Imaging with FDG PET/CT may identify children and young adult osteosarcoma patients who may experience good outcomes.
Clinician may identify which osteosarcoma patients may have a good outcome through FDG PET/CT imaging at regular intervals, according to a study published in the Journal of Nuclear Medicine.
Researchers from Tennessee, Texas, and California sought to determine the relationship of 18F-FDG uptake in the primary tumor at diagnosis of children and young adults with osteosarcoma (OS) during therapy, and after therapy with a histologic response and event-free survival.
Thirty-four newly diagnosed OS patients, 17 male, were included in the study. The patients’ median age was 12.2 years. Twenty-five of the patients (74 percent) had localized disease. Primary tumor locations were:
• Femur in 17 patients (50 percent)
• Tibia in nine patients (26 percent)
• Humerus in five patients (15 percent)
Baseline 18F-FDG PET/CT imaging was performed with all patients and repeated at five and 10 weeks after start of therapy. Whole-body images were obtained approximately one hour after injection of 18F-FDG. Logistic regression was used to study the association of tumor uptake and changes in SUVmax between zero, five, and 10 weeks for both clinical endpoints.
The results showed that SUVmax at five weeks and 10 weeks, and percentage change from baseline at 10 weeks were highly predictive of a histologic response. Using SUVmax of 4.04 at week five, SUVmax of 3.15 at week 10, and 60 percent decrease from baseline at week 10 as cutoff values, the researchers determined that the respective sensitivities were 0.93, 0.93, and 0.79 and that the respective specificities were 0.53, 0.71, and 0.76.
The researchers concluded that SUVmax on routine images at five or 10 week and percentage change in SUVmax from baseline to week 10 were metabolic predictors of a histologic response in OS. “These findings may be useful in the early identification of patients who are responding poorly to therapy and may benefit from a change in treatment,” they wrote.
Photon-Counting Computed Tomography: Eleven Takeaways from a New Literature Review
May 27th 2025In a review of 155 studies, researchers examined the capabilities of photon-counting computed tomography (PCCT) for enhanced accuracy, tissue characterization, artifact reduction and reduced radiation dosing across thoracic, abdominal, and cardiothoracic imaging applications.
Can AI Predict Future Lung Cancer Risk from a Single CT Scan?
May 19th 2025In never-smokers, deep learning assessment of single baseline low-dose computed tomography (CT) scans demonstrated a 79 percent AUC for predicting lung cancer up to six years later, according to new research presented today at the American Thoracic Society (ATS) 2025 International Conference.
Can Emerging AI Software Offer Detection of CAD on CCTA on Par with Radiologists?
May 14th 2025In a study involving over 1,000 patients who had coronary computed tomography angiography (CCTA) exams, AI software demonstrated a 90 percent AUC for assessments of cases > CAD-RADS 3 and 4A and had a 98 percent NPV for obstructive coronary artery disease.