Variability in Mesothelioma Tumor Response Classification

American Journal of Roentgenology. 2006 Apr;186(4):1000-6. [Link]

Samuel G. Armato, III1, Joseph L. Ogarek1, Adam Starkey1, Nicholas J. Vogelzang2, Hedy L. Kindler3, Masha Kocherginsky4 and Heber MacMahon1

1 Department of Radiology, The University of Chicago, 5841 S Maryland Ave., Chicago, IL 60637.
2 Nevada Cancer Institute, Las Vegas, NV 89135.
3 Department of Medicine, The University of Chicago, Chicago, IL 60637.
4 Department of Health Studies, The University of Chicago, Chicago, IL 60637.

Armato SG 3rd, Ogarek JL, Starkey A, Vogelzang NJ, Kindler HL, Kocherginsky M, Macmahon H.

Department of Radiology, The University of Chicago, 5841 S Maryland Ave., Chicago, IL 60637.


Objective: The objective of our study was to evaluate observer variability in the measurement of temporal change in mesothelioma tumor thickness and in the resulting tumor response classification from CT scans. In addition, the performance of a semiautomated measurement method was evaluated.

Materials and Methods: Four observers individually used an interface that displayed two serial CT scans from the same patient to measure mesothelioma tumor thickness on the follow-up CT scans of 22 patients based on baseline scan measurements. During one session, observers acquired measurements on the follow-up scans based on written reports of baseline scan measurements; in another session, baseline scan measurements were superimposed on the baseline scan for direct visual comparison. Follow-up scan measurements also were obtained from a semiautomated method. Measurement variability and tumor response classification concordance were evaluated for manual measurements acquired in both modes and for semiautomated measurements.

Results: Although only a small increase in tumor response classification concordance rate was obtained with the visual approach (84.8%) relative to the more standard written-report approach (82.6%), the actual measurements acquired by observers were statistically significantly different between the two approaches (p = 0.03). Both the semiautomated measurements and the resulting tumor response classifications were consistent with manual measurements.

Conclusion: The presentation of baseline scan tumor measurements affects measurements acquired on follow-up scans and could influence tumor response classification. The potential utility of semiautomated tumor thickness measurements was shown in the context of measuring tumor response.

Keywords: computer-aided diagnosis; CT; lung cancer; mesothelioma; oncologic imaging; tumor response