Karim Bensalah

Raman Spectroscopy: A Novel Experimental Approach to Evaluating Renal Tumours

BACKGROUNDnNew optical techniques of spectroscopy have shown promising results in the evaluation of solid tumours.nnnOBJECTIVEnTo evaluate the potential of Raman spectroscopy (RS) to assess renal tumours at surgery.nnnDESIGN, SETTING, AND PARTICIPANTSnOver a 5-mo period, Raman optical spectra were prospectively acquired on surgical renal specimens removed due to suspicion of cancer.nnnMEASUREMENTSnRaman 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.nnnRESULTS AND LIMITATIONSnThere 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.nnnCONCLUSIONSnRS 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.

Optical spectroscopy techniques can accurately distinguish benign and malignant renal tumours

There is little known about optical spectroscopy techniques ability to evaluate renal tumours. This study shows for the first time the ability of Raman and optical reflectance spectroscopy to distinguish benign and malignant renal tumours in an ex vivo environment. We plan to develop this optical assistance in the operating room in the near future.

Characterization of renal tumours based on Raman spectra classification

In this study, we propose to evaluate the potential of Raman spectroscopy (RS) to assess renal tumours at surgery. Different classes of Raman renal spectra acquired during a clinical protocol are discriminated using support vector machines classifiers. The influence on the classification scores of various preprocessing steps generally involved in RS are also investigated and evaluated in the particular context of renal tumour characterization. Encouraging results show the interest of RS to evaluate kidney cancer and suggest the potential of this technique as a surgical assistance during partial nephrectomy.

Noninvasive detection of bladder cancer using mid-infrared spectra classification

In this paper, we focus on the detection of Bladder Cancer (BC) via mid infrared spectroscopy. Two main contributions, material and methods, are presented. In terms of material, a new minimally invasive technology, combining fiber evanescent wave spectroscopy and newly patented biosensors, is used for the first time to acquire mid-infrared spectra from voided urine/bladder wash. This new machine promises practicality, cheapness and high-quality of spectrum acquisition. As for classical systems, the data acquired using the new system was highly correlated, resulting in a poor classification performance using classical methods. Therefore, the second contribution consists in developing statistical methods that alleviate the problem. Three new statistical methods based on Partial Least Square Discriminant Analysis algorithm (PLSDA) are proposed. PLSDA is a supervised classifier well-known for its ability to process correlated data. The key point is the choice of the most discriminant latent variables in the training step. In this work, we propose three new decision rules in order to select the most relevant latent variables. These decision rules give rise to three algorithms, namely bayesian, joint and best model PLSDA. A comparative study between the proposed methods and standard ones, namely SVM, K-MEANS and classical PLSDA, confirms clearly the efficiency of the former. The best performance in terms of accuracy is achieved by joint and best model PLSDA (82.35%). Besides, by embedding the proposed statistical methods in the new machine, we are able to provide a new medical device that is very promising in terms of automatic bladder cancer detection.

Safety and Efficacy of Sorafenib in Renal Cell Carcinoma

This article reviews data on sorafenib use in renal cell carcinoma. Mechanisms of actions and pharmacokinetics are briefly described. Major clinical trials are presented, summarizing efficacy and safety of sorafenib. Its place in current treatment of renal cell carcinoma is discussed. Sorafenib is likely to remain one of the mainstays of RCC treatment in coming years.

La spectroscopie optique: une nouvelle approche pour l'étude des tumeurs urologiques

INTRODUCTIONnOptical spectroscopy refers to a group of novel technologies that uses interaction of light with tissues to analyze their structure and chemical composition. The objective of this article is to describe these technologies and detail their potential for assessing urological tumors.nnnMATERIAL AND METHODSnIt has been shown that optical spectroscopy can accurately analyse multiple solid tumors. Several publications specifically aimed at assessing prostate cancers, renal carcinomas and urothelial tumors.nnnRESULTSnThere are three types of spectroscopy that all use light focussed on a tissue and thereafter collect a specific reflected optical signal. Optical spectroscopy can differentiate benign (adenoma or inflammation) and malignant (adenocarcinoma) prostatic tissues. It can also distinguish normal bladder tissue from inflammatory or cancerous cells. Regarding renal tumors, spectroscopy can identify normal and tumoral tissue and differentiate benign and malignant tumors. Its diagnostic accuracy is about 85%. However, reported studies only concentrate on in vitro or ex vivo specimen and the numbers of patients are quite small.nnnCONCLUSIONnOptical spectroscopy can be envisioned as an optical biopsy tool. Potential applications in the clinical field are promising. Larger studies on in vivo specimen need to be undertaken to confirm phase I preliminary reports.