Effectiveness and feasibility of nailfold microcirculation test to screen for diabetic peripheral neuropathy

Improved nested U-structure for accurate nailfold capillary segmentation

Changes in the structure and function of nailfold capillaries may be indicators of numerous diseases. Noninvasive diagnostic tools are commonly used for the extraction of morphological information from segmented nailfold capillaries to study physiological and pathological changes therein. However, current segmentation methods for nailfold capillaries cannot accurately separate capillaries from the background, resulting in issues such as unclear segmentation boundaries. Therefore, improving the accuracy of nailfold capillary segmentation is necessary to facilitate more efficient clinical diagnosis and research. Herein, we propose a nailfold capillary image segmentation method based on a U2-Net backbone network combined with a Transformer structure. This method integrates the U2-Net and Transformer networks to establish a decoder-encoder network, which inserts Transformer layers into the nested two-layer U-shaped architecture of the U2-Net. This structure effectively extracts multiscale features within stages and aggregates multilevel features across stages to generate high-resolution feature maps. The experimental results demonstrate an overall accuracy of 98.23 %, a Dice coefficient of 88.56 %, and an IoU of 80.41 % compared to the ground truth. Furthermore, our proposed method improves the overall accuracy by approximately 2 %, 3 %, and 5 % compared to the original U2-Net, Res-Unet, and U-Net, respectively. These results indicate that the Transformer-U2Net network performs well in nailfold capillary image segmentation and provides more detailed and accurate information on the segmented nailfold capillary structure, which may aid clinicians in the more precise diagnosis and treatment of nailfold capillary-related diseases.

Vascular endothelial growth factor levels in diabetic peripheral neuropathy: a systematic review and meta-analysis

Objective

Vascular endothelial growth factors (VEGFs, including VEGF-A, VEGF-B, VEGF-C, VEGF-D and PLGF) have important roles in the development and function of the peripheral nervous system. Studies have confirmed that VEGFs, especially VEGF-A (so called VEGF) may be associated with the diabetic peripheral neuropathy (DPN) process. However, different studies have shown inconsistent levels of VEGFs in DPN patients. Therefore, we conducted this meta-analysis to evaluate the relationship between cycling levels of VEGFs and DPN.

Methods

This study searched 7 databases, including PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, WanFang Database, and Chinese Biomedical Literature (CBM), to find the target researches. The random effects model was used to calculate the overall effect.

Results

14 studies with 1983 participants were included, among which 13 studies were about VEGF and 1 was VEGF-B, so only the effects of VEGF were pooled. The result showed that there were obviously increased VEGF levels in DPN patients compared with diabetic patients without DPN (SMD:2.12[1.34, 2.90], p<0.00001) and healthy people (SMD:3.50[2.24, 4.75], p<0.00001). In addition, increased circulating VEGF levels were not associated with an increased risk of DPN (OR:1.02[0.99, 1.05], p<0.00001).

Conclusion

Compared with healthy people and diabetic patients without DPN, VEGF content in the peripheral blood of DPN patients is increased, but current evidence does not support the correlation between VEGF levels and the risk of DPN. This suggests that VEGF may play a role in the pathogenesis and repairment of DPN.

Hybrid enhancement algorithm for nailfold images with large fields of view

Collecting and analyzing human nailfold images is an important component of studying human microcirculation. However, the large-field-of-view and high-resolution nailfold images captured by research microscopes introduce issues such as uneven brightness, low imaging contrast, and unclear vascular contours. To overcome these issues, this paper proposes a hybrid enhancement algorithm for nailfold images with large fields of view. First, adaptive histogram equalization with limited contrast (Clahe) is used to redistribute gray levels to enhance the brightness and contrast of images. Next, nonlocal means denoising (NL-means) is used to remove the noise amplified by Clahe algorithm. Finally, unsharp masking (Usm) is used to enhance the edge contour information of nailfold blood vessels. Comparing the enhanced images reveals that the hybrid enhancement algorithm improves the brightness and contrast of the nailfold image, makes the nailfold vessel contour more obvious, and the image noise continues to remain small, and it obtains the best visual effect. It is superior to other algorithms in terms of objective indicators and subjective evaluation.

Assessment of Microcirculation in the Type 2 Diabetic and Impaired Glucose Tolerance Feet of Elderly Men by CEUS

OBJECTIVE

To evaluate the foot microcirculation in type 2 diabetes mellitus (T2DM) and impaired glucose tolerance patients (IGT) with contrast-enhanced ultrasound (CEUS).

