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Curated Journal Articles on Mesothelioma

CT-Based Assessment of Tumor Volume in Malignant Pleural Mesothelioma

Medial Physics 2015 June [Link]

Qayyum F, Armato S, Straus C, Husain A, Vigneswaran W, Kindler H.

Abstract

Purpose

To determine the potential utility of computed tomography (CT) scans in the assessment of physical tumor bulk in malignant pleural mesothelioma patients.

Methods

Twenty-eight patients with malignant pleural mesothelioma were used for this study. A CT scan was acquired for each patient prior to surgical resection of the tumor (median time between scan and surgery: 27 days). After surgery, the ex-vivo tumor volume was measured by a pathologist using a water displacement method. Separately, a radiologist identified and outlined the tumor boundary on each CT section that demonstrated tumor. These outlines then were analyzed to determine the total volume of disease present, the number of sections with outlines, and the mean volume of disease per outlined section. Subsets of the initial patient cohort were defined based on these parameters, i.e. cases with at least 30 sections of disease with a mean disease volume of at least 3mL per section. For each subset, the R- squared correlation between CT-based tumor volume and physical ex-vivo tumor volume was calculated.

Results

The full cohort of 28 patients yielded a modest correlation between CT-based tumor volume and the ex-vivo tumor volume with an R-squared value of 0.66. In general, as the mean tumor volume per section increased, the correlation of CT-based volume with the physical tumor volume improved substantially. For example, when cases with at least 40 CT sections presenting a mean of at least 2mL of disease per section were evaluated (n=20) the R-squared correlation increased to 0.79.

Conclusion

While image-based volumetry for mesothelioma may not generally capture physical tumor volume as accurately as one might expect, there exists a set of conditions in which CT-based volume is highly correlated with the physical tumor volume. SGA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology.

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