AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CACTM) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis.

INTRODUCTION: Coronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™) predicted incident atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we investigated the performance of AI-CAC cardiac chambers for prediction of incident heart failure (HF). METHODS: We applied AI-CAC to 5750 CAC scans of asymptomatic individuals (52% female, White 40%, Black 26%, Hispanic 22% Chinese 12%) free of known cardiovascular disease at the MESA baseline examination (2000-2002). We used the 15-year outcomes data and compared the time-dependent area under the curve (AUC) of AI-CAC volumetry versus NT-proBNP, Agatston score, and 9 known clinical risk factors (age, gender, diabetes, current smoking, hypertension medication, systolic and diastolic blood pressure, LDL, HDL for predicting incident HF over 15 years. RESULTS: Over 15 years of follow-up, 256 HF events accrued. The time-dependent AUC [95% CI] at 15 years for predicting HF with AI-CAC all chambers volumetry (0.86 [0.82,0.91]) was significantly higher than NT-proBNP (0.74 [0.69, 0.77]) and Agatston score (0.71 [0.68, 0.78]) (p â€‹< â€‹0.0001), and comparable to clinical risk factors (0.85, p â€‹= â€‹0.4141). Category-free Net Reclassification Index (NRI) [95% CI] adding AI-CAC LV significantly improved on clinical risk factors (0.32 [0.16,0.41]), NT-proBNP (0.46 [0.33,0.58]), and Agatston score (0.71 [0.57,0.81]) for HF prediction at 15 years (p â€‹< â€‹0.0001). CONCLUSION: AI-CAC volumetry significantly outperformed NT-proBNP and the Agatston CAC score, and significantly improved the AUC and category-free NRI of clinical risk factors for incident HF prediction.

AI-enabled left atrial volumetry in coronary artery calcium scans (AI-CACTM) predicts atrial fibrillation as early as one year, improves CHARGE-AF, and outperforms NT-proBNP: The multi-ethnic study of atherosclerosis.

BACKGROUND: Coronary artery calcium (CAC) scans contain actionable information beyond CAC scores that is not currently reported. METHODS: We have applied artificial intelligence-enabled automated cardiac chambers volumetry to CAC scans (AI-CACTM) to 5535 asymptomatic individuals (52.2% women, ages 45-84) that were previously obtained for CAC scoring in the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis (MESA). AI-CAC took on average 21 â€‹s per CAC scan. We used the 5-year outcomes data for incident atrial fibrillation (AF) and assessed discrimination using the time-dependent area under the curve (AUC) of AI-CAC LA volume with known predictors of AF, the CHARGE-AF Risk Score and NT-proBNP. The mean follow-up time to an AF event was 2.9 â€‹± â€‹1.4 years. RESULTS: At 1,2,3,4, and 5 years follow-up 36, 77, 123, 182, and 236 cases of AF were identified, respectively. The AUC for AI-CAC LA volume was significantly higher than CHARGE-AF for Years 1, 2, and 3 (0.83 vs. 0.74, 0.84 vs. 0.80, and 0.81 vs. 0.78, respectively, all p â€‹< â€‹0.05), but similar for Years 4 and 5, and significantly higher than NT-proBNP at Years 1-5 (all p â€‹< â€‹0.01), but not for combined CHARGE-AF and NT-proBNP at any year. AI-CAC LA significantly improved the continuous Net Reclassification Index for prediction of AF over years 1-5 when added to CHARGE-AF Risk Score (0.60, 0.28, 0.32, 0.19, 0.24), and NT-proBNP (0.68, 0.44, 0.42, 0.30, 0.37) (all p â€‹< â€‹0.01). CONCLUSION: AI-CAC LA volume enabled prediction of AF as early as one year and significantly improved on risk classification of CHARGE-AF Risk Score and NT-proBNP.

AI-enabled Left Atrial Volumetry in Cardiac CT Scans Improves CHARGE-AF and Outperforms NT-ProBNP for Prediction of Atrial Fibrillation in Asymptomatic Individuals: Multi-Ethnic Study of Atherosclerosis.

