European radiology
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Comparative Study
Breast MRI during lactation: effects on tumor conspicuity using dynamic contrast-enhanced (DCE) in comparison with diffusion tensor imaging (DTI) parametric maps.
To investigate the effect of lactation on breast cancer conspicuity on dynamic contrast-enhanced (DCE) MRI in comparison with diffusion tensor imaging (DTI) parametric maps. ⋯ • Breast cancer conspicuity on DCE MRI has decreased by approximately 60% among lactating patients compared with non-lactating controls. • DTI-derived diffusion coefficients and the anisotropy indices of PABC lesions were significantly different than those of the normal lactating fibroglandular tissue. • Among lactating patients, breast cancer conspicuity on DTI-derived parametric maps provided up to 138% increase in contrast-to-noise ratio compared with DCE imaging.
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To develop and validate a radiomics nomogram for preoperative differentiating renal angiomyolipoma without visible fat (AML.wovf) from homogeneous clear cell renal cell carcinoma (hm-ccRCC). ⋯ • Differential diagnosis between AML.wovf and hm-ccRCC is rather difficult by conventional imaging modalities. • A radiomics nomogram integrated with the radiomics signature, demographics, and CT findings facilitates differentiation of AML.wovf from hm-ccRCC with improved diagnostic efficacy. • The CT-based radiomics nomogram might spare unnecessary surgery for AML.wovf.
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A combination of T2/FLAIR mismatch sign and advanced imaging parameters may improve the determination of molecular subtypes of diffuse lower-grade glioma. We assessed the diagnostic value of adding the apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) to the T2/FLAIR mismatch sign for differentiation of the IDH mutation or 1p/19q codeletion. ⋯ • The combination of the T2/FLAIR mismatch sign with the ADC or CBV histogram parameters can improve the identification of IDHmut-Noncodel diffuse lower-grade gliomas. • The multivariable model showed a significantly better performance for distinguishing the IDHmut-Noncodel group from other diffuse lower-grade gliomas than the T2/FLAIR mismatch sign alone or any single parameter. • The IDHmut-Noncodel type was associated with intermediate treatment outcomes; therefore, the identification of IDHmut-Noncodel diffuse lower-grade gliomas could be helpful for determining the clinical approach.
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Computed tomography (CT) and magnetic resonance imaging (MRI) are the most commonly selected methods for imaging gliomas. Clinically, radiotherapists always delineate the CT glioma region with reference to multi-modal MR image information. On this basis, we develop a deep feature fusion model (DFFM) guided by multi-sequence MRIs for postoperative glioma segmentation in CT images. ⋯ • A fully automated deep learning method was developed to segment postoperative gliomas on CT images guided by multi-sequence MRIs. • CT and multi-sequence MR image integration allows for improvements in deep learning postoperative glioma segmentation method. • This deep feature fusion model produces reliable segmentation results and could be useful in delineating GTV in postoperative glioma radiotherapy planning.
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Observational Study
Effects of sirolimus in lymphangioleiomyomatosis patients on lung cysts and pulmonary function: long-term follow-up observational study.
To determine whether sirolimus has beneficial effects on lymphangioleiomyomatosis (LAM) lung cysts in CT with long-term follow-up (FU) and to investigate whether CT is an appropriate imaging biomarker to monitor and evaluate LAM progression. ⋯ • Qualitative analysis showed a total of 15.8% to 21.1% of patients had a reduced lung cyst volume after sirolimus treatment, and in quantitative analysis, there was no significant difference in lung cyst volume between CT at the start of sirolimus therapy and the last CT. • Pulmonary function was also improved or maintained after sirolimus treatment. • Chest CT could be a useful imaging biomarker for evaluating and monitoring lung cysts in patients with lymphangioleiomyomatosis.