定量型雙波段紅外線乳癌診斷系統之qH值與磁振造影正子掃瞄之SUV值關聯性分析

Correlation Analysis Between The qH Value of Quantitative Dual-Spectrum Infrared Breast Cancer System and The SUV Value of MR-PET Scan

李京燕(Ching-Yen Lee)

指導教授 ： 陳中明

國立臺灣大學/工學院/醫學工程學研究所/碩士(2019年)

https://doi.org/10.6342/NTU201900606

摘要

不論是台灣或歐美，乳癌是女性最常罹患的癌症之一，也是全球女性癌症死亡的主要原因之一[1]，根據台灣國民健康署資料顯示國內婦女癌症發生率第一位為乳癌，每年乳癌確診女性有數萬人，且超過2000名女性因乳癌喪失生命，因此乳癌及早發現診斷與適當的治療能夠積極緩解乳癌對女性的威脅，進而提升預後存活率，目前臨床醫學影像技術中，常用於第一線的乳癌偵測工具在偵測早期病灶與評估化療反應仍有困難。
近年來紅外線熱影像(Infrared thermography)的研究逐漸新起，因熱影像設備的開發以及熱生理與病理學相互關係的應用，加上非侵入性、非輻射、低成本、快速且能反覆成像等優勢，使得紅外線熱影像在醫學研究應用更廣泛。
基於雙波段紅外線影像(Dual-Spectrum Infrared Image)的前期研究，本實驗室已發展一套定量型雙波段紅外線乳癌診斷系統(Quantitative Dual-Spectrum Infrared system, QDS-IR system)用於偵測乳癌腫瘤與追蹤評估前導性化療(Neoadjuvant Chemotherapy)的腫瘤化療反應(chemotherapy response)，該系統是由硬體與軟體兩大部份的結合，硬體是結合紅外線(Infrared, IR)波長中的中波(波長為3-5 μm, MIR)與長波(波長為8-9.2 μm, LIR)兩個波段紅外線熱像儀同步擷取影像，為了有效運用與解釋紅外線影像中的資訊，軟體是由三個演算法組成，依序分別是1.無標記多時間點紅外線影像對位演算法(the marker-free longitudinal IR image registration alogrithm)、2.時間序列熱影像溫度正規化演算法(Longitudinal temperature normalization algorithm)與3.雙波段熱圖譜分離演算法(Dual-Spectrum Heat Pattern Separation algorithm, DS-HPS)。經由上述演算法先將不同時間的雙波段紅外線影像間所對應像素點建立相互關係，再考量內外因素(如受測者體表溫度與檢測環境因素)影響的雙波段時間序列影像進行溫度校正調控整體溫度到同一基準水平以及計算各個時間點的高溫組織區(NqH map)與基礎體溫組織區(NqN map)，獲得量化指標NqH[2,3,4]。
前期研究已初步證明QDS-IR system有潛力應用在前導性化療期間監控腫瘤的治療反應(chemotherapy response)，初步結果一，與解剖性影像之動態對比顯影核磁共振（DCE-MR）比較，紅外線影像訊號的分布與QDS-IR量化分析後高溫組織區(NqH map) 跟核磁共振的顯影區域有某些程度的關聯性，並且可偵測到乳房表皮下深度15mm至20mm的惡性腫瘤和鄰近血管資訊[2]。初步結果二，高溫組織區(NqH map)平均能量與功能性影像之正子斷層掃描（18F-FDG PET）的葡萄醣代謝變化半定量分析值(SUV)比較，兩者的變化趨勢隨著化療不同時間點有一定程度的關聯性[2]，更進一步指出QDS-IR的NqH map中qH_max與FDG-PET的SUVmax二者的變化趨勢隨化療期間具有高度相似，以∇qH_max 和△%SUVmax計算Fleiss’ kappa值為0.7[4]。
因為前期研究的MRI與PET是分開進行，二者影像上腫瘤定位有些微差異，而QDS-IR影像因拍照時是採取坐姿，乳房擺位與前兩影像亦不同，所以在圈選腫瘤範圍邊界不太容易界定，因此，本研究加入魚油作為腫瘤標記之用，並以磁振暨正子掃瞄同步整合系統（MR-PET system）取代MRI與PET分開進行掃描的情形；預期解決1.圈選腫瘤區域邊界的不確定性，2.影像之間存在的時間差與腫瘤相對位置的差異，時間差可能使得腫瘤受到療效影響產生不同之變化，MRI與PET合併系統後腫瘤相對位置更為接近；本實驗以有效樣本16例乳癌惡性腫瘤進行NqH_max分析，所有樣本在乳癌前導性化療期間的皆有三次MR-PET scan追蹤，QDS-IR拍照則是每個化療療程都有一次以上，最後評估與分析主要三個時間點(化療前、第二個療程後與手術前)的QDS-IR之qH值變化趨勢以及磁振暨正子掃瞄同步整合系統（MR-PET system）之SUV值變化量彼此之間的關聯性，利用qH值求得線性迴歸斜率∇qH_max，以∆%SUV_max表示不同時間之間SUVmax差值百分比，藉由∇qH_max與∆%SUV_max之參數運算，獲得Fleiss’ kappa為0.977 以及Gwet’s AC1值為0.906，都顯示NqH與SUVmax在化療期間的變化趨勢呈現高度一致性，希望進一步提升QDS-IR應用於化療反應評估之有效性與穩定性。

