Machine Learning for Clinical Decision Support of Acute Streptococcal Pharyngitis: A Pilot Study.

BACKGROUND: Group A Streptococcus (GAS) is the predominant bacterial pathogen of pharyngitis in children. However, distinguishing GAS from viral pharyngitis is sometimes difficult. Unnecessary antibiotic use contributes to unwanted side effects, such as allergic reactions and diarrhea. It also may increase antibiotic resistance. OBJECTIVES: To evaluate the effect of a machine learning algorithm on the clinical evaluation of bacterial pharyngitis in children. METHODS: We assessed 54 children aged 2-17 years who presented to a primary healthcare clinic with a sore throat and fever over 38°C from 1 November 2021 to 30 April 2022. All children were tested with a streptococcal rapid antigen detection test (RADT). If negative, a throat culture was performed. Children with a positive RADT or throat culture were considered GAS-positive and treated antibiotically for 10 days, as per guidelines. Children with negative RADT tests throat cultures were considered positive for viral pharyngitis. The children were allocated into two groups: Group A streptococcal pharyngitis (GAS-P) (n=36) and viral pharyngitis (n=18). All patients underwent a McIsaac score evaluation. A linear support vector machine algorithm was used for classification. RESULTS: The machine learning algorithm resulted in a positive predictive value of 80.6 % (27 of 36) for GAS-P infection. The false discovery rates for GAS-P infection were 19.4 % (7 of 36). CONCLUSIONS: Applying the machine-learning strategy resulted in a high positive predictive value for the detection of streptococcal pharyngitis and can contribute as a medical decision aid in the diagnosis and treatment of GAS-P.

Smartphone-based detection of COVID-19 and associated pneumonia using thermal imaging and a transfer learning algorithm.

COVID-19-related pneumonia is typically diagnosed using chest x-ray or computed tomography images. However, these techniques can only be used in hospitals. In contrast, thermal cameras are portable, inexpensive devices that can be connected to smartphones. Thus, they can be used to detect and monitor medical conditions outside hospitals. Herein, a smartphone-based application using thermal images of a human back was developed for COVID-19 detection. Image analysis using a deep learning algorithm revealed a sensitivity and specificity of 88.7% and 92.3%, respectively. The findings support the future use of noninvasive thermal imaging in primary screening for COVID-19 and associated pneumonia.

Thermographic Changes following Short-Term High-Intensity Anaerobic Exercise.

Current studies report thermographic changes following aerobic or resistance exercise but not short, vigorous anaerobic exercise. Therefore, we investigated body surface temperature changes using thermal imaging following a short session of anaerobic exercise. We studied three different regions of interest (ROIs): the legs, chest, and forehead. Thermal imaging for each participant was performed before and immediately after completing a Wingate anaerobic test and every minute during a 15 min recovery period. Immediately after the test, the maximum temperature was significantly higher in all ROIs (legs, p = 0.0323; chest, p = 0.0455; forehead, p = 0.0444) compared to pre-test values. During the recovery period, both legs showed a significant and continuous temperature increase (right leg, p = 0.0272; left leg, p = 0.0382), whereas a non-significant drop was noted in the chest and forehead temperatures. Additionally, participants with a lower anaerobic capacity exhibited a higher delta increase in surface leg temperature than participants with higher anaerobic capacities, with a minimal change in surface leg temperature. This is the first study to demonstrate body surface temperature changes following the Wingate anaerobic test. This temperature increase is attributed to the high anaerobic mechanical power outputs achieved by the leg muscles and the time taken for temperature reduction post-exercise.

Morphological features of the photoplethysmographic signal: a new approach to characterize the microcirculatory response to photobiomodulation.

