Wearable laser Doppler flowmetry for non-invasive assessment of diabetic foot microcirculation: methodological considerations and clinical implications.

Significance: Type 2 diabetes mellitus (T2DM) is a global health concern with significant implications for vascular health. The current evaluation methods cannot achieve effective, portable, and quantitative evaluation of foot microcirculation. Aim: We aim to use a wearable device laser Doppler flowmetry (LDF) to evaluate the foot microcirculation of T2DM patients at rest. Approach: Eleven T2DM patients and twelve healthy subjects participated in this study. The wearable LDF was used to measure the blood flows (BFs) for regions of the first metatarsal head (M1), fifth metatarsal head (M5), heel, and dorsal foot. Typical wavelet analysis was used to decompose the five individual control mechanisms: endothelial, neurogenic, myogenic, respiratory, and heart components. The mean BF and sample entropy (SE) were calculated, and the differences between diabetic patients and healthy adults and among the four regions were compared. Results: Diabetic patients showed significantly reduced mean BF in the neurogenic (p=0.044) and heart (p=0.001) components at the M1 and M5 regions (p=0.025) compared with healthy adults. Diabetic patients had significantly lower SE in the neurogenic (p=0.049) and myogenic (p=0.032) components at the M1 region, as well as in the endothelial (p<0.001) component at the M5 region and in the myogenic component at the dorsal foot (p=0.007), compared with healthy adults. The SE in the myogenic component at the dorsal foot was lower than at the M5 region (p=0.050) and heel area (p=0.041). Similarly, the SE in the heart component at the dorsal foot was lower than at the M5 region (p=0.017) and heel area (p=0.028) in diabetic patients. Conclusions: This study indicated the potential of using the novel wearable LDF device for tracking vascular complications and implementing targeted interventions in T2DM patients.

Diabetic foot ulcers segmentation challenge report: Benchmark and analysis.

Monitoring the healing progress of diabetic foot ulcers is a challenging process. Accurate segmentation of foot ulcers can help podiatrists to quantitatively measure the size of wound regions to assist prediction of healing status. The main challenge in this field is the lack of publicly available manual delineation, which can be time consuming and laborious. Recently, methods based on deep learning have shown excellent results in automatic segmentation of medical images, however, they require large-scale datasets for training, and there is limited consensus on which methods perform the best. The 2022 Diabetic Foot Ulcers segmentation challenge was held in conjunction with the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention, which sought to address these issues and stimulate progress in this research domain. A training set of 2000 images exhibiting diabetic foot ulcers was released with corresponding segmentation ground truth masks. Of the 72 (approved) requests from 47 countries, 26 teams used this data to develop fully automated systems to predict the true segmentation masks on a test set of 2000 images, with the corresponding ground truth segmentation masks kept private. Predictions from participating teams were scored and ranked according to their average Dice similarity coefficient of the ground truth masks and prediction masks. The winning team achieved a Dice of 0.7287 for diabetic foot ulcer segmentation. This challenge has now entered a live leaderboard stage where it serves as a challenging benchmark for diabetic foot ulcer segmentation.

The usefulness of quantitative 99mTc-HMPAO WBC SPECT/CT for predicting lower extremity amputation in diabetic foot infection.

We investigated the usefulness of quantitative 99mTc-white blood cell (WBC) single photon emission computed tomography (SPECT)/computed tomography (CT) for predicting lower extremity amputation in diabetic foot infection (DFI). A total of 93 feet of 83 consecutive patients with DFI who underwent WBC SPECT/CT for treatment planning were retrospectively analysed. The clinical and SPECT/CT parameters were collected along with the measurements of the maximum standardized uptake value (SUVmax) at DFI. Statistical logistic regression analysis was performed to explore the predictors of LEA and receiver operating characteristic (ROC) curve was analysed to assess the predictive value of SPECT/CT. The independent predictors of amputation were previous amputation (OR 11.9), numbers of SPECT/CT lesions (OR 2.1), and SUVmax of DFI; either continuous SUVmax (1-increase) (OR 1.3) or categorical SUVmax > 1.1 (OR 21.6). However, the conventional SPECT/CT interpretation failed to predict amputation. In ROC analysis, the SUVmax yielded a fair predictor (area under the curve (AUC) 0.782) of amputation. The model developed from these independent predictors yielded an excellent performance for predicting amputation (AUC 0.873). Quantitative WBC SPECT/CT can provide new information useful for predicting the outcomes and guiding treatment for patients with DFI.

