计算机辅助图像分析有助于晚期神经母细胞瘤的预后评估。
Computer-assisted image analysis can aid the prognostication of advanced-stage neuroblastomas.
作者信息
Mogilner J G, Eldar S, Sabo E, Hassoun M, Attias D, Brodski A, Ben Harush M, Kuten A, Steiner Z, Misselevich I, Bejar J, Ben Yizhak D, Kerner V, Laor R, Boss J H
机构信息
Department of Pediatric Surgery, Bnai-Zion Medical Center, Haifa, Israel.
出版信息
J Cancer Res Clin Oncol. 2000 May;126(5):285-90. doi: 10.1007/s004320050344.
PURPOSE
The aim of this work was to detect nuclear parameters related to the prognosis of patients with stage III, IV or DS neuroblastomas.
METHODS
Histological sections of 25 operation specimens obtained from children with advanced-stage neuroblastomas were subjected to computer-assisted image analysis. Statistical relationships between nuclear descriptors of the tumor cells and patients' clinical outcome were determined.
RESULTS
The coefficient of variability of the mean nuclear area the mean nuclear elongation factor, and the mean nuclear averaged Feret diameter of the neuroblastoma cells were ascertained to be discriminators separating high-grade from low-grade tumors.
CONCLUSIONS
The histomorphometrically gauged nuclear parameters may help oncologists to assess the prognosis of patients with advanced-stage neuroblastoma.
目的
本研究旨在检测与Ⅲ期、Ⅳ期或播散性神经母细胞瘤患者预后相关的核参数。
方法
对25例晚期神经母细胞瘤患儿手术标本的组织切片进行计算机辅助图像分析。确定肿瘤细胞核描述符与患者临床结局之间的统计关系。
结果
神经母细胞瘤细胞的平均核面积变异系数、平均核伸长因子和平均核平均费雷特直径被确定为区分高级别和低级别肿瘤的判别指标。
结论
组织形态计量学测量的核参数可能有助于肿瘤学家评估晚期神经母细胞瘤患者的预后。
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