ArticleJapanese journal of radiology2020
Diagnostic performance and inter-operator variability of apparent diffusion coefficient analysis for differentiating pleomorphic adenoma and carcinoma ex pleomorphic adenoma: comparing one-point measurement and whole-tumor measurement including radiomics approach.
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 9 papers.
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Who cites it
9 citing papers in PubMed.
- Advanced magnetic resonance neurography for preoperative facial nerve assessment and surgical planning in parotid tumors: a review of current evidence and surgical translation.Frontiers in oncology · 2026Review
- Single-cell transcriptomics reveals cellular evolution underlying pleomorphic adenoma recurrence and malignant transformation.Scientific reports · 2025Article
- Article
- The Role of Radiomics in Salivary Gland Imaging: A Systematic Review and Radiomics Quality Assessment.Diagnostics (Basel, Switzerland) · 2022Review
- MR Imaging Findings of Carcinoma Ex Pleomorphic Adenoma Related to Extracapsular Invasion and Prognosis.AJNR. American journal of neuroradiology · 2022Article
- CT-based delta radiomics in predicting the prognosis of stage IV gastric cancer to immune checkpoint inhibitors.Frontiers in oncology · 2022Article
- Apparent Diffusion Coefficient Map-Based Radiomics Features for Differential Diagnosis of Pleomorphic Adenomas and Warthin Tumors From Malignant Tumors.Frontiers in oncology · 2022Article
- Carcinoma ex pleomorphic adenoma of major salivary glands: CT and MR imaging findings.Dento maxillo facial radiology · 2021Article
- Radiogenomics of gastroenterological cancer: The dawn of personalized medicine with artificial intelligence-based image analysis.Annals of gastroenterological surgery · 2021Review
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Authors and funding
7 authors.
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Abstract
background and purposeThe purpose of this study was to compare the diagnostic performance between apparent diffusion coefficient (ADC) analysis of one-point measurement and whole-tumor measurement, including radiomics for differentiating pleomorphic adenoma (PA) from carcinoma ex pleomorphic adenoma (CXPA), and to evaluate the impact of inter-operator segmentation variability. MATERIALS AND
methodsOne hundred and fifteen patients with PA and 22 with CXPA were included. Four radiologists with different experience independently placed one-point and whole-tumor ROIs and a radiomics-predictive model was constructed from the extracted imaging features. We calculated the area under the receiver-operator characteristic curve (AUC) for the diagnostic performance of imaging features and the radiomics-predictive model.
resultsAUCs of the imaging features from whole-tumor varied between readers (0.50-0.89). The most experienced radiologist (Reader 1) produced significantly high AUCs than less experienced radiologists (Reader 3 and 4; P = 0.01 and 0.009). AUCs were higher for the radiomics-predictive model (0.82-0.87) than for one-point (0.66-0.79) in all readers.
conclusionSome imaging features of whole-tumor and radiomics-predictive model had higher diagnostic performance than one-point. The diagnostic performance of imaging features from whole-tumor alone varied depending on operator experience. Operator experience appears less likely to affect diagnostic performance in the radiomics-predictive model.
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