Radiation-based machine learning method Helps distinguish between pituitary neuroendocrine tumors and craniopharyngioma posterior pituitary tumors

ASA, SL, Mete, O., Perry, A. &Osamura, Ry Overview Classification of Pituitary Tumors in 2022 [J]. secret. Pattle. 33 (1), 6–26 (2022).

ArticleCAS PubMed Google Scholar

LOPES, M. World Health Organization Classification for 2017: Summary of Pituitary Tumors [J]. Acta Neuropathol. 134 (4), 521–535 (2017).

ArticleCAS PubMed Google Scholar

Salge-Arrieta, F. Etal. Clinical features, diagnosis, and treatment of puicitoma: Updated [J]. J. Endocrinol. investigation. 42 (4), 371–384 (2019).

Article CAS Google Scholar

Viaene, A., Lee, E. & Nasrallah, M. Intraoperative cytoma intraoperatively [J]. diagnosis. Site Patol. 48 (4), 342–349 (2020).

ArticlePubMed Google Scholar

Guerrero-Pérez, F., Marengo, A., Vidal, N., Iglesias, P. & Villabona, C. Primary tumors in the posterior pituitary gland: a systematic review [J]. Internal review. Metabolic disorders. 20 (2), 219–238 (2019).

ArticleGoogle Scholar

Covington, M., Chin, S. &Osborn, A. Pituicytoma, Spindle cell tumor cell tumors, and granule cell tumors: Clarification and meta-analysis of world literature since 1893 [J]. ajnr am. J. Neuroradiol. 32 (11), 2067–2072 (2011).

ArticleCAS PubMed PubMed Central Google Scholar

Feng, M., Carmichael, J., Bonert, V., Bannykh, S. & Mamelak, A. Surgical management of the pituitary gland: a case series and a comprehensive literature review [J]. Pituitary 17 (5), 399–413 (2014).

ArticlePubMed Google Scholar

Chen, J. Etal. Clinical features, radiological profiles, pathological features, and pituitary surgical outcomes: Reports of 11 cases and pooled analysis of individual patient data [J]. Military medical care. res. 8 (1), 39 (2021).

Article Advertising Google Scholar

Wei, L. Etal. Treatment and prognostic factors for pidithoma: a single-center experience and a comprehensive literature review [J]. Pituitary twenty four (5), 754–767 (2021).

ArticlePubMed PubMed Central Google Scholar

Shibuya, M. New WHO classification of pituitary tumors 2017: Welcomes the revolution in TTF-1-positive posterior pituitary tumors [J]. Brain tumor pathogens. 35 (2), 62–70 (2018).

ArticleCAS PubMed Google Scholar

Secci, F., Merciadri, P., Rossi, D., D'Andrea, A. & Zona, G. Pituicytomas: Radiologic findings, clinical behavior, and surgical management [J]. Acta Neurochir., 154(4): (2012). 649 – 57;Discussion 657.

Iglesias, A. Etal. Findings of MR imaging in granular cell tumors of neurotic disorders: Preoperative diagnosis is difficult [J]. EUR. Radiol. 10 (12), 1871–1873 (2000).

ArticleCAS PubMed Google Scholar

Han, F. Etal. Clinical and imaging features of neurotypical granular cell tumors: a retrospective analysis [J]. medicine 97 (9), E9745 (2018).

ArticlePubMed PubMed Central Google Scholar

Hasiloglu, Z. Etal. New radiation cues in the diagnosis of spindle cell carcinoma in adenohyppophysis [J]. Clean. Radiol. 71 (9), 937 (2016). .e5-.e11.

ArticleGoogle Scholar

Yi, Z., Long, L., Zeng, Y. & Liu, Z. [J]. front. oncol. 11732196 (2021).

ArticleCAS PubMed PubMed Central Google Scholar

King, Y. Etal. MR-based radiation for the differential diagnosis between cystic pituitary adenomas and Lasque lacerated cysts. [J]. Calculation and Mathematical Methods in Medicine, 2021: 6438861 (2021).

