Daly AF, Beckers A (2020) The epidemiology of pituitary adenomas. Endocrinol Metab Clin North Am. https://doi.org/10.1016/j.ecl.2020.04.002

Article  PubMed  Google Scholar 

Banskota S, Adamson DC (2021) Pituitary adenomas: from diagnosis to therapeutics. Biomedicines. https://doi.org/10.3390/biomedicines90504943

Article  PubMed  PubMed Central  Google Scholar 

Molitch ME (2017) Diagnosis and treatment of pituitary adenomas: a review. JAMA. https://doi.org/10.1001/jama.2016.19699

Article  PubMed  PubMed Central  Google Scholar 

Asa SL, Mete O, Perry A, Osamura RY (2022) Overview of the 2022 WHO classification of pituitary tumors. Endocr Pathol. https://doi.org/10.1007/s12022-022-09703-7

Article  PubMed  Google Scholar 

Nishioka H, Inoshita N, Mete O et al (2015) The complementary role of transcription factors in the accurate diagnosis of clinically nonfunctioning pituitary adenomas. Endocr Pathol. https://doi.org/10.1007/s12022-015-9398-z

Article  PubMed  Google Scholar 

Drummond J, Roncaroli F, Grossman AB, Korbonits M (2019) Clinical and pathological aspects of silent pituitary adenomas. J Clin Endocrinol Metab. https://doi.org/10.1210/jc.2018-00688

Article  PubMed  Google Scholar 

Haddad AF, Young JS, Oh T et al (2020) Clinical characteristics and outcomes of null-cell versus silent gonadotroph adenomas in a series of 1166 pituitary adenomas from a single institution. Neurosurg Focus. https://doi.org/10.3171/2020.3

Article  PubMed  Google Scholar 

Cooper O (2015) Silent corticotroph adenomas. Pituitary 18(2):225–231. https://doi.org/10.1007/s11102-014-0624-3

Article  PubMed  PubMed Central  Google Scholar 

Cho HY, Cho SW, Kim SW, Shin CS, Park KS, Kim SY (2010) Silent corticotroph adenomas have unique recurrence characteristics compared with other nonfunctioning pituitary adenomas. Clin Endocrinol (Oxf). https://doi.org/10.1007/s11102-014-0624-3

Article  PubMed  Google Scholar 

Jiang S, Zhu J, Feng M et al (2021) Clinical profiles of silent corticotroph adenomas compared with silent gonadotroph adenomas after adopting the 2017 WHO pituitary classification system. Pituitary. https://doi.org/10.1007/s11102-021-01133-8

Article  PubMed  Google Scholar 

Nf L, Ai M (2023) Refractory Pit1 plurihormonal tumours and thyrotroph adenomas. Pituitary. https://doi.org/10.1007/s11102-023-01312-9

Article  PubMed  PubMed Central  Google Scholar 

Lucas JW, Bodach ME, Tumialan LM et al (2016) Congress of neurological surgeons systematic review and evidence-based guideline on primary management of patients with nonfunctioning pituitary adenomas. Neurosurgery. https://doi.org/10.1227/NEU.0000000000001389

Article  PubMed  Google Scholar 

Rui W, Qiao N, Wu Y et al (2022) Radiomics analysis allows for precise prediction of silent corticotroph adenoma among non-functioning pituitary adenomas. Eur Radiol. https://doi.org/10.1007/s00330-021-08361-3

Article  PubMed  Google Scholar 

Kasuki L, Antunes X, Coelho MCA et al (2020) Accuracy of microcystic aspect on T2-weighted MRI for the diagnosis of silent corticotroph adenomas. Clin Endocrinol (Oxf). https://doi.org/10.1111/cen.14133

Article  PubMed  Google Scholar 

Cazabat L, Dupuy M, Boulin A et al (2014) Silent, but not unseen: multimicrocystic aspect on T2-weighted MRI in silent corticotroph adenomas. Clin Endocrinol (Oxf). https://doi.org/10.1111/cen.12443

