NaF-PET Imaging Helps Evaluate Prostate Cancer Treatment
Using NaF-PET to evaluate prostate cancer progression and evidence of osseous metastases allows clinicians to change treatment plans.
Using PET imaging with sodium fluoride (NaF) allowed clinicians to evaluate treatment progress and progression of osseous metastases among patients with prostate cancer, changing treatment if appropriate, according to a study published in the Journal of Nuclear Medicine.
Researchers from the Massey Cancer Center at Virginia Commonwealth University in Richmond sought to determine if the PET imaging was an effective measurement of prostate cancer treatment compared with bone scintigraphy. The National Oncologic PET Registry (NOPR) developed a NaF-PET registry built on the foundation of its prior registry for PET with 18F-FDG. Men with prostate cancer represented 72 percent of the cases.
Prospective data were collected before and after testing with NaF-PET among men aged 65 or older: 1,024 men for initial staging (IS), 1,997 with suspected first osseous metastasis (FOM) and 510 who had suspected progression of osseous metastasis (POM).
In reviewing the findings, the researchers noted the referring physicians said they would have used other advanced imaging, such as CT, MRI or 18F-FDG to assess the patients had NaF-PET not been available in about half the cases.
The treatment plans were changed for more than half of all patients after the NaF-PET imaging:
Patient group
Change in treatment plan
IS
77 percent
FOM
52 percent
POM
71 percent
When intended management was classified as either treatment or nontreatment, the overall change in intended management ranged from 44 percent to 52 percent and from 12 percent to 16 percent if no effect was assumed for those cases with pre-PET plans for other imaging (imaging-adjusted impact).
Interpreting physicians findings:
Patient group
Definite findings of bone metastasis
IS
14 percent
FOM
29 percent
POM
76 percent
The NaF-PET had a “high overall impact, principally related to its effect on replacing intended use of other advanced imaging,” the authors concluded. “Its imaging-adjusted impact was similar to that observed with 18F-FDG PET for restaging or suspected recurrence in other cancer types.”
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.
