Valor pronóstico de los parámetros metabólicos en tomografía por emisión de positrones mamaria dedicada en cáncer de mama luminal

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Updated: Mar 1, 2026

Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer

Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer

Published on: July 21, 2018

Azusa Kai¹, Shinsuke Sasada², A I Amioka¹

¹Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan.

Anticancer research

|February 27, 2026

Abstracto

Background/Aim:

Maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) measured using whole-body positron emission tomography (PET) have attracted attention as prognostic parameters. Dedicated breast PET (dbPET), a high-resolution imaging modality, is expected to accurately reflect the metabolic parameters of breast tumors. This study aimed to investigate the prognostic value of metabolic parameters on dbPET for breast cancer.

Patients And Methods:

Ninety-six patients with luminal invasive breast cancer who underwent surgery were analyzed. SUVmax, MTV, and TLG were measured from dbPET images obtained before treatment. The associations between each parameter and recurrence-free survival (RFS) were evaluated.

Results:

During a median follow-up of 8.4 years, eight (8.3%) patients experienced recurrence. The median dbPET values were SUVmax 6.75, MTV 0.64 cm³, and TLG 2.56 cm³. Patients with high SUVmax, MTV, and TLG showed poorer RFS than those with low values: 8-year RFS was 81.9% vs. 96.3% for SUVmax (p=0.004), 68.8% vs. 96.0% for MTV (p<0.001), and 75.1% vs. 96.0% for TLG (p<0.001). Multivariate analysis identified high TLG [hazard ratio (HR)=7.81, 95% confidence interval (CI)=1.19-51.4, p=0.033] and lymphatic invasion (HR=6.64, 95% CI=1.05-41.9, p=0.044) as independent predictors of unfavorable RFS. Multiple regression models suggested that TLG was the most promising parameter for predicting RFS.

Conclusion:

Metabolic parameters on dbPET, particularly TLG, are potentially useful for predicting the prognosis of luminal breast cancer.

Palabras clave:

Cáncer de mama tomografía por emisión de positrones mamaria dedicada parámetro metabólico pronóstico glucólisis total del lesión

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