The effect of blood content on the optical and dielectric skin properties

Oxygen saturation mapping during reconstructive surgery of human forehead flaps with hyperspectral imaging and spectral unmixing

BACKGROUND

Optical spectroscopy is commonly used clinically to monitor oxygen saturation in tissue. The most commonly employed technique is pulse oximetry, which provides a point measurement of the arterial oxygen saturation and is commonly used for monitoring systemic hemodynamics, e.g. during anesthesia. Hyperspectral imaging (HSI) is an emerging technology that enables spatially resolved mapping of oxygen saturation in tissue (sO2), but needs to be further developed before implemented in clinical practice. The aim of this study is to demonstrate the applicability of HSI for mapping the sO2 in reconstructive surgery and demonstrate how spectral analysis can be used to obtain clinically relevant sO2 values.

METHODS

Spatial scanning HSI was performed on cutaneous forehead flaps, raised as part of a direct brow lift, in eight patients. Pixel-by-pixel spectral analysis, accounting for the absorption from multiple chromophores, was performed and compared to previous analysis techniques to assess sO2.

RESULTS

Spectral unmixing using a broad spectral range, and accounting for the absorption of melanin, fat, collagen, and water, provided a more clinically relevant estimate of sO2 than conventional techniques, where typically only spectral features associated with absorption of oxygenated (HbO2) and deoxygenated (HbR) hemoglobin are considered. We demonstrate its clinical applicability by generating sO2 maps of partially excised forehead flaps showed a gradual decrease in sO2 along the length of the flap from 95 % at the flap base to 85 % at the flap tip. After being fully excised, sO2 in the entire flap decreased to 50 % within a few minutes.

CONCLUSIONS

The results demonstrate the capability of sO2 mapping in reconstructive surgery in patients using HSI. Spectral unmixing, accounting for multiple chromophores, provides sO2 values that are in accordance with physiological expectations in patients with normal functioning microvascularization. Our results suggest that HSI methods that yield reliable spectra are to be preferred, so that the analysis can produce results that are of clinical relevance.

Bone marrow-derived vasculogenesis leads to scarless regeneration in deep wounds with periosteal defects

Deep skin wounds with periosteal defects, frequently caused by traffic accidents or radical dissection, are refractory. Transplant surgery is frequently performed, but patients are subjected to stress for long operation periods, the sacrifice of donor regions, or several complications, such as flap necrosis or intractable ulcers. Even if the defects are covered, a scar composed of fibrous tissue remains in the body, which can cause itching, dysesthesia, or repeated ulcers because of the lack of distribution of peripheral nerves or hair follicles. Thus, treatments with the aim of regenerating lost tissue for deep wounds with periosteal defects are needed. Here, we show that the use of gelatin sponges (GS), which have been used as haemostatic materials in clinical practice, allowed the regeneration of heterogeneous tissues, including periosteum, skin, and skin appendages, when used as scaffolds in deep wounds with periosteal defects in rats. Bone marrow transplantation in rats revealed the mechanism by which the microenvironment provided by GS enabled bone marrow-derived cells (BMDCs) to form a vascular niche, followed by regeneration of the periosteum, skin, or skin appendages such as hair follicles by local cells. Our findings demonstrated that vascular niche formation provided by BMDCs is crucial for heterogeneous tissue regeneration.

Development and validation of quantitative optical index of skin blood content

SIGNIFICANCE

We present an approach to estimate with simple instrumentation the amount of red blood cells in the skin microvasculature, designated as parameter LRBC. Variations of parameter LRBC are shown to reflect local changes in the quantity of skin red blood cells during a venous occlusion challenge.

AIM

To validate a simple algebraic model of light transport in skin using the Monte Carlo method and to develop a measure of the red blood cell content in skin microvessels using the Monte Carlo predictions; to guide the development of an instrument to measure experimentally variations of the amount of red blood cells in the skin.

APPROACH

Monte Carlo simulations were carried out in a multilayer model of the skin to compute remitted light intensities as a function of distance from the illumination locus for different values of the skin blood content. The simulation results were used to compute parameter LRBC and its variations with local skin blood content. An experimental setup was developed to measure parameter LRBC in human volunteers in whom skin blood content of the forearm increased during temporary interruption of the venous outflow.

RESULTS

In the simulations, parameter LRBC was ∼16  μm in baseline conditions, and it increased in near proportion with the blood content of the skin layers. Measuring the diffusely reflected light intensity 0.5 to 1.2 mm away from the illumination locus was optimal to detect appreciable changes of the reflected light intensity as skin blood content was altered. Parameter LRBC measured experimentally on the human forearm was 17  ±  2  μm in baseline conditions it increased at a rate of 4  ±  2  μm  /  min when venous outflow was temporarily interrupted.

CONCLUSION

Parameter LRBC derived experimentally with a two-wavelength diffuse reflectometer can be used to measure local variations of the amount of red blood cells in skin microvessels.

