A prospective trial involving 75 patients from six Dutch hospitals recommends whole-body FDG-PET over conventional scintigraphy for uncovering the cause of fevers of unknown origin.
A prospective trial involving 75 patients from six Dutch hospitals recommends whole-body FDG-PET over conventional scintigraphy for uncovering the cause of fevers of unknown origin.
The test promises to fill a gap in the diagnostic armamentarium, according to lead researcher Dr. W.J. Oyen, a nuclear physician at Nijmegen Medical Center in the Netherlands, reporting at the Society of Nuclear Medicine meeting in San Diego. Until the emergence of FDG-PET, half of all patients with fevers of unknown origin went undiagnosed despite extensive workup.
FDG-PET contributed to a final diagnosis in half of the 70 cases that could be evaluated, Oyen said. Patients were drawn from one university and five general community hospitals. Fevers were at least 38 degrees C and had persisted for at least three weeks. Whole-body FDG-PET was performed after chest x-ray, abdominal ultrasound, and a cryoglobulin blood test failed to definitively identify the fever's origin.
The positive and negative predictive values of the test were 70% and 95%, respectively, for focal disease. The mechanism of action for FDG-PET in these cases is most likely the high rate of glycolysis among neoplastic and activated inflammatory cells that cause fever.
PET was clinically helpful in 70% of the cases where it produced a positive result, and it contributed to the ultimate diagnosis in 33%. It was more useful for continuous fever than for periodic bouts, although results still favor its use in both situations because of its high negative predictive value. Clinicians can boost the efficacy of FDG-PET by excluding patients with a normal erythrocyte mentation rate or C-reactive protein. Positive FDG-PET findings never arose under those conditions.
We consider FDG-PET a valuable part of a structured diagnostic protocol in patients with fever of an unknown origin for both university and community hospitals, Oyen said.
MRI-Based AI Radiomics Model Offers 'Robust' Prediction of Perineural Invasion in Prostate Cancer
July 26th 2024A model that combines MRI-based deep learning radiomics and clinical factors demonstrated an 84.8 percent ROC AUC and a 92.6 percent precision-recall AUC for predicting perineural invasion in prostate cancer cases.
Breast MRI Study Examines Common Factors with False Negatives and False Positives
July 24th 2024The absence of ipsilateral breast hypervascularity is three times more likely to be associated with false-negative findings on breast MRI and non-mass enhancement lesions have a 4.5-fold likelihood of being linked to false-positive results, according to new research.
Can Polyenergetic Reconstruction Help Resolve Streak Artifacts in Photon Counting CT?
July 22nd 2024New research looking at photon-counting computed tomography (PCCT) demonstrated significantly reduced variation and tracheal air density attenuation with polyenergetic reconstruction in contrast to monoenergetic reconstruction on chest CT.