Background: Coronary artery calcium (CAC) scans contain actionable information beyond CAC scores that is not currently reported. Methods: We have applied artificial intelligence-enabled automated cardiac chambers volumetry to CAC scans (AI-CAC), taking on average 21 seconds per CAC scan, to 5535 asymptomatic individuals (52.2% women, ages 45-84) that were previously obtained for CAC scoring in the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis (MESA). We used the 5-year outcomes data for incident atrial fibrillation (AF) and compared the time-dependent AUC of AI-CAC LA volume with known predictors of AF, the CHARGE-AF Risk Score and NT-proBNP (BNP). The mean follow-up time to an AF event was 2.9±1.4 years. Results: At 1,2,3,4, and 5 years follow-up 36, 77, 123, 182, and 236 cases of AF were identified, respectively. The AUC for AI-CAC LA volume was significantly higher than CHARGE-AF or BNP at year 1 (0.836, 0.742, 0.742), year 2 (0.842, 0.807,0.772), and year 3 (0.811, 0.785, 0.745) (p<0.02), but similar for year 4 (0.785, 0.769, 0.725) and year 5 (0.781, 0.767, 0.734) respectively (p>0.05). AI-CAC LA volume significantly improved the continuous Net Reclassification Index for prediction of AF over years 1-5 when added to CAC score (0.74, 0.49, 0.53, 0.39, 0.44), CHARGE-AF Risk Score (0.60, 0.28, 0.32, 0.19, 0.24), and BNP (0.68, 0.44, 0.42, 0.30, 0.37) respectively (p<0.01). Conclusion: AI-CAC LA volume enabled prediction of AF as early as one year and significantly improved on risk classification of CHARGE-AF Risk Score and BNP.

Validation of Opportunistic Artificial Intelligence-Based Bone Mineral Density Measurements in Coronary Artery Calcium Scans.

BACKGROUND: Previously we reported a manual method of measuring thoracic vertebral bone mineral density (BMD) using quantitative CT in noncontrast cardiac CT scans used for coronary artery calcium (CAC) scoring. In this report, we present validation studies of an artificial intelligence-based automated BMD measurement (AutoBMD) that recently received FDA approval as an opportunistic add-on to CAC scans. METHODS: A deep learning model was trained to detect vertebral bodies. Subsequently, signal processing techniques were developed to detect intervertebral discs and the trabecular components of the vertebral body. The model was trained using 132 CAC scans comprising 7,649 slices. To validate AutoBMD, we used 5,785 cases of manual BMD measurements previously reported from CAC scans in the Multi-Ethnic Study of Atherosclerosis. RESULTS: Mean ± SD for AutoBMD and manual BMD were 166.1 ± 47.9 mg/cc and 163.1 ± 46 mg/cc, respectively (P = .006). Multi-Ethnic Study of Atherosclerosis cases were 47.5% male and 52.5% female, with age 62.2 ± 10.3. A strong correlation was found between AutoBMD and manual measurements (R = 0.85, P < .0001). Accuracy, sensitivity, specificity, positive predictive value and negative predictive value for AutoBMD-based detection of osteoporosis were 99.6%, 96.7%, 97.7%, 99.7% and 99.8%, respectively. AutoBMD averaged 15 seconds per report versus 5.5 min for manual measurements (P < .0001). CONCLUSIONS: AutoBMD is an FDA-approved, artificial intelligence-enabled opportunistic tool that reports BMD with Z-scores and T-scores and accurately detects osteoporosis and osteopenia in CAC scans, demonstrating results comparable to manual measurements. No extra cost of scanning and no extra radiation to patients, plus the high prevalence of asymptomatic osteoporosis, make AutoBMD a promising candidate to enhance patient care.

Opportunistic AI-enabled automated bone mineral density measurements in lung cancer screening and coronary calcium scoring CT scans are equivalent.

Rationale and objectives: We previously reported a novel manual method for measuring bone mineral density (BMD) in coronary artery calcium (CAC) scans and validated our method against Dual X-Ray Absorptiometry (DEXA). Furthermore, we have developed and validated an artificial intelligence (AI) based automated BMD (AutoBMD) measurement as an opportunistic add-on to CAC scans that recently received FDA approval. In this report, we present evidence of equivalency between AutoBMD measurements in cardiac vs lung CT scans. Materials and methods: AI models were trained using 132 cases with 7649 (3 mm) slices for CAC, and 37 cases with 21918 (0.5 mm) slices for lung scans. To validate AutoBMD against manual measurements, we used 6776 cases of BMD measured manually on CAC scans in the Multi-Ethnic Study of Atherosclerosis (MESA). We then used 165 additional cases from Harbor UCLA Lundquist Institute to compare AutoBMD in patients who underwent both cardiac and lung scans on the same day. Results: Mean±SD for age was 69 ± 9.4 years with 52.4% male. AutoBMD in lung and cardiac scans, and manual BMD in cardiac scans were 153.7 ± 43.9, 155.1 ± 44.4, and 163.6 ± 45.3 g/cm3, respectively (p = 0.09). Bland-Altman agreement analysis between AutoBMD lung and cardiac scans resulted in 1.37 g/cm3 mean differences. Pearson correlation coefficient between lung and cardiac AutoBMD was R2 = 0.95 (p < 0.0001). Conclusion: Opportunistic BMD measurement using AutoBMD in CAC and lung cancer screening scans is promising and yields similar results. No extra radiation plus the high prevalence of asymptomatic osteoporosis makes AutoBMD an ideal screening tool for osteopenia and osteoporosis in CT scans done for other reasons.

