Non-invasive monitoring of haemoglobin concentration in paediatric surgical patients using near-infrared spectroscopy

Emerging point-of-care technologies for anemia detection

Anemia, characterized by low blood hemoglobin level, affects about 25% of the world's population with the heaviest burden borne by women and children. Anemia leads to impaired cognitive development in children, as well as high morbidity and early mortality among sufferers. Anemia can be caused by nutritional deficiencies, oncologic treatments and diseases, and infections such as malaria, as well as inherited hemoglobin or red cell disorders. Effective treatments are available for anemia upon early detection and the treatment method is highly dependent on the cause of anemia. There is a need for point-of-care (POC) screening, early diagnosis, and monitoring of anemia, which is currently not widely accessible due to technical challenges and cost, especially in low- and middle-income countries where anemia is most prevalent. This review first introduces the evolution of anemia detection methods followed by their implementation in current commercially available POC anemia diagnostic devices. Then, emerging POC anemia detection technologies leveraging new methods are reviewed. Finally, we highlight the future trends of integrating anemia detection with the diagnosis of relevant underlying disorders to accurately identify specific root causes and to facilitate personalized treatment and care.

Non-invasive Estimation of Haemoglobin Level Using PCA and Artificial Neural Networks

Objective:

Haemoglobin(Hb) measurement is generally performed by the traditional “fingerstick” test i.e., by invasively drawing blood from the body. Although the conventional laboratory measurement is accurate, it has its own limitations such as time delay, inconvenience of the patient, exposure to biohazards and the lack of real-time monitoring in critical situations. Non-invasive Haemoglobin Measurement (SpHb) has gained enormous attention among researches and can provide an earlier diagnosis to polycythemia, anaemia, various cardiovascular diseases, etc. Currently, Photoplethysmograph signal (PPG) is used for measuring oxygen saturation, to monitor the depth of anesthesia, heart rate and respiration monitoring. But through detailed statistical analysis, PPG signal can provide further information about various blood components.

Investigation / Methodology:

In this paper, an approach for non-invasive measurement of Hb using PPG, Principal Component Analysis (PCA) and Neural Network is proposed. A transmissive type PPG sensor is developed which is interfaced with Crowduino for the acquisition of PPG. From the obtained PPG signal, Principal Components (PC) are extracted. SpHb is predicted followed by the extraction of features from the PC. The analysis involves the SpHb prediction using a single PC, double PC and finally all the three PC. The predicted SpHb is evaluated with Hblab in terms of R-value, Mean Absolute Error, Mean Squared Error and Root Mean Squared Error.

Conclusion:

An approach for non-invasive measurement of Hb using Principal Components obtained from the PPG signal is discussed. The SpHb value is compared with the Hblab values. Correlation R-value between SpHb and Hblab is 0.77 when three principal components are used. Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE) between SpHb and Hblab are 0.3, 0.44 and 0.6633 respectively when SpHb is measured with three principal components. It is evident from the result analysis that SpHb shows the promising result when all the three principal components are used. However, one of the limitations of the work is that the population setting chosen for the work does not include paediatric patients, accurately ill patient, pregnant population and surgical patients. With detailed analysis on a wide range of population setting, Hb prediction using PPG is a promising approach for non-invasive measurement.

Non-invasive prediction of hemoglobin levels by principal component and back propagation artificial neural network

To facilitate non-invasive diagnosis of anemia, specific equipment was developed, and non-invasive hemoglobin (HB) detection method based on back propagation artificial neural network (BP-ANN) was studied. In this paper, we combined a broadband light source composed of 9 LEDs with grating spectrograph and Si photodiode array, and then developed a high-performance spectrophotometric system. By using this equipment, fingertip spectra of 109 volunteers were measured. In order to deduct the interference of redundant data, principal component analysis (PCA) was applied to reduce the dimensionality of collected spectra. Then the principal components of the spectra were taken as input of BP-ANN model. On this basis we obtained the optimal network structure, in which node numbers of input layer, hidden layer, and output layer was 9, 11, and 1. Calibration and correction sample sets were used for analyzing the accuracy of non-invasive hemoglobin measurement, and prediction sample set was used for testing the adaptability of the model. The correlation coefficient of network model established by this method is 0.94, standard error of calibration, correction, and prediction are 11.29g/L, 11.47g/L, and 11.01g/L respectively. The result proves that there exist good correlations between spectra of three sample sets and actual hemoglobin level, and the model has a good robustness. It is indicated that the developed spectrophotometric system has potential for the non-invasive detection of HB levels with the method of BP-ANN combined with PCA.

Combination of different noninvasive measuring techniques: a new approach to increase accuracy of peripheral near infrared spectroscopy

One of the problems of near-infrared-spectroscopy (NIRS) measurements is low reproducibility. The aim of the present study was to introduce quality criteria to increase reproducibility of peripheral NIRS measurements. In a prospective cohort study in 40 neonates, repeated NIRS measurements were performed on the calf. During five "reapplication" periods (of NIRS optodes), five "measurements" (venous occlusions) were performed. Tissue oxygenation index (TOI), mixed venous oxygenation (SvO2), fractional oxygen extraction (FOE), hemoglobin flow (Hbflow), oxygen delivery (DO2), and oxygen consumption (VO2) were assessed. Measurements with linear changes during venous occlusions were included for further analysis (first quality criterion: R(2)>0.95). The second quality criterion was the equation 0 < or = TOI-SvO2 < or = (SaO2-SvO2)x0.2. Variance components and mean standard deviations were analyzed after introduction of the quality criteria. Variance components of reapplication and measurement decreased after introduction of the second quality criterion (TOI: 46.6-35.0%, SvO2: 76.8-38.2%, FOE: 73.1-37.5%, Hbflow: 70.3-51.9%, DO2: 71.5-52.7%, and VO2: 70.9-63.8%). Mean standard deviations of TOI (6.6+/-3.0 to 4.7+/-3.2%), SvO2 (11.1+/-4.8 to 5.7+/-3.9%), FOE (11.3+/-4.8 to 5.9+/-4.0%), Hbflow (4.3+/-2.0 to 2.9+/-1.6 micromol100 mLmin), and DO2 (17.8+/-7.6 to 11.4+/-6.2 micromol100 mLmin) decreased significantly, too. Only 12% of measurements fulfilled both quality criteria. With the introduction of two quality criteria, test-retest variability of peripheral NIRS measurements decreased significantly and reproducibility increased significantly.

Prediction of plasma hemoglobin concentration by near-infrared spectroscopy

The estimation of plasma hemoglobin concentration (Hb) is among one of the daily activities in the practice of clinical anesthesiology. The near-infrared spectroscopy of the brain (rSO(2)) represents a balance between cerebral oxygen delivery and consumption. This study was designed to assess the value of rSO(2) in the prediction of the Hb level while other variables were mathematically controlled. Thirty healthy adult patients undergoing spine surgery, expected to have a moderate degree of intraoperative bleeding, were enrolled in this study. General anesthesia was given and ventilation was mechanically controlled. Measurement of Hb and PaCO(2) were performed at random periods of time. We obtained a total of 97 data combinations for the 30 study patients. The Hb was regressed by independent variables including rSO(2) and PaCO(2). A multilinear regression analysis was performed and the final regression equation was expressed only with statistically significant variables. The measured Hb was tightly regressed with three variables. The final regression equation was Hb=+8.580+0.238.rSO(2)-0.338.PaCO(2)-0.004.anesthetic exposure duration (Tmin) (p=0.000, r(2)=0.809). Near-infrared spectroscopy was shown to be a valuable predictor of plasma Hb in the clinical anesthesiology setting.

Cerebral Near-Infrared Spectroscopy in Adult Patients After Cardiac Surgery Is Not Useful for Monitoring Absolute Values But May Reflect Trends in Venous Oxygenation Under Clinical Conditions

OBJECTIVE

Cerebral near-infrared spectroscopy (NIRS) was evaluated for use in monitoring global oxygenation in adult patients after cardiac surgery.

DESIGN

Prospective, randomized clinical monitoring study.

SETTING

Intensive care unit for cardiac surgery; university hospital.

PARTICIPANTS

The study included 35 patients scheduled for cardiac surgery with insertion of a pulmonary artery catheter; patients with known cerebral-vascular perfusion disturbances were excluded.

INTERVENTIONS

Noninvasive cerebral NIRS oxygen saturation (rSO(2)) and conventional intensive care monitoring parameters were assessed.

MEASUREMENTS AND MAIN RESULTS

Simple regression analysis was used to assess the correlation of rSO(2) to hemodynamic parameters. There was fair-to-moderate intersubject correlation to hemoglobin concentration (r = 0.45, p < 0.0001) and mixed venous oxygen saturation (SmvO(2)) (r = 0.33, p < 0.0001). Sensitivity and specificity of rSO(2) to detect substantial (>or=1 standard deviation) changes in mixed venous oxygen saturation were 94% and 81%, respectively.

CONCLUSIONS

Cerebral NIRS in adult patients might not be the tool to replace mixed venous oxygen monitoring. Further work has to be done to assess its potential to reflect intraindividual trends.

Measurement of transcutaneous hemoglobin concentration by noninvasive white-light spectroscopy in infants

OBJECTIVE

To compare transcutaneously spectroscopically measured hemoglobin values with venous hemoglobin values in infants.

STUDY DESIGN

Prospective study in healthy preterm and term infants who were breathing spontaneously.

RESULTS

Recordings were obtained from 85 stable infants (median gestational age at measurement: 36 weeks [range: 34-43 weeks]; median body weight: 1890 g [range: 1095-4360 g]). The spectroscopic hemoglobin values were corrected for inhomogeneous distribution of hemoglobin in the tissue. The venous and spectroscopic hemoglobin values were then compared by using the Bland-Altman method, which gave an error of <5%.

CONCLUSIONS

This pilot study could illustrate a good relation between the 2 methods for measuring hemoglobin. Larger studies are required to validate the spectroscopic method in those with conditions that affect the skin microcirculation (eg, septicemia).