METHODS

The study included 37 patients with T2DM but without diabetic foot (DM group), 15 patients with impaired glucose tolerance (IGT group) and 10 elderly males with normal fasting blood glucose (FBS) and negative glucose tolerance tests (control group). Color Doppler flow imaging (CDFI) and CEUS were performed on the right foot great toes for detecting the blood perfusion performance. CEUS images were recorded and parameters of CDFI and flow time-intensity curves (TICs) were analyzed by the Student's t-test.

RESULTS

There was no significant difference in CDFI parameters pulse index and peak systolic blood flow velocity (PSV) among the three groups (P >0.05). Compared with control group, CEUS images of IGT and DM groups showed lower microvascular density and were pale. Peak intensity (PI) and area under time-intensity curve (AUC) in control, IGT and DM groups were decreased gradually (PI 46.36±10.96 vs 35.26±11.65 vs 28.15±7.94, P = 0.001, AUC 5.12±1.02 vs 3.25±1.60 vs 2.81±1.20, P = 0.001). The arrival times (AT) and time to peak (TTP) tended to be increased with the extension of DM course, but the difference was not statistically significant (AT, P = 0.260, TTP, P = 0.481).

CONCLUSION

CEUS, as a noninvasive and valuable technique, could detect the alterations in foot microcirculation of DM and IGT patients.

Evaluation of the healthy median nerve elasticity: Feasibility and reliability of shear wave elastography

The present study applied the shear wave elastography (SWE) to the median nerve in order to investigate the feasibility and reliability of its use in 40 healthy volunteers. Shear wave velocities of the median nerve on bilateral forearms and right carpal tunnel were obtained with relaxing or stretching conditions. The inter- and intraobserver agreements and differences of nerve elasticity among groups were evaluated using intraclass correlation coefficients, the paired t test, and the Wilcoxon signed-rank test, respectively. The stiffness of the site was expressed by 3 types of values: mean, minimum, and maximum shear-wave velocities. The inter- and intraobserver agreements were excellent (0.852-0.930) on the right forearm. No differences were detected between the bilateral forearm (mean: P = .14), while the values of different body sites and postures were statistically different (P < .001). SWE, as a noninvasive and objective tool, reached a good consistency in evaluating the healthy median nerve. Further studies are essential to investigate the detailed influencing factors and provide an insight of SWE to estimate both the normal nerve and peripheral neuropathy.

A. V, Atluri S. Comparison of electrochemical skin conductance and vibration perception threshold measurement in the detection of early diabetic neuropathy

The early diagnosis of diabetic peripheral neuropathy (DPN) is challenging. Sudomotor dysfunction is one of the earliest detectable abnormalities in DPN. The present study aimed to determine the diagnostic performance of the electrochemical skin conductance (ESC) test in detecting early DPN, compared with the vibration perception threshold (VPT) test and diabetic neuropathy symptom (DNS) score, using the modified neuropathy disability score (NDS) as the reference standard. Five hundred and twenty-three patients with type 2 diabetes underwent an NDS-based clinical assessment for neuropathy. Participants were classified into the DPN and non-DPN groups based on the NDS (≥ 6). Both groups were evaluated further using the DNS, and VPT and ESC testing. A receiver-operator characteristic (ROC) curve analysis was performed to compare the efficacy of ESC measurements with those of DNS and VPT testing in detecting DPN. The DPN group (n = 110, 21%) had significantly higher HbA1c levels and longer diabetes durations compared with the non-DPN group (n = 413). The sensitivity of feet ESC < 60 μS, VPT testing, and DNS in detecting DPN were 85%, 72%, and 52%, respectively. The specificity of feet ESC, VPT, and DNS in detecting DPN were 85%, 90% and 60% respectively. The areas under the curves of the ROC plots for feet ESC, VPT testing, and DNS were 0.88, 0.84, and 0.6, respectively. A significant inverse linear relationship was noted between VPT and feet ESC (r = -0.45, p = <0.0001). The odds ratios for having DPN, based on the mean feet ESC testing < 60 μS, VPT testing > 15 V, and DNS ≥ 1, were 16.4, 10.9 and 1.8, respectively. ESC measurement is an objective and sensitive technique for the early detection of DPN. Feet ESC measurement was superior to VPT testing for identifying patients with early DPN.