#InsightsIntoImaging

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Educational Review: Role of imaging in visceral vascular emergencies. (Ali Devrim Karaosmanoglu et al.)

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Fenglan Li et al. discover that quantitative parameters of dual-layer spectral computed tomography (DLCT) can help predict epidermal growth factor receptor (EGFR) mutation status in non-small cell #LungCancer (NSCLC) patients.

#InsightsIntoImaging

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In this study, Jooae Choe et al. explore the reliability of using #MRI to diagnose anterior mediastinal cysts, finding MRI-based management may reduce the number of unnecessary follow-ups and surgeries.

#InsightsIntoImaging

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Through this pictorial review, Mohamed Jarraya et al. provide an overview of uncommon diseases of the popliteal artery to help radiologists avoid misdiagnosis.

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Educational Review: Monogenic autoinflammatory diseases in children - single center experience with clinical, genetic, and imaging review. (Alaa N. Alsharief et al.)

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Critical Review: Noninvasive imaging diagnosis of sinusoidal obstruction syndrome. (Yun Zhang et al.)

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This study assessed the learning-curve during the implementation of the Magnetic Resonance image-guided High-Intensity Focused Ultrasound (MR- #HIFU ) treatment of uterine fibroids in the authors' center. (K.J. Anneveldt et al.)

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When comparing the reproducibility of 2D vs 3D #radiomics , Martin L. Watzenboeck et al. discovered that fetal #MRI radiomics features extracted from 3D whole lung segmentation masks showed significantly higher reproducibility.

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Qiqi Wang et al. investigate the quantitative indicators and features of partial subscapularis tears on conventional shoulder #MRI , which can be used to improve the accuracy of preoperative MRI diagnosis.

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Lars Johannes Isaksson et al. build a #DeepLearning model that estimates the quality of prostate contours, which can be used in practice to ensure quality and monitor the performance of deployed automated contouring models.

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This study aimed to develop a #DeepLearning model to improve the diagnostic performance of EIC & ASPECTS in acute ischemic stroke, resulting in a better performance from radiologists when assisted by the model. (Weidao Chen et al.)

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📜 Statement: How does DICOM support #BigData management? Investigating its use in medical imaging community. (Marco Aiello et al.)

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Ya-Ting Jan et al. explain the development of an #AI model with #radiomics and #DeepLearning features extracted from CT images to distinguish benign from malignant ovarian tumors, showing improvement of less-experienced radiolgists. #InsightsIntoImaging

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Educational Review: Assessment of hepatocellular carcinoma treatment response with #LIRADS . (Nicolas Voizard et al., Ania Kielar, Richard K.G. Do, An Tang, SAR_DFP_HCC)

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Shu-Hui Wang et al. develop and validate a #DeepLearning model for the classification of seven categories of focal liver lesions on multisequence #MRI , comparing differential diagnosis between the proposed model and radiologists.

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This #InsightsIntoImaging study evaluated an #AI algorithm, finding it showed a higher diagnostic accuracy for detection of pulmonary embolism on CT pulmonary angiography compared to a report from the attending radiologist. (Eline Langius-Wiffen et al.)

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