Infrared spectroscopic imaging for histopathologic recognition

被引:486
作者
Fernandez, DC
Bhargava, R
Hewitt, SM
Levin, IW
机构
[1] NIDDKD, Chem Phys Lab, NIH, Bethesda, MD 20892 USA
[2] NCI, Tissue Array Res Program, Pathol Lab, Ctr Canc Res,NIH, Bethesda, MD 20892 USA
基金
美国国家卫生研究院;
关键词
D O I
10.1038/nbt1080
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
The process of histopathology, comprising tissue staining and morphological pattern recognition, has remained largely unchanged for over 140 years(1). Although it is integral to clinical and research activities, histopathologic recognition remains a time-consuming, subjective process to which only limited statistical confidence can be assigned because of inherent operator variability(2,3). Although immunohistochemical approaches allow limited molecular detection, significant challenges remain in using them for quantitative, automated pathology. Vibrational spectroscopic approaches, by contrast, directly provide nonperturbing molecular descriptors(4), but a practical spectroscopic protocol for histopathology is lacking. Here we couple high-throughput Fourier transform infrared (FTIR) spectroscopic imaging(5) of tissue microarrays(6) with statistical pattern recognition of spectra indicative of endogenous molecular composition and demonstrate histopathologic characterization of prostatic tissue. This automated histologic segmentation is applied to routine archival tissue samples, incorporates well-defined tests of statistical significance(7) and eliminates any requirement for dyes or molecular probes. Finally, we differentiate benign from malignant prostatic epithelium by spectroscopic analyses.
引用
收藏
页码:469 / 474
页数:6
相关论文
共 36 条
  • [1] Interobserver reproducibility of Gleason grading of prostatic carcinoma: Urologic pathologists
    Allsbrook, WC
    Mangold, KA
    Johnson, MH
    Lane, RB
    Lane, CG
    Amin, MB
    Bostwick, DG
    Humphrey, PA
    Jones, EC
    Reuter, VE
    Sakr, W
    Sesterhenn, IA
    Troncoso, P
    Wheeler, TM
    Epstein, JI
    [J]. HUMAN PATHOLOGY, 2001, 32 (01) : 74 - 80
  • [2] Andrus PGL, 1998, BIOSPECTROSCOPY, V4, P37, DOI 10.1002/(SICI)1520-6343(1998)4:1<37::AID-BSPY4>3.0.CO
  • [3] 2-P
  • [4] [Anonymous], 2003, Statistical pattern recognition
  • [5] The framework of pathology: Good Laboratory Practice by quantitative and molecular methods
    Baak, JPA
    [J]. JOURNAL OF PATHOLOGY, 2002, 198 (03) : 277 - 283
  • [6] Fourier transform infrared imaging: Theory and practice
    Bhargava, R
    Levin, IW
    [J]. ANALYTICAL CHEMISTRY, 2001, 73 (21) : 5157 - 5167
  • [7] Boydston-White S, 1999, BIOSPECTROSCOPY, V5, P219, DOI 10.1002/(SICI)1520-6343(1999)5:4<219::AID-BSPY2>3.0.CO
  • [8] 2-O
  • [9] The use of the area under the roc curve in the evaluation of machine learning algorithms
    Bradley, AP
    [J]. PATTERN RECOGNITION, 1997, 30 (07) : 1145 - 1159
  • [10] A decade of vibrational micro-spectroscopy of human cells and tissue (1994-2004)
    Diem, M
    Romeo, M
    Boydston-White, S
    Miljkovic, M
    Matthäus, C
    [J]. ANALYST, 2004, 129 (10) : 880 - 885