關鍵字

乳癌 ； 雙波段紅外線影像 ； 前導性化療 ； 高溫組織區(NqH map ； 正子斷層掃描 ； 半定量分析值 ； 磁振暨正子掃瞄同步整合系統

並列摘要

Breast cancer is one of the most common types of cancer among women in Taiwan, Europe, and the United States and is one of the leading causes of cancer deaths worldwide [1]. Current medical imaging techniques used for the first-line detection of breast cancer involve difficulties in the identification of early-stage lesions and evaluation of chemotherapy response.The application of infrared thermography in medical research has increasingly been adopted owing to the advancement of thermographic equipment and improved understanding of the application of the interrelations among thermal physiology and pathology. This technique affords advantages such as non-invasiveness, absence of ionizing radiation, low cost, and rapid and repeatable imaging.
On the basis of previous studies on dual-spectrum infrared imaging, our laboratory has developed a quantitative dual-spectrum infrared (QDS-IR) system for breast cancer diagnosis. The system can detect breast cancer tumors and provide the follow-up evaluation of tumor response to neoadjuvant chemotherapy; it is composed of hardware and software components. The hardware consists of dual-spectrum thermal imagers that can simultaneously capture images in mid-wavelength (MIR; 3–5 μm wavelength) and long-wavelength infrared (LIR; 8.0–9.2 μm wavelength) ranges. The software, which was designed for the effective utilization and interpretation of information contained in the infrared (IR) images, essentially entails the sequential execution of the following three algorithms: a marker-free longitudinal IR image registration algorithm; longitudinal temperature normalization algorithm; and dual-spectrum heat pattern separation algorithm (DS-HPS). These algorithms are first used to establish the interrelations among the pixels of the dual-spectrum IR images captured at different time instances. Subsequently, temperature correction is performed on the dual-spectrum time-series images that have been affected by internal and external factors (e.g., body surface temperature of the participant and detection environment) to adjust the overall temperature to the same baseline level. The tissue high-temperature map (NqH map) and tissue basal temperature map (NqN map) are then obtained for each time instance to obtain a quantitative indicator, NqH. [2]
Previous studies have demonstrated that the QDS-IR system can potentially be used to monitor the chemotherapy response of tumors during neoadjuvant chemotherapy. Their preliminary results showed that, as compared to anatomical images based on dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging, the distribution of IR imaging signals and the NqH maps obtained by the quantitative analysis of QDS-IR data are correlated to enhanced areas in the MRI. Furthermore, information on malignant tumors and adjacent blood vessels at 15–20 mm of depth beneath the breast epidermis can be detected. These studies have also shown that the trends of change between the average energy indicated by the NqH map and the semiquantitative measurement of glucose metabolic changes (i.e., standardized uptake value; SUV) are correlated over different time instances during chemotherapy, by using functional imaging based on 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) [2]. Furthermore, the results demonstrated a high degree of similarity between the trends of change in the qH_max value of the NqH map in QDS-IR and the SUVmax value of FDG-PET, yielding a Fleiss’ kappa of 0.7 between ∇q_(H_max)and△%SUVmax. [3]
