Spectral imaging of multi-color chromogenic dyes in pathological specimens

被引:22
作者
Macville, MVE
Van der Laak, JAWM
Speel, EJM
Katzir, N
Garini, Y
Soenksen, D
McNamara, G
de Wilde, PCM
Hanselaar, AGJM
Hopman, AHN
Ried, T
机构
[1] Univ Med Ctr St Radboud, Dept Pathol, Lab ISH, NL-6500 HB Nijmegen, Netherlands
[2] NCI, Dept Genet, Div Clin Sci, NIH, Bethesda, MD 20892 USA
[3] Univ Maastricht, Dept Mol Cell Biol, Maastricht, Netherlands
[4] Appl Spectral Imaging, Migdal Haemeq, Israel
[5] Aperio Technol, Carlsbad, CA USA
[6] Childrens Hosp, Res Inst, Los Angeles, CA 90027 USA
来源
ANALYTICAL CELLULAR PATHOLOGY | 2001年 / 22卷 / 03期
关键词
spectral imaging; Fourier-transform spectroscopy; multicolor; in situ hybridization; immunocytochemistry; bright-field microscopy; absorption; optical density; pathology;
D O I
10.1155/2001/740909
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
We have investigated the use of spectral imaging for multicolor analysis of permanent cytochemical dyes and enzyme precipitates on cytopathological specimens. Spectral imaging is based on Fourier-transform spectroscopy and digital imaging. A pixel-by-pixel spectrum-based color classification is presented of single-, double-, and triple-color in situ hybridization for centromeric probes in T24 bladder cancer cells, and immunocytochemical staining of nuclear antigens Ki-67 and TP53 in paraffin-em bedded cervical brush material (AgarCyto). The results demonstrate that spectral imaging unambiguously identities three chromogenic dyes in a single bright-field microscopic specimen. Serial microscopic fields from the same specimen can be analyzed using a spectral reference library. We conclude that spectral imaging of multi-color chromogenic dyes is a reliable and robust method for pixel color recognition and classification. Our data further indicate that the use of spectral imaging (a) may increase the number of parameters studied simultaneously in pathological diagnosis, (b) may provide quantitative data (such as positive labeling indices) more accurately, and (c) may solve segmentation problems currently faced in automated screening of cell- and tissue specimens.
引用
收藏
页码:133 / 142
页数:10
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