Diagnosis and prognosis of breast cancer by magnetic resonance spectroscopy of fine-needle aspirates analysed using a statistical classification strategy

被引:90
作者
Mountford, CE
Somorjai, RL
Malycha, P
Gluch, L
Lean, C
Russell, P
Barraclough, B
Gillett, D
Himmelreich, U
Dolenko, B
Nikulin, AE
Smith, ICP
机构
[1] Univ Sydney, Inst Magnet Resonanc Res, Dept Magnet Resonance Med, St Leonards, NSW 1590, Australia
[2] Univ Sydney, Inst Magnet Resonanc Res, Dept Pathol, St Leonards, NSW 1590, Australia
[3] Univ Sydney, Inst Magnet Resonanc Res, Dept Surg, St Leonards, NSW 1590, Australia
[4] Univ Adelaide, Royal Adelaide Hosp, Dept Surg, Adelaide, SA 5005, Australia
[5] Natl Res Council Canada, Inst Biodiagnost, Winnipeg, MB R3B 1Y6, Canada
关键词
D O I
10.1046/j.0007-1323.2001.01864.x
中图分类号
R61 [外科手术学];
学科分类号
摘要
Background: The aim was to develop robust classifiers to analyse magnetic resonance spectroscopy (MIRS) data of fine-needle aspirates taken from breast tumours. The resulting data could provide computerized, classification-based diagnosis and prognostic indicators. Methods: Fine-needle aspirate biopsies obtained at the time of surgery for both benign and malignant breast diseases were analysed by one-dimensional proton MRS at 8.5 Tesla. Diagnostic correlation was performed between the spectra and standard pathology reports, including the presence of vascular invasion by the primary cancer and involvement of the excised axillary lymph nodes. Results: Malignant tissue was distinguished from benign lesions with an overall accuracy of 93 per cent. From the same spectra, lymph node involvement was predicted with an overall accuracy of 95 per cent, and tumour vascular invasion with an overall accuracy of 94 per cent. Conclusion: The pathology, nodal involvement and tumour vascular invasion were predicted by computerized statistical classification of the proton MRS spectrum from a fine-needle aspirate biopsy taken from the primary breast lesion.
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收藏
页码:1234 / 1240
页数:7
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