游離皮瓣即時監測系統：基於可見光影像之術後血管阻塞偵測演算法

Abstract

口腔癌是現今發生率及死亡率成長速度最快的癌症，其死亡人數在兩性的癌症十大死因中已經竄升至第五位。對於口腔癌的病患而言，進行手術切除病灶即為現今最主要的治療方式，而面對此類因口腔癌腫瘤切除造成顏面部位組織缺損而受影響的病患，臨床上行之有年又可靠的重建手術即為游離皮瓣手術。目前游離皮瓣手術移植成功的機率已可達到九成以上，然而，仍有少數皮瓣在手術後一周內出現血循障礙。在發生阻塞的案例中，於手術後二十四小時內發生阻塞的比例更高達八成，加上自發生阻塞到執行再次手術的時間間隔越長，就會大幅提高第二次手術的失敗機率，因此術後監控就顯得十分重要。 目前臨床上所採用的常規監控方式不僅缺乏客觀的診斷條件，對醫護人員而言更是非常大的負載。現今較客觀的方式如：手持都卜勒探測器、植入式都卜勒探測系統及微透析等，卻可能因其具侵入性或是與患處的直接接觸造成患處有二次感染的風險，甚至可能因耗材昂貴而有所限制。因此臨床上仍缺少一能夠有效進行游離皮瓣術後監控的系統。 為解決上述問題，考量到皮瓣在發生阻塞時可能會有發紫腫脹等現象，加上護理人員每隔一段時間便會替病患進行翻身或是調整病房內燈光，本研究開發了一建立在一以機器手臂內建的可見光相機為監控主體的監控系統上之演算法。透過扣除經由皮瓣及周圍正常組織以因素分析演算法所估計出的環境光線因素，取得皮瓣真實的色彩變化，進而以此偵測皮瓣可能發生血管阻塞的時間，達到監測皮瓣手術後血管阻塞情況的目的。本研究也設計了驗證實驗、動物實驗及臨床試驗以驗證其有效性，以上影像材料之蒐集過程皆通過台北榮總動物實驗及臨床試驗之審核。 驗證實驗建立在一室內光源有變動的環境中，實驗過程會隨時間改變觀察目標區域的色彩，透過其結果可得知本研究所發展之因素分析演算法具有消除室內燈光以及其餘環境光線因子對於皮膚色彩觀察的影響之潛力。而動物實驗在控制環境光源並模擬血管阻塞的情況下進行，其與臨床試驗的資料經分析後之結果則顯示，無論動脈或是靜脈發生阻塞時，皆能透過可見光影像觀察出皮瓣表面所發生的色彩變化，且根據Red、Green、Blue三者之間的相對變化差異，亦可區分出動脈與靜脈阻塞，進而達到監控皮瓣手術後血管阻塞之目的。然而由於目前臨床試驗中僅有一例阻塞的案例可循，因此未來若能提供更多的病患資料進行分析，進而驗證並建立更加完善的偵測演算法，本研究將有望成為臨床上輔助監控皮瓣血管阻塞的重要工具之一。

Oral cancer is a disease with the fastest growing of mortality rate currently which ranks the fifth place among the top ten causes of cancer in both genders. For the patients with oral cancer, surgical resection of the lesion is the most important treatment. The free flap surgery is a reliable and important reconstruction method for the patients which has been followed for years, and the success rate of it can achieve more than 90%. However, there are still several flaps having circulatory compromise after surgery, and the success rate of reoperation will become lower with the belated detection of circulatory compromise. Therefore, the free flap monitoring is very important for early detection of circulatory compromise. The clinical monitoring for circulatory compromise is not objective enough and is undoubtedly a great loading of medical staffs. Other monitoring methods such as Handheld Doppler, Implantable Doppler Probes, and Microdialysis have their limitations like invasive, contact with flap or high-cost, etc. Therefore, an effective system for monitoring flap pedicle thrombosis after free flap surgery is desirable currently. In order to solve the problem above, this study developed an algorithm based on a monitoring system of a robot arm with visible light camera to monitor the color change when the flap having circulatory compromise. After the elimination of common factor, estimated by our factor analysis algorithm, between the flap and surrounding normal tissue, the real color change of the flap will be obtained and can be used to detect the occurrence of circulatory compromise. And three experiments, including a verification experiment, an animal experiments and a clinical trial, were designed to verify the utility of our algorithm. Based on the results of the verification experiment, we can tell that our algorithm has the potential to eliminate the influence of the surrounding illumination or other light factors during the skin color observation. The results of animal experiments and clinical trials show that the color change of the surface of flap with arterial occlusion and venous occlusion can be observed respectively. It is also possible to distinguish arterial and venous occlusion according to the difference of color change between Red, Green and Blue to achieve the purpose of monitoring. Therefore this study may become one of the important tools for the monitoring after free flap surgery if we can have more clinical data to verify and establish a more complete algorithm.