Radiomics Approach for Prediction of Recurrence in Non-Functioning Pituitary Macroadenomas

Frontiers in Oncology

Ching-Chung Ko¹  Yu-Kun Tsui²  Sher-Wei Lim⁴  Yang Zhang⁵  Kai-Ting Chang⁵  Min-Ying Su⁵  Jeon-Hor Chen⁶  Tai-Yuan Chen⁷ 

[1] Department of Health and Nutrition, Chia Nan University of Pharmacy and Science, Tainan, Taiwan;Department of Medical Imaging, Chi-Mei Medical Center, Tainan, Taiwan;Department of Neurosurgery, Chi-Mei Medical Center, Chiali, Tainan, Taiwan;Department of Nursing, Min-Hwei College of Health Care Management, Tainan, Taiwan;Department of Radiological Sciences, University of California, Irvine, Irvine, CA, United States;Department of Radiology, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan;Graduate Institute of Medical Sciences, Chang Jung Christian University, Tainan, Taiwan;

关键词: radiomics;    MRI;    pituitary;    macroadenoma;    recurrence;   

DOI  :  10.3389/fonc.2020.590083

来源: DOAJ

【 摘 要 】

ObjectivesA subset of non-functioning pituitary macroadenomas (NFPAs) may exhibit early progression/recurrence (P/R) after surgical resection. The purpose of this study was to apply radiomics in predicting P/R in NFPAs.MethodsOnly patients who had undergone preoperative MRI and postoperative MRI follow-ups for more than 1 year were included in this study. From September 2010 to December 2017, 50 eligible patients diagnosed with pathologically confirmed NFPAs were identified. Preoperative coronal T2WI and contrast-enhanced (CE) T1WI imaging were analyzed by computer algorithms. For each imaging sequence, 32 first-order features and 75 texture features were extracted. Support vector machine (SVM) classifier was utilized to evaluate the importance of extracted parameters, and the most significant three parameters were used to build the prediction model. The SVM score was calculated based on the three selected features.ResultsTwenty-eight patients exhibited P/R (28/50, 56%) after surgery. The median follow-up time was 38 months, and the median time to P/R was 20 months. Visual disturbance, hypopituitarism, extrasellar extension, compression of the third ventricle, large tumor height and volume, failed optic chiasmatic decompression, and high SVM score were more frequently encountered in the P/R group (p < 0.05). In multivariate Cox hazards analysis, symptoms of sex hormones, hypopituitarism, and SVM score were high risk factors for P/R (p < 0.05) with hazard ratios of 10.71, 2.68, and 6.88. The three selected radiomics features were T1 surface-to-volume radio, T1 GLCM-informational measure of correlation, and T2 NGTDM-coarseness. The radiomics predictive model shows 25 true positive, 16 true negative, 6 false positive, and 3 false negative cases, with an accuracy of 82% and AUC of 0.78 in differentiating P/R from non-P/R NFPAs. For SVM score, optimal cut-off value of 0.537 and AUC of 0.87 were obtained for differentiation of P/R. Higher SVM scores were associated with shorter progression-free survival (p < 0.001).ConclusionsOur preliminary results showed that objective and quantitative MR radiomic features can be extracted from NFPAs. Pending more studies and evidence to support the findings, radiomics analysis of preoperative MRI may have the potential to offer valuable information in treatment planning for NFPAs.

【 授权许可】

Unknown