Quantitative diffuse optical spectroscopy for noninvasive measurements of the malaria pigment hemozoin

Rapid and non-invasive detection of malaria parasites using near-infrared spectroscopy and machine learning

BACKGROUND

Novel and highly sensitive point-of-care malaria diagnostic and surveillance tools that are rapid and affordable are urgently needed to support malaria control and elimination.

METHODS

We demonstrated the potential of near-infrared spectroscopy (NIRS) technique to detect malaria parasites both, in vitro, using dilutions of infected red blood cells obtained from Plasmodium falciparum cultures and in vivo, in mice infected with P. berghei using blood spotted on slides and non-invasively, by simply scanning various body areas (e.g., feet, groin and ears). The spectra were analysed using machine learning to develop predictive models for infection.

FINDINGS

Using NIRS spectra of in vitro cultures and machine learning algorithms, we successfully detected low densities (<10-7 parasites/μL) of P. falciparum parasites with a sensitivity of 96% (n = 1041), a specificity of 93% (n = 130) and an accuracy of 96% (n = 1171) and differentiated ring, trophozoite and schizont stages with an accuracy of 98% (n = 820). Furthermore, when the feet of mice infected with P. berghei with parasitaemia ≥3% were scanned non-invasively, the sensitivity and specificity of NIRS were 94% (n = 66) and 86% (n = 342), respectively.

INTERPRETATION

These data highlights the potential of NIRS technique as rapid, non-invasive and affordable tool for surveillance of malaria cases. Further work to determine the potential of NIRS to detect malaria in symptomatic and asymptomatic malaria cases in the field is recommended including its capacity to guide current malaria elimination strategies.

Nanoparticle tracking analysis of natural hemozoin from Plasmodium parasites

BACKGROUND

Hemozoin is a byproduct of hemoglobin digestion crucial for parasite survival. It forms crystals that can be of interest as drug targets or biomarkers of malaria infection. However, hemozoin has long been considered as an amorphous crystal of simple morphology. Studying the consequences of biomineralization of this crystal during the parasite growth may provide more comprehensive evidence of its role during malaria.

OBJECTIVES

This study aimed to investigate the interest of nanoparticles tracker analysis for measuring the concentration and size of hemozoin particles produced from different parasite sources and conditions.

METHODS

Hemozoin was extracted from several clones of Plasmodium falciparum both asexual and sexual parasites. Hemozoin was also extracted from blood samples of malaria patients and from saliva of asymptomatic malaria carriers. Nanoparticles tracking analysis (NTA) was performed to assess the size and concentration of hemozoin.

RESULTS

NTA data showed variation in hemozoin concentration, size, and crystal clusters between parasite clones, species, and stages. Among parasite clones, hemozoin concentration ranged from 131 to 2663 particles/infected red blood cell (iRBC) and size ranged from 149.6 ± 6.3 nm to 234.8 ± 40.1 nm. The mean size was lower for Plasmodium vivax (176 ± 79.2 nm) than for Plasmodium falciparum (254.8 ± 74.0 nm). Sexual NF54 parasites showed a 7.5-fold higher concentration of hemozoin particles (28.7 particles/iRBC) compared to asexual parasites (3.8 particles/iRBC). In addition, the mean hemozoin size also increased by approximately 60 % for sexual parasites. Compared to in vitro cultures of parasites, blood samples showed low hemozoin concentrations.

CONCLUSIONS

This study highlights the potential of NTA as a useful method for analyzing hemozoin, demonstrating its ability to provide detailed information on hemozoin characterization. However, further research is needed to adapt the NTA for hemozoin analysis.

Review of recent advances in frequency-domain near-infrared spectroscopy technologies [Invited]

Over the past several decades, near-infrared spectroscopy (NIRS) has become a popular research and clinical tool for non-invasively measuring the oxygenation of biological tissues, with particular emphasis on applications to the human brain. In most cases, NIRS studies are performed using continuous-wave NIRS (CW-NIRS), which can only provide information on relative changes in chromophore concentrations, such as oxygenated and deoxygenated hemoglobin, as well as estimates of tissue oxygen saturation. Another type of NIRS known as frequency-domain NIRS (FD-NIRS) has significant advantages: it can directly measure optical pathlength and thus quantify the scattering and absorption coefficients of sampled tissues and provide direct measurements of absolute chromophore concentrations. This review describes the current status of FD-NIRS technologies, their performance, their advantages, and their limitations as compared to other NIRS methods. Significant landmarks of technological progress include the development of both benchtop and portable/wearable FD-NIRS technologies, sensitive front-end photonic components, and high-frequency phase measurements. Clinical applications of FD-NIRS technologies are discussed to provide context on current applications and needed areas of improvement. The review concludes by providing a roadmap toward the next generation of fully wearable, low-cost FD-NIRS systems.

Accurately calibrated frequency domain diffuse optical spectroscopy compared against chemical analysis of porcine adipose tissue

Frequency domain diffuse optical spectroscopy (fdDOS) is a noninvasive technique to estimate tissue composition and hemodynamics. While fdDOS has been established as a valuable modality for clinical research, comparison of fdDOS with direct chemical analysis (CA) methods has yet to be reported. To compare the two approaches, we propose a procedure to confirm accurate calibration by use of liquid emulsion and solid silicone phantoms. Tissue fat (FAT) and water (H₂ O) content of two ex vivo porcine tissue samples were optically measured by fdDOS and compared to CA values. We show an average H₂ O error (fdDOS minus CA) and SD of 1.9 ± 0.2% and -0.9 ± 0.2% for the two samples. For FAT, we report a mean error of -9.3 ± 1.3% and 0.8 ± 1.3%. We also measured various body sites of a healthy human subject using fdDOS with results suggesting that accurate calibration may improve device sensitivity.