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Item type:Publication, Diabetes Status is Associated With Plantar Soft Tissue Stiffness Measured Using Ultrasound Reverberant Shear Wave Elastography Approach(SAGE Publishing, 2020-10-23)Introduction: The purpose of this study was to investigate the association between the mechanical properties of plantar soft tissue and diabetes status. Method: 51 (M/F: 21/30) participants with prediabetes onset (fasting blood sugar [FBS] level > 100 mg/dL), age >18 years, and no lower limb amputation were recruited after ethical approval was granted from Pontificia Universidad Catolica del Peru ethical review board. Ultrasound reverberant shear wave elastography was used to assess the soft tissue stiffness at the 1st metatarsal head (MTH), 3rd MTH, and the heel at both feet. Results: Spearman’s rank-order correlation (rho) test indicated a significant ( P < .05) positive correlations between FBS level and the plantar soft tissue shear wave speed at the 1st MTH: rho = 0.402 (@400 Hz), rho = 0.373 (@450 Hz), rho = 0.474 (@500 Hz), rho= 0.395 (@550 Hz), and rho = 0.326 (@600 Hz) in the left foot and rho = 0.364 (@450 Hz) in the right foot. Mann-Whitney U test indicated a significantly ( P < .05) higher shear wave speed in the plantar soft tissue with the following effect sizes (r) at the 1st MTH of the left foot at all tested frequencies: r = 0.297 (@450 Hz), r = 0.345 (@500 Hz), r = 0.322 (@550 Hz), and r = 0.275 (@600 Hz), and at the 1st MTH of right foot r = 0.286 (@400 Hz) in diabetes as compared with the age and body mass index matched prediabetes group. Conclusion: An association between fasting blood sugar level and the stiffness of the plantar soft tissue with higher values of shear wave speed in diabetes versus prediabetes group was observed. This indicated that the proposed approach can improve the assessment of the severity of diabetic foot complications with potential implications in patient stratification. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Plantar soft tissue characterization using reverberant shear wave elastography: a proof-of-concept study(Elsevier, 2021-10-25)Plantar soft tissue stiffness provides relevant information on biomechanical characteristics of the foot. Therefore, appropriate monitoring of foot elasticity could be useful for diagnosis, treatment or health care of people with complex pathologies such as a diabetic foot. In this work, the reliability of reverberant shear wave elastography (RSWE) applied to plantar soft tissue was investigated. Shear wave speed (SWS) measurements were estimated at the plantar soft tissue at the first metatarsal head, the third metatarsal head and the heel from both feet in five healthy volunteers. Experiments were repeated for a test–retest analysis with and without the use of gel pad using a mechanical excitation frequency range between 400 and 600 Hz. Statistical analysis was performed to evaluate the reliability of the SWS estimations. In addition, the results were compared against those obtained with a commercially available shear wave-based elastography technique, supersonic imaging (SSI). The results indicate a low coefficient of variation for test–retest experiments with gel pad (median: 5.59%) and without gel pad (median: 5.83%). Additionally, the values of the SWS measurements increase at higher frequencies (median values: 2.11 m/s at 400 Hz, 2.16 m/s at 450 Hz, 2.24 m/s at 500 Hz, 2.21 m/s at 550 Hz and 2.31 m/s at 600 Hz), consistent with previous reports at lower frequencies. The SWSs at the plantar soft tissue at the first metatarsal head, third metatarsal head and heel were found be significantly (p<0.05) different, with median values of 2.42, 2.16 and 2.03 m/s, respectively which indicates the ability of the method to differentiate between shear wave speeds at different anatomical locations. The results indicated better elastographic signal-to-noise ratios with RSWE compared to SSI because of the artifacts presented in the SWS generation. These preliminary results indicate that the RSWE approach can be used to estimate the plantar soft tissue elasticity, which may have great potential to better evaluate changes in biomechanical characteristics of the foot. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Can deep learning wound segmentation algorithms developed for a dataset be effective for another dataset? A specific focus on diabetic foot ulcers(Institute of Electrical and Electronics Engineers Inc., 2024-01-01)Diabetic foot ulcers (DFU) represent a severe complication, often resulting from poor glycemic control, neuropathy, peripheral vascular disease, or inadequate foot care. DFUs can lead to significant morbidity, including amputation and, in severe cases, can be fatal. Recently, advancements in computer vision technologies based on artificial intelligence (AI) have shown promise in DFU management. Particularly deep learning (DL) models such as U-Net and other models and techniques, were utilized to enhance wound segmentation