April 19th 2024
Examining current trends in brain cancer diagnostics, these authors discuss diagnostic imaging advances, pathways with adaptive radiotherapy and the ongoing quest to provide optimal precision with dosimetry.
Revolutionizing Early-Stage NSCLC Treatment: Pathologists’ Key Insights into Predicting Pathologic Responses to Immunotherapies
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Medical Crossfire®: Critical Questions on Diagnosis, Sequencing, and Selection of Systemic and Radioligand Therapy Options for Patients with GEP-NETs
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Medical Crossfire®: Expert Exchanges to Maximize Clinical Outcomes for Patients with CRPC Through Evidence-Based Personalized Therapy
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23rd Annual International Congress on the Future of Breast Cancer® West
July 12-13, 2024
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25th Annual International Lung Cancer Congress®
July 25-27, 2024
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2023 ASCO Direct™ Highlights: Practice-Changing Data From the Leading Oncology Conference
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6th Annual Precision Medicine Symposium: An Illustrated Tumor Board
October 18-19, 2024
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Community Practice Connections™: 24th Annual International Lung Cancer Congress®
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Study of Ofatumumab for Multiple Sclerosis Shows 'Profoundly Suppressed MRI Lesion Activity'
The use of continuous ofatumumab in patients within three years of a relapsing multiple sclerosis diagnosis led to substantial reductions in associated lesions on brain MRI scans, according to research recently presented at the American Academy of Neurology (AAN) conference.
Emerging PET Agent Gets FDA Fast Track Designation for Glioma Imaging
A positron emission tomography (PET) agent that targets LAT1 and LAT2 membrane transport proteins, TLX101-CDx or 18F-floretyrosine could be utilized to help characterize progressive or recurrent glioma.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
MRI-Based AI Model Shows Promise in Predicting Lymph Node Metastasis with Breast Cancer
For the prediction of axillary lymph node metastasis in patients with breast cancer, an MRI-based, 4D convolutional neural network model demonstrated an AUC of 87 percent and sensitivity of 89 percent, according to new research.
Improving the Quality of Breast MRI Acquisition and Processing
Discussing findings from a new study presented at the Society for Breast Imaging (SBI) conference, Shahrzad Tavana, M.D., detailed the significant impact of training sessions for MRI technologists in improving breast positioning, optimal field of view and accuracy of sequence submissions to PACS for breast MRI exams.
AI Adjudication Bolsters Chest CT Assessment of Lung Adenocarcinoma
The inclusion of simulated adjudication for resolving discordant nodule classifications in a deep learning model for assessing lung adenocarcinoma on chest CT resulted in a 12 percent increase in sensitivity rate.
New Research Examines Socioeconomic Factors with Mammography No-Shows
Patients with Medicaid or means-tested insurance were over 27 percent more likely to miss mammography appointments, and only 65 percent of women with three of more adverse social determinants of health had a mammography exam in a two-year period covering 2020 and 2021, according to new research and a report from the CDC.
Mammography-Based AI Abnormality Scoring May Improve Prediction of Invasive Upgrade of DCIS
Emerging research suggests that an artificial intelligence (AI) score of 75 or greater for mammography abnormalities more than doubles the likelihood of invasive upgrade of ductal carcinoma in situ (DCIS) diagnosed with percutaneous biopsy.