Article  PubMed  Google Scholar 

Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology. https://doi.org/10.1148/radiol.2015151169

Article  PubMed  Google Scholar 

Kitajima M, Hirai T, Katsuragawa S et al (2009) Differentiation of common large sellar-suprasellar masses effect of artificial neural network on radiologists’ diagnosis performance. Acad Radiol. https://doi.org/10.1016/j.acra.2008.09.015

Article  PubMed  Google Scholar 

Zhang S, Song G, Zang Y et al (2018) Non-invasive radiomics approach potentially predicts non-functioning pituitary adenomas subtypes before surgery. Eur Radiol. https://doi.org/10.1007/s00330-017-5180-6

Article  PubMed  PubMed Central  Google Scholar 

Niu J, Zhang S, Ma S et al (2019) Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images. Eur Radiol. https://doi.org/10.1007/s00330-018-5725-3

Article  PubMed  PubMed Central  Google Scholar 

Zhang Y, Luo Y, Kong X, Wan T, Long Y, Ma J (2022) A preoperative MRI-based radiomics-clinicopathological classifier to predict the recurrence of pituitary macroadenoma within 5 years. Front Neurol. https://doi.org/10.3389/fneur.2021.780628

Article  PubMed  PubMed Central  Google Scholar 

Peng A, Dai H, Duan H et al (2020) A machine learning model to classify pituitary adenoma subtypes precisely immunohistochemically with radiomics based on preoperative magnetic resonance imaging. Eur J Radiol. https://doi.org/10.1016/j.ejrad.2020.108892

Article  PubMed  PubMed Central  Google Scholar 

Huang X, Wang D, Ma Y et al (2023) Perihematomal edema-based CT-radiomics model to predict functional outcome in patients with intracerebral hemorrhage. Diagn Interv Imaging. https://doi.org/10.1016/j.diii.2023.04.008

Article  PubMed  Google Scholar 

Su X, Chen N, Sun H et al (2020) Automated machine learning based on radiomics features predicts H3K27M mutation in midline gliomas of the brain. Neuro Oncol. https://doi.org/10.1093/neuonc/noz184

Article  PubMed  PubMed Central  Google Scholar 

Zhang K, Shou X, Chen H et al (2021) Clinical parameters of silent corticotroph adenomas with positive and negative adrenocorticotropic hormone immunostaining: a large retrospective single-center study of 105 cases. Front Endocrinol (Lausanne) 11:608691. https://doi.org/10.3389/fendo.2020.608691

Article  PubMed  Google Scholar 

Kim D, Ku CR, Park SH, Moon JH, Kim EH, Kim SH, Lee EJ (2018) Clinical parameters to distinguish silent corticotroph adenomas from other nonfunctioning pituitary adenomas. World Neurosurg 115:e464–e471. https://doi.org/10.1016/j.wneu.2018.04.070

Article  PubMed  Google Scholar 

Mete O, Cintosun A, Pressman I, Asa SL (2018) Epidemiology and biomarker profile of pituitary adenohypophysial tumors. Mod Pathol. https://doi.org/10.1038/s41379-018-0016-8

Article  PubMed  Google Scholar 

Wang X, Dai Y, Lin H et al (2023) Shape and texture analyses based on conventional MRI for the preoperative prediction of the aggressiveness of pituitary adenomas. Eur Radiol. https://doi.org/10.1007/s00330-023-09412-7

Article  PubMed  PubMed Central  Google Scholar 

Zhang Y, Ko CC, Chen JH et al (2020) Radiomics approach for prediction of recurrence in non-functioning pituitary macroadenomas. Front Oncol. https://doi.org/10.3389/fonc.2020.590083

Article  PubMed  PubMed Central  Google Scholar 

Machado LF, Elias PCL, Moreira AC, Dos Santos AC, Murta Junior LO (2020) MRI radiomics for the prediction of recurrence in patients with clinically non-functioning pituitary macroadenomas. Comput Biol Med. https://doi.org/10.1016/j.compbiomed.2020.103966

Article  PubMed  Google Scholar