January 17th 2025
In the second part of a two-part interview on the recently published appropriate use criteria for brain positron emission tomography (PET) for patients with mild cognitive impairment (MCI), Phillip Kuo, M.D. discusses clinical cases involving the use of amyloid and tau PET imaging.
Annual Hawaii Cancer Conference
January 25-26, 2025
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21st Annual International Symposium on Melanoma and Other Cutaneous Malignancies®
February 8, 2025
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Community Practice Connections™: The 2nd Annual Hawaii Lung Cancers Conference®
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18th Annual New York GU Cancers Congress™
March 28-29, 2025
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Clinical Case Vignette Series™: 41st Annual Miami Breast Cancer Conference®
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Medical Crossfire®: How Can Thoracic Teams Facilitate Optimized Care of Patients With Stage I-III EGFR Mutation-Positive NSCLC?
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Lung Cancer Tumor Board®: How Do Emerging Data for ICIs, BiTEs, ADCs, and Targeted Strategies Address Unmet Needs in the Therapeutic Continuum for SCLC?
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26th Annual International Lung Cancer Congress®
July 25-26, 2025
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CT Study Reveals Key Indicators for Angiolymphatic Invasion in Non-Small Cell Lung Cancer
In computed tomography (CT) scans for patients with solid non-small cell lung cancer (NSCLC) < 30 mm, emerging research suggests the lollipop sign is associated with a greater than fourfold likelihood of angiolymphatic invasion.
Can Generative AI Facilitate Simulated Contrast Enhancement for Prostate MRI?
Deep learning synthesis of contrast-enhanced MRI from non-contrast prostate MRI sequences provided an average multiscale structural similarity index of 70 percent with actual contrast-enhanced prostate MRI in external validation testing from newly published research.
In a recent interview, Phillip Kuo, M.D., discussed the impact of newer anti-amyloid antibody therapies for Alzheimer’s disease upon recently issued appropriate use criteria (AUC) for amyloid positron emission tomography (PET) imaging as well as the incorporation of tau PET into the AUC for patients with mild cognitive impairment.
Can MRI-Based AI Enhance Risk Stratification in Prostate Cancer?
Employing baseline MRI and clinical data, an emerging deep learning model was 32 percent more likely to predict the progression of low-risk prostate cancer (PCa) to clinically significant prostate cancer (csPCa), according to new research.
Shaping the Future of Radiology in 2025: Trends, Threats, and Opportunities
January 10th 2025How do we respond to challenges with staff recruitment, cybersecurity, and looming hospital takeovers in radiology? This author assesses key trends in radiology and offers key insights to stay competitive in the field.
Can MRI Have an Impact with Fertility-Sparing Treatments for Endometrial and Cervical Cancers?
In a literature review that includes insights from recently issued guidelines from multiple European medical societies, researchers discuss the role of magnetic resonance imaging (MRI) in facilitating appropriate patient selection for fertility-sparing treatments to address early-stage endometrial and cervical cancer.
Surveillance Breast MRI Associated with Lower Risks of Advanced Second Breast Cancers
After propensity score matching in a study of over 3,000 women with a personal history of breast cancer, researchers found that surveillance breast MRI facilitated a 59 percent lower risk in advanced presentations of second breast cancers.
SNMMI Issues New Appropriate Use Criteria for Amyloid PET and Tau PET Imaging
The appropriate use criteria (AUC) reflect updates to the 2013 AUC for amyloid PET and new criteria for tau PET in the diagnosis and monitoring of patients with mild cognitive impairment (MCI).
Teleradiology and Breast Imaging: Keys to Facilitating Personalized Service, Efficiency and Equity
In a recent interview, Arlene Sussman, M.D., discussed her experience in leading vRad’s teleradiology breast imaging service, how to foster personalized care in breast cancer screening, utilizing AI to help mitigate daunting worklists and improving access to subspecialty care.
New Survey Explores Radiologist and Neurologist Comfort Level with AI Triage for Brain MRI
Survey results revealed that 71 percent of clinicians preferred adjunctive AI in facilitating triage of brain MRI scans and 58 percent were comfortable utilizing AI triage without input from radiologists.