High Frequency of Microvascular Dysfunction in US Outpatient Clinics: A Sign of High Residual Risk? Data from 7,105 Patients.

Previous studies have linked peripheral microvascular dysfunction measured by arterial tonometry to high residual risk in on-statin patients. Digital thermal monitoring (DTM) of microvascular function is a new and simplified technique based on fingertip temperature measurements that has been correlated with the burden of atherosclerosis and its risk factors. Here, we report analyses of DTM data from two large US registries: Registry-I (6,084 cases) and Registry-II (1,021 cases) across 49 US outpatient clinics. DTM tests were performed using a VENDYS device during a 5-minute arm-cuff reactive hyperemia. Fingertip temperature falls during cuff inflation and rebounds after deflation. Adjusted maximum temperature rebound was reported as vascular reactivity index (VRI). VRI distributions were similar in both registries, with mean ± SD of 1.58 ± 0.53 in Registry-I and 1.52 ± 0.43 in Registry-II. In the combined dataset, only 18% had optimal VRI (≥2.0) and 82% were either poor (<1.0) or intermediate (1.0-2.0). Women had slightly higher VRI than men (1.62 ± 0.56 vs. 1.54 ± 0.47, p < 0.001). VRI was inversely but mildly correlated with age (r = -0.19, p < 0.001). Suboptimal VRI was found in 72% of patients <50 years, 82% of 50-70 years, and 86% of ≥70 years. Blood pressure was not correlated with VRI. In this largest registry of peripheral microvascular function measurements, suboptimal scores were highly frequent among on-treatment patients, possibly suggesting a significant residual risk. Prospective studies are warranted to validate microvascular dysfunction as an indicator of residual risk.

The association of nadir CD4-T cell count and endothelial dysfunction in a healthy HIV cohort without major cardiovascular risk factors.

OBJECTIVES: HIV-infected population may have increased risk of cardiovascular disease. The prevalence of traditional cardiovascular disease risk factors such as hypertension, diabetes and dyslipidemia in HIV-infected individuals has made it difficult to assess the direct effects of HIV and immune factors on endothelial dysfunction and associated increased risk of atherosclerosis. The purpose of this study was to investigate indicators of endothelial dysfunction in an HIV cohort without hypertension and diabetes. METHODS: We studied 19 HIV-infected patients between the ages of 25-76 years old with effectively suppressed viral load and without diagnosis of hypertension or diabetes. Endothelial function was measured by digital thermal monitoring of vascular reactivity using the VENDYS technique. Endothelial function was reported as vascular reactivity index. Systolic blood pressure and diastolic blood pressure at the time of VENDYS test were measured and latest lipid panels were recorded. The association between vascular reactivity index and CD4-T cells count, different antiretroviral therapy types (non-nucleoside reverse transcriptase, nucleoside reverse transcriptase, protease inhibitors, integrase inhibitors), vitamins use, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol was investigated. RESULTS: Mean vascular reactivity index was 1.87 ± 0.53. Vascular reactivity index, marker of endothelial dysfunction, showed a significant correlation with lower nadir CD4 count (p = 0.003) as well as low-density lipoprotein cholesterol (p = 0.02). No additional significant correlation between vascular reactivity index and the rest of the investigated variables was found. CONCLUSION: Vascular reactivity index, a clinical predictor of endothelial dysfunction, is associated with lower nadir CD4-T cell and low-density lipoprotein cholesterol in HIV-infected men with no history of hypertension or diabetes and before clinical evidence of cardiovascular disease.

Coronary artery calcium testing: A call for universal coverage.