Amide proton transfer weighted contrast has diagnostic capacity in detecting diabetic foot: an MRI-based case-control study.

Objective: To evaluate the role of foot muscle amide proton transfer weighted (APTw) contrast and tissue rest perfusion in quantifying diabetic foot (DF) infection and its correlation with blood parameters. Materials and methods: With approval from an ethical review board, this study included 40 diabetes mellitus (DM) patients with DF and 31 DM patients without DF or other lower extremity arterial disease. All subjects underwent MRI, which included foot sagittal APTw and coronal arterial spin labeling (ASL) imaging. The normalized MTRasym (3.5 ppm) and the ratio of blood flow (rBF) in rest status of the affected side lesions to the non-affected contralateral side were determined. The inter-group differences of these variables were evaluated. Furthermore, the association between normalized MTRasym (3.5 ppm), rBF, and blood parameters [fasting blood glucose (FBG), glycosylated hemoglobin content, C-reactive protein, neutrophil percentage, and white blood cell count] was explored. Using an ROC curve, the diagnostic capacity of normalized MTRasym (3.5 ppm), BF, and blood biochemical markers in differentiating with or without DF in DM was assessed. Results: In the DF group, MTRasym (3.5 ppm) and BF in lesion and normalized MTRasym (3.5 ppm) were higher than those in the control group (p < 0.05). In addition, correlations were identified between normalized MTRasym (3.5 ppm) and blood parameters, such as C-reactive protein, glycosylated hemoglobin content, FBG, neutrophil ratio, and white blood cell (p < 0.001). Meanwhile, association between BF in lesion and blood parameters, such as C-reactive protein, neutrophil percentage, and FBG (p < 0.01). AUC of normalized MTRasym (3.5 ppm) in identifying with/without DF in patients with DM is 0.986 (95% CI, 0.918-1.00) with the sensitivity of 97.22% and the specificity of 100%. Conclusion: Normalized MTRasym (3.5 ppm) and the BF in lesion may be treated as a safer and more convenient new indicator to evaluate the tissue infection without using a contrast agent, which may be useful in monitoring and preoperatively assessing DF patients with renal insufficiency.

The role of diabetic foot treatment in improving left ventricular function: Insights from global longitudinal strain echocardiography.

We decided to evaluate the effect of treatment of diabetic foot ulcers in improving heart function by strain echocardiography than conventional transthoracic echocardiography. This prospective cross-sectional study included patients with diabetic foot ulcer (DFU). Conventional and two-dimensional strain echocardiography performed before and after three months diabetic foot treatment. Then, we compared the echocardiographic parameters including left ventricular ejection fraction (LV-EF), left ventricular global longitudinal strain (LV-GLS). Multivariate and univariate logistic regression analysis were performed to find which variable was mainly associated with LV-GLS changes. 62 patients with DFU were conducted. After echocardiography, all patients underwent surgical or non-surgical treatments. Three months after the treatment, LV-EF was not significantly different with its' primary values (P = 0.250), but LV-GLS became significantly different (P<0.05). In the multivariate logistic regression analysis, with the increase in the grade of ulcer, LV-GLS improved by 6.3 times. Not only the treatment of DFU helps to control adverse outcomes like infection, limb loss and morbidity but also it enhances cardiac function. Of note, strain echocardiography found to be a better indicator of myocardial dysfunction than LV-EF. These findings make a strong reason for the routine assessment of cardiac function in patients with DFU.

Diagnostic Performance of Ultrasonography for Diabetic Foot Osteomyelitis.

