Diagnosis of Pregnancy Based Classification of Embryo Culture Medium Samples by Infrared Spectrometry and Chemometrics Publisher



Zandbaaf S¹ ; Khanmohammadi Khorrami MR¹ ; Bagheri Garmarudi A¹ ; Hossein Rashidi B² Show Affiliations
Source: Infrared Physics and Technology Published:2020

Abstract

Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with chemometric procedures was utilized to examine embryo culture medium (ECM) samples in in vitro fertilization (IVF) to differentiate between positive and negative pregnancy. Principal component analysis (PCA) method was successfully applied to mid-IR spectra as outlier detection by application of Hotelling T2 statistic procedure. Unsupervised and supervised pattern recognition techniques, such as hierarchical agglomerative cluster algorithm (HACA), soft independent modeling of class analogy (SIMCA) as a linear supervised pattern recognition technique, binned nearest neighbors (BNN) as a local classifier and counter-propagation artificial neural networks (CP-ANN) as a non-linear technique were used in spectral data analysis for classification and differentiation. Also, the genetic algorithm (GA) as the variable reduction was employed to develop the diagnostic model. A total of 46 ECM samples were examined in the 3000–1000 cm−1 spectral region. Classification efficiency parameters including accuracy (ACC), error rates (ER), sensitivity (Sens), specificity (Spec) and non-error rate (NER) were calculated. Classification ACC of 92.00% and ER of 8.300% was acquired using GA-BNN algorithm, while GA-CP-ANN and GA-SIMCA algorithms provided 93.00% and 5.00% of ACC and ER for the test set, respectively. The results of this study presented that the GA-SIMCA and the GA-CP-ANN chemometric approaches using the infrared data, achieved acceptable results. Also, both of methods could provide the Sens rate of 100.00% and 91.00%, and the Spec rate of 91.00% and 100.00% for positive pregnancy samples (class 1) and negative ones (class 2) in prediction test, respectively. In general, the main advantages of the proposed method could be represented as a reliable, fast, simple, and accurate method for the classification and discrimination of the ECM samples based on their serum beta- subunit human chorionic gonadotropin (β-hCG) levels after embryo transfer (ET) about 15 days later. © 2019 Elsevier B.V.