2014
DOI: 10.1148/radiol.14131643
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Diffusion-weighted MR Imaging in Thymic Epithelial Tumors: Correlation with World Health Organization Classification and Clinical Staging

Abstract: ADC value is a noninvasive, reliable, and reproducible imaging parameter that may help to assess and characterize thymic epithelial tumors.

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Cited by 91 publications
(73 citation statements)
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“…Moreover, mean ADC of B3 thymoma was significantly lower than that of B2 thymoma. ADC levels were significantly associated with disease-free survival of patients with a recurrence rate being higher for patients with ADC ≤ 1.299 × 10 −3 mm 2 / s. To conclude, ADC helps to differentiate high-risk from low-risk thymomas and may be used as a prognostic indicator of recurrence, yet further studies are needed to validate these results [26,27]. conducted prospective/retrospective studies to quantitatively assess and differentiate benign and malignant mediastinal lesions using DWI.…”
Section: Discussionmentioning
confidence: 92%
“…Moreover, mean ADC of B3 thymoma was significantly lower than that of B2 thymoma. ADC levels were significantly associated with disease-free survival of patients with a recurrence rate being higher for patients with ADC ≤ 1.299 × 10 −3 mm 2 / s. To conclude, ADC helps to differentiate high-risk from low-risk thymomas and may be used as a prognostic indicator of recurrence, yet further studies are needed to validate these results [26,27]. conducted prospective/retrospective studies to quantitatively assess and differentiate benign and malignant mediastinal lesions using DWI.…”
Section: Discussionmentioning
confidence: 92%
“…Such sequences, known to be penalized by motion and/or respiratory artefacts in uncooperative or dyspneic patients [16,17], could benefit from VP-MR.…”
Section: Discussionmentioning
confidence: 99%
“…Radiomics can extract a high-throughput objective and quantitative image features from CT, magnetic resonance imaging (MRI), or positron emission tomography (PET) to reflect tumor heterogeneity [10][11][12] and explore the potential relationships between features and pathophysiology to predict clinical outcomes, such as differential diagnosis, classification, distant metastases, survival [13][14][15][16]. Image characteristic analysis, quantitative image analysis, and texture analysis have been used to differentiate high-risk thymomas from lowrisk thymomas according to the WHO classification, to differentiate advanced stage thymomas from early stage thymomas according to the Masaoka clinical stage with all types of thymic tumours and to distinguish anterior mediastinal cysts from other solid masses [17][18][19][20]; however, radiomics-based studies of only AMC distinguished from type B1 and B2 thymomas have not been reported. Therefore, this retrospective study attempts to study whether CT radiomics can reflect the heterogeneity between AMC and type B1 and B2 thymoma and to avoid the resection of AMC that are misdiagnosed as thymomas.…”
Section: Introductionmentioning
confidence: 99%