accuracy. This research focuses on evaluating the generalization capabilities of DL models across different DFU datasets. Specifically, we investigated whether models trained on one dataset can be effective when utilized on another dataset, addressing the challenge of cross-dataset generalization. We employed 7 popular DL models, U-Net-VGG16, U-Net-EfficientNetV2S, ABANet, Ma-Net, LinkNet, DeepLabV3+, and Segment Anything Model (SAM), with 2 DFU datasets: FUSeg challenge and DFUC challenge. A total of 54 experiments were conducted plus 27 for SAM, involving training on one dataset, and testing on another, as well as training and testing on combined datasets. The results indicate substantial variability in segmentation performance when models trained on one dataset are tested on another, highlighting the influence of dataset characteristics on model generalization. The study underscores the importance of using diverse and comprehensive datasets to develop robust DL models for DFU segmentation and its generalization. This research contributes to the understanding of DL model performance in medical image segmentation and emphasizes the need for standardized datasets in improving DFU management through computer vision. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Characterisation of the Soft Tissue Viscous and Elastic Properties Using Ultrasound Elastography and Rheological Models: Validation and Applications in Plantar Soft Tissue Assessment(Institute of Physics, 2023-05-21)Objective. The mechanical behaviour of soft tissue is influenced by its elastic and viscous characteristics. Therefore, the aim of this study was to develop a validated method to characterise the viscoelastic properties of soft tissues based on ultrasound elastography data. Approach. Plantar soft tissue was chosen as the tissue of interest, and gelatine-phantoms replicating its mechanical properties were manufactured for validation of the protocol. Both plantar soft tissue and the phantom were scanned using Reverberant shear wave ultrasound (US) elastography at 400-600 Hz. Shear wave speed was estimated using the US particle velocity data. The viscoelastic parameters were extracted by fitting the Young’s modulus as a function of frequency derived from the constitutive equations of the eight rheological models (four classic and their fractional-derivative versions) to the shear wave dispersion data. Furthermore, stress-time functions derived from the eight rheological models were fitted to the phantom stress-relaxation data. Main results. The viscoelastic parameters estimated using elastography data based on the fractional-derivative (FD) models, compared to the classic models, were closer to those quantified using the mechanical test. In addition, the FD-Maxwell and FD-Kelvin-Voigt models showed to more effectively replicate the viscoelastic behaviour of the plantar soft tissue with minimum number of model parameters ( R 2 = 0.72 for both models) . Hence the FD-KV and FD-Maxwell models can more effectively quantify the viscoelastic characteristics of the soft tissue compared to other models. Significance. In this study, a method for mechanical characterisation of the viscoelastic properties of soft tissue in ultrasound elastography was developed and fully validated. An investigation into the most valid rheological model and its applications in plantar soft tissue assessment were also presented. This proposed approach for the characterisation of viscous and elastic mechanical properties of soft tissue has implications in assessing the soft tissue function where those can be used as markers for diagnosis or prognosis of tissue status. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An Evaluation of the Effect of Dimple Insoles on Foot Temperature in Diabetic Patients(Multidisciplinary Digital Publishing Institute (MDPI), 2025-03-01)OBJECTIVE: Insoles play a crucial role in foot comfort, with their effect on foot temperature being a key factor. This study aims to evaluate and compare the effect of walking with two different insole types-dimple insoles versus a conventional insole-on foot temperature changes in patients with diabetic neuropathy. METHODS: Thermal imaging was used to measure the foot temperature of nine participants immediately before and after walking 250 m in each insole. Temperature variations were analyzed for the whole foot across four specific regions to assess and compare the effect of each insole on foot temperature. RESULTS: The Wilcoxon Signed-Rank Test revealed that contralateral temperature differences between the left and right feet after walking (∆TAfter) were significantly (p<0.05) lower in dimple insoles compared to the conventional insoles. This effect was particularly strong in the midfoot and toe regions. CONCLUSIONS: The results indicate that insole type can influence foot contralateral temperature differences after walking. These findings provide valuable insights for selecting insoles based on thermal data and can have implications in improving patient outcomes.1