Estimation of regional hemoglobin concentration in biological tissues using diffuse reflectance spectroscopy with a novel spectral interpretation algorithm

Application Research of Visible Near-Infrared Spectroscopy Technology for Detecting Intracerebral Hematoma

OBJECTIVE

To explore the visible near-infrared spectroscopic (VNIRS) characteristics of intracerebral hematoma, and provide experimental basis for hematoma localization and residual detection in hypertensive intracerebral hemorrhage (HICH) surgery.

METHODS

Using VNIRS, spectral data of cerebral hematoma and cortex were collected during HICH craniotomy, and characteristic spectra were matched with paired-sample T-test. A partial least squares (PLS) quantitative model for cerebral hematoma spectra was established.

RESULTS

The reflectance of cerebral hematoma spectra in the 500-800 nm band was lower than that of the cortex, and there were statistically significant differences in the 510, 565, and 630 nm bands (P < 0.05). The calibration correlation coefficient of the PLS quantitative model for cerebral hematoma spectra was R2 = 0.988, the cross-validation correlation coefficient was R2cv = 0.982, the root mean square error of calibration was RMSEC = 0.101, the root mean square error of cross-validation was RMSEV = 0.122, the external validation correlation coefficient was CORRELATION = 0.902, and the root mean square error of prediction was RMSEP = 0.426, indicating that the model had high fitting degree and good predictive ability.

CONCLUSIONS

VNIRS as a noninvasive, real-time and portable analysis technology, can be used for real-time detection of hematoma during HICH surgery, and provide reliable basis for hematoma localization and residual detection.

Algorithms for mapping kidney tissue oxygenation during normothermic machine perfusion using hyperspectral imaging

The lack of donor grafts is a severe problem in transplantation medicine. Hence, the improved preservation of existing and the usage of organs that were deemed untransplantable is as urgent as ever. The development of novel preservation techniques has come into focus. A promising alternative to traditional cold storage is normothermic machine perfusion (NMP), which provides the benefit of improving the organs' viability and of assessing the organs' status under physiological conditions. For this purpose, methods for evaluating organ parameters have yet to be developed. In a previous study, we determined the tissue oxygen saturation (StO2) of kidneys during NMP with hyperspectral imaging (HSI) based on a discrete wavelength (DW) algorithm. The aim of the current study was to identify a more accurate algorithm for StO2 calculation. A literature search revealed three candidates to test: a DW algorithm and two full spectral algorithms - area under a curve and partial least square regression (PLSR). After obtaining suitable calibration data to train each algorithm, they were evaluated during NMP. The wavelength range from 590 to 800 nm was found to be appropriate for analyzing StO2 of kidneys during NMP. The PLSR method shows good results in analyzing the tissues' oxygen status in perfusion experiments.

IR Spectra of Different O2-Content Hemoglobin from Computational Study: Promising Detector of Hemoglobin Variant in Medical Diagnosis

IR spectra of heme and different O₂-content hemoglobin were studied by the quantum computation method at the molecule level. IR spectra of heme and different O₂-content hemoglobin were quantificationally characterized from 0 to 100 THz. The IR spectra of oxy-heme and de-oxy-heme are obviously different at the frequency regions of 9.08-9.48, 38.38-39.78, 50.46-50.82, and 89.04-91.00 THz. At 24.72 THz, there exists the absorption peak for oxy-heme, whereas there is not the absorption peak for de-oxy-heme. Whether the heme contains Fe-O-O bond or not has the great influence on its IR spectra and vibration intensities of functional groups in the mid-infrared area. The IR adsorption peak shape changes hardly for different O₂-content hemoglobin. However, there exist three frequency regions corresponding to the large change of IR adsorption intensities for containing-O₂ hemoglobin in comparison with de-oxy-hemoglobin, which are 11.08-15.93, 44.70-50.22, and 88.00-96.68 THz regions, respectively. The most differential values with IR intensity of different O₂-content hemoglobin all exceed 1.0 × 10⁴ L mol^-1 cm^-1. With the increase of oxygen content, the absorption peak appears in the high-frequency region for the containing-O₂ hemoglobin in comparison with de-oxy-hemoglobin. The more the O₂-content is, the greater the absorption peak is at the high-frequency region. The IR spectra of different O₂-content hemoglobin are so obviously different in the mid-infrared region that it is very easy to distinguish the hemoglobin variant by means of IR spectra detector. IR spectra of hemoglobin from quantum computation can provide scientific basis and specific identification of hemoglobin variant resulting from different O₂ contents in medical diagnosis.

Dynamic spectrum extraction method based on independent component analysis combined dual-tree complex wavelet transform

The proposed new dynamic spectrum (DS) extraction method based on ICA combined DTCWT could improve the precision accuracy of non-invasive measurement of blood components effectively.

Body-monitoring and health supervision by means of optical fiber-based sensing systems in medical textiles

Long-term monitoring with optical fibers has moved into the focus of attention due to the applicability for medical measurements. Within this Review, setups of flexible, unobtrusive body-monitoring systems based on optical fibers and the respective measured vital parameters are in focus. Optical principles are discussed as well as the interaction of light with tissue. Optical fiber-based sensors that are already used in first trials are primarily selected for the section on possible applications. These medical textiles include the supervision of respiration, cardiac output, blood pressure, blood flow and its saturation with hemoglobin as well as oxygen, pressure, shear stress, mobility, gait, temperature, and electrolyte balance. The implementation of these sensor concepts prompts the development of wearable smart textiles. Thus, current sensing techniques and possibilities within photonic textiles are reviewed leading to multiparameter designs. Evaluation of these designs should show the great potential of optical fibers for the introduction into textiles especially due to the benefit of immunity to electromagnetic radiation. Still, further improvement of the signal-to-noise ratio is often necessary to develop a commercial monitoring system.