Assessment of Acute Pulmonary Embolism by Computer-Aided Technique: A Reliability Study

被引:5
作者
Sun, Zhen-Ting [1 ]
Hao, Fen-E [1 ]
Guo, You-Min [2 ]
Liu, Ai-Shi [1 ]
Zhao, Lei [1 ]
机构
[1] Inner Mongolia Med Univ, Dept Radiol, Affiliated Hosp, Hohhot, Inner Mongolia, Peoples R China
[2] Xi An Jiao Tong Univ, Dept Radiol, Affiliated Hosp 1, Xian, Shaanxi, Peoples R China
来源
MEDICAL SCIENCE MONITOR | 2020年 / 26卷
关键词
Angiography; Pulmonary Embolism; Tomography; X-Ray Computed; RIGHT-VENTRICULAR DYSFUNCTION; ASSISTED DETECTION PROTOTYPE; TOMOGRAPHY; DIAGNOSIS; ANGIOGRAPHY; PERFORMANCE; BURDEN;
D O I
10.12659/MSM.920239
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Background: Acute pulmonary embolism is one of the most common cardiovascular diseases. Computer-aided technique is widely used in chest imaging, especially for assessing pulmonary embolism. The reliability and quantitative analyses of computer-aided technique are necessary. This study aimed to evaluate the reliability of geometry-based computer-aided detection and quantification for emboli morphology and severity of acute pulmonary embolism. Material/Methods: Thirty patients suspected of acute pulmonary embolism were analyzed by both manual and computer-aided interpretation of vascular obstruction index and computer-aided measurements of emboli quantitative parameters. The reliability of Qanadli and Mastora scores was analyzed using computer-aided and manual interpretation. Results: The time costs of manual and computer-aided interpretation were statistically different (374.90 +/- 150.16 ver- sus 121.07 +/- 51.76, P<0.001). The difference between the computer-aided and manual interpretation of Qanadli score was 1.83 +/- 2.19, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (intraclass correlation coefficient, ICC=0.998). The difference between the computer-aided and manual interpretation of Mastora score was 1.46 +/- 1.62, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (ICC=0.997). The emboli quantitative parameters were moderately correlated with the Qanadli and Mastora scores (all P<0.001). Conclusions: Computer-aided technique could reduce the time costs, improve the and reliability of vascular obstruction index and provided additional quantitative parameters for disease assessment.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Improved Accuracy of Pulmonary Embolism Computer-Aided Detection Using Iterative Reconstruction Compared With Filtered Back Projection
    Lahiji, Kian
    Kligerman, Seth
    Jeudy, Jean
    White, Charles
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2014, 203 (04) : 763 - 771
  • [2] Computer-aided detection for the automated evaluation of pulmonary embolism
    Li, Yan
    Dai, Yongliang
    Deng, Lei
    Yu, Nan
    Guo, Youmin
    TECHNOLOGY AND HEALTH CARE, 2017, 25 : S135 - S142
  • [3] Missed Pulmonary Emboli on CT Angiography: Assessment With Pulmonary Embolism-Computer-Aided Detection
    Kligerman, Seth J.
    Lahiji, Kian
    Galvin, Jeffrey R.
    Stokum, Carly
    White, Charles S.
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2014, 202 (01) : 65 - 73
  • [4] Influence of spectral detector CT based monoenergetic images on the computer-aided detection of pulmonary artery embolism
    Kroeger, Jan Robert
    Hickethier, Tilman
    Pahn, Gregor
    Gerhardt, Felix
    Maintz, David
    Bunck, Alexander C.
    EUROPEAN JOURNAL OF RADIOLOGY, 2017, 95 : 242 - 248
  • [5] Impact of Image Quality on the Performance of Computer-Aided Detection of Pulmonary Embolism
    Wittenberg, Rianne
    Peters, Joost F.
    Sonnemans, Jeroen J.
    Bipat, Shandra
    Prokop, Mathias
    Schaefer-Prokop, Cornelia M.
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2011, 196 (01) : 95 - 101
  • [6] Seeking an optimal approach for Computer-aided Diagnosis of Pulmonary Embolism
    Ul Islam, Nahid
    Zhou, Zongwei
    Gehlot, Shiv
    Gotway, Michael B.
    Liang, Jianming
    MEDICAL IMAGE ANALYSIS, 2024, 91
  • [7] Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection
    Ul Islam, Nahid
    Gehlot, Shiv
    Zhou, Zongwei
    Gotway, Michael B.
    Liang, Jianming
    MACHINE LEARNING IN MEDICAL IMAGING, MLMI 2021, 2021, 12966 : 692 - 702
  • [8] Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers?
    Blackmon, Kevin N.
    Florin, Charles
    Bogoni, Luca
    McCain, Joshua W.
    Koonce, James D.
    Lee, Heon
    Bastarrika, Gorka
    Thilo, Christian
    Costello, Philip
    Salganicoff, Marcos
    Schoepf, U. Joseph
    EUROPEAN RADIOLOGY, 2011, 21 (06) : 1214 - 1223
  • [9] Evaluation of computer-aided detection and dual energy software in detection of peripheral pulmonary embolism on dual-energy pulmonary CT angiography
    Lee, Choong Wook
    Seo, Joon Beom
    Song, Jae-Woo
    Kim, Mi-Young
    Lee, Ha Young
    Park, Yang Shin
    Chae, Eun Jin
    Jang, Yu Mi
    Kim, Namkug
    Krauss, Bernard
    EUROPEAN RADIOLOGY, 2011, 21 (01) : 54 - 62
  • [10] Robustness evaluation of a computer-aided detection system for pulmonary embolism (PE) in CTPA using independent test set from multiple institutions
    Zhou, Chuan
    Chan, Heang-Ping
    Chughtai, Aamer
    Kuriakose, Jean W.
    Kazerooni, Ella A.
    Hadjiiski, Lubomir M.
    Wei, Jun
    Patel, Smita
    MEDICAL IMAGING 2015: COMPUTER-AIDED DIAGNOSIS, 2015, 9414