ArticleJapanese journal of radiology2020
Discrimination between pituitary adenoma and craniopharyngioma using MRI-based image features and texture features.
Article in Japanese journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 22 citations in OpenAlex.
- MRI mimics of primary empty sella: a retrospective educational case series highlighting clinical and uncommon magnetic resonance imaging presentations.Acta neurologica Belgica · 2026Article
- Isolated primary craniopharyngioma of the fourth ventricle: a rare case report and literature update.Frontiers in oncology · 2026Article
- Radiomics in Pituitary Adenomas: A Systematic Review of Clinical Applications and Predictive Models.Journal of clinical medicine · 2025Review
- Limitations of MRI in differentiating solid and cystic components of craniopharyngiomas.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2025Article
- Review
- Review
- Radiogenomics Map-Based Molecular and Imaging Phenotypical Characterization in Localised Prostate Cancer Using Pre-Biopsy Biparametric MR Imaging.International journal of molecular sciences · 2024Article
- The current state of MRI-based radiomics in pituitary adenoma: promising but challenging.Frontiers in endocrinology · 2024Review
- Imaging of pituitary tumors: an update with the 5th WHO Classifications-part 2. Neoplasms other than PitNET and tumor-mimicking lesions.Japanese journal of radiology · 2023Review
- Ultrasound-guided endoscopic endonasal resection of sellar and suprasellar craniopharyngiomas.Frontiers in surgery · 2023Article
- Quality reporting of radiomics analysis in pituitary adenomas: promoting clinical translation.The British journal of radiology · 2022Article
- A Radiomics-Based Model with the Potential to Differentiate Growth Hormone Deficiency and Idiopathic Short Stature on Sella MRI.Yonsei medical journal · 2022Article
- Machine learning in neuro-oncology: toward novel development fields.Journal of neuro-oncology · 2022Review
- Xanthogranuloma of the Sellar Region: A Comprehensive Review of Neuroimaging in a Rare Inflammatory Entity.Journal of personalized medicine · 2022Review
- Texture Analysis in Brain Tumor MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2022Article
- Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging.Insights into imaging · 2021Review
- Usefulness of the Texture Signatures Based on Multiparametric MRI in Predicting Growth Hormone Pituitary Adenoma Subtypes.Frontiers in oncology · 2021Article
- Application of Artificial Intelligence in Diagnosis of Craniopharyngioma.Frontiers in neurology · 2021Review
- Development of a Nomogram Based on Preoperative Bi-Parametric MRI and Blood Indices for the Differentiation Between Cystic-Solid Pituitary Adenoma and Craniopharyngioma.Frontiers in oncology · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
purposeTo investigate differences between pituitary adenoma and craniopharyngioma on magnetic resonance imaging (MRI) with image features and three-dimensional texture features. MATERIALS AND
methodsA total of 126 patients diagnosed with pituitary adenoma (N = 63) or craniopharyngioma (N = 63) were enrolled. Qualitative magnetic resonance (MR) image features and texture features of tumors were extracted from preoperative MRI and evaluated using chi-square test or Mann-Whitney U test. Binary logistic regression analyses were performed to assess their abilities as independent diagnostic predictors, and ROC analyses were conducted to evaluate the diagnostic value of significant features. Mann-Whitney U test and ROC analyses were performed to explore the relationship between MR image features and texture features.
resultsFive MR image features were suggested to be significantly different between pituitary adenoma and craniopharyngioma. Three texture features from contrast-enhanced T1WI (HISTO-Skewness, GLCM-Contrast and GLCM-Energy), two texture features from T2WI (HISTO-Skewness and GLCM-Contrast) showed significant differences between two types of tumors. Logistic regression analyses suggested GLCM-Energy from contrast-enhanced T1WI, HISTO-Skewness and GLCM-Contrast from T2WI could be taken as independent predictors. Moreover, HISTO-Skewness and GLCM-Contrast from T2WI were found to be significantly related to cystic change.
conclusionMR image features and texture features were associated with each other, and both types of features represented feasible diagnostic value in discrimination between pituitary adenoma and craniopharyngioma.
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