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Meeting ReportPoster - PhysicianPharm

Metabolic Tumor Volume of Methionine PET in Early Lung Cancer is Useful for Predicting Prognosis of Patients treated with Carbon Ion Radiotherapy

Kentaro Tamura, Ryuichi Nishii, Kana Yamazaki, Naoyoshi Yamamoto, Tatsuya Higashi and Hiroshi Tsuji
Journal of Nuclear Medicine May 2021, 62 (supplement 1) 1030;
Kentaro Tamura
1National Institute of Radiological Sciences Chiba Japan
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Ryuichi Nishii
2National Institute of Radiological Sciences (NIRS) Chiba Japan
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Kana Yamazaki
3National Institute of Quantum and Radiological Sci Chiba Japan
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Naoyoshi Yamamoto
1National Institute of Radiological Sciences Chiba Japan
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Tatsuya Higashi
4Dept. of Molecular Imaging and Theranostics National Institute of Radiological Sciences (NIRS) Chiba Japan
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Hiroshi Tsuji
1National Institute of Radiological Sciences Chiba Japan
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Abstract

1030

Objectives: Lung cancer is one of the most prevalent cancers worldwide, and non-small cell lung cancer (NSCLC) accounts for about 85-90% of all lung tumor types. Carbon ion radiation therapy (CIRT) has achieved outcomes comparable to surgery due to its excellent dose-concentration and high biological effectiveness. However, two-year progression-free survival of patients treated with CIRT for locally advanced lung cancer is reported as 40%. C11-methionine (MET) is an amino acid radiotracer known to show tumor-specific accumulation and MET-PET/CT imaging is useful in evaluating lung tumors. However, the correlation between MET-PET/CT imaging biomarkers and prognosis in NSCLC patients is still unknown. The aim of this study was to investigate the predictive values of MET-PET/CT in patients treated with CIRT for NSCLC.

Methods: Sixty consecutive patients (36 males and 24 females; mean age 73.3y; range 51-89y) with locally advanced NSCLC who underwent MET-PET/CT prior to CIRT between 2007 and 2012 were enrolled. Patients were treated with 40-50 Gy of CIRT. The mean follow-up period was 77.3 months. For quantitative analysis of PET image data, metabolic tumor volume was obtained with a threshold of standardized sptake value (SUV) greater than 1.5. Tumor contouring on MET-PET/CT image was determined by a consensus of two board-certified diagnostic radiologists. Univariate and Multivariate Cox proportional hazard regression analyses and Kaplan-Meir analyses were performed to assess the predictive value for disease-free survival (DFS) among a diameter of solid tumor component (Solid-Diameter), SUVmax, Metabolic Tumor Volume (MTV), Total Lesion Metabolism of the amino acid (TLM), and clinical factors. Statistical analyses were calculated with SPSS statistical software, version 26 with P values of less than 0.05 considered statistically significant.

Results: The mean SUVmax of the tumor was 3.53±1.0. Univariate Cox proportional hazard regression analyses showed that SUVmax (p<0.05, HR 3.22 95% CI 1.21-8.56), MTV (p<0.005, HR 4.45, 95% CI 1.78-11.2), and TLM (p<0.005, HR 0.249, 95% CI 0.10-0.62) were significant prognostic factors for DFS. While, the Solid-Diameter, age, sex, and the treatment radiation dose were not significant prognostic factors for DFS. After checking multicollinearity, multivariate Cox hazard analysis was performed with five elements: Solid-Diameter, SUVmax, MTV, age, and sex. MTV was revealed to be the only independent prognostic factor (p<0.05, HR 0.257, 95% CI 0.072-0.923). Kaplan-Meier analysis of MTV demonstrated that patients with MTV lower than 6ml had longer DFS (p<0.001).

Conclusions: Metabolic Tumor Volume (thresholds of SUV 1.5) in MET-PET/CT would be a useful predictor of disease-free survival of NSCLC treated with CIRT.

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Journal of Nuclear Medicine
Vol. 62, Issue supplement 1
May 1, 2021
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Metabolic Tumor Volume of Methionine PET in Early Lung Cancer is Useful for Predicting Prognosis of Patients treated with Carbon Ion Radiotherapy
Kentaro Tamura, Ryuichi Nishii, Kana Yamazaki, Naoyoshi Yamamoto, Tatsuya Higashi, Hiroshi Tsuji
Journal of Nuclear Medicine May 2021, 62 (supplement 1) 1030;

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Metabolic Tumor Volume of Methionine PET in Early Lung Cancer is Useful for Predicting Prognosis of Patients treated with Carbon Ion Radiotherapy
Kentaro Tamura, Ryuichi Nishii, Kana Yamazaki, Naoyoshi Yamamoto, Tatsuya Higashi, Hiroshi Tsuji
Journal of Nuclear Medicine May 2021, 62 (supplement 1) 1030;
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