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    Five artificial intelligence (AI) algorithms for mammography assessment were better at predicting breast cancer risk over five years than the Breast Cancer Surveillance Consortium (BCSC) risk model, according to new retrospective research involving over 13,000 women.

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    • Study Assesses Ability of #Mammography #AI Algorithms to Predict #BreastCancer Risk https://t.co/b7Ox7zINv2 @ACRRFS @ACRYPS @JBI_SBI @BreastImaging @SBIRFS @RadiologyACR @ARRS_Radiology @RadiologyUcla @UofURadiology @UNMRadiology @MayoRadiologyAZ @UCSFimaging #radiology #RadRes https://t.co/qjr6sEs3Ma

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    In a recently published review, radiology researchers from the University of Wisconsin discussed the potential and key considerations for applying accelerated magnetic resonance imaging (MRI) protocols in the assessment of emergent and urgent conditions.

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    • Can Abbreviated #MRI Have an Impact in #Neuroradiology? https://t.co/02lzLMFe9n @ACRRFS @RadiologyACR @ARRS_Radiology @RSNA @JNeuroradiology @TheASNR @UWRadRes @UWiscNeuroRad @PennRadiology @DukeRadiology @MontefioreRAD @NYUImaging @UVARadiology @EmoryRadiology #radiology #RadRes https://t.co/1TY6dOS19b

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    In a recent lecture at the American Roentgen Ray Society (ARRS) 2023 Annual Meeting, Andrew Callen, M.D., discussed a variety of imaging features associated with cerebrospinal fluid (CSF) leaks, the diagnostic utility of the Bern score as well as the merits of 3D T2FS MRI and dynamic computed tomography myelography.

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    • Spine #Radiology Insights on Venous Fistula Localization and Cerebrospinal Fluid Leaks https://t.co/uWom2a1GRH @ACRRFS @ACRYPS @RadiologyACR @ARRS_Radiology @RSNA @TheASNR @JNeuroradiology @PennRadiology @DukeRadiology @YaleRadiology @UVARadiology #radiology #RadRes #ARRS23 https://t.co/sa1G52ceEu

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    For the detection of obstructive coronary artery disease (CAD), stress cardiovascular magnetic resonance imaging (MRI) demonstrated a sensitivity rate of 81 percent and a specificity rate of 86 percent, according to a meta-analysis of 64 studies and data from 74,470 patients with stable chest pain.

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    • Stress Cardiovascular #MRI: What a New Meta-Analysis Reveals https://t.co/qh8vKcG4Av @ACRRFS @ACRYPS @RadiologyACR @ARRS_Radiology @RSNA @SIRspecialists @PennRadiology @BrighamRad @UVARadiology @EmoryRadiology @YaleRadiology @UABRadiology @NYUImaging @ISMRM #radiology #RadRes https://t.co/RgFOTSDRul

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    FIRMM-pix, a brain magnetic resonance imaging (MRI) software module recently launched at the International Society for Magnetic Resonance in Medicine (ISMRM) conference, reportedly employs visual biofeedback and gamification that coaches patients to stay still during brain MRI exams.

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    • Could #Gamification Enhance Brain #MRI Acquisition? https://t.co/2uNAuyHCIo @ACRRFS @ACRYPS @RadiologyACR @ARRS_Radiology @PennRadiology @DukeRadiology @YaleRadiology @EmoryRadiology @MontefioreRAD @TheASNR @SocPedRad @CHOPRadiology @CincyKidsRad @RadNet_Inc #radiology #RadRes https://t.co/oXZKLqsQyd

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    In order to facilitate optimal detection and assessment of liver fibrosis and steatosis, the newly launched Hepatus 6 Diagnostic Ultrasound System offers the capabilities of real-time two-dimensional ultrasound with visual transient elastography in one device.

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    • New System Combines Diagnostic #Ultrasound and Transient #Elastography https://t.co/AVyCZ4ZZ0l @ACRRFS @ACRYPS @RadiologyACR @ARRS_Radiology @RSNA @PennRadiology @UMMCRads @UABRadiology @EmoryRadiology @NYUImaging @UVARadiology @Mindray_NA @AIUMultrasound #radiology #RadRes https://t.co/SVUGxATWjE

  • Mashup Score: 1

    For the detection of obstructive coronary artery disease (CAD), stress cardiovascular magnetic resonance imaging (MRI) demonstrated a sensitivity rate of 81 percent and a specificity rate of 86 percent, according to a meta-analysis of 64 studies and data from 74,470 patients with stable chest pain.

    Tweet Tweets with this article
    • Stress Cardiovascular #MRI: What a New Meta-Analysis Reveals https://t.co/tx3kJSOiyt @ACRRFS @ACRYPS @RadiologyACR @ARRS_Radiology @RSNA @ISMRM @PennRadiology @UNCRadiology @BURadiology @UVARadiology @MontefioreRAD @WCMRadiology @fabrizioricci @SIRspecialists #radiology #RadRes https://t.co/cpEQtBdYSg

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    In a study of over 1,200 men with over 3,200 prostatic lesions, an explainable artificial intelligence (AI) model demonstrated a sensitivity rate of 93 percent for detecting clinically significant prostate cancer.

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    • Can Explainable #AI Enhance Diagnosis and PI-RADS Classification of #ProstateCancer on #MRI? https://t.co/M1bgBaHnpg @ACRRFS @ACRYPS @RadiologyACR @ARRS_Radiology @RSNA @SocietyAbdRad @PennRadiology @UNCRadiology @DukeRadiology @BURadiology @OchsnerRads #radiology #RadRes https://t.co/VgDAtrxUoa