Raman Spectroscopy: A Novel Experimental Approach to Evaluating Renal Tumours

被引:38
作者
Bensalah, Karim [1 ,2 ,3 ]
Fleureau, Julien [2 ,3 ]
Rolland, Denis [4 ]
Lavastre, Olivier [4 ]
Rioux-Leclercq, Nathalie [5 ]
Guille, Francois
Patard, Jean-Jacques [3 ]
Senhadji, Lotfi [3 ]
de Crevoisier, Renaud [3 ,6 ]
机构
[1] CHU Rennes, Hop Pontchaillou, Dept Urol, F-35000 Rennes, France
[2] INSERM, U642, F-35000 Rennes, France
[3] Univ Rennes 1, LTSI, F-35000 Rennes, France
[4] Univ Rennes 1, Inst Chem, CNRS, ProCaDec,UMR 6226, F-35000 Rennes, France
[5] CHU Rennes, Dept Pathol, F-35000 Rennes, France
[6] CRLCC Eugene Marquis, Dept Radiotherapy, F-35000 Rennes, France
关键词
Raman spectroscopy; Renal cell carcinoma; Diagnosis; Spectrum analysis; OPTICAL REFLECTANCE SPECTROSCOPY; DIFFERENTIATE BENIGN; CELL CARCINOMA; DIAGNOSIS; CANCER; IDENTIFY; BLADDER;
D O I
10.1016/j.eururo.2010.06.002
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Background: New optical techniques of spectroscopy have shown promising results in the evaluation of solid tumours. Objective: To evaluate the potential of Raman spectroscopy (RS) to assess renal tumours at surgery. Design, setting, and participants: Over a 5-mo period, Raman optical spectra were prospectively acquired on surgical renal specimens removed due to suspicion of cancer. Measurements: Raman measures were normalised to ensure comparison between spectra. A lower resolution signal was computed using a wavelet decomposition procedure to diminish the size of the signal and exploit the complete spectrum. A support vector machine (SVM) with a linear kernel and a sequential minimal optimisation solver was applied. A leave-one-out cross-validation technique was used to train and test the SVM. Results and limitations: There were 36 patients with 34 malignant tumours (27 clear-cell, 6 papillary, and 1 chromophobe) and 2 benign (1 oncocytoma and 1 metanephric cyst) tumours. A total of 241 analysable Raman spectra were obtained. The SVM was able to classify tumoural and normal tissue with an accuracy of 84% (sensitivity 82%, specificity 87%). High-grade and low-grade tumours were differentiated with a precision of 82% (sensitivity 84%, specificity 80%). Histologic subtype could be categorised with an accuracy of 93% (sensitivity 96%, specificity 87%). SVM could not be applied to classify benign and malignant tumours because of the restricted number of benign spectra. Conclusions: RS can accurately differentiate normal and tumoural renal tissue, low-grade and high-grade renal tumours, and histologic subtype of renal cell carcinoma. Larger prospective studies are needed to confirm these preliminary data. (C) 2010 European Association of Urology. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:602 / 608
页数:7
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