Assessment of tumor heterogeneity: An emerging imaging tool for clinical practice?

被引：741

作者：

Davnall F. ^{[1
]}

Yip C.S.P. ^{[2
]}

Ljungqvist G. ^{[1
]}

Selmi M. ^{[1
]}

Ng F. ^{[3
]}

Sanghera B. ^{[3
]}

Ganeshan B. ^{[4
]}

Miles K.A. ^{[4
]}

Cook G.J. ^{[5
]}

Goh V. ^{[1
,2
,6
]}

机构：

[1] Division of Imaging Sciences and Biomedical Engineering, King's College London, London

[2] Department on Oncology, Guy's and St Thomas' NHS Foundation Trust, London

[3] Paul Strickland Scanner Centre, Mount Vernon Hospital, London, Middlesex

[4] Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton, Sussex, Falmer

[5] Division of Imaging Sciences and Biomedical Engineering, King's College London, PET Imaging Centre, London

[6] Chair of Clinical Cancer Imaging, Lambeth Wing, St Thomas Hospital, London, SE1 7EH, Lambeth Palace Road

来源：

Insights into Imaging | 2012年 / 3卷 / 6期

关键词：

Cancer; CT; Fractal analysis; MRI; PET; Texture analysis;

D O I：

10.1007/s13244-012-0196-6

中图分类号：

学科分类号：

摘要：

Background: Tumor spatial heterogeneity is an important prognostic factor, which may be reflected in medical imagesMethods: Image texture analysis is an approach of quantifying heterogeneity that may not be appreciated by the naked eye. Different methods can be applied including statistical-, model-, and transform-based methods. Results: Early evidence suggests that texture analysis has the potential to augment diagnosis and characterization as well as improve tumor staging and therapy response assessment in oncological practice. Conclusion: This review provides an overview of the application of texture analysis with different imaging modalities, CT, MRI, and PET, to date and describes the technical challenges that have limited its widespread clinical implementation so far. With further efforts to refine its application, image texture analysis has the potential to develop into a valuable clinical tool for oncologic imaging. Teaching Points: • Tumor spatial heterogeneity is an important prognostic factor.• Image texture analysis is an approach of quantifying heterogeneity.• Different methods can be applied, including statistical-, model-, and transform-based methods.• Texture analysis could improve the diagnosis, tumor staging, and therapy response assessment. © 2012 The Author(s).

引用

页码：573 / 589

页数：16

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