Introduction and Objectives: Advanced analysis of the morphological features of the photoplethysmographic (PPG) waveform may provide greater understanding of mechanisms of action of photobiomodulation (PBM). Photobiomodulation is a non-ionizing, red to near-infrared irradiation shown to induce peripheral vasodilatation, promote wound healing, and reduce pain. Using laser Doppler flowmetry combined with thermal imaging we found previously in a clinical study that PBM stimulates microcirculatory blood flow and that baseline palm skin temperature determines, at least in part, why some individuals respond favorably to PBM while others do not. "Responders" (n = 12) had a skin temperature range of 33°C-37.5°C, while "non-responders" (n = 8) had "cold" or "hot" skin temperature (<33°C or >37.5°C respectively). The continuous PPG signals recorded from the index fingers of both hands in the original clinical study were subjected to advanced post-acquisitional analysis in the current study, aiming to identify morphological features that may improve the accuracy of discrimination between potential responders and non-responders to PBM. Methods: The PPG signals were detrended by subtracting the lower envelope from the raw signal. The Root Mean Square (RMS) and Entropy features were extracted as were two additional morphological features -- Smoothness and number of local extrema per PPG beat (#Extrema). These describe the signal jaggedness and were developed specifically for this study. The Wilcoxon test was used for paired comparisons. Correlations were determined by the Spearman correlation test (rs). Results: The PPG waveforms of responders to PBM had increased amplitude and decreased jaggedness (Baseline vs. 10' post-irradiation: Entropy, 5.0 ± 1.3 vs. 3.9 ± 1.1, p = 0.012; #Extrema, 4.0 ± 1.1 vs. 3.0 ± 1.6, p = 0.009; RMS, 1.6 ± 0.9 vs. 2.3 ± 1.2, p = 0.004; Smoothness, 0.10 ± 0.05 vs. 0.19 ± 0.16, p = 0.016). In addition, unilateral irradiation resulted in a bilateral response, although the response of the contralateral, non-irradiated hand was shorter in duration and lower in magnitude. Although subjects with 'cold,' or 'hot,' baseline skin temperature appeared to have morphologically distinct PPG waveforms, representing vasoconstriction and vasodilatation, these were not affected by PBM irradiation. Conclusion: This pilot study indicates that post-acquisitional analysis of morphological features of the PPG waveform provides new measures for the exploration of microcirculation responsiveness to PBM.

Natural history of changes in knee skin temperature following total knee arthroplasty: a systematic review and meta-analysis.

Patients undergoing total-knee arthroplasty (TKA) have transient increases in anterior knee skin temperature (ST) that subside as recovery progresses-except in cases of systemic or local prosthetic joint infections (PJI). This meta-analysis was designed to quantify the changes in knee ST following TKA in patients with uncomplicated recovery as a prerequisite for assessing the usefulness of thermal imaging for diagnosis of PJI. This meta-analysis (PROSPERO-CRD42021269864) was performed according to PRISMA guidelines. PUBMED and EMBASE were searched for studies reporting knee ST of patients that underwent unilateral TKA with uncomplicated recovery. The primary outcome was the weighted means of the differences in ST between the operated and the non-operated knees (ΔST) for each time point (before TKA, and 1 day; 1,2, and 6 weeks; and 3,6, and 12-months post-TKA). For this analysis, 318 patients were included from 10 studies. The elevation in ST was greatest during the first 2-weeks (ΔST = 2.8 °C) and remained higher than pre-surgery levels at 4-6 weeks. At 3-months, ΔST was 1.4 °C. It decreased to 0.9 °C and 0.6 °C at 6 and 12-months respectively. Establishing the baseline profile of knee ST following TKA provides the necessary first step for evaluating the usefulness of thermography for the diagnosis of post-procedural PJI.

Automatized Detection of Crohn's Disease in Intestinal Ultrasound Using Convolutional Neural Network.

