Quantification of thermal asymmetry in diabetic foot disease

Fuentes-Oliver, E. I.; García‐Segundo, C.; Serrano-Loyola, Raúl; Solalinde-Vargas, R.; Ortiz-Sosa, R.; Gastélum-Strozzi, A.

doi:10.1063/1.5095905

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…Expression of metabolic functionality of each leg is independent from each other [1,3,12], but conserves a normal relation in absence of perturbations, as we observed in [13,4]. In turn, if a perturbation arises then heat release would express abnormal thermal pattern distributions, able of being displayed in the IRIs.…”

Section: Cross-entropy and Information As A Perturbationmentioning

confidence: 54%

“…This has been previously studied in [13,4], aiming to detect changes in the metabolic response of the lower extremities with a temporal sequence of images taken each 15 seconds for a period of 5 minutes. In this work we propose to reduce the number of images acquired in this sequence at 2 key times during a thermally-induced response, reducing in that way the image acquisition time, and still delivering an acceptable diagnosis.…”

Section: Image Acquisition and Data Analysismentioning

confidence: 99%

“…IRIs pictured the lower limbs of the subjects. The acquisition was performed using an IR-camera FLIR-A320, and following some guidelines suggested in [26], which were also used by [13,4]. Physical and environmental parameters were adjusted with the camera interface to have a controlled environment.…”

Section: Image Acquisition and Data Analysismentioning

confidence: 99%

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Analysis of the density and distribution of entropy in biomedical infrared imaging for Diabetes Mellitus Type II

Ortiz-Sosa¹,

Fuentes-Oliver²,

García‐Segundo³

et al. 2021

Biomed. Phys. Eng. Express

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We report a methodology to analyze data extracted from infrared images. These pictures show the lower limbs of a cohort of individuals belonging to, (1) voluntary controls and (2) patients diagnosed with diabetes mellitus type II. The analysis is presented in terms of Cross Entropy and temperature distributions; both using the associated thermal histograms. The temperature analysis is placed in terms of comparing the extreme values of dS/dQ, for controls and patients. In this analysis for the frontal view, the values of specificity and sensitivity calculated were 77.77% and 91.66%, respectively. For the back view, the specificity and sensitivity obtained were 88.8% and 83.3%, respectively. Instead of that, the cross-entropy analysis is placed in the modality of self-referencing. In this part of the study we obtained the coefficient of asymmetry and thermal response (ATR). The values of specificity and sensitivity for the ATR quotient in both cases were 83.3%. The results of both studies have a significant correlation with glucose (p < 0.01) and HbA1c (p < 0.01). It means that both approaches have statistical correspondence. By means of the Mann-Whitney U test, for independent samples, we get that the characteristic parameters we analyze can be differentiated among the populations of interest with a significance of p < 0.05. This suggests that both studies show consistency with the clinical diagnosis; exhibiting clear differences between control and patient groups.

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Section: Cross-entropy and Information As A Perturbationmentioning

confidence: 54%

Section: Image Acquisition and Data Analysismentioning

confidence: 99%

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Analysis of the density and distribution of entropy in biomedical infrared imaging for Diabetes Mellitus Type II

Ortiz-Sosa¹,

Fuentes-Oliver²,

García‐Segundo³

et al. 2021

Biomed. Phys. Eng. Express

View full text Add to dashboard Cite

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Quantitative interpretation of infrared images of lower limbs in individuals with and without type 2 diabetes mellitus

Fuentes‐Oliver,

Ortiz‐Sosa,

Serrano‐Loyola

et al. 2024

Skin Research and Technology

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BackgroundThe quantitative interpretation of the radiometric information extracted from infrared (IR) images in individuals with and without type 2 diabetes mellitus (DM2) is an open problem yet to be solved. This is of particular value given that DM2 is a worldwide health problem and onset for evolution toward diabetic foot disease (DFD). Since DM2 causes changes at the vascular and neurological levels, the metabolic heat distribution on the outer skin is modified as a consequence of such alterations. Of particular interest in this contribution are those alterations displayed over the skin's heat patterns at the lower limbs. At the core of such alterations is the deterioration of the vascular and neurological networks responsible for procuring systemic thermoregulation. It is within this context that IR imaging is introduced as a likely aiding tool to assist with the clinical diagnosis of DM2 at stages early enough to prevent the evolution of the DFD.MethodsIR images of lower limbs are acquired from a cohort of individuals clinically diagnosed with and without DM2. Additional inclusion criteria for patients are to be free from any visible wound or tissue‐related trauma (e.g., injuries, edema, and so forth), and also free from non‐metabolic comorbidities. All images and data are equally processed and analyzed using indices that evaluate the spatial and temporal evolution of temperature distribution in lower limbs. We studied the temporal response of individuals’ legs after inducing an external stimulus. For this purpose, we combine the information of the asymmetry and thermal response index (ATR) and the thermal response index (TRI), computed using images at different times, improving the results previously obtained individually with ATR and TRI.ResultsA novel representation of the information extracted from IR images of the lower limbs in individuals with and without DM2 is presented. This representation was built using the ATR and TRI indices for the anterior and posterior views (PVs), individually and combining the information from both views. In all cases, the information of each index and each view presents linearity properties that allow said information to be interpreted quantitatively in a well‐defined and limited space. This representation, built in a polar coordinate space, allows obtaining sensitivity values of 86%, 97%, and 97%, and specificity values of 83%, 72%, and 78% for the anterior view (AV), the PV, and the combined views, respectively. Additionally, it was observed that the angular variable that defines this new representation space allows to significantly (p < 0.01) differentiate the groups, while correlating with clinical variables of interest, such as glucose and glycated hemoglobin.ConclusionThe linearity properties that exist between the ATR and TRI indices allow a quantitative interpretation of the information extracted from IR images of the lower extremities of individuals with and without DM2, and allow the construction of a representation space that eliminates possible ambiguities in the interpretation, while simplifying it, making it accessible for clinical use.

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Quantification of thermal asymmetry in diabetic foot disease

Cited by 2 publications

References 9 publications

Analysis of the density and distribution of entropy in biomedical infrared imaging for Diabetes Mellitus Type II

Analysis of the density and distribution of entropy in biomedical infrared imaging for Diabetes Mellitus Type II

Quantitative interpretation of infrared images of lower limbs in individuals with and without type 2 diabetes mellitus

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