Objective: This study aims to analyze the potential diagnostic capability of ultrasonography (US) in detecting diabetic foot osteomyelitis (DFO) in patients with diabetic foot ulcers (DFUs). Approach: A 1-year prospective study was conducted on 47 consecutive patients with active DFUs and suspicion of DFO at a specialized diabetic foot unit. The following ultrasonographic features were evaluated at baseline: (1) periosteal reaction; (2) periosteal elevation; (3) cortical disruption; (4) sequestrum; and (5) positive power Doppler. The primary outcome measure aimed to establish the effectiveness of ultrasonographic features compared with aseptic bone culture for diagnosing DFO. Receiver operating characteristic (ROC) curves were utilized to evaluate the diagnostic performance of ultrasonographic features. Sample size could not be determined as it is the first study to assess ultrasonographic features for the diagnosis of DFO. The research adhered to the guidelines for diagnostic accuracy studies (Standards for Reporting of Diagnostic Accuracy Studies [STARD] 2015). Results: All patients (n = 24) diagnosed with DFO exhibited positive power Doppler, resulting in a sensitivity (S) and specificity (SP) of 1 and an area under the curve (AUC) of 1 (p < 0.001 [1-1]). Cortical disruption was present in 23 patients (95.8%) with DFO, yielding an S of 0.93, SP of 1, and AUC of 0.96 (p < 0.001 [0.88-1]). Innovation: It validates the diagnostic value of US for DFO as it is the first and largest study of its kind to establish a clear reference standard to guide clinician decision-making. Conclusion: This study demonstrates the effectiveness of cortical disruption and positive power Doppler in assessing DFO through US.

Image Smart Segmentation Analysis Against Diabetic Foot Ulcer Using Internet of Things with Virtual Sensing.

Diabetic foot ulcer (DFU) is a problem worldwide, and prevention is crucial. The image segmentation analysis of DFU identification plays a significant role. This will produce different segmentation of the same idea, incomplete, imprecise, and other problems. To address these issues, a method of image segmentation analysis of DFU through internet of things with the technique of virtual sensing for semantically similar objects, the analysis of four levels of range segmentation (region-based, edge-based, image-based, and computer-aided design-based range segmentation) for deeper segmentation of images is implemented. In this study, the multimodal is compressed with the object co-segmentation for semantical segmentation. The result is predicting the better validity and reliability assessment. The experimental results demonstrate that the proposed model can efficiently perform segmentation analysis, with a lower error rate, than the existing methodologies. The findings on the multiple-image dataset show that DFU obtains an average segmentation score of 90.85% and 89.03% correspondingly in two types of labeled ratios before DFU with virtual sensing and after DFU without virtual sensing (i.e., 25% and 30%), which is an increase of 10.91% and 12.22% over the previous best results. In live DFU studies, our proposed system improved by 59.1% compared with existing deep segmentation-based techniques and its average image smart segmentation improvements over its contemporaries are 15.06%, 23.94%, and 45.41%, respectively. Proposed range-based segmentation achieves interobserver reliability by 73.9% on the positive test namely likelihood ratio test set with only a 0.25 million parameters at the pace of labeled data.

Feasibility of Multiparametric Perfusion Assessment in Diabetic Foot Ulcer Using Intravoxel Incoherent Motion and Blood Oxygenation-Level Dependent MRI.

BACKGROUND: Patients with type-2 diabetes (T2DM) are at increased risk of developing diabetic foot ulcers (DFU) and experiencing impaired wound healing related to underlying microvascular disease. PURPOSE: To evaluate the sensitivity of intra-voxel incoherent motion (IVIM) and blood oxygen level dependent (BOLD) MRI to microvascular changes in patients with DFUs. STUDY TYPE: Case-control. POPULATION: 20 volunteers who were age and body mass index matched, including T2DM patients with DFUs (N = 10, mean age = 57.5 years), T2DM patients with controlled glycemia and without DFUs (DC, N = 5, mean age = 57.4 years) and healthy controls (HC, N = 5, mean age = 52.8 years). FIELD STRENGTH/SEQUENCE: 3T/multi-b-value IVIM and dynamic BOLD. ASSESSMENT: Resting IVIM parameters were obtained using a multi-b-value diffusion-weighted imaging sequence and two IVIM models were fit to obtain diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and microvascular volume fraction (MVF) parameters. Microvascular reactivity was evaluated by inducing an ischemic state in the foot with a blood pressure cuff during dynamic BOLD imaging. Perfusion indices were assessed in two regions of the foot: the medial plantar (MP) and lateral plantar (LP) regions. STATISTICAL TESTS: Effect sizes of group mean differences were assessed using Hedge's g adjusted for small sample sizes. RESULTS: DFU participants exhibited elevated D*, f, and MVF values in both regions (g ≥ 1.10) and increased D (g = 1.07) in the MP region compared to DC participants. DC participants showed reduced f and MVF compared to HC participants in the MP region (g ≥ 1.06). Finally, the DFU group showed reduced tolerance for ischemia in the LP region (g = -1.51) and blunted reperfusion response in both regions (g < -2.32) compared to the DC group during the cuff-occlusion challenge. DATA CONCLUSION: The combined use of IVIM and BOLD MRI shows promise in differentiating perfusion abnormalities in the feet of diabetic patients and suggests hyperperfusion in DFU patients. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 1.