INTRODUCTION: The use of intestinal ultrasound (IUS) for the diagnosis and follow-up of inflammatory bowel disease is steadily growing. Although access to educational platforms of IUS is feasible, novice ultrasound operators lack experience in performing and interpreting IUS. An artificial intelligence (AI)-based operator supporting system that automatically detects bowel wall inflammation may simplify the use of IUS by less experienced operators. Our aim was to develop and validate an artificial intelligence module that can distinguish bowel wall thickening (a surrogate of bowel inflammation) from normal bowel images of IUS. METHODS: We used a self-collected image data set to develop and validate a convolutional neural network module that can distinguish bowel wall thickening >3 mm (a surrogate of bowel inflammation) from normal bowel images of IUS. RESULTS: The data set consisted of 1008 images, distributed uniformly (50% normal images, 50% abnormal images). Execution of the training phase and the classification phase was performed using 805 and 203 images, respectively. The overall accuracy, sensitivity, and specificity for detection of bowel wall thickening were 90.1%, 86.4%, and 94%, respectively. The network exhibited an average area under the ROC curve of 0.9777 for this task. CONCLUSIONS: We developed a machine-learning module based on a pretrained convolutional neural network that is highly accurate in the recognition of bowel wall thickening on intestinal ultrasound images in Crohn's disease. Incorporation of convolutional neural network to IUS may facilitate the use of IUS by inexperienced operators and allow automatized detection of bowel inflammation and standardization of IUS imaging interpretation.

We developed a machine-learning module based on a pretrained convolutional neural network that is highly accurate in the recognition of bowel wall thickening on intestinal ultrasound images in Crohn's disease.

Automated thermal imaging monitors the local response to cervical cancer brachytherapy.

Malignant tumors have high metabolic and perfusion rates, which result in a unique temperature distribution as compared to healthy tissues. Here, we sought to characterize the thermal response of the cervix following brachytherapy in women with advanced cervical carcinoma. Six patients underwent imaging with a thermal camera before a brachytherapy treatment session and after a 7-day follow-up period. A designated algorithm was used to calculate and store the texture parameters of the examined tissues across all time points. We used supervised machine learning classification methods (K Nearest Neighbors and Support Vector Machine) and unsupervised machine learning classification (K-means). Our algorithms demonstrated a 100% detection rate for physiological changes in cervical tumors before and after brachytherapy. Thus, we showed that thermal imaging combined with advanced feature extraction could potentially be used to detect tissue-specific changes in the cervix in response to local brachytherapy for cervical cancer.

Automated processing of thermal imaging to detect COVID-19.

Rapid and sensitive screening tools for SARS-CoV-2 infection are essential to limit the spread of COVID-19 and to properly allocate national resources. Here, we developed a new point-of-care, non-contact thermal imaging tool to detect COVID-19, based on advanced image processing algorithms. We captured thermal images of the backs of individuals with and without COVID-19 using a portable thermal camera that connects directly to smartphones. Our novel image processing algorithms automatically extracted multiple texture and shape features of the thermal images and achieved an area under the curve (AUC) of 0.85 in COVID-19 detection with up to 92% sensitivity. Thermal imaging scores were inversely correlated with clinical variables associated with COVID-19 disease progression. In summary, we show, for the first time, that a hand-held thermal imaging device can be used to detect COVID-19. Non-invasive thermal imaging could be used to screen for COVID-19 in out-of-hospital settings, especially in low-income regions with limited imaging resources.

Physiological measurements of facial skin response under personal protective equipment.

Medical device-related pressure ulcers (MDRPUs) were traditionally associated with skin-contacting medical devices applied to patients, eventually causing tissue damage. The coronavirus-2019 pandemic has brought a new variant of MDRPUs: facial skin irritation or damage associated with extended use of protective personal equipment (PPE), e.g. facemasks and respirators. In this context, we report here a comprehensive experimental evaluation including facial contact forces, skin temperatures and sub-epidermal moisture (SEM) measurements pre/post-PPE usage, to determine how these physiological parameters change under the effects of surgical facemasks and KN95 respirators and whether such potential changes can explain the commonly reported skin irritation or damage. We found that a surgical mask is potentially less irritating to facial skin than the KN95 respirator, as it applies lower forces and facilitates faster return of facial temperatures to their basal levels. Further, we demonstrated that use of dressing cuts for padding under a KN95 respirator considerably reduced localized forces and did not worsen the thermal and SEM readings at the skin-device contact sites. This study provides a basis for improvement of PPE designs, as it describes physiological measurement methodologies for quantitative comparisons of the effects of different PPE types on facial skin status.

Assessment of blood distribution in response to post-surgical steal syndrome: A novel technique based on Thermo-Anatomical Segmentation.

