Comparison of Automated 4D-Mspect and Visual Analysis for Evaluating Myocardial Perfusion in Coronary Artery Disease

比較自動化4D-MSPECT與目測法對於冠狀動脈疾病的心肌灌注分析

徐健欽(Chien-Chin Hsu) ； 陳毓雯(Yu-Wen Chen) ； 郝繼隆(Chi-Long Hao) ； 張雲德(Jun-Ted Chong) ； 李俊毅(Chun-I Lee) ； 陳孝棟(Hau-Tong Tan) ； 吳明昇(Ming-Sheng Wu) ； 吳榮州(Jung-Chou Wu)

《The Kaohsiung Journal of Medical Sciences》 24卷9期 (2008/09) Pp. 445-452

摘要

本研究的目的在於評估使用自動化電腦軟體(4D-MSPECT)來分析心肌灌注掃描對於冠狀動脈疾病診斷的可行性與可重複性，並且與專科醫師目測評估的結果做比較。本研究包含了60位未知冠狀動脈疾病的患者進行雙同位素心肌灌注掃描，並在三個月內進行心導管檢查。設定4D-MSPECT以17區5分法半定量分析心肌灌注掃描，產生自動總和壓力分數(A-SSS)、總和休息分數(A-SRS)和總和差異分數(A-SDS)。一位核醫科專科醫師分析兩次來評估同一觀察者間差異。另一位資深核醫放射師分析一次與核醫科專科醫師分析的結果來評估不同觀察者間差異。由兩位核醫科專科醫師採用同樣的17區5分法，經討論後一致的評分結果產生目測總和壓力分數(V-SSS)、總和休息分數(V-SRS)和總和差異分數(V-SDS)。我們發現不管是同一觀察者或是不同觀察者以4D-MSPECT進行自動半定量分析均呈現優異的一致性與相關性。目測與軟體自動化對於心臟區域的半定量評分結果呈現中等程度的一致性，總和分數則呈現高度的相關性。以ROC分析法分析V-SSS、V-SDS、A-SSS和A-SDS這四種分數對冠狀動脈疾病的診斷，曲線下面積分別為0.78±0.06、0.87±0.05、0.84±0.05和0.90±0.04，A-SDS對冠狀動脈疾病的診斷優於A-SSS和V-SSS，但A-SDS與V-SDS之間則沒有顯著的差異。如果用V-SDS大於等於2當作診斷冠狀動脈疾病的閾值，其靈敏度、特異度和正確率分別為83.1%、76.5%和81.7%，用A-SDS大於等於3當作診斷冠狀動脈疾病的閾值，其靈敏度、特異度和正確率則分別為79.1%、82.4%和80.0%。我們的結論是利用4D-MSPECT這個電腦軟體的自動化半定量分析心肌灌注掃描，對於冠狀動脈疾病的診斷具有高度的可重複性，而且與目測半定量分析的結果相當。

關鍵字

自動半定量分析 ； 冠狀動脈疾病 ； 4D-MSPECT ； 心肌灌注掃描 ； 目測半定量分析

並列摘要

The aim of this study was to assess the reproducibility and diagnostic performance for coronary artery disease (CAD) of an automated software package, 4D-MSPECT, and compare the results with a visual approach. We enrolled 60 patients without previously known CAD, who underwent dual-isotope rest Tl-201/stress Tc-99 m sestamibi myocardial perfusion imaging and subsequent coronary angiography within 3 months. The automated summed stress score (A-SSS), summed rest score (A-SRS) and summed difference score (A-SDS) were obtained using a 17-segment five-point scale model with 4D-MSPECT. For intraobserver and interobserver variability assessment, auto-mated scoring was done by a nuclear medicine physician twice and by a nuclear medicine technologist. The visual summed stress score (V-SSS), summed rest score (V-SRS), and summed difference score (V-SDS) were obtained by consensus of two nuclear medicine physicians. The intraobserver and interobserver agreements of automated segmental scores were excellent. The intraobserver and interobserver summed scores also correlated well. Agreements between visual and automated segmental scores were moderate (weighted of 0.55 and 0.50 for stress and rest images, respectively). Correlations between automated and visual summed scores were high, with correlation coefficients of 0.89, 0.85 and 0.82 for SSS, SRS and SDS, respectively (all p＜0.001). The receiver operating characteristic area under the curve for diagnosis of CAD by V-SSS, V-SDS, A-SSS and A-SDS were 0.780.06, 0.870.05, 0.840.05 and 0.900.04, respectively. A-SDS had better diagnos-ticperformance than A-SSS and V-SSS (p=0.043 and p=0.032, respectively), whereas there was no statistically significant difference between A-SDS and V-SDS (p=0.56). Using V-SDS2 as a diagnostic threshold, the sensitivity, specificity, and accuracy for CAD were 83.7%, 76.5% and 81.7%, respectively. Using A-SDS3 as a diagnostic threshold, the sensitivity, specificity, and accuracy for CAD were 79.1%, 82.4% and 80.0%, respectively. In conclusion, the reproducibility of automated semiquantitative analysis with 4D-MSPECT was excellent. The diagnostic performance of auto- mated semiquantitative analysis with 4D-MSPECT was comparable with the visual approach.

並列關鍵字

automated semiquantitative scoring ； coronary artery disease ； 4D-MSPECT ； myocardial perfusion imaging ； visual semiquantitative scoring