Heart attacks kill more Americans than all cancers combined. Fatal heart attack victims have no symptoms until minutes before they die, hence early detection of high-risk asymptomatic individuals is needed. Even though heart attacks kill and cost more than cancers, as a nation we spend over 20 times more on screening for asymptomatic cancer than for asymptomatic atherosclerotic cardiovascular disease (ASCVD), the underlying cause of heart attacks. Currently, payers only cover screening for risk factors of ASCVD such as blood pressure and blood cholesterol. This approach tends to miss high-risk and over-treat low-risk individuals. Although treadmill stress testing with ECG is not indicated for ASCVD detection in asymptomatic individuals, it is done often, and frequently leads to misleading conclusions or unnecessary downstream diagnostic procedures. For example, former President Clinton had passed his treadmill stress tests for several years during his presidential annual checkup but had a heart attack shortly after his presidency. This common practice is a waste of our limited resources. Instead, a more accurate risk assessment using coronary artery calcium (CAC) testing is available; and has just been adopted by ACC/AHA guidelines, however payers do not cover it. CAC is measured non-invasively with a 5-minute CT-scan of the heart, and costs less than $200, whereas cancer screening with colonoscopy and mammography costs over $3000. There is an opportunity to save lives and dollars if CAC testing is covered for appropriately selected individuals. Texas has already passed HB1290 to mandate CAC coverage. Other states must step up and take actions.

Radiation exposure and coronary artery calcium scans in the society for heart attack prevention and eradication cohort.

Coronary artery calcium (CAC) scoring is used in asymptomatic patients to improve their clinically predicted risk for future cardiovascular events. Current CT protocols seek to reduce radiation exposure without diminishing image quality. Reported radiation exposure remains widely variable (0.8-5 mSv) depending on the type of protocol. In this study, we report the radiation exposure of CAC scoring from the Society for Heart Attack Prevention and Eradication (SHAPE) early detection program cohort sites, which spanned multiple centers using 64-MDCT (multi-detector computed tomography) scanners. We reviewed radiation exposure in milliSieverts (mSv) for 82,214 participants from the SHAPE early detection program cohort who underwent CAC scoring. This occurred over a 2.5-year period (2012-2014) divided among 33 sites in 7 countries with four different types 64-MDCT scanners. The effective radiation dose was reported as mSv. Mean radiation dosing amongst all 82,214 participants was 1.03 mSv, a median dose of 0.94 mSv. The mean radiation dose ranged from 0.76 to 1.31 mSv across the 33 sites involved with the SHAPE program cohort. Subgroup analysis by age, gender or body mass index (BMI) less than 30 kg/m2 showed no variability. Radiation dose in patients with BMI > 30 kg/m2 were significantly greater than other subgroups (µ = 1.96 mSv, p < 0.001). The use of 64-MDCT scanners and protocols provide the effective radiation dose for CAC scoring, which is approximately 1 mSv. This is consistently lower than previously reported for CAC scanning, regardless of scanner type, age or gender. In contrast, a greater BMI influenced mean radiation doses.

Machine Learning Outperforms ACC / AHA CVD Risk Calculator in MESA.

Background Studies have demonstrated that the current US guidelines based on American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Equations Risk Calculator may underestimate risk of atherosclerotic cardiovascular disease ( CVD ) in certain high-risk individuals, therefore missing opportunities for intensive therapy and preventing CVD events. Similarly, the guidelines may overestimate risk in low risk populations resulting in unnecessary statin therapy. We used Machine Learning ( ML ) to tackle this problem. Methods and Results We developed a ML Risk Calculator based on Support Vector Machines ( SVM s) using a 13-year follow up data set from MESA (the Multi-Ethnic Study of Atherosclerosis) of 6459 participants who were atherosclerotic CVD-free at baseline. We provided identical input to both risk calculators and compared their performance. We then used the FLEMENGHO study (the Flemish Study of Environment, Genes and Health Outcomes) to validate the model in an external cohort. ACC / AHA Risk Calculator, based on 7.5% 10-year risk threshold, recommended statin to 46.0%. Despite this high proportion, 23.8% of the 480 "Hard CVD " events occurred in those not recommended statin, resulting in sensitivity 0.76, specificity 0.56, and AUC 0.71. In contrast, ML Risk Calculator recommended only 11.4% to take statin, and only 14.4% of "Hard CVD " events occurred in those not recommended statin, resulting in sensitivity 0.86, specificity 0.95, and AUC 0.92. Similar results were found for prediction of "All CVD " events. Conclusions The ML Risk Calculator outperformed the ACC/AHA Risk Calculator by recommending less drug therapy, yet missing fewer events. Additional studies are underway to validate the ML model in other cohorts and to explore its ability in short-term CVD risk prediction.