Improved small vessel visibility in diabetic foot arteriography using dual-energy CT.

AIM: To test the feasibility and performance of dual-energy computed tomography (DECT) in foot arteriography of diabetic patients, where contrast medium is largely reduced within the small vessels. MATERIALS AND METHODS: A total of 50 diabetic patients were enrolled prospectively, where DECT was acquired immediately after the CT angiography (CTA, group A) of the lower extremity. Two images were derived from the DECT data, one optimal virtual monochromatic image (VMI, group B) and one fusion image (group C), both of which were compared against the CTA image for visualising the foot arteries. The contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were evaluated. The arterial course and contrast were graded each using a five-point scale. The clarity of small vessel depiction was quantified by comparing the number of plantar metatarsal arteries found in the maximum intensity projection image. RESULTS: The median CNRs and SNRs obtained in group B were approximately 45% and 20% higher than those in groups A and C, respectively (p<0.05). Group B also received higher subjective scores on the posterior tibial artery and the foot arteries (all >3) than groups A and C. The number of visible branches of the plantar metatarsal arteries was found to be substantially higher (p<0.05) in group B (median=6) than in groups A (median=2) and C (median=4). CONCLUSION: DECT was found to be superior to conventional CTA in foot arteriography, and beyond the lower extremity, it might be a general favourable solution for imaging regions with small vessels and reduced contrast medium.

Sub-calcaneal plantar fat pad assessment using dual-energy computed tomography: First experience in the diabetic foot.

BACKGROUND: This study assessed the use of dual-energy computed tomography (CT) to evaluate sub-calcaneal plantar fat pad changes in people with diabetic neuropathy. METHODS: Dual-energy CT scans of people with diabetic neuropathy and non-diabetic controls were retrospectively included. Average CT values (in Hounsfield Units) and thickness (in centimeters) of the sub-calcaneal plantar fat pad were measured in mono-energetic images at two energy levels (40 keV and 70 keV). The CT values measured in patients with diabetic neuropathy were correlated to barefoot plantar pressure measurements performed during walking in a clinical setting. FINDINGS: Forty-five dual-energy CT scans of people with diabetic neuropathy and eleven DECT scans of non-diabetic controls were included. Mean sub-calcaneal plantar fat pad thickness did not significantly differ between groups (diabetes group 1.20 ± 0.34 cm vs. control group 1.21 ± 0.28 cm, P = 0.585). CT values at both 40 keV (-34.7 ± 48.7 HU vs. -76.0 ± 42.8 HU, P = 0.013) and 70 keV (-11.2 ± 30.8 HU vs. -36.3 ± 27.2 HU, P = 0.017) were significantly higher in the diabetes group compared to controls, thus contained less fatty tissue. This elevation was most apparent in patients with Type 1 diabetes. CT values positively correlated with the mean peak plantar pressure. INTERPRETATION: Dual-energy CT was able to detect changes in the plantar fat pad of people with diabetic neuropathy.

Diabetic Plantar Foot Segmentation in Active Thermography Using a Two-Stage Adaptive Gamma Transform and a Deep Neural Network.

