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DEVELOPMENT OF A NONINVASIVE OPTICAL AND THERMOGRAPHIC IMAGING PROTOCOL FOR IDENTIFICATION OF PEDIATRIC LOW CARDIAC OUTPUT

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Secondly, I would like to acknowledge and thank my family for their love and care during the pursuit of my education. Finally, I would like to thank my partner, Joshua, for never failing to believe in me and being my rock throughout my college years.

Congenital Heart Disease

Although congenital heart disease can present in various forms of defects and in their combinations, milder lesions are the most commonly reported form of CHD at birth. In fact, the number of newborns and infants requiring surgery increased from 26% to just over 40% in the early 2000s alone.

Fig. 1: Birth Prevalence of CHD Subtypes. The birth prevalence of CHD subtypes and their changes over time
Fig. 1: Birth Prevalence of CHD Subtypes. The birth prevalence of CHD subtypes and their changes over time

Low Cardiac Output Syndrome

  • Motivation
  • Clinical Presentation and Diagnosis
  • Etiology of LCOS
  • Risk Factors for LCOS
  • Postoperative Management of LCOS
  • Hemodynamic Monitoring
  • Core-Peripheral Temperature Gradients

CO is a measure of cardiac function because it is affected by cardiac preload, afterload, and contractility: factors that cause changes in blood pressure and stroke volume that promote end-organ perfusion [11]. One of the biggest sources for the development of LCOS is the heart repair process itself that uses CPB.

Fig. 2: Correlation between cardiac index and toe temperature, 100 sequential points, modified from [48]
Fig. 2: Correlation between cardiac index and toe temperature, 100 sequential points, modified from [48]

Medical Thermography

The camera detector measures the amount of spectral emission at each spatial position within its field of view and converts the radiation into temperature values ​​at each pixel in the acquired image. The resulting image, called a thermogram, describes the temperature recorded at each pixel in the image. Since the technique is non-invasive, non-contact, fast, harmless and can monitor large areas simultaneously, medical thermography has been widely used to correlate thermal trends with clinical pathologies and diseases [56].

Medical thermography has been used to study the relationship between skin temperature and blood pressure, oxygen saturation, identification of tumors and lesions, orthopedic injuries, diabetic pathologies, rheumatic diseases, and to monitor critically ill and dying patients. The accuracy of medical thermography has been extensively studied and found to be closely correlated with invasive thermal monitoring methods [61]. When examining neonatal and infant populations, medical thermography is particularly advantageous in considering their physiology.

Given that circulation is the primary mechanism of heat transfer in the body, investigations of thermal trends in the pediatric population can provide accurate and immediate assessment of circulatory status and document when circulation is abnormally disturbed [54 ].

Objectives and Aims

Under the guidance of the research team, potential candidates for the study were identified using the inclusion criteria outlined in the protocol. The selection of the six ROIs was consistent with the core and peripheral definitions in the literature (see Chapter I). Once the warm-up condition began, the subject's core temperature steadily increased to approximately 33°C during the first 6 h of the recovery period.

Cardiac output was also different between both cases at the time of the reported event in Case 2. Kirsch, “Management of the Low Cardiac Output Syndrome Following Surgery for Congenital Heart Disease,” Curr. In the PRIMACORP trial, Hoffman et al. specifically defined LCOS as a constellation of the following clinical features:.

In 2012, Children's Hospital was recognized as one of the best children's hospitals in the country by the U.S.

THERMOGRAPHIC QUANTIFICATION PROTOCOL

Clinical Study Deployment

The second aim of the study was to preliminarily determine whether thermographic imaging provides additional diagnostic information for potential inclusion in standard clinical practice. The imaging procedure generated thermographs, or heat maps, of the patient's body temperature over time. The tablet system is mounted above the horizontal plane of the hospital bed by attaching to a Stryker articulating arm system (Fig. 3).

In the beginning of the study, thermograph images included the entire uncovered body of the patient to provide an anatomical reference for image registration and processing techniques. After initial imaging, a minimum of one arm and/or one leg remained exposed to the camera system, but the patient was otherwise covered for the remainder of the study. At the end of the 24-hour observation period, the system was turned off and the PI safely downloaded the study images and relevant clinical information.

Study personnel informed clinical staff about the study and provided a protocol to immediate care staff (Appendix C) before the system was activated.

Fig. 3: Coupled Imaging System Mount
Fig. 3: Coupled Imaging System Mount

Processing Software

Software Procedure

  • Vital Data Entry
  • Image Conversion
  • Image Quality
  • Image Registration and Segmentation
  • Post Analysis Processing Methods

The basis of the image quality index procedure was rooted in the identification of the six primary regions of interest (ROI) for thermographic analysis. Normalization of core temperature to 32-34°C within the first six hours is expected in normal recovery profiles. While the peripheral hand temperatures fluctuated more at the beginning of the study, the peripheral foot temperatures increased steadily from 26 to 28°C during the first 6 hours.

However, by the 3-hour mark, CPTG had decreased and generally did not exceed 5°C by the end of the recovery period. Surprisingly, CO was 35% below its mean value by the time the event was reported. Notably, the drop in peripheral arm temperature during the first 2 hours of the study preceded and was greater than the change in core temperature in case 2.

The change in trend was caused by the continued decline in core temperature in this patient and the plateau of peripheral temperature, resulting in a decreasing difference between core and peripheral temperatures.

