| Summary: | 碩士 === 國立臺灣大學 === 醫學工程學研究所 === 106 === One of the most common cancer with the highest mortality rate is Oral cancer. The most frequently adopted approach of curative treatment of oral cancer is by resecting cancer legions and reconstructing the affected regions by unaffected tissues of the patient. Free flap surgery is a reliable reconstruction method operated by many medical professionals. However, circulatory compromises were sometimes observed within five to seven days after surgeries, even if the operations were performed by experienced microvascular surgeons. Furthermore, research shows that that the success rate of surgeries diminishes due to late detection of circulatory compromises. Therefore, monitoring and early detection of circulatory compromises signs are crucial to the free flap surgery.
At present, clinical free flap care and monitoring are performed mainly through scheduled inspections by nursing staff. The caring process is labor-intensive and the success rate of detection varies owing to subjective judgement and experiences of carers. Other available methods of monitoring includes the continuity usage of monitor systems, which are invasive and incur higher cost. It is noticeable that an alternative method of monitoring is imminent.
Therefore, previous scholars suggested infrared imaging as an alternative method to current monitoring for its inexpensive, non-invasive, non-contacting, non-radioactive, real-time, and repeatable features. Through the Factor Analysis algorithm, it could effectively remove the common factors of human physiology and observe the changes of real temperature. However, the method does not apply in more complex situations. If the estimation of common factors is not a linear combination of all factors but one factor occurs after another, the Factor analysis algorithms is unable to segregate the factors. Because if the estimated of the common factor is not a linear combination of all factors, but a certain factor occurs first and then a factor occurs later, then Factors Analysis algorithms can''t separate them.
Therefore, based on theoretical basis of prior researches, this study aimed to analyze the unique features of the observed signals by using the Independent Component Analysis algorithms for its flexibility. Plus, the factors could not be easily explained by the Factor Analysis algorithm. Through the advantages and capabilities of the Independent Component Analysis algorithm, the study hope to propouse a temperature variation detection algorithm that is more suitable for the Infrared thermography monitoring system for microvascular free flap after surgery. Out of the four animal experiments and twenty-three cases monitored in the study, only one patient developed venous thrombosis. Through the Factors Analysis algorithm, we found that the temperature of the free flap had significantly decreased. According to the results of the Independent Component Analysis algorithm, we found that there was two independent factors that may affect the temperature of the free flap region. One of the independent factors could detect the drop of the temperature earlier than the result of the factor analysis, and the other is the same as the result of the Factor Analysis. Both of the results showed the potential of early detection in temperature changes comparing to nursing records.
However, due to the limitation of sampling, the study was unable to provide further verifications and discussions. It is hoped that more data will be available in the future to support the aim analytical methods. The goal of this study it to setup a foundation in the development of an auxiliary monitoring tool to monitor free flap pedicel thrombosis after a lesion removal surgery.
|
|---|
