Infrared thermography in children: a reliable tool for differential diagnosis of peripheral microvascular dysfunction and Raynaud’s phenomenon?

Martini, Giorgia; Cappella, Michela; Culpo, Roberta; Vittadello, Fabio; Sprocati, Monica; Zulian, Francesco

doi:10.1186/s12969-019-0371-0

Cited by 18 publications

(9 citation statements)

References 33 publications

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“…Similar results were obtained in [2,60]. Recent studies explored the possibility to classify RP patients based on their hands' temperature in baseline condition [61,62]. Horikoshi et al demonstrated that the baseline nail fold temperature was significantly lower in RP patients than in controls [48].…”

Section: Comparisons With Previous Studies and Discussion On Machine ...supporting

confidence: 55%

Convolutional Neural Networks for Differential Diagnosis of Raynaud’s Phenomenon Based on Hands Thermal Patterns

et al. 2021

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Raynaud’s phenomenon (RP) is a microvessels’ disorder resulting in transient ischemia. It can be either primary or secondary to connective tissue diseases, such as systemic sclerosis. The differentiation between primary and secondary to systemic sclerosis is of paramount importance to set the proper therapeutic strategy. Thus far, thermal infrared imaging has been employed to accomplish this task by monitoring the finger temperature response to a controlled cold challenge. A completely automated methodology based on deep convolutional neural network is here introduced with the purpose of being able to differentiate systemic sclerosis from primary RP patients by relying uniquely on thermal images of the hands acquired at rest. The classification performance of such a method was compared to that of a three-dimensional convolutional neural network model implemented to classify thermal images of the hands recorded during rewarming from a cold challenge. No significant differences were found between the two procedures, thus ensuring the possibility to avoid the cold challenge. Moreover, the convolutional neural network models were compared with standard feature-based approaches and showed higher performances, thus overcoming the limitations related to the feature extraction (e.g., biases introduced by the operator). Such automated procedures can constitute promising tools for large scale screening of primary RP and secondary to systemic sclerosis in clinical practice.

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Section: Comparisons With Previous Studies and Discussion On Machine ...supporting

confidence: 55%

Convolutional Neural Networks for Differential Diagnosis of Raynaud’s Phenomenon Based on Hands Thermal Patterns

et al. 2021

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“…Typically, image processing includes selection of areas of interest and possibly temperature gradients. The use of temperature gradients from acral to more proximal parts of the hand depends on the type of RP in question, as the distal–dorsal difference has been shown to be able to distinguish pRP from RP secondary to SSc [ 13 , 30 ]. However, gradients are not necessarily a good predictor of the condition where structural tissue changes are not a prominent part of the condition such as in VWF [ 31 ].…”

Section: Discussionmentioning

confidence: 99%

“…The advantage of the image processing for both laser Doppler methods and thermographic imaging is that it is easily comprehensible and simple to perform. Although a study suggested systematic differences between observers [ 12 ], another study reported a good inter-rater reliability in thermographic imaging [ 30 ]. Accordingly, the disadvantages of this type of image processing are the inter-observer difference, the time consumption, and the need for image analysis training.…”

Section: Discussionmentioning

confidence: 99%

Characteristic Features of Infrared Thermographic Imaging in Primary Raynaud’s Phenomenon

et al. 2021

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Raynaud’s phenomenon (RP) is characterized by the episodic whitening of the fingers upon exposure to cold. Verification of the condition is crucial in vibration-exposed patients. The current verification method is outdated, but thermographic imaging seems promising as a diagnostic replacement. By investigating patients diagnosed with RP, the study aimed at developing a simple thermographic procedure that could be applied to future patients where verification of the diagnosis is needed. Twenty-two patients with primary RP and 58 healthy controls were examined using thermographic imaging after local cooling of the hands for 1 min in water of 10°C. A logistic regression model was fitted with the temperature curve characteristics to convey a predicted probability of having RP. The characteristics time to end temperature and baseline temperature were the most appropriate predictors of RP among those examined (p = 0.004 and p = 0.04, respectively). The area under the curve was 0.91. The cut-off level 0.46 yielded a sensitivity and specificity of 82% and 86%, respectively. The positive and negative predictive values were 69% and 93%, respectively. This newly developed thermographic method was able to distinguish between patients with RP and healthy controls and was easy to operate. Thus, the method showed great promise as a method for verification of RP in future patients. Trial registration: ClinicalTrials.gov NCT03094910.

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“… 9 Thermography has been used to diagnose and evaluate several diseases that cause changes in local body temperature, including Raynaud’s phenomenon, scleroderma, burns, and diabetic feet. 10 11 Inflammation, infection, or malignancy can cause a local temperature rise that can be detected by thermal imaging. Thermography has also emerged as another non-invasive imaging tool for evaluating arthritis in that it reflects increased pathological blood flow associated with inflamed joints.…”

Section: Introductionmentioning

confidence: 99%

The Value of Thermal Imaging for Knee Arthritis: A Single-Center Observational Study

et al. 2022

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Purpose To compare (non-contact) thermal imaging with power Doppler (PD) for the evaluation of knee arthritis with joint effusion. Materials and Methods We enrolled patients with knee arthritis who were scheduled to undergo an arthrocentesis of the knee from April to December 2020 at a single tertiary hospital. A thermography camera, FLIR ONE Pro, was used to obtain both thermographic and digital images on subjects. For each subject, thermography, ultrasonography, arthrocentesis, and blood tests were conducted at the same study visit. Thermal imaging findings and clinical characteristics were compared by dividing the subjects into PD-positive and PD-negative groups on ultrasound. The receiver operating characteristic (ROC) curve analysis was used to determine the accuracy of PD positivity. Results A total of 30 knee arthritis patients were enrolled in this study. Knee temperature was significantly higher in PD-positive group compared to PD-negative group [maximum temperature (T max): 33.2℃ vs. 30.5℃, p =0.025; minimum temperature (T min): 30.7℃ vs. 27.0℃, p =0.015; average temperature (T ave): 32.1℃ vs. 29.1℃, p =0.016]. Also, the joint fluid white blood cell count was considerably higher in PD-positive group than in PD-negative group (24556 cells/mm 3 vs. 7840 cells/mm 3 , p =0.010). The area under the ROC curve of the point measurement of T max, T min, and T ave ranged between 0.764 and 0.790. Conclusion In this study, we found that high thermographic temperatures of the knee suggest a positive PD signal. Thus, thermography might be used as an adjuvant tool of PD for non-invasive evaluation of knee arthritis.

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Infrared thermography in children: a reliable tool for differential diagnosis of peripheral microvascular dysfunction and Raynaud’s phenomenon?

Cited by 18 publications

References 33 publications

Convolutional Neural Networks for Differential Diagnosis of Raynaud’s Phenomenon Based on Hands Thermal Patterns

Convolutional Neural Networks for Differential Diagnosis of Raynaud’s Phenomenon Based on Hands Thermal Patterns

Characteristic Features of Infrared Thermographic Imaging in Primary Raynaud’s Phenomenon

The Value of Thermal Imaging for Knee Arthritis: A Single-Center Observational Study

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