The distal ischemic steal syndrome (ISS) is a complication following the construction of an arteriovenous (A-V) access for hemodialysis. The ability to non-invasively monitor changes in skin microcirculation improves both the diagnosis and treatment of vascular diseases. In this study, we propose a novel technique for evaluating the palms' blood distribution following arteriovenous access, based on thermal imaging. Furthermore, we utilize the thermal images to identify typical recovery patterns of patients that underwent this surgery and show that thermal images taken post-surgery reflect the patient's follow-up status. Thermal photographs were taken by a portable thermal camera from both hands before and after the A-V access surgery, and one month following the surgery, from ten dialysis patients. A novel term "Thermo-Anatomical Segmentation", which enables a functional assessment of palm blood distribution was defined. Based on this segmentation it was shown that the greatest change after surgery was in the most distal region, the fingertips (p < 0.05). In addition, the changes in palm blood distribution in both hands were synchronized, which indicates a bilateral effect. An unsupervised machine learning model revealed two variables that determine the recovery pattern following the surgery: the palms' temperature difference pre- and post-surgery and the post-surgery difference between the treated and untreated hand. Our proposed framework provides a new technique for quantitative assessment of the palm's blood distribution. This technique may improve the clinical treatment of patients with vascular disease, particularly the patient-specific follow-up, in clinics as well as in homecare.

Automated thermal imaging for the detection of fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) comprises a spectrum of progressive liver pathologies, ranging from simple steatosis to non-alcoholic steatohepatitis (NASH), fibrosis and cirrhosis. A liver biopsy is currently required to stratify high-risk patients, and predicting the degree of liver inflammation and fibrosis using non-invasive tests remains challenging. Here, we sought to develop a novel, cost-effective screening tool for NAFLD based on thermal imaging. We used a commercially available and non-invasive thermal camera and developed a new image processing algorithm to automatically predict disease status in a small animal model of fatty liver disease. To induce liver steatosis and inflammation, we fed C57/black female mice (8 weeks old) a methionine-choline deficient diet (MCD diet) for 6 weeks. We evaluated structural and functional liver changes by serial ultrasound studies, histopathological analysis, blood tests for liver enzymes and lipids, and measured liver inflammatory cell infiltration by flow cytometry. We developed an image processing algorithm that measures relative spatial thermal variation across the skin covering the liver. Thermal parameters including temperature variance, homogeneity levels and other textural features were fed as input to a t-SNE dimensionality reduction algorithm followed by k-means clustering. During weeks 3,4, and 5 of the experiment, our algorithm demonstrated a 100% detection rate and classified all mice correctly according to their disease status. Direct thermal imaging of the liver confirmed the presence of changes in surface thermography in diseased livers. We conclude that non-invasive thermal imaging combined with advanced image processing and machine learning-based analysis successfully correlates surface thermography with liver steatosis and inflammation in mice. Future development of this screening tool may improve our ability to study, diagnose and treat liver disease.

The microclimate under dressings applied to intact weight-bearing skin: Infrared thermography studies.

BACKGROUND: When a patient is lying in a hospital bed (e.g. supine or prone), bodyweight forces distort soft tissues by compression, tension and shear, and may lead to the onset of pressure ulcers in those who are stationary and insensate, especially at their pelvic region. Altered localized microclimate conditions, particularly elevated skin temperatures leading to perspiration and resulting in skin moisture or wetness, are known to further increase the risk for pressure ulcers, which is already high in immobile patients. METHODS: We have used infrared thermography to measure local skin temperatures at the buttocks of supine healthy subjects, to quantitatively determine, for the first time in the literature, how skin microclimate conditions associated with a weight-bearing Fowler's position are affected by application of dressings. Our present methodology has been applied to compare a polymeric membrane dressing versus placebo foam, with a no-dressing case used as reference. FINDINGS: One hour of lying in a Fowler's position was already enough to cause considerable heat trapping (~3 °C rise) between the weight-bearing body and the support surface. Analyses of normalized local skin temperatures and entropy of the temperature distributions indicated that the polymeric membrane dressing material allowed better and more homogenous clearance of locally accumulated body-heat with respect to simple foam. INTERPRETATION: Infrared thermography is suitable for characterizing skin microclimate conditions under different dressings, and, accordingly, is effective in developing and evaluating pressure ulcer prevention and treatment strategies - both of which require adequate skin microclimate.