Pathological conditions in diabetic feet cause surface temperature variations, which can be captured quantitatively using infrared thermography. Thermal images captured during recovery of diabetic feet after active cooling may reveal richer information than those from passive thermography, but diseased foot regions may exhibit very small temperature differences compared with the surrounding area, complicating plantar foot segmentation in such cold-stressed active thermography. In this study, we investigate new plantar foot segmentation methods for thermal images obtained via cold-stressed active thermography without the complementary information from color or depth channels. To better deal with the temporal variations in thermal image contrast when planar feet are recovering from cold immersion, we propose an image pre-processing method using a two-stage adaptive gamma transform to alleviate the impact of such contrast variations. To improve upon existing deep neural networks for segmenting planar feet from cold-stressed infrared thermograms, a new deep neural network, the Plantar Foot Segmentation Network (PFSNet), is proposed to better extract foot contours. It combines the fundamental U-shaped network structure, a multi-scale feature extraction module, and a convolutional block attention module with a feature fusion network. The PFSNet, in combination with the two-stage adaptive gamma transform, outperforms multiple existing deep neural networks in plantar foot segmentation for single-channel infrared images from cold-stressed infrared thermography, achieving an accuracy of 97.3% and 95.4% as measured by Intersection over Union (IOU) and Dice Similarity Coefficient (DSC) respectively.

Grading Fractures on Foot and Ankle X-rays and MRI Scans in the Active Charcot Foot in Diabetes: How Strong Is the Agreement Between Modalities?

OBJECTIVE: To compare X-ray and MRI as diagnostic tests of active Charcot neuro-osteoarthropathy (CNO) in diabetes. RESEARCH DESIGN AND METHODS: X-rays and MRI scans of 48 participants were rated for severity of fracture (0 = no fracture, 1 = fracture, 2 = collapse/fragmentation), and for absence/presence of bone marrow edema (BME) on MRI and absence/presence of bone injury on X-ray. The agreement between modalities was assessed with tests for symmetry, marginal homogeneity, and κ-coefficients. RESULTS: X-ray underscored MRI in grading fractures in the metatarsals (P = 0.05) and tarsals (P < 0.001) and reported as normal 79% of the bones with BME. The agreement between X-ray and MRI for grading severity of fracture was moderate to substantial (κ = 0.53; P < 0.001) and for detecting bone injury, slight to fair (κ = 0.17; P < 0.001). CONCLUSIONS: The significant underperformance of X-ray in the assessment of the hot, swollen foot in diabetes should be considered when confirming or refuting the diagnosis of active CNO.

A fluoroscopic imaging-guided computational analyses to inform internal tissue loads within fat pad of the diabetic foot during gait.

To accurately predict internal tissue loads for early diagnostics of diabetic foot ulcerations, a novel data-driven computational analysis was conducted. A dedicated dual fluoroscopic system was combined with a pressure mat to simultaneously characterize foot motions and soft tissue's material properties during gait. Finite element (FE) models of the heel pad of a diabetic patient were constructed with 3D trajectories of the calcaneus applied as boundary conditions to simulate gait events. The tensile and compressive stresses occurring in the plantar tissue were computed. Predictions of the layered tissue FE model with anatomically-accurate heel pad structures (i.e., fat and skin) were compared with those of the traditional lumped tissue (i.e., homogeneous) models. The influence of different material properties (patient-specific versus generic) on internal tissue stresses was also investigated. The results showed the peak tensile stresses in the layered tissue model were predominantly found in the skin and distributed towards the circumferential regions of the heel, while peak compressive stresses in the fat tissue-bone interface were up to 51.4% lower than those seen in the lumped models. Performing FE analyses at four different phases of walking revealed that ignorance of layered tissue structures resulted in an unphysiological increase of peak-to-peak value of stress fluctuation in the fat and skin tissue components. Thus, to produce more clinical-relevant predictions, foot FE models are suggested to include layered tissue structures of the plantar tissue for an improved estimation of internal stresses in the diabetic foot in gait.

Diabetic Foot Ulcer Imaging: An Overview and Future Directions.

