Ritu R Gill1, David P Naidich2, Alan Mitchell3, Michelle Ginsberg4, Jeremy Erasmus5, Samuel G Armato6, Christopher Straus6, Sharyn Katz7, Demetrois Patios8, William G Richards9, Valerie W Rusch10. 1. Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts. Electronic address: rgill@partners.org. 2. Department of Radiology, New York University School of Medicine, New York, New York. 3. Cancer Research and Biostatistics, Seattle, Washington. 4. Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York. 5. Department of Radiology, M. D. Anderson Cancer Center, Houston, Texas. 6. Department of Radiology, The University of Chicago, Chicago, Illinois. 7. Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. 8. Department of Radiology, Toronto General Hospital and Princess Margaret Hospital, Toronto, Canada. 9. Department of Surgery, Brigham and Women's Hospital, Boston, Massachusetts. 10. Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York; Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.
Abstract
BACKGROUND: Clinical tumor (T), node, and metastasis staging is based on a qualitative assessment of features defining T descriptors and has been found to be suboptimal for predicting the prognosis of patients with malignant pleural mesothelioma (MPM). Previous work suggests that volumetric computed tomography (VolCT) is prognostic and, if found practical and reproducible, could improve clinical MPM classification. METHODS: Six North American institutions electronically submitted clinical, pathologic, and imaging data on patients with stages I to IV MPM to an established multicenter database and biostatistical center. Two reference radiologists blinded to clinical data independently reviewed the scans; calculated clinical T, node, and metastasis stage by standard criteria; performed semiautomated tumor volume calculations using commercially available software; and submitted the findings to the biostatistical center. Study end points included the feasibility of a multi-institutional VolCT network, concordance of independent VolCT assessments, and association of VolCT with pathological T classification. RESULTS: Of 164 submitted cases, 129 were evaluated by both reference radiologists. Discordant clinical staging of most cases confirmed the inadequacy of current criteria. The overall correlation between VolCT estimates was good (Spearman correlation 0.822), but some were significantly discordant. Root cause analysis of the most discordant estimates identified four common sources of variability. Despite these limitations, median tumor volume estimates were similar within subgroups of cases representing each pathological T descriptor and increased monotonically for each reference radiologist with increasing pathological T status. CONCLUSIONS: The good correlation between VolCT estimates obtained for most cases reviewed by two independent radiologists and qualitative association of VolCT with pathological T status combine to encourage further study. The identified sources of user error will inform design of a follow-up prospective trial to more formally assess interobserver variability of VolCT and its potential contribution to clinical MPM staging.
BACKGROUND: Clinical tumor (T), node, and metastasis staging is based on a qualitative assessment of features defining T descriptors and has been found to be suboptimal for predicting the prognosis of patients with malignant pleural mesothelioma (MPM). Previous work suggests that volumetric computed tomography (VolCT) is prognostic and, if found practical and reproducible, could improve clinical MPM classification. METHODS: Six North American institutions electronically submitted clinical, pathologic, and imaging data on patients with stages I to IV MPM to an established multicenter database and biostatistical center. Two reference radiologists blinded to clinical data independently reviewed the scans; calculated clinical T, node, and metastasis stage by standard criteria; performed semiautomated tumor volume calculations using commercially available software; and submitted the findings to the biostatistical center. Study end points included the feasibility of a multi-institutional VolCT network, concordance of independent VolCT assessments, and association of VolCT with pathological T classification. RESULTS: Of 164 submitted cases, 129 were evaluated by both reference radiologists. Discordant clinical staging of most cases confirmed the inadequacy of current criteria. The overall correlation between VolCT estimates was good (Spearman correlation 0.822), but some were significantly discordant. Root cause analysis of the most discordant estimates identified four common sources of variability. Despite these limitations, median tumor volume estimates were similar within subgroups of cases representing each pathological T descriptor and increased monotonically for each reference radiologist with increasing pathological T status. CONCLUSIONS: The good correlation between VolCT estimates obtained for most cases reviewed by two independent radiologists and qualitative association of VolCT with pathological T status combine to encourage further study. The identified sources of user error will inform design of a follow-up prospective trial to more formally assess interobserver variability of VolCT and its potential contribution to clinical MPM staging.
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