Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images

Abstract

Objectives To predict cavernous sinus (CS) invasion by pituitary adenomas (PAs) pre-operatively using a radiomics method based on contrast-enhanced T1 (CE-T1) and T2-weighted magnetic resonance (MR) imaging. Methods A total of 194 patients with Knosp grade two and three PAs (training set: n = 97; test set: n = 97) were enrolled in this retrospective study. From CE-T1 and T2 MR images, 2553 quantitative imaging features were extracted. To select the most informative features, least absolute shrinkage and selection operator (LASSO) was performed. Subsequently, a linear support vector machine (SVM) was used to fit the predictive model. Furthermore, a nomogram was constructed by incorporating clinico-radiological risk factors and radiomics signature, and the clinical usefulness of the nomogram was validated using decision curve analysis (DCA). Results Three imaging features were selected in the training set, based on which the radiomics model yielded area under the curve (AUC) values of 0.852 and 0.826 for the training and test sets. The nomogram based on the radiomics signature and the clinico-radiological risk factors yielded an AUC of 0.899 in the training set and 0.871 in the test set. Conclusions The nomogram developed in this study might aid neurosurgeons in the pre-operative prediction of CS invasion by Knosp grade two and three PAs, which might contribute to creating surgical strategies. Key Points • Pre-operative diagnosis of CS invasion by PAs might affect creating surgical strategies • MRI might help for diagnosis of CS invasion by PAs before surgery • Radiomics might improve the CS invasion detection by MR images. Electronic supplementary material The online version of this article (10.1007/s00330-018-5725-3) contains supplementary material, which is available to authorized users.

Development and Interpretation of Multiple Machine Learning Models for Predicting Postoperative Delayed Remission of Acromegaly Patients During Long-Term Follow-Up

“…The tumor size and the Knosp grade were determined using preoperative pituitary contrast-enhanced MRI images ( 20 , 21 ). The cavernous sinus invasion ( 22 ) and the tumor texture ( 2 ) were determined by the surgeon during the operation. The cavernous sinus invasion of tumors was considered to be positive if the tumor extended the cavernous sinus and a cavernous sinus defect was observed ( 23 ).…”

Pituitary Adenomas and Invasiveness from Anatomo-Surgical, Radiological, and Histological Perspectives: A Systematic Literature Review

“…Recently, radiomics is playing an increasingly important role: its preoperative prediction of CS invasion based on contrast-enhanced T1 and T2-weighted magnetic resonance (MR) imaging might support clinical decision-making and predict outcomes [127]. Three-dimensional anisotropy contrast (3DAC) MR imaging [128], CE-MRA 3T (contrast-enhanced MR angiography) [129] or CE 3D FIESTA (contrast-enhanced 3D fast-imaging employing steady-state acquisition) [130] might be used to evaluate CS invasion and study the involvement of its cranial nerves.…”

A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study

“…Recent studies have shown several applications of radiomics in meningiomas, such as different diagnoses, prediction of the grade and histological subtype, and prediction recurrence-free survival in meningioma [ 5 , [15] , [16] , [17] ]. Moreover, a recent study showed that radiomics might predict preoperative cavernous sinus invasion by pituitary adenomas [18] . These studies show the value of radiomics in medical imaging, which can also be a potential method for the prediction of brain invasion in meningiomas on MRI.…”