Microcirculatory Response to Photobiomodulation-Why Some Respond and Others Do Not: A Randomized Controlled Study.

BACKGROUND AND OBJECTIVES: Photobiomodulation (PBM), a non-ionizing, non-thermal irradiation, used clinically to accelerate wound healing and inhibit pain, was previously shown to increase blood flow. However, some individuals respond to PBM, but others do not. The purpose of this study was to investigate factors affecting this patient-specific response using advanced, noninvasive methods for monitoring microcirculatory activity. STUDY DESIGN/MATERIALS AND METHODS: In this prospective, randomized controlled clinical trial (NCT03357523), 20 healthy non-smoking volunteers (10:10 males:females, 30 ± 8 years old) were randomized to receive either red- (633 nm and 70 W/cm2 ) or near-infrared light (830 nm and 55 mW/cm2 ) over the wrist for 5 minutes. Photoplethysmography, laser Doppler flowmetry, and thermal imaging were used to monitor palm microcirculatory blood volume, blood flow, and skin temperature, respectively, before, during, and 20 minutes after irradiation. Participants with skin temperature change ≥0.5°C from baseline were considered "responders". RESULTS: Near-infrared PBM was found to induce a 27% increase in microcirculatory flow that increased to 54% during the 20-minute follow-up period (P = 0.049 and P = 0.004, respectively), but red light PBM did not increase the median flow. Only 10 of 20 participants were responders by thermal imaging (i.e., ≥0.5°C from baseline), and their initial skin temperature was between 33 and 37.5°C. The non-responders had either "hot" hands (≥37.5°C) or "cold" hands (≤33°C). In responders, the meantime to 20% increase in microcirculatory blood volume and blood flow was less than 2.5 minutes after initiation of PBM irradiation. CONCLUSIONS: We demonstrated that PBM induces arteriolar vasodilatation that results in both immediate and long-lasting increased capillary flow and tissue perfusion in healthy individuals. This response was wavelength-dependent and modified by skin temperature. These findings regarding physiological parameters associated with sensitivity or resistance to PBM provide information of direct relevance for patient-specific therapy. Lasers Surg. Med. © 2020 Wiley Periodicals, Inc.

Thermal Monitoring of Tumor and Tissue State during Radiation Therapy - A Complex Case of Radiation Recall.

Common radiation dermatitis over radiation fields can be mild as minor erythema but can also be associated with blisters and skin desquamation. This phenomenon has been widely investigated and documented, especially in breast cancer patients. Obesity, smoking, and diabetes are known risk factors; however, we cannot predict the severity of radiation dermatitis prior to treatment. The overwhelming radiation recall dermatitis is an acute inflammatory reaction confined to previously irradiated areas that can be triggered when chemotherapy agents are administered after radiotherapy. This rare, painful skin reaction leads to treatment cessation or alteration. In this study, we investigate the feasibility of using thermography as a tool to predict the response of normal breast tissue and skin to radiation therapy and the risk of developing radiation recall dermatitis. Six women with viable in-breast tumor (breast cancer) and eight women who underwent tumor resection (lumpectomy) were monitored by a thermal camera prior to radiotherapy treatment (breast region) and on weekly basis, in the same environmental conditions, through the radiation course of treatment. One patient developed radiation recall dermatitis when treated with chemotherapy following radiation therapy, and needed intensive local treatments and narcotics with full recovery thereafter. Clinical and treatment data as well as response to radiation were collected prospectively. The ongoing thermal changes observed during the radiation treatment for all patients, with and without viable tumor in the breast, were documented, analyzed, and reported here with detailed comparison to the recognized data for the patient diagnosed with radiation recall dermatitis.

Non-invasive thermal imaging of cardiac remodeling in mice.

