Saving resources is a paramount issue for the modern laboratory, and new trainable as well as smart technologies can be used to allow the automated instrumentation to manage samples more efficiently in order to achieve streamlined processes. In this regard the serum free light chain (sFLC) testing represents an interesting challenge, as it usually causes using a number of assays before achieving an acceptable result within the analytical range. An artificial neural network based on the multi-layer perceptron (MLP-ANN) was used to infer the starting dilution status of sFLC samples based on the information available through the laboratory information system (LIS). After the learning phase, the MLP-ANN simulation was applied to the nephelometric testing routinely performed in our laboratory on a BN ProSpec® System analyzer (Siemens Helathcare) using the N Latex FLC kit. The MLP-ANN reduced the serum kappa free light chain (κ-FLC) and serum lambda free light chain (λ-FLC) wasted tests by 69.4% and 70.8% with respect to the naïve stepwise dilution scheme used by the automated analyzer, and by 64.9% and 66.9% compared to a "rational" dilution scheme based on a 4-step dilution. Although it was restricted to follow-up samples, the MLP-ANN showed good predictive performance, which alongside the possibility to implement it in any automated system, made it a suitable solution for achieving streamlined laboratory processes and saving resources.

Ialongo, C., Pieri, M., Bernardini, S. (2017). Smart management of sample dilution using an artificial neural network to achieve streamlined processes and saving resources: The automated nephelometric testing of serum free light chain as case study. CLINICAL CHEMISTRY AND LABORATORY MEDICINE, 55(2), 231-236 [10.1515/cclm-2016-0263].

Smart management of sample dilution using an artificial neural network to achieve streamlined processes and saving resources: The automated nephelometric testing of serum free light chain as case study

Pieri M.;Bernardini S.
2017-01-01

Abstract

Saving resources is a paramount issue for the modern laboratory, and new trainable as well as smart technologies can be used to allow the automated instrumentation to manage samples more efficiently in order to achieve streamlined processes. In this regard the serum free light chain (sFLC) testing represents an interesting challenge, as it usually causes using a number of assays before achieving an acceptable result within the analytical range. An artificial neural network based on the multi-layer perceptron (MLP-ANN) was used to infer the starting dilution status of sFLC samples based on the information available through the laboratory information system (LIS). After the learning phase, the MLP-ANN simulation was applied to the nephelometric testing routinely performed in our laboratory on a BN ProSpec® System analyzer (Siemens Helathcare) using the N Latex FLC kit. The MLP-ANN reduced the serum kappa free light chain (κ-FLC) and serum lambda free light chain (λ-FLC) wasted tests by 69.4% and 70.8% with respect to the naïve stepwise dilution scheme used by the automated analyzer, and by 64.9% and 66.9% compared to a "rational" dilution scheme based on a 4-step dilution. Although it was restricted to follow-up samples, the MLP-ANN showed good predictive performance, which alongside the possibility to implement it in any automated system, made it a suitable solution for achieving streamlined laboratory processes and saving resources.
2017
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA
English
artificial neural network; clinical chemistry; clinical laboratory information system; free light chains; laboratory automation; Humans; Immunoglobulin Light Chains; Automation; Indicator Dilution Techniques; Nephelometry and Turbidimetry; Neural Networks, Computer
Ialongo, C., Pieri, M., Bernardini, S. (2017). Smart management of sample dilution using an artificial neural network to achieve streamlined processes and saving resources: The automated nephelometric testing of serum free light chain as case study. CLINICAL CHEMISTRY AND LABORATORY MEDICINE, 55(2), 231-236 [10.1515/cclm-2016-0263].
Ialongo, C; Pieri, M; Bernardini, S
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/239397
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