That old saying, "kill two birds with one stone" (or the People for the Ethical Treatment of Animals version, "feed two birds with one scone") is particularly appropriate for CT imaging these days, as clinicians explore the opportunistic use of the modality. Millions of CT scans are performed each year -- often for lung cancer screening, but also as a first-line test when a patient presents in the emergency room -- and information from these tests can shed light on other conditions.
At the RSNA meeting, attendees will hear animated discussion on the opportunistic use of CT imaging, including, for example, how it can provide information on a patient's bone mineral density, catch pancreatic ductal adenocarcinoma earlier, and predict the presence of coronary artery disease by measuring epicardial fat volume.
A key theme at the conference this year will be the use of CT with AI. Researchers are exploring the combination for the analysis of bone and muscle loss in chronic obstructive pulmonary disease (COPD), for coronary artery disease risk assessment, and for predicting future major cardiovascular events by measuring carotid plaque and body composition data.
Other themes will include photon-counting CT, or PCCT -- look for research that evaluates how it can improve image quality and thus improve reader confidence -- and the state of lung cancer screening, especially how to increase uptake and make it more effective (spoiler alert: multidisciplinary review of low-dose CT scans appears to reduce incidence of interval imaging).
The RSNA will also host "hot topic" educational sessions, including one that will investigate the use of multi-energy CT in the emergency room and another that will outline the current state of cardiac CT.
CT is a proverbial workhorse when it comes to patient care, and the RSNA meeting will highlight its potential for new indications. For more information on the presentations we're highlighting below and other abstracts, check out the RSNA 2024 meeting program.
Algorithms analyze multipathway bone and muscle loss in COPD
Sunday, December 1 | 9:10 a.m.-9:20 a.m. | S1-SSCH01-2 | Room E451A
Computing thoracic bone and muscle metrics in patients with chronic obstructive pulmonary disease (COPD) improves understanding of the role of certain comorbidities in COPD disease progression, according to findings to be announced in this scientific presentation.
CT imaging for pneumonia diagnosis increases among elderly
Sunday, December 1 | 9:20 a.m.-9:30 a.m. | S1-SSCH01-3 | Room E451A
The accessibility of chest CT has improved, and this trend has contributed to increased use of the exam to diagnose pneumonia in elderly patients, according to research to be presented Sunday morning.
First PANORAMA findings support AI-based opportunistic screening
Sunday, December 1 | 10:40 a.m.-10:50 a.m. | S2-SSGI01-2 | Room E451B
Transparently benchmarked, expert AI can enable opportunistic screening to start catching pancreatic ductal adenocarcinoma (PDAC) on contrast-enhanced computed tomography (CECT) at earlier stages, according to first results of the PANORAMA (Pancreatic cancer diagnosis: Radiologists meet AI) study.
French researchers test PE triage tool with surveillance CTs
Sunday, December 1 | 10:50 a.m.-11:00 a.m. | S2-SSRO01-3 | Room E451B
In this scientific presentation, researchers will describe AI's capability to spot an incidental pulmonary embolism on surveillance CT scans of cancer patients.
Ultrahigh-resolution CTPA improves reader confidence
Sunday, December 1 | 11:45 a.m.-12:15 p.m. | S3A-SPCH-1 | Learning Center
Ultrahigh-resolution photon-counting CT (PCCT) pulmonary angiography improves not only image quality but also reader confidence, German researchers have found.
AI can perform coronary artery disease risk stratification
Sunday, December 1 | 3:20 p.m.-3:30 p.m. | S5-SSCA02-5 | Room E353C
In this Trainee Research Prize-winning presentation, researchers will review an AI model for coronary artery disease (CAD) risk stratification on CT myocardial perfusion imaging (MPI) and coronary computed tomography angiography (CCTA).
AI improves coronary artery volume quantification on chest CT
Monday, December 2 | 9:00 a.m.-9:30 a.m. | M2-SPCA-5 | Learning Center
Using AI with chest CT scans improves quantification of coronary artery calcium (CAC) volume, Texas researchers have found.
Radiomics model predicts future symptomatic carotid plaque
Monday, December 2 | 10:20 a.m.-10:30 a.m. | M3-SSNR04-6 | Room S406B
A deep learning-based radiomics model based on dual-energy computed tomography (DECT) may effectively predict symptomatic carotid plaque in asymptomatic conditions, according to findings to be presented in this neuroradiology scientific session.
Lung-RADS review identifies radiologist 'blind spots'
Monday, December 2 | 12:15 p.m.-12:45 p.m. | M5A-SPCH-4 | Learning Center
A review of the Lung-RADS v2022 metric has revealed radiologist "blind spots" when it comes to catching lung cancer on screening CT, according to findings to be presented Monday afternoon.
CAC results on CT imaging could reduce cardiovascular disease mortality
Tuesday, December 3 | 9:00 a.m.-9:30 a.m. | T2-SPCH-5 | Learning Center
CT lung cancer screening coronary artery calcification results could decrease morbidity and mortality from cardiovascular events, University of Rochester Medical Center researchers have found.
CT body composition AI tool predicts MACE
Wednesday, December 4 | 8:20 a.m.-8:30 a.m. | W1-SSNPM03-3 | Room S402
For this scientific session, Harvard researchers applied an AI-based body composition algorithm to 1,277 emergency abdominal CT exams from people in their 30s for the purpose of predicting major adverse cardiovascular events (MACE) and dyslipidemia.
Large study finds benefit for AI in acute pulmonary embolism
Wednesday, December 4 | 9:40 a.m.-9:50 a.m. | W3-SSIN06-02 | Room E450B
AI can assist radiologists in detecting acute cases of pulmonary embolism (PE), according to the results of a large, prospective study.
Multidisciplinary review of LCS CT scans reduces interval imaging
Wednesday, December 4 | 3:00 p.m.-3:10 p.m. | W7-SSCH07-1 | Room E451A
Multidisciplinary review of lung cancer screening (LCS) CT scans that indicate high risk of disease decreases unnecessary interval imaging and supports more rapid lung cancer diagnosis, according to research to be presented Wednesday afternoon.
CT-measured epicardial fat volume predicts presence of coronary artery disease
Wednesday, December 4 | 3:10 p.m.-3:20 p.m. | W7-SSCA08-2 | Room E353C
Measuring epicardial fat volume on CT imaging helps predict the presence of obstructive coronary artery disease and the occurrence of major adverse cardiovascular events, according to research to be presented Wednesday afternoon.
Chest CT quantitative metrics plus AI predict low bone mineral density
Thursday, December 5 | 8:30 a.m.-8:40 a.m. | R4-SSCH09-4 | Room E451A
In this Thursday morning session, researchers will describe how quantitative metrics extracted from chest CT scans using AI can be integrated with machine-learning algorithms to predict low bone mineral density.
Body composition analysis foretells survival in esophageal cancer patients
Thursday, December 5 | 11:40 a.m.-11:50 a.m. | R4-SSCH10-6 | Room E451A
Automated 3D body composition CT analysis software can predict shorter survival in patients with esophageal cancer, according to this scientific presentation.