Zhao, Z. et al. Development of blood index-based nomograms for preoperative biparametric MRI and differentiation of cystic lytic pituitary adenomas and craniopharyngiomas [J]. front. oncol. 11709321 (2021).

ArticlePubMed PubMed Central Google Scholar

Zhang, S. Etal. Non-invasive radiation approaches may potentially predict pituitary adenoma subtypes that do not function before surgery [J]. EUR. Radiol. 28 (9), 3692–3701 (2018).

ArticlePubMed Google Scholar

Peng, A. Etal. Machine learning model that accurately immunohistochemically classifies pituitary adenoma subtypes using radiation based on preoperative magnetic resonance imaging. [J]. EUR. J. Radiol. 125108892 (2020).

ArticlePubMed Google Scholar

Huang, Z. et al. Machine learning-based multiparametric magnetic resonance imaging model for the identification of pathological subtypes of craniopharyngiomas. [J]. J. Magnu. Resonance. Imaging: JMRI. 54 (5), 1541–1550 (2021).

ArticlePubMed Google Scholar

Liu, C. Etal. Utility of multiparametric MRI-based texture signatures in the prediction of growth hormone pituitary adenoma subtypes [J]. front. oncol. 11640375 (2021).

ArticlePubMed PubMed Central Google Scholar

Rui, W. et al. Radioactive analysis allows for accurate prediction of silent corticotrophic adenomas among non-functional pituitary adenomas [J]. EUR. Radiol. 32 (3), 1570–1578 (2022).

ArticlePubMed Google Scholar

Sahin, S. et al. Identification between non-functional pituitary adenomas and pituititis using a machine learning method based on magnetic resonance imaging. [J]. Pituitary twenty five (3), 474–479 (2022).

ArticleCAS PubMed Google Scholar

Chen, X. Etal. Non-invasive molecular diagnosis of craniopharyngioma using an MRI-based radioactive approach [J]. BMC New Roll. 19 (1), 6 (2019).

ArticlePubMed PubMed Central Google Scholar

Uga, L. Etal. Predicting high growth index in large pituitary tumors using MRI-based radioactive and machine learning [J]. Neuroradiology 61 (12), 1365–1373 (2019).

ArticlePubMed Google Scholar

Fan, Y. Etal. Machine learning-based radioactivity predicts radiotherapy response in patients with amorphosis [J]. front. Endocrinol. 10588 (2019).

ArticleGoogle Scholar

Fan, Y. Etal. Development and verification of MRI-based radiation signatures for preoperative prediction of treatment response in patients with invasive functional pituitary adenomas [J]. EUR. J. Radiol. 121108647 (2019).

ArticlePubMed Google Scholar

Zhang, Y. Etal. Preoperative MRI-based radiomolecular pathological classifier to predict recurrence of large pituitary gland exclusion within 5 years [J]. front. New Roll. 12780628 (2021).

ArticlePubMed Google Scholar

Jenkinson, M. , Beckman, cf, Behrens, TE, Woolrich, MW & Smith, SM FSL [J] Neuro image, 62(2): 782–790. (2012).

ArticlePubMed Google Scholar

Molitch, ME diagnosis and treatment of pituitary adenoma: a review [J]. Jama 317 (5), 516–524 (2017).

ArticlePubMed Google Scholar

Zhou, Z., Zhang, S. & Hu, F. Endocrine disorders in patients with craniopharyngioma [J]. front. New Roll. 12737743 (2021).

ArticlePubMed PubMed Central Google Scholar

Jipa, A. & Jain, V. Imaging of the Seller and Paraser Regions [J]. Clean. Imaging. 77254–275 (2021).

ArticlePubMed Google Scholar

Zhang, Y. Etal. Machine learning classifiers in the identification of lesions at the anterior skull base. [J]. front. oncol. 10752 (2020).

ArticleCAS PubMed PubMed Central Google Scholar

Saeger, W. et al. Co-occurrence of pituitary neuroendocrine tumors (pitonets) and neurotic tumors [J]. secret. Pattle. 32 (4), 473–479 (2021).

ArticleCAS PubMed Google Scholar