherapy;European Journal of Radiology;2024-09

3. Oncologic Applications of Artificial Intelligence and Deep Learning Methods in CT Spine Imaging—A Systematic Review;Cancers;2024-08-28

4. Deep Learning to Differentiate Benign and Malignant Vertebral Fractures at Multidetector CT;Radiology;2024-03-01

5. Autoimmune Encephalitis and Blood-Brain Barrier Permeability at Dynamic Contrast-enhanced MRI;Radiology;2024-03-01