| Summary: | 碩士 === 國立臺灣大學 === 醫學工程學研究所 === 106 === Oral cancer is the fastest growing cancer in mortality rate in Taiwan. The most prevalent curative treatment of oral cancer exploits a multi-step approach starting with the resection of lesions. After the removal of cancer lesions, surgeons would employ unaffected tissues of the patients to reconstruct the affected regions. Free flap surgery is a reliable reconstruction method operated by many medical professionals. However, circulatory compromises were sometimes observed within five to seven days of surgeries, even when the operations were performed by experienced microvascular surgeons. Furthermore, it is documented that the success rate of re-surgeries diminishes as the detection of circulatory compromises delays. Therefore, it is crucial to monitor and detect signs of circulatory compromises quickly after the free flap surgery.
At present, clinical free flap care and monitoring are performed mainly through scheduled inspections by nursing staff. This process is very labor-intensive and the success rate of detection varies greatly based on the opinions and experiences of the caregivers. Other currently available methods of monitoring, including the use of non-continuous monitoring systems, are invasive and incur higher costs. It is evident that an alternative method of monitoring is imminent.
Previous scholars proposed infrared imaging as an inexpensive, non-invasive, non-contact, non-radioactive, rapid, and repeatable alternative to current monitoring methods. It was proposed that the image registration can be accomplished by manually selecting features points and utilize both factor analysis and eigenvalue analysis to observe temperature variation. However, such process was hand-operated and relies heavily on technician experience and time-consuming. Detection of temperature changes in free flap was prone to errors in the factor analysis algorithm. This study aimed to resolve the disadvantages of the manual image registration process by introducing an automatic longitudinal infrared image registration algorithm and a flap temperature variation detection algorithm.
In this study, automatic longitudinal infrared image registration algorithm, utilizing the homography matrix coordinate transformation algorithm, was used to convert the free flap edge feature points detected under the visible light to infrared thermal images. After obtaining the infrared thermal image feature points, this study utilized non-rigid Coherence Point Drift (CPD) to calculate the corresponding relationship of the feature points. Using this relationship, the image registration was completed by affine transformation, so that the free flap regions at different time series were mapped together. After the registration, factor analysis was employed to analyze the temperature variation of free flaps to observe thrombosis.
Out of the ten clinical cases monitored by this study, one patient developed venous thrombosis. Analysis using the methods proposed by this study indicated a significant temperature decrease in the subject''s free flap. In comparison to nursing records, it was discovered that the methods proposed by this study had the potential to detect temperature changes earlier. However, due to the sample size limitation, this study was unable to provide further verification and discussion. It is hoped that more data will be available in the future to support the proposed analytical methods. The goal of this study it to setup a foundation in the development of an auxiliary monitoring tool to monitor free flap pedicle thrombosis after a lesion removal surgery.
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