Diffuse reflectance spectroscopy was successfully applied in transfusion medicine, for the diagnosis of the quality of blood units, in recent studies. However, removal of blood sample from the bag is still required for measuring donor dependent hematological variations in stored units. If these hematological variables are successfully interpreted from diffuse reflectance spectra, there would be no need for invasive tests. In this study, diffuse reflectance spectra of 103 erythrocyte suspensions were modeled with their donor-dependent hematological variations on the first day of storage. The final model given in this study, fitted well at 610 nm with goodness of fit of 0.94 for erythrocyte suspensions and 0.96 for 87 leukocyte-depleted units, when selecting 474 nm for normalizing diffuse reflectance spectra of each blood unit and minimizing the effects of plastic blood bag.
Free hemoglobin (FHB) concentration is considered a prospect quality indicator for erythrocyte suspensions (ES) under storage. Storage lesions alter the optical properties of ES and can be monitored by diffuse reflectance spectroscopy. Due to storage lesions, erythrocytes lyse and release hemoglobin into the extracellular medium. The purpose of the study is to model and assess the quality of ES units in a blood bank with diffuse reflectance measurements together with hematological variables reflecting absorption and scattering characteristics of ES. FHB concentrations were modeled based on the increased scattering in the extracellular medium. A semiempirical model was used for relating optical properties of ES to the diffuse reflectance measurements. The attenuation in the blood bag was computed and its influence was discarded via normalization, in accordance with Monte Carlo simulations. In the experiments, 40 ES units were measured multiple times during prolonged storage of 70 days. A generalized linear model was used for modeling the training set, and, in the validation, the highest correlation coefficient between predicted and actual FHB concentrations was 0.89. Predicting the actual value was accurate at a maximum level of R2 = 0.80. The error rate of the model in diagnosing the true quality was about 10%.
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