The Diagnostic Imaging CT modality focus page provides information, videos, podcasts, and the latest news about industry product developments, trial results, screening guidelines, and protocol guidance that touch on the use of CT across the healthcare continuum, from various cancer screenings, such as lung and colon, to cardiothoracic imaging, to appendicitis, and more.
November 20th 2024
While a large retrospective study found that interstitial lung abnormalities (ILAs) were evident on 1.7 percent of computed tomography (CT) scans, researchers found that 43.9 percent of ILAs, including fibrotic ILAs, were not reported.
19th Annual New York Lung Cancers Symposium®
November 16, 2024
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Medical Crossfire®: How Does Recent Evidence on PARP Inhibitors and Combinations Inform Treatment Planning for Prostate Cancer Now and In the Future?
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Medical Crossfire®: How Do the Experts Select and Sequence Therapies to Optimize Patient Outcomes and Quality of Life in Advanced Prostate Cancer?
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Lung Cancer Tumor Board®: Enhancing Multidisciplinary Communication to Optimize Immunotherapy in Stage I-III NSCLC
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Clinical Vignettes™: The Experts Explain How They Integrate PET Imaging into Metastatic HR+ Breast Cancer Care Settings
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School of Breast Oncology® Live Video Webcast: Clinical Updates from San Antonio
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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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2025 International Symposium of Gastrointestinal Oncology (ISGIO)
September 12-13, 2025
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Lung Cancer Tumor Board: Enhancing Precision Medicine in NSCLC Through Advancements in Molecular Testing and Optimal Therapy Selection
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(CME Credit Only) New Frontiers in Immunotherapy for SCLC: Insights From Latest Clinical Trials and Their Application in Real-World Treatment
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(MOC and CME Credit) New Frontiers in Immunotherapy for SCLC: Insights From Latest Clinical Trials and Their Application in Real-World Treatment
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(CME Credit Only) Lung Cancer Tumor Board®: The Pivotal Role of Multimodal Therapy in Leveraging Immunotherapy for Stage I-III NSCLC When the Goal Is Cure
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(MOC and CME Credit) Lung Cancer Tumor Board®: The Pivotal Role of Multimodal Therapy in Leveraging Immunotherapy for Stage I-III NSCLC When the Goal Is Cure
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Study: AI More Than Doubles the Sensitivity Rate for Lung-RADS Category 4 Nodules on Chest X-Rays
February 7th 2023In newly published research, researchers found that an artificial intelligence (AI) computer-aided detection (CAD) system was more than twice as likely as non-AI assessment to diagnose actionable lung nodules on chest X-rays.
Could Photon Counting Reduce Iodinated Contrast Media for CT Angiography?
January 27th 2023Preliminary research suggests the use of photon-counting detector computed tomography (CT) may facilitate a 25 percent reduction of iodinated contrast media (ICM) in comparison to energy-integrating detector CT for angiographic imaging of the thoracoabdominal aorta.
Could an Emerging Deep Learning Modality Enhance CCTA Assessment of Coronary Artery Disease?
January 26th 2023Employing deep learning capabilities, the DeepVessel FFR reportedly provides enhanced non-invasive evaluation of coronary arteries through semi-automated analysis of coronary computed tomography angiography (CCTA) imaging.
Deep Learning Model May Predict Lung Cancer Risk from a Single CT Scan
January 23rd 2023Trained and developed on over 35,000 low-dose computed tomography (LDCT) scans and validated in three independent data sets, a deep learning algorithm demonstrated an average area under the curve (AUC) of 90.6 percent for predicting lung cancer within one year.
ACR Offers Recommendations for Addressing 'Cost-Prohibitive' IDR Process in Radiology
January 20th 2023Noting the significant administrative fees for the Independent Dispute Resolution (IDR) process of the No Surprises Act and onerous restrictions that have led to a nearly “non-existent” use of batching of disputed claims in radiology, the American College of Radiology (ACR) has sent formal recommendations to the United States Departments of Health and Human Services, Labor, and Treasury for addressing these issues.
Nine Takeaways from New Article Examining Health Equity in the Radiology Field
January 17th 2023In a provocative new article, radiology researchers discuss the impact of social determinants of health (SDoH) upon access to care and patient outcomes, and present strategies within the realms of radiology education, research, clinical care, and innovation that may help mitigate health-care disparities.
Viz.ai Launches AI-Powered Vascular Imaging Software
January 16th 2023The artificial intelligence (AI)-enabled Viz™ Vascular Suite reportedly allows automated detection of vascular conditions, shown on computed tomography (CT) and other imaging modalities, and facilitates timely triage among interdisciplinary teams.
Can Dual-Energy CT Have an Impact in Differentiating Primary Lung Cancer and Pulmonary Metastases?
January 12th 2023In comparison to primary lung cancer, pulmonary metastases had a 33 percent higher frequency of ring-like peripheral high iodine concentration on dual-energy computed tomography (DECT), according to a new retrospective study.
Nine Takeaways from Recent Meta-Analysis on Lung Cancer Screening with Low-Dose CT
January 9th 2023From incidental findings and screening for chronic obstructive pulmonary disease (COPD) to surveillance imaging protocols and the advent of artificial intelligence (AI), the authors of a new meta-analysis examine insights and emerging trends from the last two decades of research on the use of low-dose computed tomography (CT) in lung cancer screening.