Acute and Subacute Triggers of Cardiovascular Events.

Inability to predict short-term cardiovascular (CV) events and take immediate preemptive actions has long been the Achilles heel of cardiology. However, certain triggers of these events have come to light. Although these triggers are nonspecific and are part of normal life, studying their temporal relationship with the onset of CV events provides an opportunity to alert high-risk atherosclerotic patients who may be most vulnerable to such triggers, the "vulnerable patient". Herein, we review the literature and shed light on the epidemiology and underlying pathophysiology of different triggers. We describe that certain adrenergic triggers can precipitate a CV event within minutes or hours; whereas triggers that elicit an immune or inflammatory response such as infections may tip an asymptomatic "vulnerable patient" to become symptomatic days and weeks later. In conclusion, healthcare providers should counsel high-risk CV patients (e.g., in secondary prevention clinics or those with coronary artery Calcium >75th percentile) on the topic, advise them to avoid such triggers, take protective measures once exposed, and seek emergency care immediately after becoming symptomatic after such triggers. Furthermore, clinical trials targeting triggers (prevention or intervention) are needed.

New Indices of Endothelial Function Measured by Digital Thermal Monitoring of Vascular Reactivity: Data from 6084 Patients Registry.

Background. Endothelial function is viewed as a barometer of cardiovascular health and plays a central role in vascular reactivity. Several studies showed digital thermal monitoring (DTM) as a simple noninvasive method to measure vascular reactivity that is correlated with atherosclerosis risk factors and coronary artery disease. Objectives. To further evaluate the relations between patient characteristics and DTM indices in a large patient registry. Methods. DTM measures were correlated with age, sex, heart rate, and systolic and diastolic blood pressure in 6084 patients from 18 clinics. Results. DTM vascular reactivity index (VRI) was normally distributed and inversely correlated with age (r = -0.21, p < 0.0001). Thirteen percent of VRI tests were categorized as poor vascular reactivity (VRI < 1.0), 70 percent as intermediate (1.0 ≤ VRI < 2.0), and 17 percent as good (VRI ≥ 2.0). Poor VRI (<1.0) was noted in 6% of <50 y, 10% of 50-70 y, and 18% of ≥70 y. In multiple linear regression analyses, age, sex, and diastolic blood pressure were significant but weak predictors of VRI. Conclusions. As the largest database of finger-based vascular reactivity measurement, this report adds to prior findings that VRI is a meaningful physiological marker and reflects a high level of residual risk found in patients currently under care.

Cardiovascular health informatics: risk screening and intervention.

Despite enormous efforts to prevent cardiovascular disease (CVD) in the past, it remains the leading cause of death in most countries worldwide. Around two-thirds of these deaths are due to acute events, which frequently occur suddenly and are often fatal before medical care can be given. New strategies for screening and early intervening CVD, in addition to the conventional methods, are therefore needed in order to provide personalized and pervasive healthcare. In this special issue, selected emerging technologies in health informatics for screening and intervening CVDs are reported. These papers include reviews or original contributions on 1) new potential genetic biomarkers for screening CVD outcomes and high-throughput techniques for mining genomic data; 2) new imaging techniques for obtaining faster and higher resolution images of cardiovascular imaging biomarkers such as the cardiac chambers and atherosclerotic plaques in coronary arteries, as well as possible automatic segmentation, identification, or fusion algorithms; 3) new physiological biomarkers and novel wearable and home healthcare technologies for monitoring them in daily lives; 4) new personalized prediction models of plaque formation and progression or CVD outcomes; and 5) quantifiable indices and wearable systems to measure them for early intervention of CVD through lifestyle changes. It is hoped that the proposed technologies and systems covered in this special issue can result in improved CVD management and treatment at the point of need, offering a better quality of life to the patient.

Analysis of contrast-enhanced intravascular ultrasound images for the assessment of coronary plaque neoangiogenesis: another step closer to the identification of the vulnerable plaque.

