Renal tumor quantification and classification in contrast-enhanced abdominal CT

PATTERN RECOGNITION

卷:42

Article

Linguraru, Marius George¹  Yao, Jianhua¹  Gautam, Rabindra²  Peterson, James²  Li, Zhixi¹  Linehan, W. Marston²  Summers, Ronald M.¹ 

[1] NIH, Ctr Clin, Dept Radiol & Imaging Sci, Bethesda, MD 20892 USA

[2] NCI, Urol Oncol Branch, NIH, Bethesda, MD 20892 USA

关键词: Contrast-enhanced CT;    Kidney cancer;    von Hippel Lindau syndrome;    Hereditary papillary renal carcinoma;    Segmentation;    Quantification;    Classification;    Monitoring;    Level sets;    Computer-assisted radiology;   

DOI  :  10.1016/j.patcog.2008.09.018

来源: Elsevier

【 摘 要 】

Kidney cancer Occurs in both hereditary (inherited) and sporadic (non-inherited) form. It is estimated that almost a quarter of a million people in the USA are living with kidney cancer and their number increases, with 51,000 diagnosed with the disease every year. In clinical practice, the response to treatment is monitored by manual measurements of tumor size, which are 21), do not reflect the 3D geometry and enhancement of tumors, and show high intra- and inter-operator variability. We propose a computer-assisted radiology too] to assess renal tumors in contrast-enhanced CT for the management Of tumor diagnoses and responses to now treatments. The algorithm employs anisotropic diffusion (for smoothing), a combination of fast-marching and geodesic level-sets (for segmentation), and a novel statistical refinement step to adapt to the shape of the lesions. It also quantifies the 3D size, volume and enhancement (If the lesion, and allows serial management over time. Tumors are robustly segmented and the comparison between manual and semi-automated quantifications shows disparity within the limits of inter-observer variability. The analysis of lesion enhancement for tumor classification shows great separation between cysts, von Hippel-Lindau syndrome lesions. and hereditary papillary renal carcinomas (HPRC) with p-values inferior to 0.004. The results on temporal evaluation of tumors from serial scans illustrate the potential of the method to become an important tool for disease monitoring, drug trials, and non-invasive clinical surveillance. (C) 2008 Published by Elsevier Ltd.

【 授权许可】

Free