Diabetic foot ulcers (DFUs) affect one in every three people with diabetes. Imaging plays a vital role in objectively complementing the gold-standard visual yet subjective clinical assessments of DFUs during the wound treatment process. Herein, an overview of the various imaging techniques used to image DFUs is summarized. Conventional imaging modalities (e.g., computed tomography, magnetic resonance imaging, positron emission tomography, single-photon emitted computed tomography, and ultrasound) are used to diagnose infections, impact on the bones, foot deformities, and blood flow in patients with DFUs. Transcutaneous oximetry is a gold standard to assess perfusion in DFU cases with vascular issues. For a wound to heal, an adequate oxygen supply is needed to facilitate reparative processes. Several optical imaging modalities can assess tissue oxygenation changes in and around the wounds apart from perfusion measurements. These include hyperspectral imaging, multispectral imaging, diffuse reflectance spectroscopy, near-infrared (NIR) spectroscopy, laser Doppler flowmetry or imaging, and spatial frequency domain imaging. While perfusion measurements are dynamically monitored at point locations, tissue oxygenation measurements are static two-dimensional spatial maps. Recently, we developed a spatio-temporal NIR-based tissue oxygenation imaging approach to map for the extent of asynchrony in the oxygenation flow patterns in and around DFUs. Researchers also measure other parameters such as thermal maps, bacterial infections (from fluorescence maps), pH, collagen, and trans-epidermal water loss to assess DFUs. A future direction for DFU imaging would ideally be a low-cost, portable, multi-modal imaging platform that can provide a visual and physiological assessment of wounds for comprehensive wound care intervention and management.

Combined evaluation of blood flow and tissue perfusion in diabetic feet by intra-arterial dynamic 4DCT imaging.

Critical limb ischemia is associated with high mortality and major amputations. Intra-arterial digital subtraction angiography (IADSA) has been the reference standard but has some shortcomings including the two-dimensional projection and the lack of tissue perfusion information. The aim of this exploratory study is to examine four-dimensional computed tomography (4DCT) angiography and perfusion imaging using low-volume intra-arterial contrast injections for an improved anatomic and hemodynamic assessment in patients with foot ulcers. Three patients underwent a low-volume (2 mL) intra-arterial contrast-enhanced 4DCT examination combined with a diagnostic IADSA. An automated assessment of blood flow and tissue perfusion from the 4DCT data was performed. Vascular structures and corresponding blood flows were successfully assessed and correlated well with the IADSA results. Perfusion values of the affected tissue were significantly higher compared to the unaffected tissue. The proposed 4DCT protocol combined with the minimal usage of contrast agent (2 mL) provides superior images compared to IADSA as three phases (arterial, perfusion, and venous) are captured. The obtained parameters could allow for an improved diagnosis of critical limb ischemia as both the proximal vasculature and the extent of the perfusion deficit in the microvasculature can be assessed.Relevance statementIntra-arterial 4DCT allows for assessing three phases (arterial, perfusion and venous) using minimal contrast (2 mL). This method could lead to an improved diagnosis of critical limb ischemia as both proximal vasculature and the extent of the perfusion deficit are assessed.Trial registrationISRCTN, ISRCTN95737449. Registered 14 March 2023-retrospectively registered, https://www.isrctn.com/ISRCTN95737449 Key points• Three phases (arterial, perfusion, and venous) are obtained from 2 mL intra-arterial 4DCT.• The obtained hemodynamic parameters correlated well with the IADSA findings.• 4DCT surpassed IADSA in terms of assessment of venous blood flow and inflammatory hyperperfusion.• The assessment of tissue perfusion could lead to optimizing the revascularization strategy.

Imaging of the Diabetic Foot.

Diabetic foot complications are increasingly prevalent in the world, leading to significant morbidity and driving up associated health care costs. Complex pathophysiology and suboptimal specificity of current imaging modalities have made diagnosis challenging, mainly in the evaluation of superimposed foot infection to underlying arthropathy or other marrow lesions. Recent advances in radiology and nuclear medicine have the potential to streamline the assessment of diabetic foot complications. But we must be aware of the specific strengths and weaknesses of each modality, and their applications. This review offers a comprehensive approach to the spectrum of diabetic foot complications and their imaging appearances in conventional and advanced imaging studies, including optimal technical considerations for each technique. Advanced magnetic resonance imaging (MRI) techniques are highlighted, illustrating their complementary role to conventional MRI, in particular their potential impact in avoiding additional studies.