Non-coding RNAs and Pathological Cardiac Hypertrophy

Cardiovascular disease (CVD) is a common disease which poses a serious threat to human health and it is characterized by high prevalence, high disability and high mortality. Myocardial hypertrophy (MH) is a common pathological process of various cardiovascular diseases and is considered as an independent risk factor for increased cardiovascular morbidity and mortality. Therefore, it is particularly important to understand its pathological mechanism and treatment. In recent years, it has been found that many non-coding RNAs (ncRNAs) play key regulatory roles in humans' various pathophysiological processes. Abnormal expression of ncRNAs in different types of cardiac cells is associated with pathological cardiac hypertrophy. Understanding the relationship between various ncRNAs and intercellular communication through extracellular vesicles (EV) can identify the key ncRNAs which are the accurate targets of precise therapy in this network of action, it also can potentially be a marker for clinical disease diagnosis, which will reflect the progress of the disease earlier and more accurately. There are many factors that regulate the occurrence and development of cardiac hypertrophy, ncRNAs are only a part of them. There are also mutual promotion or inhibition between ncRNAs and other molecules. It will be helpful for us to comprehend the mechanism of cardiac hypertrophy better and provide a sufficient theoretical basis for clinical diagnosis and treatment by defining these relationships.

Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device

Even if still at an early stage of development, non-invasive continuous glucose monitoring (NI-CGM) sensors represent a promising technology for optimizing diabetes therapy. Recent studies showed that the Multisensor provides useful information about glucose dynamics with a mean absolute relative difference (MARD) of 35.4% in a fully prospective setting. Here we propose a method that, exploiting the same Multisensor measurements, but in a retrospective setting, achieves a much better accuracy. Data acquired by the Multisensor during a long-term study are retrospectively processed following a two-step procedure. First, the raw data are transformed to a blood glucose (BG) estimate by a multiple linear regression model. Then, an enhancing module is applied in cascade to the regression model to improve the accuracy of the glucose estimation by retrofitting available BG references through a time-varying linear model. MARD between the retrospectively reconstructed BG time-series and reference values is 20%. Here, 94% of values fall in zone A or B of the Clarke Error Grid. The proposed algorithm achieved a level of accuracy that could make this device a potential complementary tool for diabetes management and also for guiding prediabetic or nondiabetic users through life-style changes.

Neuregulin-1β Partially Improves Cardiac Function in Volume-Overload Heart Failure Through Regulation of Abnormal Calcium Handling

Background: Neuregulin (NRG-1), an essential stress-mediated paracrine growth factor, has a cardioprotective effect in failing heart. However, the underlying mechanism remains unclear. The role of NRG-1β in heart failure (HF) rats was examined.

Methods and Results: Volume-overload HF rat model was created by aortocaval fistula surgery. The sham-operated (SO) rats received the same surgical intervention without the fistula. Thirty-five HF rats were injected with NRG-1β (NRG, 10 μg/kg·d) via the tail vein for 7 days, whereas 35 HF rats and 20 SO rats were injected with the same dose of saline. The echocardiographic findings showed left ventricular dilatation, systolic and diastolic dysfunction, and QTc interval prolongation in HF rats. The NRG-1β treatment attenuated the ventricular remodeling and shortened the QTc interval. Patch clamp recordings showed I_Ca-L was significantly decreased in the HF group, and NRG-1β treatment attenuated the decreased I_Ca-L. No significant differences in the kinetic properties of I_Ca-L were observed. The expressions of Cav1.2 and SERCA2a were significantly reduced, but the expression level of NCX1 was increased dramatically in the HF group. NRG-1β treatment could partially prevent the decrease of Cav1.2 and SERCA2a, and the increase of NCX1 in HF rats.

Conclusions: NRG-1β could partly attenuate the heart function deterioration in the volume-overload model. Reduced function and expression of calcium transportation-related proteins might be the underlying mechanism.

First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: The Investigators' View

BACKGROUND

Extensive past work showed that noninvasive continuous glucose monitoring with a wearable multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions.

METHOD

To test previous findings also in uncontrolled conditions, a long term at home study has been organized to collect multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking multisensor data to glucose applied to estimate glucose levels noninvasively.

RESULTS

The algorithm used here calculates glucose values from sensor data and adds a constant obtained by a daily calibration. It provides point inaccuracy measured by a MARD of 35.4 mg/dL on test data. This is higher than current state-of-the-art minimally invasive devices, but still 86.9% of glucose rate points fall within the zone AR+BR.

CONCLUSIONS

The multisensor device and the algorithmic routine used earlier in controlled conditions tracks glucose changes also in uncontrolled conditions, although with lower accuracy. The examination of learning curves suggests that obtaining more data would not improve the results. Therefore, further efforts would focus on the development of more complex algorithmic routines able to compensate for environmental and physiological confounders better.

