AUTHOR=Feng Pengyang , Shao Zehua , Dong Bai , Fang Ting , Huang Zhun , Li Ziqiang , Fu Fangfang , Wu Yaping , Wei Wei , Yuan Jianmin , Yang Yang , Wang Zhe , Wang Meiyun 

TITLE=Application of diffusion kurtosis imaging and 18F-FDG PET in evaluating the subtype, stage and proliferation status of non-small cell lung cancer

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.989131

DOI=10.3389/fonc.2022.989131

ISSN=2234-943X

ABSTRACT=Background Lung cancer has become one of the deadliest tumors in the world. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for approximately 80%-85% of all lung cancer cases. This study aimed to investigate the value of DKI, DWI and 18F-FDG PET in differentiating SCC and AC and to evaluate the correlation of each parameter with stage and proliferative status Ki-67.
Methods Seventy-seven patients with lung lesions were prospectively scanned by hybrid 3.0-T chest 18F-FDG PET/MR. MK, MD, ADC, SUVmax, MTV and TLG were measured. The independent samples t test or Mann–Whitney U test was used to compare and analyze the differences in each parameter of SCC and AC. The diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve analysis and compared with the DeLong test. A logistic regression analysis was used for the evaluation of independent predictors. 
Results The MK and ADC values of the AC group were significantly higher than those of the SCC group, and the SUVmax, MTV, and TLG values of the SCC group were significantly higher than those of the AC group. There was no significant difference in the MD value between the two groups. Moreover, MK, SUVmax, TLG and MTV were independent predictors of the NSCLC subtype, and the combination of these parameters had an optimal diagnostic efficacy (AUC, 0.876), which was significantly better than that of MK (AUC = 0.758), ADC (AUC = 0.679), SUVmax (AUC = 0.740), MTV (AUC = 0.715) or TLG (AUC = 0.716). The ROC curve showed that the validation model had high accuracy in identifying AC and SCC (AUC, 0.844; 95% CI, 0.785-0.885). The SUVmax value was weakly positively correlated with the Ki-67 index (r = 0.340), the ADC and MD values were weakly negatively correlated with the Ki-67 index (r = -0.256, -0.282), and the MTV and TLG values were weakly positively correlated with NSCLC stage (r = 0.342, 0.337).
Conclusion DKI, DWI and 18F-FDG PET are all effective methods for assessing the NSCLC subtype, and some parameters are correlated with stage and proliferation status.