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Published on: January 17, 2018
Preoperative vascular heterogeneity and aggressiveness assessment of pituitary macroadenoma based on dynamic
YangYing Qiu Liu1, Bing Bing Gao1, Bin Dong2
1Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, 116000, China.
Purpose:
To assess the vascular heterogeneity and aggressiveness of pituitary macroadenomas (PM) using texture analysis based on Dynamic Contrast-Enhanced MRI (DCE-MRI).
Method:
Fifty patients with pathologically confirmed PM, including 32 patients with aggressive PM (aggressive group) and 18 patients with non-aggressive PM (non-aggressive group), were included in this study. The preoperative DCE-MRI and clinical data were collected from all patients. The features based on Ktrans, Ve, and Kep were generated using Omni-Kinetics software. Independent-samples t-test and Mann-Whitney U test were used for comparison between two groups. Logistic regression analysis was used to determine the optimal model for distinguishing aggressive and non-aggressive PM.
Results:
Six features related to tumor morphology, 24 features in Ktrans, 20 features in Ve, and 3 features in Kep were significantly different between the aggressive and non-aggressive groups. Volume count, gray-level non-uniformity in Ktrans, voxel value sum in Ve and run-length non-uniformity in Kep (AUC = 0.816, 0.903, 0.785, 0.813) were considered the best feature for tumor diagnosis. After modeling, the diagnosis efficiency of mean model and total model was desirable (AUC = 0.859 and 0.957), and the diagnostic efficiency of morphological, Ktrans, Ve and Kep features model was improved (AUC = 0.845, 0.951, 0.847, 0.804).
Conclusions:
Texture analysis based on DCE-MRI elucidates the vascular heterogeneity and aggressiveness of pituitary adenoma. The total model could be used as a new noninvasive method for predicting the aggressiveness of pituitary macroadenoma.
Insights
Texture analysis of Dynamic Contrast-Enhanced MRI (DCE-MRI) reveals vascular differences in pituitary macroadenomas (PM). This noninvasive method accurately predicts tumor aggressiveness, aiding clinical decisions.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Pituitary macroadenomas (PM) are common tumors requiring accurate assessment of aggressiveness.
- Differentiating aggressive from non-aggressive PM is crucial for treatment planning.
- Dynamic Contrast-Enhanced MRI (DCE-MRI) offers insights into tumor vascularity.
Purpose of the Study:
- To evaluate the utility of texture analysis on DCE-MRI for assessing vascular heterogeneity and aggressiveness in PM.
- To identify MRI-based features that can distinguish aggressive from non-aggressive PM.
Main Methods:
- Fifty patients with pathologically confirmed PM (32 aggressive, 18 non-aggressive) underwent preoperative DCE-MRI.
- Texture analysis was performed on DCE-MRI data, generating features related to Ktrans, Ve, and Kep.
- Logistic regression was used to develop models for predicting PM aggressiveness.
Main Results:
- Significant differences in texture features related to morphology, Ktrans, Ve, and Kep were observed between aggressive and non-aggressive PM groups.
- Specific features like gray-level non-uniformity in Ktrans and run-length non-uniformity in Kep showed high diagnostic accuracy (AUC > 0.8).
- A total model incorporating multiple features achieved a high AUC of 0.957 for distinguishing aggressive PM.
Conclusions:
- Texture analysis of DCE-MRI effectively characterizes vascular heterogeneity and predicts aggressiveness in pituitary macroadenomas.
- The developed total model presents a promising noninvasive tool for predicting PM aggressiveness, potentially improving patient management.
