Diagnosis supporting algorithm for lymph node metastases from colorectal carcinoma on 18F-FDG PET/CT

Objective We studied the improvement of the detect-ability of lymph node (LN) metastases from colorectal cancer in ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG PET)/computed tomography (CT) by analyzing the acquired counts with a statistical method. Methods Thirty-nine metastatic LNs from 32 cases with colorectal cancer were included in this study. “Uptake region” was defined as the site where counts were higher than the average plus 3 standard deviations (SDs) on each transaxial image of FDG PET. After the initial uptake regions were selected, these high accumulation areas were automatically excluded from consideration thereafter. This method was repeated and new uptake regions were identified. This method was repeated up to five times. After that, the stacked-up uptake regions were compared with computed tomography (CT) images, and the high accumulation areas that were superimposed on the normal structures, such as intestine, vessels, and ureters, were excluded from the consideration. The remaining uptake regions were diagnosed as metastatic LNs, and the detectability of LN metastases was calculated. We then compared these statistical results with the results obtained on the basis of visual assessments by radiologists. Results Our proposed method showed the best results when the procedures were repeated three times in the light of detectability. After being repeated three times, this method detected 15/23 (65.2%) metastatic LNs in the first LN group, 16/16 (100%) in the second-third LN groups and 31/39 (79.4%) in the total LNs, whereas the radiologists diagnosed 8/23 (34.8%) of metastatic first LNs, 12/16 (75.0%) in the second-third LNs and 20/39 (51.3%) in the total LNs. A statistically significant difference was observed between the result of iteration number 3 and that by radiologists as for the second—third LNs and the total LNs. Conclusions This study suggests that our proposed statistical method could improve the detectability of LN metastases from colorectal cancer. Our method will help radiologists to detect small metastatic lesions such as LN metastases.