Analysis Of Imaging And Endocrine Injury Characteristics Of Cystic And Cystic-Solid Lesions In Sellar Area

Background:Cystic lesions are important parts of lesions of the sellar area.There are various types of lesions,including pituitary apoplexy,Rathke’s cleft cyst,cystic craniopharyngioma,etc.These cystic lesions are found to be less common than solid lesions in clinical practice,but epidemiological research shows that their proportion may be underestimated.Purpose:This study aimed to distinguish the pathological types of cystic lesions in sellar area through preoperative magnetic resonance imaging examinations and to explore the influence modes of different lesions on endocrine function of the pituitary glands.This study utilized gadolinium-enhanced magnetic resonance imaging of cystic lesions to identify the common pathological types of cystic lesions in the sellar area with radiomics methods and deep-learning approaches.Through the analysis of the endocrine laboratory examinations,the influence of common sellar cystic lesions on the functions of the pituitary endocrine axis was investigated.Methods:This study screened patients who had a clear diagnosis of sellar disease with cystic components at Peking Union Medical College Hospital in the past 15 years,who had complete preoperative scans of gadolinium-enhanced magnetic resonance imaging.After the series were registered,an artificial neural network for automatic segmentation was applied to the images to annotate the regions of interest,and the segmented regions were manually confirmed later.Both the three-dimensional image and the two-dimensional at the largest layer were used to extract radiomics features.The extracted features were analyzed using statistics,traditional machine learning algorithms,and a fully connected neural network,to classify in pairs to evaluate the performance of these algorithm models.Convolutional neural networks were used to directly identify and evaluate the effect of the largest layer of two-dimensional images of the original magnetic resonance series.We also explored the relationship between the growth hormone axis,thyroid axis,and gonadal axis damage and the size and type of lesions with endocrine laboratory examination data.We further described clinical patterns of pituitary abscess,lymphocytic hypophysitis,and metastatic cancer,which had too few cases to be analyzed with quantitative methods.Results:In this study,399 patients were enrolled.Paired imaging differentiations were performed on pituitary apoplexy,cystic pituitary adenoma,Rathke’s cleft cyst,and cystic craniopharyngioma.The model based on support vector machine could simply distinguish cystic craniopharyngioma from Rathke’s cleft cyst or cystic pituitary adenoma,and the area under the curve can be 0.8522.Cystic pituitary adenomas and pituitary apoplexy were difficult to distinguish,and they were almost unclassifiable with any algorithms on any feature sets,which may be related to their pathological basis.Logistic regression suggested that the type of lesion was not an independent variable of the damage of growth hormone axis,thyroid axis,or gonadal axis.The analysis of the relationship between the damage and the volume of the lesion with an estimate method suggested that as the size of the pituitary apoplexy increased,the endocrine axis of injury happened with the order of the gonadal,the growth hormones,and the thyroid sequentially.Conclusion:Through radiomics,machine learning and artificial neural network approaches,most of the pituitary apoplexy,cystic pituitary adenoma,Rathke’s cleft cyst,and cystic craniopharyngioma can be distinguished with contrast-enhanced magnetic resonance imaging.Pituitary apoplexy and cystic pituitary adenoma cannot be distinguished with these methods.There is no significant difference between the pathology type and the damage of the growth hormone axis,thyroid axis,and gonadal axis.