2018-08-012024-05-18https://scholars.lib.ntu.edu.tw/handle/123456789/703392皮膚軟組織感染是一常見的感染性疾病，且因抗藥性細菌的增加，近年內因複雜性軟組織感染就診或住院的人次，在各國均有逐年增加的趨勢。根據美國感染症學會於2014制定之皮膚軟組織感染治療指引(Infectious Diseases Society of America (IDSA))，一般臨床診斷方法，是以患處之紅、腫、熱、痛等理學檢查來進行診斷。在觸診時會利用雙手觸摸患部與其鏡像解剖構造之對側位置，比較其溫度或腫脹程度之差異程度，加上白血球計數(WBC)、C-反應蛋白(CRP)等實驗數據之結果，及MRI影像作為參考依據。然而追蹤與評估複雜性軟組織感染治療療效的關鍵，在於需要量化指標以描述治療療效之變化。而目前的現況是許多臨床診斷評估之判讀標準難以量化，其主要原因如下：(1)很難達成前後差異的比較(intra-rater bias)；(2)很難達到良好的一致性(inter-rater bias)；(3)過於主觀性。雖然臨床評估指標如發炎指數、白血球數可以量化，但無法作為終止治療單一的指標。而MRI雖為建議之參考標準，但其價格昂貴且具有潛在腎毒性之風險，不適合用於密集追蹤治療療效之評估。因此本計畫提出建構複雜性軟組織感染性疾病之遠紅外線診斷系統，藉由量化感染區域於治療過程中之熱變化以評估其治療療效，且與MRI比較驗證。此一紅外線診斷系統之關鍵，在於針對患處相同區域(小至一個像素，大至一整片之患處)進行多時間點紅外線熱影像量化分析。然而患處溫度之改變除受到感染之影響外，人體生理因素亦會造成病患基準體溫之浮動；不同時間點所拍攝之紅外線熱影像也會因為不同拍攝角度、姿勢等問題，造成紅外線熱圖譜(Heat pattern)之壓縮與形變，而使得於每一單時間點(Cross-sectional)所觀察之區域範圍並非一致。因此本計畫為了克服上述這些問題，必須發展多時間序列之紅外線熱影像溫度正規化，以及多時間序列之紅外線熱影像對位。但由於多時間序列複雜性軟組織感染的紅外線熱影像，並無足夠且持續存在之特徵資訊可用於多時間序列之對位；且紅外線熱影像與MRI影像間亦無可用來對位之依據，以進行後續之比較驗證。因此為了克服其無法對位之困難，本計畫提出以三維掃描影像為關鍵之核心技術，利用三維掃描影像作為媒介，以解決多時間序列之紅外線熱影像對位，以及多時間序列之紅外線熱影像與MRI影像序列影像間對位之困難Skin and soft tissue infection (SSTI) is a major infectious disease and leads not only to increasing medical cost, but also tremendous morbidity and mortality among the patients. According to the latest Infectious Diseases Society of America (IDSA) guideline for SSTI, the diagnosis is mainly based on physical examination of infected site with the local heat, redness, swelling, and pain. The laboratory tests can include white blood cell count (WBC) and C-reactive protein (CRP). The Magnetic Resonance Imaging (MRI) will be considered if deep site infection is suspected as a diagnostic or follow-up tool. However, the longitudinal follow up of treatment outcome of SSTI is usually difficult. The reasons include: 1) intra-rater bias; 2) poor consistency if interpreted by different physicians (inter-rater bias); 3) the local infection signs are subjective and hard to be quantified. Even though WBC and CRP can be quantified, they are usually returned to normal range after initial antibiotics treatment and can’t be relied as a single marker to determine treatment duration. For MRI, the evaluation tool suggested by guideline, it may not be available for every hospitals, costly, and still carries the risk for nephrotoxicity. Thus, it may not be suitable as a continuous monitoring tool. Thus, we aim to propose an infrared thermometer system to evaluate the treatment response of SSTI. By quantify the longitudinal change of local temperature, we may provide a non-invasive, portable, and quantified evaluation tool and correlated the finding with the traditional gold standard, such as MRI.The technical threshold of infrared diagnostic system include the methods to objectively define infected site, quantify temperature change and adjust the effects from normal human anatomy (the bony surface or the distribution of artery or veins). The extension of a cross-sectional finding to comparable longitudinal observations also need to conquer the effects by different position of the patients and the observer with time.To overcome the above possible technique gaps, the two-year study aims to develop the infrared system for longitudinal observation and compare with MRI findings. We propose 3D scan as a core technique to link the longitudinal infrared image with serial change of MRI signal. The pilot studies will enroll patients with SSTI in the lower extremities in a tertiary care hospital. The specific study process include:1. Development of transfer registration algorithm on longitudinal infrared images■Development of registration algorithm on longitudinal 3D surface image■Deformation and registration of 2D infrared thermal image and longitudinal 3D surface image2. Quantification analysis algorithm of longitudinal infrared image■Normalization of 2D longitudinal infrared image■Quantification analysis of infection severity on infrared image3. Image fusion algorithm of 2D infrared image and 3D MRI■Registration of 3D surface image and corresponded MRI4. Quantification analysis algorithm of MRI■Registration of longitudinal 3D MRI5. Quantification analysis of infection severity on MRI6. Validation of the infrared quantification index with currently available clinical infection evaluation methods