Raman spectral analysis of renal tissue: a novel application Eric Yi-Hsiu Huang, a,b,c Shou-Chia Chu, b He Guei Chen, b Wayne Yen-Hwa Chang, a,c Ying-Ju Kuo, d Chin-Chen Pan, d Allen W. Chiu, a,c Alex TL Lin a,c and Huihua Kenny Chiang b * Renal cell carcinoma (RCC) accounts for 85% of all primary renal cancers. The definitive diagnosis of RCC relies exclusively on the subjective pathological interpretation of the surgical specimen. In this study, we aimed to analyze renal tissue using ob- jective Raman spectroscopy (RS). We obtained 15 pairs of RCC (T) and corresponding normal renal parenchymal tissues (N) from our biobank. There are three subtypes of RCC: clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (cRCC). Five pairs of tissue of each subtype were enrolled. Fresh-frozen sliced tissues were used for the RS detection. The Raman spec- tra between T and N were compared and analyzed using partial least squares (PLS) regression. Data for a total of 55 T and 58 N analyzable RS samples were obtained. The spectra were normalized by dividing the intensity of the characteristic peak at 1003 cm À1 using phenylalanine’s Raman peak. After further analysis with PLS, the sensitivity and specificity for discriminating T from N were 95% and 93%, respectively. The RCC subtypes can be discriminated at an accuracy of 72% for ccRCC, 88% for cRCC, and 86% for pRCC. This study demonstrates the feasibility of analyzing renal tissue using RS. RS, with its advantages of easy and objective tissue assessment, may be applied to aid intraoperative decision making and pathological tissue assess- ment. Copyright © 2014 John Wiley & Sons, Ltd. Additional supporting information may be found in the online version of this article at the publisher’s web site. Keywords: carcinoma, renal cell; spectrum analysis, Raman; pathology Introduction Renal cell carcinoma (RCC) makes up 3% of cancers in adults and 85% of primary renal cancers. [1] The associated prognosis is disas- trous if delayed or if a patient goes undiagnosed. Chow et al. re- ported that the 5-year relative survival rate of RCC in the U.S. was 85.8%–93.4% for patients with localized disease, 55%–64.2% for regional tumors, and ≤11% for patients with metastatic disease. With the tremendous advancement of diagnostic and surgical techniques and newly developed medications in recent years, significant improvements have been made in terms of survival in both early and advanced stages of disease. [2] RCC can be classified into several subtypes based on morphol- ogy and cytogenetic characteristics, including clear cell (ccRCC), papillary (pRCC), chromophobe (cRCC), collecting duct carcinoma, renal medullary carcinoma, etc. ccRCC is the most common adult RCC, comprising 70% of all RCCs. Comparatively, pRCC represents for 10%–15%, cRCC 3%–5%, collecting duct carcinoma <1%, and unclassified lesions 1%–3% of all RCCs. [3] There are differences in the clinical presentation and patient outcomes between the subtypes. Patients with ccRCC are more likely to present with advanced-stage disease compared with patients with pRCC or cRCC. The prognosis in patients with ccRCC is typically poorer than that with pRCC or cRCC. [4] Therefore, it is important to differentiate between the histologic subtypes. Diagnosis and subtyping of RCC are usually confirmed by mor- phological assessment of the resected tumor. Ancillary markers are sometimes needed to verify the histological subtypes or differ- entiate RCC from benign tumors. [5] However, the interpretation of the pathology relies mainly on subjective judgment and experi- ence. In addition to the traditional method, there is a need for an objective tool to aid in current practice. Optical diagnostics has the potential to improve the traditional diagnostic methods owing to its advantages of reducing inter- or intraobserver bias in the interpretation of pathological findings. Raman spectroscopy (RS), optical coherence tomography, and fluorescence spectroscopy are commonly used optical diagnostic methods. [6] RS is based on molecular inelastic scattering of light. [7] The Raman spectrum is directly related to a tissue’s mo- lecular composition. With the advantages of being non-destruc- tion to tissue, objectivity, and fast acquisition of the spectrum, it has the potential for assisting with and improving a specimen’s pathological interpretation. Over the past few years, interest has increased in using RS for characterizing several urological cancer tissues. [8–10] However, few reports have examined the RS charac- terization of RCC specimens. * Correspondence to: Huihua Kenny Chiang, Institute of Biomedical Engineering, National Yang-Ming University, No. 155, Sec. 2, Linong Street, Taipei 112, Taiwan. E-mail: hkennychiang@gmail.com a Department of Urology, Taipei Veterans General Hospital, Taipei, Taiwan b Institute of Biomedical Engineering, National Yang-Ming University, Taipei, Taiwan c Department of Urology, School of Medicine, National Yang-Ming University, Taipei, Taiwan d Department of Pathology, Taipei Veterans General Hospital, Taipei, Taiwan J. Raman Spectrosc. (2014) Copyright © 2014 John Wiley & Sons, Ltd. Research article Received: 9 March 2014 Revised: 15 June 2014 Accepted: 17 June 2014 Published online in Wiley Online Library (wileyonlinelibrary.com) DOI 10.1002/jrs.4546