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Feb 9, 2024
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Fast Food
PET scans tie fast food to altered blood flow in the heart
August 8, 2025
Pulmonary Embolism
AI boosts rads' identification of incidental PE on CT imaging
August 8, 2025
Technologist Happy
How are technologists dealing with higher vacancy rates?
August 8, 2025
Ultrasound Sonographer 400 (1)
Ultrasound screening for vasa previa tied to better pregnancy outcomes
August 7, 2025
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Images obtained in a 50-year-old female patient with a new biopsy-proven malignant lesion in the left breast. (A) Craniocaudal mammogram of the right breast does not show any lesion. (B) The malignant lesion corresponds with a 7-cm irregular and spiculated mass on the left craniocaudal mammogram. Ultrasound-guided core-needle biopsy revealed grade 2 invasive lobular carcinoma. (C) The bilateral positron emission mammographic craniocaudal color image obtained one hour after intravenous injection of 185 MBq of F-18-labeled fluorodeoxyglucose (F-18 FDG) shows a mass with intense uptake in the left breast with known cancer and no abnormal uptake in the right breast. Positron emission mammographic craniocaudal images of the left breast obtained (D) one hour and (E) four hours after intravenous injection of 185 MBq of F-18 FDG show no substantial visual difference in uptake of the known cancer. (F) Axial contrast-enhanced fat-saturated subtracted T1-weighted MR image with maximum intensity projection reconstruction obtained 90 seconds after intravenous injection of 0.1 mmol of gadolinium-based contrast material per kilogram of body weight also shows the enhancing mass corresponding to known malignancy (arrow) and marked bilateral background parenchymal enhancement, with multiple nonspecific foci of enhancement in the contralateral breast. The patient opted for bilateral mastectomy, which confirmed left-sided malignancy and no malignancy in the contralateral breast. Image courtesy of the RSNA,
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Data analysis validation. Panel A: Image and line profile through the bottle on scans 1 (top) and 2 (middle), and the difference image (bottom) calculated according to Equation 3. Panel B: Data from a representative participant showing the effect of the dose correction on the PETWALK image using Equation 1 when applied to co-registered images in native subject space. The images were then warped to standard Montreal Neurological Institute (MNI) space Top: PETSTAND, middle – uncorrected PETWALK, bottom – corrected PETWALK. The color bar shows image intensity across the three images. Image courtesy of NeuroImage.
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More in Home
PET scans tie fast food to altered blood flow in the heart
By Will Morton
Ultraprocessed foods may acutely affect vascular and brain function, researchers report.
August 8, 2025
Fast Food
AI boosts rads' identification of incidental PE on CT imaging
By Kate Madden Yee
Study results suggest that AI could serve as an effective "second look" tool for incidental pulmonary emboli (PE) on CT imaging.
August 8, 2025
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How are technologists dealing with higher vacancy rates?
By Amerigo Allegretto
High technologist vacancy rates among imaging practices could be addressed through outreach, education, and philanthropy, experts say.
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Ultrasound screening for vasa previa tied to better pregnancy outcomes
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Screening for vasa previa with ultrasound leads to higher survival rates among prenatally diagnosed cases in pregnancy.
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AI could be cost-effective for osteoporosis screening
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A study highlights the public health potential of AI-driven osteoporosis screening to improve early detection.
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Watching a movie during MR imaging reduces kids' need for sedation
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The findings are good news for pediatric patients, who often struggle to remain still during an MRI exam.
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Is imaging being used to its full potential to diagnose dementia?
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As disease-modifying therapies for various types of dementia become more available, MR and CT imaging predominate for diagnosis.
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MRI shows promise profiling hepatocellular carcinoma tumors
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A study suggests that imaging-based screening with targeted pathological workup could help refine treatment strategies.
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MRI-based DL model improves ovarian lesion classification
By Amerigo Allegretto
A deep-learning (DL) model accurately differentiated malignant from benign ovarian lesions on MRI scans and reduced segmentation time.
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Open-source DL model does well for identifying lung cancer risk
By Kate Madden Yee
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