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.
December 9th 2024
Do we get mired in the rut of generational grumbling, or do we reframe resentments into perspective of what we have overcome?
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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19th Annual New York Lung Cancers Symposium®
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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) 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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(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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43rd Annual CFS: Innovative Cancer Therapy for Tomorrow®
November 12-14, 2025
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20th Annual New York Lung Cancers Symposium®
November 15, 2025
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Adjunctive AI Leads to 16 Percent Increase in CT Sensitivity for Incidental Pulmonary Embolism
June 20th 2024Artificial intelligence facilitated a 96.2 percent sensitivity rate for incidental pulmonary embolism (IPE) on contrast-enhanced CT chest or abdomen exams, according to new prospective research involving over 4,300 patients.
SNMMI: Can Ultra-Low Dose PET Supplant the Need for CT Attenuation Correction?
June 11th 2024Ultra-low dosing with long axial field-of-view positron emission tomography (PET) scanners facilitates qualitative PET imaging at a more than 50 percent reduction of conventional radiation dosing with PET, according to new research presented at the SNMMI 2024 conference.
Nanox Adds AI Applications to Teleradiology Platform for CT Second Opinions
Published: June 7th 2024 | Updated: June 7th 2024Facilitating additional consultation on chest and abdominal CT scans, the Second Opinions teleradiology platform now features FDA-cleared AI tools for cardiac, bone and liver assessments.
Large CT Study Shows Benefits of AI in Predicting CV Risks in Patients Without Obstructive CAD
June 3rd 2024An AI algorithm that incorporates scoring of coronary inflammation based on coronary CT angiography (CCTA) may enhance long-term cardiovascular risk stratification beyond conventional risk factor and imaging assessments, even in patients without obstructive CAD.
CT-Based AI Model May Enhance Prediction of Lung Cancer Recurrence
May 30th 2024An AI model that includes extracted radiomic features from CT scans more than doubled the sensitivity rate for preoperative prediction of lung cancer recurrence in comparison to traditional TNM staging, according to study findings to be presented at the 2024 American Society of Clinical Oncology (ASCO) Annual Meeting in Chicago.
Qure.ai to Debut Multimodality AI Platform for Lung Cancer Imaging at ASCO 2024
May 29th 2024In addition to detecting missed lung nodules on X-rays, the AI-powered Qure.ai lung cancer continuum platform reportedly automates lung nodule measurement on CT scans and facilitates multimodality reporting.
Can Deep Learning Models Improve CT Differentiation of Small Solid Pulmonary Nodules?
May 29th 2024One deep learning model had a 72.4 percent accuracy rate for differentiating between benign and malignant solid pulmonary nodules on non-contrast CT while another deep learning model demonstrated an 87.1 percent AUC for differentiating benign and inflammatory findings.
CT-Based Fractional Flow Reserve Analysis Improves Five-Year Outcomes After Major Vascular Surgery
May 24th 2024For patients with no history of coronary artery disease (CAD), new research shows the use of CT-derived fractional flow reserve (FFR-CT) guided revascularizations after elective vascular surgery reduced myocardial infarction and all-cause death by 20 percent in comparison to standard care.
AI-Based Denoising for Neck CT May Facilitate Reductions in Radiation Dosing
May 23rd 2024Image quality, sharpness, and contrast with AI-based denoising were significantly enhanced for neck CT in comparison to conventional CT image reconstruction at 100 percent and 50 percent mAs, according to newly published research.
Multicenter CT Study Shows Benefits of Emerging Diagnostic Model for Clear Cell Renal Cell Carcinoma
May 15th 2024Combining clinical and CT features, adjunctive use of a classification and regression tree (CART) diagnostic model demonstrated AUCs for detecting clear cell renal cell carcinoma (ccRCC) that were 15 to 22 percent higher than unassisted radiologist assessments.
CT Study: AI Algorithm Comparable to Radiologists in Differentiating Small Renal Masses
May 14th 2024An emerging deep learning algorithm had a lower AUC and sensitivity than urological radiologists for differentiating between small renal masses on computed tomography (CT) scans but had a 21 percent higher sensitivity rate than non-urological radiologists, according to new research.
What a New Meta-Analysis Reveals About Fractional Flow Reserve Assessment with Computed Tomography
Published: May 13th 2024 | Updated: May 13th 2024While acknowledging variable accuracy overall with CT-derived fractional flow reserve (FFR-CT) values, researchers found that the accuracy rate increased to 90 percent for FFR-CT values greater > 0.90 and < 0.49.
Study Finds High Concordance Between AI and Radiologists for Cervical Spine Fractures on CT
May 6th 2024Researchers found a 98.3 percent concordance between attending radiology reports and AI assessments for possible cervical spine fractures on CT, according to new research presented at the 2024 ARRS Annual Meeting.