Frequency-range optimized preprocessing methods for quantitative analysis of glucose in blood serum from broadband dielectric spectra

This paper presents the results of combining scatter correction and spectral derivation preprocessing methods with frequency-range optimization to improve the accuracy of blood glucose concentration prediction when using a Partial Least Square Regression model. Using broadband dielectric spectroscopy, absorption spectrums in the frequency range of 500 MHz to 50 GHz were gathered from blood serums. Partial Least Square Regression models were trained using data gathered from samples of varying glucose concentrations and temperatures, and the quality of the predictions were evaluated by performing leave-one-out cross validation. Potential improvements in prediction accuracy were assessed by finding the optimal frequency ranges of dielectric absorption spectrums through iteration, in addition to treatments using common preprocessing methods. The most effective combination of preprocessing method and its corresponding characteristic frequency range was determined from validation using several samples. Finally, among all the preprocessing methods and the frequency ranges explored, performing Savitzky-Golay filtering without derivations lowered the average root mean squared error amongst all the samples from 172 mg/dL without preprocessing, to 143 mg/dL. Additionally, by focusing on a specific frequency range, the root mean squared error dropped to 80.2 mg/dL.

The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System

BACKGROUND

We study here the influence of different patients and the influence of different devices with the same patients on the signals and modeling of data from measurements from a noninvasive Multisensor glucose monitoring system in patients with type 1 diabetes. The Multisensor includes several sensors for biophysical monitoring of skin and underlying tissue integrated on a single substrate.

METHOD

Two Multisensors were worn simultaneously, 1 on the upper left and 1 on the upper right arm by 4 patients during 16 study visits. Glucose was administered orally to induce 2 consecutive hyperglycemic excursions. For the analysis, global (valid for a population of patients), personal (tailored to a specific patient), and device-specific multiple linear regression models were derived.

RESULTS

We find that adjustments of the model to the patients improves the performance of the glucose estimation with an MARD of 17.8% for personalized model versus a MARD of 21.1% for the global model. At the same time the effect of the measurement side is negligible. The device can equally well measure on the left or right arm. We also see that devices are equal in the linear modeling. Thus hardware calibration of the sensors is seen to be sufficient to eliminate interdevice differences in the measured signals.

CONCLUSIONS

We demonstrate that the hardware of the 2 devices worn on the left and right arms are consistent yielding similar measured signals and thus glucose estimation results with a global model. The 2 devices also return similar values of glucose errors. These errors are mainly due to nonstationarities in the measured signals that are not solved by the linear model, thus suggesting for more sophisticated modeling approaches.

A dielectric inverse problem applied to human skin measurements during glucose excursions

A fringing field capacitive sensor has been used to measure the dielectric properties of human skin and underlying tissue in the MHz frequency range. It has recently been shown in clinical experimental studies that these dielectric properties can be related to the effects of in vivo glucose variations of the test subject. Previously, the relationship between electrical impedance and the glucose level has been established via statistical methods, such as the regression method. In this work, we explored a different approach, namely the resolution of the so-called inverse problem. First we applied the method on an artificial two-layer lossy system in order to test the sensitivity of the solution to forced changes in the layer properties and its stability to a constant setting. After validation of this method on artificial systems, a similar inverse problem was set and solved for dielectric measurements on human skin during an induced glucose excursion, where the skin is also modelled as a double-layer system. The changes of the measured permittivity and conductivity of the second layer versus the glucose changes are calculated for 22 study days. The statistical distribution shows that the median slopes of both dielectric properties are negative. These results can be used to test our hypothesis and to continue building potential explanations for the phenomena induced by the glucose changes on the skin layer dielectric parameters.

Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation

The Multisensor Glucose Monitoring System (MGMS) features non invasive sensors for dielectric characterisation of the skin and underlying tissue in a wide frequency range (1 kHz-100 MHz, 1 and 2 GHz) as well as optical characterisation. In this paper we describe the results of using an MGMS in a miniaturised housing with fully integrated sensors and battery. Six patients with Type I Diabetes Mellitus (age 44±16 y; BMI 24.1±1.3 kg/m(2), duration of diabetes 27±12 y; HbA1c 7.3±1.0%) wore a single Multisensor at the upper arm position and performed a total of 45 in-clinic study days with 7 study days per patient on average (min. 5 and max. 10). Glucose changes were induced either orally or by i.v. glucose administration and the blood glucose was measured routinely. Several prospective data evaluation routines were applied to evaluate the data. The results are shown using one of the restrictive data evaluation routines, where measurements from the first 22 study days were used to train a linear regression model. The global model was then prospectively applied to the data of the remaining 23 study days to allow for an external validation of glucose prediction. The model application yielded a Mean Absolute Relative Difference of 40.8%, a Mean Absolute Difference of 51.9 mg dL(-1), and a correlation of 0.84 on average per study day. The Clarke error grid analyses showed 89.0% in A+B, 4.5% in C, 4.6% in D and 1.9% in the E region. Prospective application of a global, purely statistical model, demonstrates that glucose variations can be tracked non invasively by the MGMS in most cases under these conditions.