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

Objectives: Therapy 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.

Methods: CT 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.

Results: Manual 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.

Conclusions: By 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.