ArticleThe neuroradiology journal2019
Accuracy of diffusion-weighted imaging-magnetic resonance in differentiating functional from non-functional pituitary macro-adenoma and classification of tumor consistency.
Article in The neuroradiology journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Integrating Molecular and Imaging Insights: Ryanodine Receptor 2 (RyR2) Expression, CK18 Status, and Conventional MRI Findings in Pituitary Neuroendocrine Tumors.International journal of molecular sciences · 2026Article
- Machine Learning Prediction of Pituitary Macroadenoma Consistency: Utilizing Demographic Data and Brain MRI Parameters.Journal of imaging informatics in medicine · 2025Article
- Preoperative prediction of pituitary neuroendocrine tumor consistency based on multiparametric MRI radiomics: a multicenter study.BMC cancer · 2025Article
- Role of diffusion-weighted imaging in the diagnosis of pituitary region tumors.Neuroradiology · 2025Article
- Diffusion-weighted imaging does not seem to be a predictor of consistency in pituitary adenomas.Pituitary · 2024Article
- The current state of MRI-based radiomics in pituitary adenoma: promising but challenging.Frontiers in endocrinology · 2024Review
- The Party Wall: Redefining the Indications of Transcranial Approaches for Giant Pituitary Adenomas in Endoscopic Era.Cancers · 2023Review
- Diffusion Weighted Imaging in Neuro-Oncology: Diagnosis, Post-Treatment Changes, and Advanced Sequences-An Updated Review.Cancers · 2023Review
- Image-driven classification of functioning and nonfunctioning pituitary adenoma by deep convolutional neural networks.Computational and structural biotechnology journal · 2021Article
- Prediction of pituitary adenoma surgical consistency: radiomic data mining and machine learning on T2-weighted MRI.Neuroradiology · 2020Article
- Differentiating glioblastoma multiforme from cerebral lymphoma: application of advanced texture analysis of quantitative apparent diffusion coefficients.The neuroradiology journal · 2020Article
- Prediction of high proliferative index in pituitary macroadenomas using MRI-based radiomics and machine learning.Neuroradiology · 2019Article
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Authors and funding
9 authors.
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Abstract
purposeThe purpose of this study was to determine the accuracy of selected first or second-order histogram features in differentiation of functional types of pituitary macro-adenomas. MATERIALS AND
methodsDiffusion-weighted imaging magnetic resonance imaging was performed on 32 patients (age mean±standard deviation = 43.09 ± 11.02 years; min = 22 and max = 65 years) with pituitary macro-adenoma (10 with functional and 22 with non-functional tumors). Histograms of apparent diffusion coefficient were generated from regions of interest and selected first or second-order histogram features were extracted. Collagen contents of the surgically resected tumors were examined histochemically using Masson trichromatic staining and graded as containing <1%, 1-3%, and >3% of collagen.
resultsAmong selected first or second-order histogram features, uniformity ( p = 0.02), 75th percentile ( p = 0.03), and tumor smoothness ( p = 0.02) were significantly different between functional and non-functional tumors. Tumor smoothness > 5.7 × 10
conclusionFirst or second-order histogram features could be helpful in differentiating functional vs non-functional pituitary macro-adenoma tumors.
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