Efficacy of ¹⁸F-Fluoro-2-Deoxyglucose Positron Emission Tomography as a Predictor of Treatment Response to Neoadjuvant S-1 + Oxaliplatin Chemotherapy for Gastric Cancer

Background: Neoadjuvant chemotherapy is widely recognized as the established treatment for advanced gastric cancer. However, predicting its efficacy before surgery remains challenging. Aim: The present study aimed to evaluate the effectiveness of 18F-fluoro-2-deoxyglucose positron emission tomography (FDG-PET) as a predictor of treatment response to the S-1+Oxaliplatin regimen (SOX). Methods and Results: Thirty patients who underwent gastrectomy following neoadjuvant SOX between January 2021 and July 2023 were included. Patients underwent FDG-PET pre- and postsurgery. The maximum standardized uptake value (SUVmax) from FDG-PET was examined in relation to histological tumor response and prognosis. SUVmax decreased significantly after chemotherapy in all patients (p < 0.001), especially in those with Grade 1a, 2, and 3 tumors (p < 0.05). SUV reduction increased stepwise with the histological response grade. Optimal cut-off values for the percentage decrease in SUVmax (ΔSUVmax) predictive of histologic efficacy were identified as 53% (area under curve 0.855, p = 0.0018) for Grade 1b or higher and 75% (area under curve 0.806, p = 0.0044) for Grade 2 or higher. Patients with ΔSUVmax > 50% had improved recurrence-free survival (p = 0.027). Conclusion: FDG-PET may be useful as a predictor of treatment response in neoadjuvant SOX therapy for gastric cancer. The determination of the optimal ΔSUVmax value may enhance the precision of histological tumor response prediction.

Publication Details

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Kobe University Repository Kernel (Kobe University)
Published
2025-04-01
Primary Topic
Gastric Cancer Management and Outcomes
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article

Efficacy of ¹⁸F-Fluoro-2-Deoxyglucose Positron Emission Tomography as a Predictor of Treatment Response to Neoadjuvant S-1 + Oxaliplatin Chemotherapy for Gastric Cancer

Kobe University Repository Kernel (Kobe University)
Gastric Cancer Management and Outcomes
article

Efficacy of ¹⁸F-Fluoro-2-Deoxyglucose Positron Emission Tomography as a Predictor of Treatment Response to Neoadjuvant S-1 + Oxaliplatin Chemotherapy for Gastric Cancer

article en

Abstract

Background: Neoadjuvant chemotherapy is widely recognized as the established treatment for advanced gastric cancer. However, predicting its efficacy before surgery remains challenging. Aim: The present study aimed to evaluate the effectiveness of 18F-fluoro-2-deoxyglucose positron emission tomography (FDG-PET) as a predictor of treatment response to the S-1+Oxaliplatin regimen (SOX). Methods and Results: Thirty patients who underwent gastrectomy following neoadjuvant SOX between January 2021 and July 2023 were included. Patients underwent FDG-PET pre- and postsurgery. The maximum standardized uptake value (SUVmax) from FDG-PET was examined in relation to histological tumor response and prognosis. SUVmax decreased significantly after chemotherapy in all patients (p < 0.001), especially in those with Grade 1a, 2, and 3 tumors (p < 0.05). SUV reduction increased stepwise with the histological response grade. Optimal cut-off values for the percentage decrease in SUVmax (ΔSUVmax) predictive of histologic efficacy were identified as 53% (area under curve 0.855, p = 0.0018) for Grade 1b or higher and 75% (area under curve 0.806, p = 0.0044) for Grade 2 or higher. Patients with ΔSUVmax > 50% had improved recurrence-free survival (p = 0.027). Conclusion: FDG-PET may be useful as a predictor of treatment response in neoadjuvant SOX therapy for gastric cancer. The determination of the optimal ΔSUVmax value may enhance the precision of histological tumor response prediction.

Kobe University Repository Kernel (Kobe University)
Good health and well-being
Openalex Percentile: Top 35%
Gastric Cancer Management and Outcomes
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Efficacy of ¹⁸F-Fluoro-2-Deoxyglucose Positron Emission Tomography as a Predictor of Treatment Response to Neoadjuvant S-1 + Oxaliplatin Chemotherapy for Gastric Cancer · Kobe University Repository Kernel (Kobe University) (2025) | TGRS Research Map | TGRS