Thermal infrared imaging has been suggested as a non-invasive alternative to monitor physiological processes and disease. However, the use of this technique to image internal organs, such as the heart, has not yet been investigated. We sought to determine the ability of our novel thermal image-processing algorithm to detect structural and functional changes in a mouse model of hypertension and cardiac remodeling. Twelve mice were randomly assigned to receive either the pro-inflammatory, hypertensive hormone angiotensin-II (2 mg/kg/day, n = 6) or saline (n = 6) infusion for 28 days. We performed weekly blood pressure measurements, together with serial trans-thoracic echocardiography studies and histopathological evaluation of the hearts. Thermal images were captured with a commercially available thermal camera, and images were processed by our novel algorithm which analyzes relative spatial temperature variation across the animal's thorax. We assessed cardiac inflammation by measuring inflammatory cell infiltration through flow cytometry. Angiotensin infusion increased blood pressure together with cardiac hypertrophy and fibrosis. Thermal imaging at day 28 of the experiment detected an increase in the fraction of the skin heated by the heart in angiotensin-treated mice. Thermal image findings were significantly correlated to left ventricular volume and mass parameters seen on echocardiography (r = 0.8, p < 0.01 and r = 0.6, p = 0.07). We also identified distinct changes in the spatial heat profiles of all angiotensin-treated hearts, possibly reflecting remodeling processes in the hypertensive heart. Finally, a machine learning based model using thermal imaging parameters predicted intervention status in 10 out of 11 mice similar to a model using echocardiographic measurements. Our findings suggest, for the first time, that a new thermal image-processing algorithm successfully correlates surface thermography with cardiac structural changes in mice with hypertensive heart disease.

Dressings cut to shape alleviate facial tissue loads while using an oxygen mask.

Non-invasive ventilation (NIV) masks are commonly used for respiratory support where intubation or a surgical procedure can be avoided. However, prolonged use of NIV masks involves risk to facial tissues, which are subjected to sustained deformations caused by tightening of the mask and microclimate conditions. The risk of developing such medical device-related pressure ulcers can be reduced by providing additional cushioning at the mask-face interface. In this work, we determined differences in facial tissue stresses while using an NIV mask with versus without using dressing cuts (Mepilex Lite; Mölnlycke Health Care, Gothenburg, Sweden). First, we developed a force measurement system that was used to experimentally determine local forces applied to skin at the bridge of the nose, cheeks, and chin in a healthy sample group while using a NIV mask. We further demonstrated facial temperature distributions after use of the mask using infrared thermography. Next, using the finite element method, we delivered the measured compressive forces per site of the face in the model and compared maximal effective stresses in facial tissues with versus without the dressing cuts. The dressings have shown substantial biomechanical effectiveness in alleviating facial tissues deformations and stresses by providing localised cushioning to the tissues at risk.

An innovative appendage invagination procedure to reduce thrombus formation - a numerical model.

Invagination is an innovative technique for closing the left atrial appendage (LAA) to reduce the risk of thrombi formation. The influence of LAA invagination on the flow fields in the atria was investigated based on a computational fluid dynamics. The simulation results demonstrated that the novel invagination process can eliminate low velocities (blood stasis) and low shear rate and thus decrease the risk of thrombus formation during atrial fibrillation. This innovative technique may enhance the clinical treatment of patients with atrial fibrillation by improving the atrial flow field while lowering the risk of creating emboli.

Thermal imaging as a tool for evaluating tumor treatment efficacy.

Breast cancer is the most frequently diagnosed cancer among women in the Western world. Thermography is a nonionizing, noninvasive, portable, and low-cost method that can be used in an outpatient clinic. It was tried as a tool to detect breast cancer tumors, however, it had too many false readings. Thermography has been extensively studied as a breast cancer detection tool but was not used as a treatment monitoring tool. The purpose of this study was to investigate the possibility of using thermal imaging as a feedback system to optimize radiation therapy. Patients were imaged with a thermal camera prior and throughout the radiotherapy sessions. At the end of the session, the images were analyzed for temporal vasculature changes through vessels segmentation image processing tools. Tumors that were not responsive to treatment were observed before the radiation therapy sessions were concluded. Assessing the efficacy of radiotherapy during treatment makes it possible to change the treatment regimen, dose, and radiation field during treatment as well as to individualize treatment schedules to optimize treatment effectiveness.