4.7 Article

Lung cancer: Computerized quantification of tumor response - Initial results

Journal

RADIOLOGY
Volume 241, Issue 3, Pages 892-898

Publisher

RADIOLOGICAL SOC NORTH AMERICA
DOI: 10.1148/radiol.2413051887

Keywords

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Funding

  1. NCI NIH HHS [P01 CA005826-39, R21 CA113653-01] Funding Source: Medline

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Purpose: To prospectively quantify tumor-response or progression in patients with lung cancer by using thin-section computed tomography (CT) and a semiautomated algorithm to calculate tumor volume and other parameter values. Materials and Methods: This HIPAA-compliant study was institutional review board approved; informed patient consent was waived. CT scans of 15 measurable non-small cell lung cancers (in five men and 10 women; mean age, 64 years; range, 38-78 years) before and after gefitinib treatment were analyzed. A semiautomated three-dimensional lung cancer segmentation, algorithm was developed and applied to each tumor at baseline and follow-up. The computer calculated the greatest diameter (unidimensional measurement), the product of the greatest diameter and the greatest perpendicular diameter (bidimensional measurement), and the volume of each tumor. Exact McNemar testis were used to analyze differences in the percentage change calculated with different measurement techniques. Results: The computer accurately segmented 14 of the 15 tumors. One paramediastinal tumor required manual separation from the mediastinum. Eleven (73%) of the 15 patients had an absolute change in tumor volume of at least 20% compared with one (7%) and four (27%) patients who had similar changes in unsealed unidimensional (P < .01) and bidimensional (P = .04) tumor measurements, respectively. Seven (47%) patients had an absolute change in tumor volume of at least 30%. In contrast, at unscaled analysis, no patients at unidimensional measurement (P = .02) and two (13%) patients at bidimensional measurement (P = .06) had a change of at least 30%. Conclusion: Compared with the unidimensional and bidimensional techniques, semiautornated tumor segmentation enabled the identification of a larger nunber of patients with absolute changes in tumor volume of at least 20% and 30%. (c) RSNA, 2006.

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