PET/CT colonography outperforms CT colonography for tumor staging
The assumption that CT colonography is the logical choice for pairing with optical colonoscopy to stage colorectal cancer took a hit at the RSNA meeting today. A prospective study from Europe shows that whole-body FDG-PET/CT is significantly more accurate than CT colonography for staging colorectal tumors.
The assumption that CT colonography is the logical choice for pairing with optical colonoscopy to stage colorectal cancer took a hit at the RSNA meeting today. A prospective study from Europe shows that whole-body FDG-PET/CT is significantly more accurate than CT colonography for staging colorectal tumors.
The study of 52 patients performed by Dr. Peter Veit at the University of Essen in Germany found that whole-body FDG-PET/CT colonography was 74% sensitive for T-staging, compared with a sensitivity rate for CT colonography of 52%. The results were confirmed by histopathology specimens and clinical follow-up 310 days after the initial evaluation. Veit has since joined the nuclear medicine residency program at the University of Zurich in Switzerland.
FDG-PET/CT colonography contributed to alteration of the clinical management of four patients, Veit said. In one instance, PET/CT colonography uncovered a second liver metastasis that was not detected with CT colonography alone. That finding identified the need for a second surgical session to resect the second lesion.
No significant differences in metastasis or lymph node staging were observed.
PET/CT colonography takes about seven minutes longer than the conventional 30-second PET/CT whole-body protocol for colorectal cancer staging, Veit said. Additional time is needed for pharmacological bowel relaxation and rectal water filling.
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: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
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.
