Diagnostic Imaging sat down with medical physicist and CT expert Cynthia H. McCollough, PhD, to learn more about the history of CT and its expanding potential in medical imaging.
Despite what has already been an illustrious career in health care, now is not the time to sleep on computed tomography (CT). Fifty years in, CT remains a cornerstone of medical imaging, aiding not only in diagnosis of disease or trauma, but also in helping to plan and guide therapeutic interventions as well as monitor their outcomes.
Withstanding the test of time and new technology, CT has also weathered bouts of criticism over the years. Although questions about overuse and radiation dose exposure have at times hindered its role, the risk/benefit ratio conversation nearly always tips towards the benefits of the modality, with its ability to quickly answer questions that might otherwise lead providers and patients down a road filled with a multitude of less specific—and so-called less ‘risky’—tests.
To help address some of these questions and improve education around dose, the American Association of Physicists in Medicine (AAPM) in 2010 formed the Alliance for Quality Computed Tomography, which provides several educational and informational resources, including a CT Dose-Check, up-to-date CT imaging protocols for both adult and pediatric patients, as well as CT dose and automatic exposure control educational materials.
To learn more about the history of CT and how to optimize its current use, Diagnostic Imaging spoke with Cynthia H. McCollough, PhD, Brooks-Hollern Professor and professor of medical physics and biomedical engineering at Mayo Clinic. McCollough, who is also director, CT Clinical Innovation Center and X-ray Imaging Core, discussed how CT is currently utilized and highlighted the many ways we can optimize its use in different clinical scenarios, especially when taking into account the technology that allows us to personalize the experience for each patient.
In further commemoration of the anniversary, McCollough helped to put together an online gallery through the AAPM that illustrates the amazing history of CT. View the gallery here.
What is the Best Use of AI in CT Lung Cancer Screening?
April 18th 2025In comparison to radiologist assessment, the use of AI to pre-screen patients with low-dose CT lung cancer screening provided a 12 percent reduction in mean interpretation time with a slight increase in specificity and a slight decrease in the recall rate, according to new research.
The Reading Room: Racial and Ethnic Minorities, Cancer Screenings, and COVID-19
November 3rd 2020In this podcast episode, Dr. Shalom Kalnicki, from Montefiore and Albert Einstein College of Medicine, discusses the disparities minority patients face with cancer screenings and what can be done to increase access during the pandemic.
Can CT-Based AI Radiomics Enhance Prediction of Recurrence-Free Survival for Non-Metastatic ccRCC?
April 14th 2025In comparison to a model based on clinicopathological risk factors, a CT radiomics-based machine learning model offered greater than a 10 percent higher AUC for predicting five-year recurrence-free survival in patients with non-metastatic clear cell renal cell carcinoma (ccRCC).
Could Lymph Node Distribution Patterns on CT Improve Staging for Colon Cancer?
April 11th 2025For patients with microsatellite instability-high colon cancer, distribution-based clinical lymph node staging (dCN) with computed tomography (CT) offered nearly double the accuracy rate of clinical lymph node staging in a recent study.