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Proceedings Paper

Automated segmentation of mesothelioma volume on CT scan
Author(s): Binsheng Zhao; Lawrence Schwartz; Raja Flores; Fan Liu; Peter Kijewski; Lee Krug; Valerie Rusch
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Paper Abstract

In mesothelioma, response is usually assessed by computed tomography (CT). In current clinical practice the Response Evaluation Criteria in Solid Tumors (RECIST) or WHO, i.e., the uni-dimensional or the bi-dimensional measurements, is applied to the assessment of therapy response. However, the shape of the mesothelioma volume is very irregular and its longest dimension is almost never in the axial plane. Furthermore, the sections and the sites where radiologists measure the tumor are rather subjective, resulting in poor reproducibility of tumor size measurements. We are developing an objective three-dimensional (3D) computer algorithm to automatically identify and quantify tumor volumes that are associated with malignant pleural mesothelioma to assess therapy response. The algorithm first extracts the lung pleural surface from the volumetric CT images by interpolating the chest ribs over a number of adjacent slices and then forming a volume that includes the thorax. This volume allows a separation of mesothelioma from the chest wall. Subsequently, the structures inside the extracted pleural lung surface, including the mediastinal area, lung parenchyma, and pleural mesothelioma, can be identified using a multiple thresholding technique and morphological operations. Preliminary results have shown the potential of utilizing this algorithm to automatically detect and quantify tumor volumes on CT scans and thus to assess therapy response for malignant pleural mesothelioma.

Paper Details

Date Published: 29 April 2005
PDF: 6 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.594596
Show Author Affiliations
Binsheng Zhao, Memorial Sloan-Kettering Cancer Ctr. (United States)
Lawrence Schwartz, Memorial Sloan-Kettering Cancer Ctr. (United States)
Raja Flores, Memorial Sloan-Kettering Cancer Ctr. (United States)
Fan Liu, Memorial Sloan-Kettering Cancer Ctr. (United States)
Peter Kijewski, Memorial Sloan-Kettering Cancer Ctr. (United States)
Lee Krug, Memorial Sloan-Kettering Cancer Ctr. (United States)
Valerie Rusch, Memorial Sloan-Kettering Cancer Ctr. (United States)


Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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