Measurement of mesothelioma on thoracic CT scans: a comparison of manual and computer-assisted techniques.
Our purpose in this study was to evaluate the variability of manual mesothelioma tumor thickness measurements in computed tomography (CT) scans and to assess the relative performance of six computerized measurement algorithms. The CT scans of 22 patients with malignant pleural mesothelioma were collected. In each scan, an initial observer identified up to three sites in each of three CT sections at which tumor thickness measurements were to be made. At each site, five observers manually measured tumor thickness through a computer interface. Three observers repeated these measurements during three separate sessions. Inter- and intra-observer variability in the manual measurement of tumor thickness was assessed. Six automated measurement algorithms were developed based on the geometric relationship between a specified measurement site and the automatically extracted lung regions. Computer-generated measurements were compared with manual measurements. The tumor thickness measurements of different observers were highly correlated (r > or = 0.99); however, the 95% limits of agreement for relative inter-observer difference spanned a range of 30%. Tumor thickness measurements generated by the computer algorithms also correlated highly with the average of observer measurements (r > or = 0.93). We have developed computerized techniques for the measurement of mesothelioma tumor thickness in CT scans. These techniques achieved varying levels of agreement with measurements made by human observers.
Armato
Samuel G
SG
Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637, USA. s-armato@uchicago.edu
Oxnard
Geoffrey R
GR
MacMahon
Heber
H
Vogelzang
Nicholas J
NJ
Kindler
Hedy L
HL
Kocherginsky
Masha
M
Starkey
Adam
A
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D008297:Male; D008654:Mesothelioma / Q000000981:diagnostic imaging* / Q000473:pathology; D008875:Middle Aged; D009716:Numerical Analysis, Computer-Assisted; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D010997:Pleural Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D011785:Quality Assurance, Health Care / Q000379:methods; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted