Literature DB >> 10787084

Measuring the tumor volume of gastric carcinoma by computer image analysis: clinical significance.

S Kikuchi1, Y Hiki, Y Sakakibara, A Kakita, S Kuwao.   

Abstract

The tumor diameter of gastric carcinoma, measured by gross or histologic examination, is a rough indicator of actual tumor size. Therefore we investigated the utility of three-dimensional reconstruction of tumors in gastric carcinoma. Altogether 105 primary gastric carcinoma lesions, consisting of 16 advanced and 89 early carcinomas, were analyzed. A total of 942 lesion tissue sections, comprising 2 to 37 sections per lesion (mean 9 sections), were examined histologically. Surface rendering using a computer graphics analysis program was then performed from serial sections to create a three-dimensional reconstruction of tumor morphology from which to measure tumor volume. For the 105 lesions the tumor diameter ranged between 4 and 106 mm (average +/- SE: 32.4 +/- 2.0 mm), and tumor volume ranged between 4 and 5853 mm3 (average +/- SE: 773.0 +/- 104.6 mm3). A significant correlation was found between tumor diameter and the log of the tumor volume (r = 0.733, p < 0.0001). Although the logs of tumor volume for advanced carcinomas were all > 2.5, in 11 of these 16 patients (66%) the tumor diameter was < 4 cm, and in one patient < 2 cm. In addition, tumor diameter did not differ significantly between the 16 advanced and the 89 early gastric carcinomas (p = 0.114), whereas the log of the tumor volume did (p < 0.0001). In conclusion, conventional measurements of tumor diameter as a rough indicator of tumor size can predict the actual tumor size of a gastric carcinoma. Three-dimensional reconstruction using computer graphics provides a better estimation of true tumor size and extent of progression than tumor diameter.

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Year:  2000        PMID: 10787084     DOI: 10.1007/s002689910096

Source DB:  PubMed          Journal:  World J Surg        ISSN: 0364-2313            Impact factor:   3.352


  1 in total

1.  Tumor volume of resectable gastric adenocarcinoma on multidetector computed tomography: association with N categories.

Authors:  Hang Li; Xiao-Li Chen; Jun-Ru Li; Zhen-Lin Li; Tian-Wu Chen; Hong Pu; Long-Lin Yin; Guo-Hui Xu; Zhen-Wen Li; Jing Reng; Peng Zhou; Zhu-Zhong Cheng; Ying Cao
Journal:  Clinics (Sao Paulo)       Date:  2016-04       Impact factor: 2.365

  1 in total

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