Atherosclerotic cardiovascular disease (CVD), primarily manifested as heart attacks and strokes, remains the main cause of death in the developed countries and is rapidly increasing in the developing world. Early detection and aggressive treatment of hidden (asymptomatic) atherosclerotic plaques that cause heart attack or stroke are most needed. However, existing clinical tools are not sufficient to address this need. Intravascular ultrasound (IVUS) is a catheter-based medical imaging tool that is capable of providing cross-sectional images of arteries. It is by far the most powerful clinical tool available for characterization of atherosclerotic plaques. However, existing IVUS is unable to detect plaque inflammation which is a key factor in complications of atherosclerotic plaques. Contrast enhanced IVUS (CE-IVUS) for detection of Vasa Vasorum (VV), microvessles that feed the vessel wall, can indirectly image plaque inflammation and thereby significantly increase the diagnostic power of IVUS. Several studies have shown that the density of VV in the atherosclerotic plaques is strongly correlated with the intensity of plaque inflammation and related processes which lead to plaque destabilization and rupture (the Vulnerable Plaque). Therefore the detection and measurement of VV in plaque, and leakage of blood from VV into plaques using CE-IVUS, can enable the development of an index for plaque vulnerability. In this paper, we present a review of our original work on coronary VV imaging, discuss subsequent reports by others, and also present the latest on the detection of VV based on CE-IVUS.

Reproducibility and variability of digital thermal monitoring of vascular reactivity.

BACKGROUND: Previous studies demonstrated that digital thermal monitoring (DTM) of vascular reactivity, a new test for vascular function assessment, is well correlated with Framingham Risk Score, coronary calcium score and CT angiography. This study evaluates the variability and reproducibility of DTM measurements. We hypothesized that DTM is reproducible, and its variability falls within the accepted range of clinical diagnostic tests. METHOD: A fully automated DTM device (VENDYS, Endothelix Inc., Houston, TX, USA) was used for repeated measurement of vascular function in 18 healthy volunteers (age 35 ± 4 years, 74% men) after 24 h. All subjects underwent overnight fasting, and the test was preceded by 30-min rest in a supine position inside a dimmed room with temperature 22-24°C. The measurements were obtained during and after a 2-min supra systolic arm-cuff occlusion-induced reactive hyperaemia procedure. As a part of this study, the Doppler ultrasound hyperaemic, low-frequency, blood velocity of radial artery and a fingertip DTM of vascular function were compared simultaneously. Postcuff deflation temperature rebound and area under the curve, DTM indices of vascular function, were studied. RESULTS: Temperature rebound area under the curve correlated closely with Doppler hyperaemic, low-frequency, blood velocity (r = 0·97, P = 0·0001). Day-to-day intra-subject variability was 6·2% for baseline temperature, 8·7% for mean blood pressure and 11·4% for heart rate. The coefficient of repeatability of temperature rebound and area under the curve were 2·4% and 2·8%. CONCLUSION: In a controlled environment, the repeatability of DTM is excellent. DTM can be used as a reproducible and operator-independent test for non-invasive measurement of vascular function.

Use of temperature alterations to characterize vascular reactivity.

Monitoring alterations in fingertip temperature during ischaemia and the subsequent hyperaemia provides a novel way of studying microvascular reactivity. The relations between parameters characterizing blood perfusion and the thermal response of fingertips were studied using experimental and theoretical approaches. During the experimental protocol, two brachial artery occlusion tests were conducted in 12 healthy volunteers, and fingertip temperature, heat flux and skin perfusion using laser Doppler flowmetry (LDF) were measured. The temperature curves provide a smooth and robust response that is able to capture occlusion and reperfusion. The temperature fall during occlusion as well as the maximum temperature recorded depended linearly on the initial temperature. The magnitude of the LDF signal was associated with local tissue temperature and followed an exponential response. Heat flux measurements demonstrated rapid changes and followed variations in blood perfusion closely. The time points at which the heat flux reached its maximum corresponded to the time at which the fingertip temperature curves showed an inflection point after cuff release. The time required for the fingertip temperature to arrive at the maximum temperature was greater than the time to peak for the heat flux signal, which was greater than the LDF signal to reach a maximum. The time lag between these signals was a function of the finger size and finger temperature at the moment reperfusion restarted. Our present results indicate that finger temperature, heat flux and perfusion display varying rates of recovery following ischaemic stimuli and that differential responses are associated with the initial finger temperature.

Sensitivity of digital thermal monitoring parameters to reactive hyperemia.

