SPECT/CT imaging of PD-L1 expression in non-small cell lung cancer based on 99Tc m labeled anti-PD-L1 nanoantibodies / 中华核医学与分子影像杂志
Chinese Journal of Nuclear Medicine and Molecular Imaging
;
(6): 80-83, 2022.
Article
in Chinese
| WPRIM
| ID: wpr-932899
ABSTRACT
Objective:
To explore the value of SPECT/CT imaging on programmed death receptor 1 ligand (PD-L1) expression in patients with non-small cell lung cancer (NSCLC) based on 99Tc m labeled anti-PD-L1 nanoantibodies (NM-01).Methods:
From January 2019 to March 2020, a total of 14 patients (11 males, 3 females; age (61.9±11.0) years) with pathologically confirmed NSCLC in Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine were prospectively enrolled. NM-01 were labeled with 99Tc m, and patients were recruited for SPECT/CT imaging 2 h after injection with 99Tc m-NM-01((359.1±68.0) MBq). The differences of SUV max in primary and metastatic lesions between PD-L1 positive and negative patients were compared by independent sample t test. The correlation between the SUV max and PD-L1 expression of primary lesions was analyzed by Pearson correlation analysis.Results:
Of 14 patients, 6 were PD-L1 positive and 8 were PD-L1 negative. 99Tc m-NM-01 showed obviously increased uptake in kidneys and liver, while mildly increased uptake in spleen and bone marrow. The SUV max of primary lesions was 4.69±1.88 and the SUV max of metastatic lesions was 2.04±1.32. The SUV max of primary lesions in PD-L1 positive patients was significantly higher than that of PD-L1 negative patients (5.99±1.99 vs 3.72±1.10; t=5.98, P=0.039). There was no significant difference in the SUV max of metastatic lesions between PD-L1 positive and negative patients (1.66±1.03 vs 2.35±1.46; t=-1.77, P=0.084). The SUV max of primary lesions was positively correlated with PD-L1 expression ( r=0.648, P=0.042).Conclusion:
99Tc m-NM-01 can demonstrate the expression of PD-L1 in primary and metastatic lesions in NSCLC.
Full text:
Available
Index:
WPRIM (Western Pacific)
Language:
Chinese
Journal:
Chinese Journal of Nuclear Medicine and Molecular Imaging
Year:
2022
Type:
Article
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