Inter-observer reproducibility of semi-automatic tumor diameter measurement and volumetric analysis in patients with lung cancer

Abstract

ObjectivesTherapy monitoring in oncologic patient requires precise measurement methods. In order to improve the precision of measurements, we used a semi-automated generic segmentation algorithm to measure the size of large lung cancer tumors. The reproducibility of computer-assisted measurements were assessed and compared with manual measurements. MethodsCT scans of 24 consecutive lung cancer patients who were referred to our hospital over a period of 6 months were analyzed. The tumor sizes were measured manually by 3 independent radiologists, according to World Health Organization (WHO) and the Revised Response Evaluation Criteria in Solid Tumors (RECIST) guidelines. At least 10 months later, measurements were repeated semi-automatically on the same scans by the same radiologists. The inter-observer reproducibility of all measurements was assessed and compared between manual and semi-automated measurements. ResultsManual measurements of the tumor longest diameter were significantly (p<0.05) smaller compared with the semi-automated measurements. The intra-rater correlations coefficients were significantly higher for measurements of longest diameter (intra-class correlation coefficients: 0.998 vs. 0.986; p<0.001) and area (0.995 vs. 0.988; p=0.032) using semi-automated compared with manual method. The variation coefficient for manual measurement of the tumor area (WHO guideline, 15.7% vs. 7.3%) and the longest diameter (RECIST guideline, 7.7% vs. 2.7%) was 2–3 times that of semi-automated measurement. ConclusionsBy using computer-assisted size assessment in primary lung tumor, interobserver-variability can be reduced to about half to one-third compared to standard manual measurements. This indicates a high potential value for therapy monitoring in lung cancer patients.