Quantitative MDCT analysis of pulmonary solid nodules using three parameters

被引:1
作者
Kutuya, Naoki [1 ]
Ozaki, Yutaka [1 ]
Kurosaki, Yoshihisa [1 ]
机构
[1] Juntendo Univ, Sch Med, Dept Radiol, Bunkyo Ku, Tokyo 1138421, Japan
来源
RADIATION MEDICINE | 2008年 / 26卷 / 07期
关键词
Pulmonary nodule; Computed tomography; Quantitative analysis;
D O I
10.1007/s11604-008-0246-7
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose. The purpose of this prospective study was to perform quantitative multidetector computed tomography (MDCT) analysis of pulmonary solid nodules using three parameters (long-short ratio, compactness, and intranodular CT number) and to evaluate the usefulness of each parameter in the differentiation of the nodules. Materials and methods. Seventy solitary pulmonary nodules with a long axis length of 5-30 mm were examined using one multidetector CT (MDCT) system and one three-dimensional (3D) system, and the findings regarding the three parameters were statistically analyzed among five diseases (hamartoma, organizing pneumonia, adenocarcinoma, squamous cell carcinoma, and metastasis). Results. The long-short ratio of the pulmonary nodule showed no significant differences among five diseases. The compactness showed significant differences (P<0.05) in five pairs of diseases. Intranodular CT number showed significant differences (P<0.05) in three pairs of diseases. Conclusion. Our results are insufficient for the complete differentiation of pulmonary solid nodules. However, among the three parameters, compactness and intranodular CT number contribute somewhat to the differentiation of pulmonary nodules.
引用
收藏
页码:389 / 395
页数:7
相关论文
共 30 条
  • [1] IMAGE-ANALYSIS METHODS FOR SOLITARY PULMONARY NODULE CHARACTERIZATION BY COMPUTED-TOMOGRAPHY
    CAVOURAS, D
    PRASSOPOULOS, P
    PANTELIDIS, N
    [J]. EUROPEAN JOURNAL OF RADIOLOGY, 1992, 14 (03) : 169 - 172
  • [2] Characteristics of regions suspicious for pulmonary nodules at chest radiography
    Drayer, JA
    Vittitoe, NF
    Vargas-Voracek, R
    Baydush, AH
    Ravin, CE
    Floyd, CE
    [J]. ACADEMIC RADIOLOGY, 1998, 5 (09) : 613 - 619
  • [3] DRAYER JA, 1996, RADIOLOGY, V200, P327
  • [4] New classification of small pulmonary nodules by margin characteristics on high-resolution CT
    Furuya, K
    Murayama, S
    Soeda, H
    Murakami, J
    Ichinose, Y
    Yabuuchi, H
    Katsuda, Y
    Koga, M
    Masuda, K
    [J]. ACTA RADIOLOGICA, 1999, 40 (05) : 496 - 504
  • [5] CT DENSITOMETRY OF PULMONARY NODULES - A PHANTOM STUDY
    GODWIN, JD
    FRAM, EK
    CANN, CE
    GAMSU, GG
    [J]. JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 1982, 6 (02) : 254 - 258
  • [6] DISTINGUISHING BENIGN FROM MALIGNANT PULMONARY NODULES BY COMPUTED-TOMOGRAPHY
    GODWIN, JD
    SPECKMAN, JM
    FRAM, EK
    JOHNSON, GA
    PUTMAN, CE
    KOROBKIN, M
    BREIMAN, RS
    [J]. RADIOLOGY, 1982, 144 (02) : 349 - 351
  • [7] DETERMINING THE LIKELIHOOD OF MALIGNANCY IN SOLITARY PULMONARY NODULES WITH BAYESIAN-ANALYSIS .2. APPLICATION
    GURNEY, JW
    LYDDON, DM
    MCKAY, JA
    [J]. RADIOLOGY, 1993, 186 (02) : 415 - 422
  • [8] DETERMINING THE LIKELIHOOD OF MALIGNANCY IN SOLITARY PULMONARY NODULES WITH BAYESIAN-ANALYSIS .1. THEORY
    GURNEY, JW
    [J]. RADIOLOGY, 1993, 186 (02) : 405 - 413
  • [9] COMPUTERIZED TOMOGRAPHIC DENSITOMETRY OF THE SOLITARY PULMONARY NODULE USING A NODULE PHANTOM
    JONES, FA
    WIEDEMANN, HP
    ODONOVAN, PB
    STOLLER, JK
    [J]. CHEST, 1989, 96 (04) : 779 - 784
  • [10] Example-based assisting approach for pulmonary nodule classification in three-dimensional thoracic computed tomography images
    Kawata, Y
    Niki, N
    Ohmatsu, H
    Moriyama, N
    [J]. ACADEMIC RADIOLOGY, 2003, 10 (12) : 1402 - 1415