The separation of MRI and PET scans in previous studies has led to slight variations in the detection of tumor locations between the two imaging modalities. Furthermore, QDS-IR imaging is conducted in a sitting position; therefore, a different breast placement from the previous two modalities is required. These differences have resulted in difficulties in delineating the boundary of the tumor. As a result, fish oil was added as a tumor marker in this study, and an integrated MR-PET system was adopted instead of individual MR and PET scans. These adaptations also resolve the following issues: uncertainties in delineating the boundary of tumor extent; and the temporal and spatial differences between the results of the imaging modalities. Temporal differences may lead to different changes in the tumor chemotherapy response detection. Moreover, the spatial difference in tumor locations between MRI and PET is reduced when an integrated system is employed. In this study, an NqH_max analysis was performed on 16 valid samples of malignant breast cancer tumors, which were monitored via MR-PET scans three times during the neoadjuvant chemotherapy for breast cancer. In addition, QDS-IR imaging was performed at least once during each course of chemotherapy. Finally, the correlation between the changes in qH of QDS-IR and the SUV of the integrated MR-PET system was evaluated and analyzed before chemotherapy, after the second course of chemotherapy, and before surgery. Afterward, by using qH to obtain the slope of the linear regression, ∇qH_max, and defining ∆%SUV_max as the percentage difference in SUVmax between different time instances, the parametric operation between ∇qH_max and ∆%SUV_max was applied, resulting in a Fleiss’ kappa of 0.977 and Gwet’s AC1 of 0.906. These values indicate a high agreement between the trends of NqH and SUVmax during chemotherapy; therefore, the validity and reliability of applying QDS-IR in the assessment of chemotherapy response can be further improved.

並列關鍵字

breast cancer ； dual-spectrum infrared imaging ； neoadjuvant chemotherapy ； tissue high-temperature map (NgH map) ； positron emission tomography (PET) ； semiquantitative standardized uptake value (SUV) ； integrated magnetic resonance-positron emission tomography (MR-PET) system

參考文獻

1. F. Bray, J. Ferlay, I. Soerjomataram, R. L. Siegel, L. A. Torre, and A. Jemal, "Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries," CA Cancer J Clin, vol. 68, no. 6, pp. 394-424, 2018, doi: 10.3322/caac.21492.

2. 簡鈺峻 (民100)。定量型雙波段紅外線乳癌診斷系統：與動態對比顯影磁振造影和正子斷層造影於乳癌化療反應效能監控成效上之比較。未出版之碩士論文，國立台灣大學醫學工程學研究所，台北市。

3. 陳中明、黃俊升、張允中、李奇恩、鄭瑋達、張芳懿 (民104)。萌芽個案計畫-雙波段紅外線乳房影像系統：化療反應監控。科技部補助專題研究計畫成果報告(編號：MOST 102-3011-P-002-011-)，未出版。

4. 陳中明等人 (民104)。整合型多波段紅外線/近紅外線乳房功能性影像系統之研發：雛型系統建構與乳癌偵測效能初步評估。科技部補助專題研究計畫成果報告(編號：MOST 103-2221-E-002-020-)，未出版。

5. 107年衛生福利年報。(民107年11月)。檢自 http://www.cdway.com.tw/gov/mhw2/book107/book1/ (Jun. 20, 2019)