Nan Hu1,2,3, ShaoHan Yin1,2,4, Qiwen Li1,2,3, Haoqiang He1,2,4, Linchang Zhong1,2,4, Nan-Jie Gong5, Jinyu Guo1,2,3, Peiqiang Cai1,2,4, Chuanmiao Xie1,2,4, Hui Liu1,2,3, Bo Qiu1,2,3. 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.
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.
Authors: J P B O'Connor; C J Rose; A Jackson; Y Watson; S Cheung; F Maders; B J Whitcher; C Roberts; G A Buonaccorsi; G Thompson; A R Clamp; G C Jayson; G J M Parker Journal: Br J Cancer Date: 2011-06-14 Impact factor: 7.640
Authors: S Corradini; F Alongi; N Andratschke; C Belka; L Boldrini; F Cellini; J Debus; M Guckenberger; J Hörner-Rieber; F J Lagerwaard; R Mazzola; M A Palacios; M E P Philippens; C P J Raaijmakers; C H J Terhaard; V Valentini; M Niyazi Journal: Radiat Oncol Date: 2019-06-03 Impact factor: 3.481
Authors: Luc G T Morris; Nadeem Riaz; Alexis Desrichard; Yasin Şenbabaoğlu; A Ari Hakimi; Vladimir Makarov; Jorge S Reis-Filho; Timothy A Chan Journal: Oncotarget Date: 2016-03-01