Photon-counting CT-optimized features with the OmniTom Elite system include 30 cm field of view scanning, continuous spiral scanning, and an ultra-high-resolution capability of 0.141 mm resolution.
The Food and Drug Administration (FDA) has granted 510(k) clearance for the latest version of the OmniTom Elite system, which has been enhanced with photon-counting CT (PCCT) technology.
The PCCT-optimized features of the device range from advanced image processing and an expanded scope of scanning to helical scanning capability, according to NeuroLogica, a subsidiary of Samsung that manufactures the OmniTom Elite system.
The enhanced OmniTomElite computed tomography (CT) system offers a variety of photon-counting CT features including an ultra-high resolution mode with 0.141 mm resolution and expanded scanning to capture a 30 cm field of view. (Image courtesy of NeuroLogica.)
NeuroLogica said key benefits include access to 0.141 mm resolution with the system’s ultra-high resolution mode, post-reconstruction features such as bone removal and virtual non-contrast, continuous spiral scanning capability and expanded scanning to capture a 30 cm field of view.
“With these new features, the OmniTom® Elite PCD not only offers exquisite image quality and diagnostic capabilities but also ensures a more versatile and efficient imaging process. This is a significant advancement for point-of-care imaging, continuing our commitment to enable clinicians to make a more confident diagnosis due to the improved clinical information,” noted Renaud Maloberti, the vice president and head of mCT business at NeuroLogica.
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.