Automated Detection Improves Identification of Oligometastatic Disease and Prevention of Missing Metastases During Local Ablative Therapies.

PURPOSE/OBJECTIVE(S) In patients with a limited oligometastatic tumor burden, emerging evidence suggests that the treatment of all visible metastatic sites with locally ablative therapies (LAT) can improve oncologic outcomes. Appropriate identification of the oligometastatic patient requires comprehensive evaluation medical images. In this context, this study aims to evaluate the clinical utility of computer-aided detection (CAD) in the identification of lung nodules in pulmonary oligo-metastases. MATERIALS/METHODS From the database of 1395 patients who were diagnosed with lung metastasis of colorectal cancer from March 2006 to November 2018, chest CT scans of randomly selected three-hundred five patients were collected. CAD counted suspicious lung nodules from chest CT scans of all 305 patients while the radiologist counted nodules of 50 randomly selected patients among them. For those 50 patients, respective percentage of patients with oligo-nodules (< 5), false-positive and false-negative rate of CAD against the radiologist were calculated. With the results from 305 patients, metastatic burden quantification ability of CAD was indirectly evaluated by comparing survival outcomes of these patients according to the number of detected nodules. The nomogram was generated by multiple factors related to the prognosis of colorectal cancer. RESULTS In per patient analysis for the first cohort with 50 patients, the percentage of patients who were defined to have oligometastatic state was 70% (35/50) by CAD and 64% (32/50) by the radiologist, respectively (P = 0.377). Respective false-positive and false-negative rate of CAD in determining oligometastatic state compared to the radiologist were 11.4% and 6.7%. The sensitivity of CAD was 96.9% (95% confidence interval (CI), 82.0-99.8) and the specificity of CAD was 77.8% (95% CI, 51.9-92.6). In per lesion analysis among these patients, sensitivity of CAD was 81.6% (95% CI, 74.3-87.2) for nodules equal to or bigger than 3 mm. Respective 5-year survival rates and mean overall survival in the expanded cohort with 305 patients according to the number of nodules were as follows: 75.2%, 106.9 months (95% CI, 89.0-124.8) for patients with a single nodule, 52.9%, 96.1 months (95% CI, 71.5-120.8) for patients with two nodules, 45.7%, 86.9 months (95% CI, 62.4-111.4) for patients with three nodules, 29.1%, 51.2 months (95% CI, 32.4-70.0) for patients with four nodules, and 22.7%, 36.5 months (95% CI, 29.9-43.0) for patients with equal to or more than five nodules. Internal validation of the nomogram based on the data of expanded cohort showed good discrimination with the median time-dependent area under curve at 5-year of 0.830 (Interquartile range, 0.813-0.828). CONCLUSION Proper identification of oligo-metastatic state for local ablative therapy with acceptable quantification of metastatic burden was achievable by utilizing CAD.