Evaluating variability in tumor measurements from same-day repeat CT scans of patients with non-small cell lung cancer - PubMed (original) (raw)

Evaluating variability in tumor measurements from same-day repeat CT scans of patients with non-small cell lung cancer

Binsheng Zhao et al. Radiology. 2009 Jul.

Abstract

Purpose: To evaluate the variability of tumor unidimensional, bidimensional, and volumetric measurements on same-day repeat computed tomographic (CT) scans in patients with non-small cell lung cancer.

Materials and methods: This HIPAA-compliant study was approved by the institutional review board, with informed patient consent. Thirty-two patients with non-small cell lung cancer, each of whom underwent two CT scans of the chest within 15 minutes by using the same imaging protocol, were included in this study. Three radiologists independently measured the two greatest diameters of each lesion on both scans and, during another session, measured the same tumors on the first scan. In a separate analysis, computer software was applied to assist in the calculation of the two greatest diameters and the volume of each lesion on both scans. Concordance correlation coefficients (CCCs) and Bland-Altman plots were used to assess the agreements between the measurements of the two repeat scans (reproducibility) and between the two repeat readings of the same scan (repeatability).

Results: The reproducibility and repeatability of the three radiologists' measurements were high (all CCCs, >or=0.96). The reproducibility of the computer-aided measurements was even higher (all CCCs, 1.00). The 95% limits of agreements for the computer-aided unidimensional, bidimensional, and volumetric measurements on two repeat scans were (-7.3%, 6.2%), (-17.6%, 19.8%), and (-12.1%, 13.4%), respectively.

Conclusion: Chest CT scans are well reproducible. Changes in unidimensional lesion size of 8% or greater exceed the measurement variability of the computer method and can be considered significant when estimating the outcome of therapy in a patient.

(c) RSNA, 2009.

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Figures

Figure 1:

Figure 1:

Three radiologists' manual unidimensional (UNI, in millimeters) and bidimensional (BI, in square millimeters) measurements of tumors on CT scans. Two greatest diameters (lines) were drawn by radiologists. Measurement values are at top of each scan.

Figure 2:

Figure 2:

Bland-Altman plots of radiologists' measurements. Difference is plotted by using average of both tumor measurements for each patient. Dashed line (center) represents mean of differences. Top dotted line shows upper limit of agreement (mean difference plus 2 times standard deviation); bottom line shows lower limit of agreement (mean difference minus 2 times standard deviation). Plots show possible relationship between nodule size and relative difference in measurements (ie, the smaller the nodule, the larger the relative difference in measurements).

Figure 3:

Figure 3:

Computer-generated contours (white lines, superimposed on original images), two maximal perpendicular diameters (black lines, lower left image for first and second scans), and three-dimensional views (lower right image for first and second scans) of peripheral tumor on first (measurements: unidimensional = 29.7 mm, bidimensional = 507.9 mm2, volumetric = 5564.4 mm3) and repeat (measurements: unidimensional = 29.5 mm, bidimensional = 510.4 mm2, volumetric = 5875.3 mm3) scans. Every second sectional image was displayed.

Figure 4:

Figure 4:

Bland-Altman plots of computer-generated measurements. Difference is plotted by using average of both tumor measurements for each patient. Dashed line represents mean of differences. Top dotted line shows upper limit of agreement (mean difference plus 2 times standard deviation); bottom line shows lower limit of agreement (mean difference minus 2 times standard deviation). Plots show possible relationship between nodule size and relative difference in measurements (ie, the smaller the nodule, the larger the relative difference in measurements).

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