Non-Invasive Hemoglobin Assessment with NIR Imaging of Blood Vessels in Transmittance Geometry: Monte Carlo and Experimental Evaluation

Author:

Bardadin Ilia1,Petrov Vladimir2,Denisenko Georgy2,Armaganov Artashes3,Rubekina Anna1,Kopytina Daria4,Panov Vladimir1,Shatalov Petr5ORCID,Khoronenko Victoria5,Shegai Petr5,Kaprin Andrey5,Shkoda Andrey6,Yakimov Boris126

Affiliation:

1. Faculty of Physics, Lomonosov Moscow State University, 1-2 Leninskie Gory, 119234 Moscow, Russia

2. Laboratory of Clinical Biophotonics, Biomedical Science and Technology Park, Sechenov First Moscow State Medical University, Trubetskaya 8, 119048 Moscow, Russia

3. Medical Research and Education Center, M.V. Lomonosov Moscow State University, 119991 Moscow, Russia

4. Endocrinology Research Center, Dmitriya Ulianova Street 11, 117036 Moscow, Russia

5. FSBI “National Medical Research Radiological Centre” (NMRRC) of the Ministry of Health of the Russian Federation, 2nd Botkinsky Proezd 3, 125284 Moscow, Russia

6. Moscow State Budgetary Institution of Healthcare “L.A. Vorohobov City Clinical Hospital No. 67 MHD”, Salama Adil Str., 2/44, 123423 Moscow, Russia

Abstract

Non-invasive methods for determining blood hemoglobin (Hb) concentration are urgently needed to avoid the painful and time-consuming process of invasive venous blood sampling. Many such methods rely on assessing the average attenuation of light over a tissue area where hemoglobin is the dominant chromophore, without separating those areas corresponding to vessels and bloodless tissue. In this study, we investigate whether it is possible to determine hemoglobin levels in the blood by assessing the changes in light intensity when passing through large vessels in comparison to adjacent tissues, using this as a Hb level predictor. Using Monte Carlo light transport modeling, we evaluate the accuracy of determining hemoglobin levels via light intensity contrast and vessel widths estimated in the transmittance illumination geometry and estimate the influence of physiologically significant parameters such as vessel depth, dermis vascularization, and melanin content in the epidermis on the blood Hb prediction error. The results show that physiological variations in tissue parameters limit the mean absolute error of this method to ~15 g/L for blood Hb levels varying in the 60–160 g/L range, which finding is also supported by experimental data obtained for volunteers with different total blood Hb levels that have been determined invasively. We believe the application of new approaches to the non-invasive assessment of Hb levels will lead to the creation of reliable and accurate devices that are applicable in point-of-care and clinical practice.

Funder

Moscow government

MSU Program of Development

Publisher

MDPI AG

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