Age-specific discrimination of blood plasma samples of healthy and ovarian cancer prone mice using laser-induced breakdown spectroscopy

Abstract

Epithelial ovarian cancer (EOC) mortality rates are strongly correlated with the stage at which it is diagnosed. Detection of EOC prior to its dissemination from the site of origin is known to significantly improve the patient outcome. However, there are currently no effective methods for early detection of the most common and lethal subtype of EOC. We sought to determine whether laser-induced breakdown spectroscopy (LIBS) and classification techniques such as linear discriminant analysis (LDA) and random forest (RF) could classify and differentiate blood plasma specimens from transgenic mice with ovarian carcinoma and wild type control mice. Herein we report results using this approach to distinguish blood plasma samples obtained from serially bled (at 8, 12, and 16 weeks) tumor-bearing TgMISIIR-TAg transgenic and wild type cancer-free littermate control mice. We have calculated the age-specific accuracy of classification using 18,000 laser-induced breakdown spectra of the blood plasma samples from tumor-bearing mice and wild type controls. When the analysis is performed in the spectral range 250 nm to 680 nm using LDA, these are 76.7 (±2.6)%, 71.2 (±1.3)%, and 73.1 (±1.4)%, for the 8, 12 and 16 weeks. When the RF classifier is used, we obtain values of 78.5 (±2.3)%, 76.9 (±2.1)% and 75.4 (±2.0)% in the spectral range of 250 nm to 680 nm, and 81.0 (±1.8)%, 80.4 (±2.1)% and 79.6 (±3.5)% in 220 nm to 850 nm. In addition, we report, the positive and negative predictive values of the classification of the two classes of blood plasma samples. The approach used in this study is rapid, requires only 5 μL of blood plasma, and is based on the use of unsupervised and widely accepted multivariate analysis algorithms. These findings suggest that LIBS and multivariate analysis may be a novel approach for detecting EOC.

Discrimination of lymphoma using laser-induced breakdown spectroscopy conducted on whole blood samples

“…Two classification models were applied for the discrimination analysis, i.e., LDA classification and kNN classification. LDA is a supervised classification method which has been widely used for discrimination in the literature [15,16,[20][21][22][23][24]. It separates two or more classes of data based on the assumption that different classes have different multivariate normal distributions of the predictor features.…”

“…In total, 3300 LIBS spectra were collected for the discrimination analysis. The reproducibility of the LIBS spectra was estimated by measuring the fluctuation of the shot-to-shot intensity ratios of Na D lines (588.99 nm and 589.59 nm) of the 25-time averaged spectrum data sets [16]. The reproducibility of the 100 spectra of each sample is less than 1% and the corresponding value across all the samples is about 6%.…”

“…In the aforementioned references [13][14][15], the laser-induced breakdown was performed directly on the malignant tissues such that the LIBS discrimination can only be performed after the invasive biopsy collection, and it still cannot be used for the early cancer cases. In a recent publication, Melikechi et al realized age-specific discrimination of blood plasma samples of healthy and ovarian cancer prone mice using LIBS, LDA and random forest analysis [16]. Recently, for the first time, we achieved successful diagnosis and discrimination of lymphoma and multiple myeloma using LIBS conducted on human serum samples in combination with LDA, quadratic discriminant analysis (QDA) and k nearest neighbor (kNN) classification [17].…”

Chemometrics in laser‐induced breakdown spectroscopy

“…Compared with PLS‐DA and SVM, the RF model showed a better classification performance for steel samples. Melikechi et al used LDA and RF to distinguish blood plasma samples obtained from serially bled (at 8, 12, and 16 weeks) tumor‐bearing TgMISIIR‐TAg transgenic and wild‐type cancer‐free litter mate control mice. The age‐specific classification accuracy was calculated using 18 000 LIBS spectra of the blood plasma samples from tumor‐bearing mice and wild‐type controls, and the RF classifier showed a better predictive performance.…”

Determination of excitation temperature in laser-induced plasmas using columnar density Saha-Boltzmann plot

“…Over the past decades, laser-induced breakdown spectroscopy (LIBS) technique has matured into an interesting, simple, sensitive, and rapid tool for the quantitative and qualitative analyses of a large group of samples [1], [2], [3], [4], [5]. It has been used for a wide range of applications including industrial [6], [7], medical [8], [9], forensic [10], [11], and cultural heritage fields [12], [13]. In this technique, a high-power laser pulse is used to create a plasma on the sample surface.…”