A new strategy based on fluorodeoxyglucose-positron emission tomography for managing liver metastasis from colorectal cancer

Background: Prognostic models are needed to manage liver metastasis from colorectal cancer (CRLM). Thus, we developed an algorithm to guide treatment based on the standardized uptake value (SUV) from fluorodeoxyglucose-positron emission tomography (FDG-PET). Methods: We retrospectively evaluated 148 patients who underwent surgery for CRLM, including 107 cases of primary surgery and 41 cases with preoperative chemotherapy before conversion surgery. We evaluated the prognostic value of perioperative SUV among primary surgery cases, as well as the prognostic value of the SUV change ratio after conversion surgery (postchemotherapy/prechemotherapy SUV). Results: In the primary surgery group, recurrence-free survival (RFS) was independently predicted by an SUV of ≥6.04 (P = 0.042) and ≥4 liver metastases (P = 0.003). The combination of an SUV of ≥6.04 and ≥4 liver metastases was strongly associated with poor RFS (P < 0.001). In the conversion surgery group, the SUV change ratio was associated with tumor size change and pathological response. An SUV change ratio of ≥0.293 was associated with shorter RFS (P = 0.006) and independently predicted RFS (P = 0.026). We established a therapeutic algorithm for managing CRLM based on these results. Conclusion: FDG-PET may be useful for predicting recurrence and prognosis in cases of CRLM, and our algorithm may be useful for managing multiple CRLMs.