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  • Title: PV-MBLL algorithm for extraction of absolute tissue oxygenation information by diffuse optical spectroscopy.
    Author: Bai J, Zhu Q, Liu Y, Zhou Y, Shi T, Gui Z, Shang Y.
    Journal: Comput Methods Programs Biomed; 2020 Sep; 193():105456. PubMed ID: 32305645.
    Abstract:
    BACKGROUND AND OBJECTIVE: Tissue blood oxygenation contains critical information for biomedical studies and healthcare. The primary approach to extract the absolute value of tissue blood oxygenation (e.g., oxygen saturation) is spatial-resolved algorithm for near-infrared diffuse optical spectroscopy with continues-wave (CW) light, which require acquisition of the optical signals from multiple pairs of sources and detectors (S-D). This study reports the first attempt for absolute oxygenation measurement with single S-D pair of optical signals. METHODS: A novel algorithm, namely, phantom-validation modified Beer-Lambert law (PV-MBLL), was created to fully utilize the optical signals from single S-D pair. This algorithm is combined with two-step phantom measurement to extract the absolute value of tissue oxygenation in CW system. The proposed PV-MBLL algorithm was compared with the conventional spatial-resolved algorithm on both step-varied liquid phantom and human experiment of cuff occlusion on arms. The one-way ANOVA analysis was performed to investigate the difference between the two algorithms. RESULTS: By using the PV-MBLL algorithm, the reconstructed tissue absorption coefficient is highly accurate (not larger than 5.35% in error) over a wide range (0.02-0.20 cm-1). By contrast, the spatial-resolved algorithm leads to much larger errors (up to 37.57% in error). Moreover, the responses of oxygen saturation to cuff occlusion differ significantly (p < 0.005) with the two algorithms. CONCLUSIONS: The proposed PV-MBLL algorithm has promising potential for accurate acquisition of oxygenation information. Additionally, the single S-D pair greatly reduces the size of optical probe and instrument cost, thus it is highly appropriate for the tissues with small size and large curvature.
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