Table 2: List of Recorded Vital Values  Recorded Vital Value
Table 2: List of Recorded Vital Values Recorded Vital Value

CASE ANALYSIS AND DISCUSSION

Pilot Study Analysis

  • Case 1: Background
  • Discussion

Following this procedure, the core-periphery gradient was expected to decrease during the first six hours of the study, and peripheral temperatures were expected to increase from baseline during the same time period (see Chapter I, Subsection 1.2.7). A moving average was calculated using a 50-point interval to estimate changes in trends in CO values, and the trend line shows these CO fluctuations during the recovery period. Similar to cardiac output, systemic vascular resistance (SVR) values ​​were outside the reference range, which may be a factor in the patient's exact age.

Therefore, the overall change in SVR throughout the study was considered a more accurate assessment of the degree of vasoconstriction. The patient's mean core temperature began to normalize over the course of the study and followed the predicted warming pattern as described by Matthews (Fig. 19) [50]. The gradient in this case was slightly elevated than the reference initially (CPTG ∼= 5°C at T = 2 H) and exhibited peak values ​​above 5°C in the first 2.5 h of postoperative recovery.

CPTG at the start of the study may have been slightly greater than expected, but may be related to the hypothermic temperature to which the subject was cooled during surgery.

Table 3: Observed and Calculated Hemodynamic Monitoring Values (Case 1)
Table 3: Observed and Calculated Hemodynamic Monitoring Values (Case 1)

Pilot Study Analysis

  • Case 2: Background
  • Discussion

Additional hemodynamic assessment revealed that systolic, diastolic, and mean arterial pressures were each about 15% lower than their mean value at the time of the reported event, indicating a decrease in the patient's stroke volume. CVPm also rose during this time point and was at the upper end of the reference range and reflected the decrease in CO. Therefore, analysis of thermographic trends for this patient was considered a high priority to decipher whether significant changes in temperature preceded the dramatic change in hemodynamic values ​​observed at the 3-hour mark.

Core temperature continued to decrease over the next hour until the time of the reported event at the 3-hour time point, which is not expected in normal postoperative heating patterns. Pickering, "The Use of Central and Peripheral Temperature Measurements in the Care of the Critically Ill Child," Arch. Perfusion and cardiac output will be considered normal as the slope of the temperature difference at the extremity of the postoperative subject mirrors that of age-matched normal controls.

Lieberman, E.H., et al., Flow-induced vasodilation of the human brachial artery is impaired in patients <40 years with coronary artery disease.

Table 4: Observed and Calculated Hemodynamic Monitoring Values (Case 2)
Table 4: Observed and Calculated Hemodynamic Monitoring Values (Case 2)

CONCLUSIONS AND FUTURE WORK

Conclusions

Overall, the presented work has fulfilled the two main objectives of establishing a thermal quantification protocol and initial analysis of suitable case studies. Developing the thermal quantification protocol took considerable effort to ensure that it was dynamic enough to analyze different types of case studies, which is particularly challenging in an acute care clinical setting. The health, safety and comfort of patients is a top priority when conducting these clinical studies; therefore, discontinuities in study observations and incomplete data sets are expected and motivate the need for additional case analyses.

I also created extensive documentation to ensure thermographic analysis remained consistent between operators and in compliance with IRB standards. Initial analysis of both case studies shows promise for monitoring thermographic trends in a susceptible pediatric population and the differences observed between “normal” and.

Future Work

Dong, “Analysis of risk factors of low cardiac output after surgery for congenital heart disease: what can we do,” J. Du et al., “Risk factors for low cardiac output in children with congenital heart disease undergoing cardiac surgery: a retrospective cohort study”, BMC Pediatr., vol. Hoffman et al., “Efficacy and safety of milrinone in preventing low cardiac output in infants and children after corrective surgery for congenital heart disease,” Circulation, vol.

Zimmerman, “An elevated low cardiac output syndrome score is associated with morbidity in infants after congenital heart surgery,” Pediatr. Cavigelli-Brunner et al., "Prevention of Low Cardiac Output Syndrome After Pediatric Cardiac Surgery: A Double-Blind Randomized Clinical Pilot Study Comparing Dobutamine and Milrinone." Pedro, “Cellular and molecular mechanisms of low cardiac output syndrome after pediatric cardiac surgery,” Curr.

Weil, "Temperature of the Big Toe as an Indicator of Severity of Shock," Circulation, vol. The slope of the model will represent the normal variation in temperature across and extreme from central to peripheral. Conversely, perfusion and cardiac output will be considered impaired (ie, LCOS) as the slope of the temperature difference across the extremity of the post-operative subject increases above that of similar age-matched normal controls.

Fig. 28: Cycle Tracker Report Card
Fig. 28: Cycle Tracker Report Card

Gambar

Fig. 1: Birth Prevalence of CHD Subtypes. The birth prevalence of CHD subtypes and their changes over time
Fig. 2: Correlation between cardiac index and toe temperature, 100 sequential points, modified from [48]
Fig. 3: Coupled Imaging System Mount
Fig. 4: Clinical Deployment of Coupled Imaging System
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Abbreviations The following abbreviations are used in this manuscript: ADC apparent diffusion coefficient AFP alpha fetoprotein AI artificial intelligence ANN artificial neural