Evaluating Heterogeneity of Primary Lung Tumor Using Clinical Routine Magnetic Resonance Imaging and a Tumor Heterogeneity Index

Nan Hu; ShaoHan Yin; Qiwen Li; Haoqiang He; Linchang Zhong; Nan-Jie Gong; Jinyu Guo; Peiqiang Cai; Chuanmiao Xie; Hui Liu; Bo Qiu

doi:10.3389/fonc.2020.591485

Evaluating Heterogeneity of Primary Lung Tumor Using Clinical Routine Magnetic Resonance Imaging and a Tumor Heterogeneity Index

Front Oncol. 2021 Jan 8:10:591485. doi: 10.3389/fonc.2020.591485. eCollection 2020.

Authors

Nan Hu^{1

2

3}, ShaoHan Yin^{1

2

4}, Qiwen Li^{1

2

3}, Haoqiang He^{1

2

4}, Linchang Zhong^{1

2

4}, Nan-Jie Gong⁵, Jinyu Guo^{1

2

3}, Peiqiang Cai^{1

2

4}, Chuanmiao Xie^{1

2

4}, Hui Liu^{1

2

3}, Bo Qiu^{1

2

3}

Affiliations

¹ Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
² Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
³ Department of Radiation Oncology, Guangdong Association Study of Thoracic Oncology, Guangzhou, China.
⁴ Department of Radiology, Sun Yat-sen University Cancer Center, Guangzhou, China.
⁵ Vector Lab for Intelligent Medical Imaging and Neural Engineering, International Innovation Center of Tsinghua University, Shanghai, China.

Abstract

Objective: To improve the assessment of primary tumor heterogeneity in magnetic resonance imaging (MRI) of non-small cell lung cancer (NSCLC), we proposed a method using basic measurements from T1- and T2-weighted MRI.

Methods: One hundred and four NSCLC patients with different T stages were studied. Fifty-two patients were analyzed as training group and another 52 as testing group. The ratios of standard deviation (SD)/mean signal value of primary tumor from T1-weighted (T1WI), T1-enhanced (T1C), T2-weighted (T2WI), and T2 fat suppression (T2fs) images were calculated. In the training group, correlation analyses were performed between the ratios and T stages. Then an ordinal regression model was built to generate the tumor heterogeneous index (THI) for evaluating the heterogeneity of tumor. The model was validated in the testing group.

Results: There were 11, 32, 40, and 21 patients with T1, T2, T3, and T4 disease, respectively. In the training group, the median SD/mean on T1WI, T1C, T2WI, and T2fs sequences was 0.11, 0.19, 0.16, and 0.15 respectively. The SD/mean on T1C (p=0.003), T2WI (p=0.000), and T2fs sequences (p=0.002) correlated significantly with T stages. Patients with more advanced T stage showed higher SD/mean on T2-weighted, T2fs, and T1C sequences. The median THI in the training group was 2.15. THI correlated with T stage significantly (p=0.000). In the testing group, THI was also significantly related to T stages (p=0.001). Higher THI had relevance to more advanced T stage.

Conclusions: The proposed ratio measurements and THI based on MRI can serve as functional radiomic markers that correlated with T stages for evaluating heterogeneity of lung tumors.

Keywords: MRI; T stage; heterogeneity; non-small cell lung cancer; radiation therapy.