Both structural and functional evaluations of the endothelium exist in order to diagnose cardiovascular disease (CVD) in its asymptomatic stages. Vascular reactivity, a functional evaluation of the endothelium in response to factors such as occlusion, cold, and stress, in addition to plasma markers, is the most widely accepted test and has been found to be a better predictor of the health of the endothelium than structural assessment tools such as coronary calcium scores or carotid intima-media thickness. Among the vascular reactivity assessment techniques available, digital thermal monitoring (DTM) is a noninvasive technique that measures the recovery of fingertip temperature after 2-5 min of brachial occlusion. On release of occlusion, the finger temperature responds to the amount of blood flow rate overshoot referred to as reactive hyperemia (RH), which has been shown to correlate with vascular health. Recent clinical trials have confirmed the potential importance of DTM as an early stage predictor of CVD. Numerical simulations of a finger were carried out to establish the relationship between DTM and RH. The model finger consisted of essential components including bone, tissue, major blood vessels (macrovasculature), skin, and microvasculature. The macrovasculature was represented by a pair of arteries and veins, while the microvasculature was represented by a porous medium. The time-dependent Navier-Stokes and energy equations were numerically solved to describe the temperature distribution in and around the finger. The blood flow waveform postocclusion, an input to the numerical model, was modeled as an instantaneous overshoot in flow rate (RH) followed by an exponential decay back to baseline flow rate. Simulation results were similar to clinically measured fingertip temperature profiles in terms of basic shape, temperature variations, and time delays at time scales associated with both heat conduction and blood perfusion. The DTM parameters currently in clinical use were evaluated and their sensitivity to RH was established. Among the parameters presented, temperature rebound (TR) was shown to have the best correlation with the level of RH with good sensitivity for the range of flow rates studied. It was shown that both TR and the equilibrium start temperature (representing the baseline flow rate) are necessary to identify the amount of RH and, thus, to establish criteria for predicting the state of specific patient's cardiovascular health.

Digital thermal monitoring (DTM) of vascular reactivity closely correlates with Doppler flow velocity.

The noninvasive measurement of peripheral vascular reactivity, as an indicator of vascular function, provides a valuable tool for cardiovascular screening of at-risk populations. Practical and economical considerations demand that such a test be low-cost and simple to use. To this end, it is advantageous to substitute digital thermal monitoring (DTM) for the more costly and complex Doppler system commonly used for this measurement. A signal processing model was developed to establish the basis for the relationship between finger temperature reactivity and blood flow reactivity following a transient brachial artery occlusion and reperfusion protocol (reactive hyperemia). Flow velocity signals were acquired from the radial artery of human subjects via an 8 MHz Doppler probe while simultaneous DTM signals were acquired from a distal fingertip via DTM sensors. The model transforms the DTM temperature signals into normalized flow signals via a deconvolution method which employs an exponential impulse function. The DTM normalized flow signals were compared to simultaneous, low-frequency, normalized flow signals computed from Doppler sensors. The normalized flow signals, derived from DTM and Doppler sensors, were found to yield similar reactivity responses during reperfusion. The reactivity areas derived from DTM and Doppler sensors, indicative of hyperemic volumes, were found to be within +/- 15%. In conclusion, this signal processing model provides a means to measure vascular reactivity using DTM sensors, that is equivalent to that obtained by more complex Doppler systems.

Vascular function measured by fingertip thermal reactivity is impaired in patients with metabolic syndrome and diabetes mellitus.

Digital thermal monitoring (DTM) of vascular function has already been shown to correlate well with coronary artery calcium (CAC) score and coronary artery disease. To determine its utility in the metabolic syndrome (MS) and diabetes mellitus (DM), 233 asymptomatic patients with DM/MS but without coronary artery disease underwent DTM during and after 5 minutes of supra-systolic arm cuff inflation, as well as CAC. Post-cuff deflation adjusted temperature rebound (aTR) was lower in MS and DM compared with the normal group. The odds ratio of lowest vs upper 2 tertiles of aTR was 2.3 for MS and 3.5 for DM compared with the normal group, independent of age, sex, and risk factors. The area under the receiver operating characteristic curve to predict CAC > or =100 was 0.69 for metabolic status (DM/MS), 0.79 for aTR, and 0.87 for both. This study demonstrates that vascular dysfunction measured by DTM is associated with DM/MS and could potentially be used to detect asymptomatic individuals with increased subclinical atherosclerosis.