Metabolic imaging with FDG-PET is an alternative to morphologic MR imaging for detecting metastatic lymph nodes in patients with cervical cancer.

The aim of this study was to evaluate and compare the diagnostic accuracy, the inter-rater agreement and raters’ certainty of cone beam computed tomography (CBCT) and radiography for the detection of scaphoid fractures. Our hypothesis is that the CBCT has a higher diagnostic accuracy for scaphoid fractures than radiography. We retrospectively analysed patients who underwent both radiography and CBCT examinations within 4 days to rule out a scaphoid fracture over a 2-year period in our institution. 4 blinded radiologists and orthopaedic surgeons independently rated the images regarding the presence of a scaphoid fracture. The reference standard was evaluated by two radiologists in a consensus reading. Inter-rater correlation was evaluated, pooled sensitivity, specificity, positive and negative predictive values were calculated and compared. 102 patients met the inclusion criteria. 52% of them had a scaphoid fracture. The inter-rater correlation was higher in the CBCT compared to radiography (P < 0.001). Sensitivity, specificity, positive and negative predictive values were higher for CBCT than for radiography (P < 0.019). Observers’ fracture classifications showed a higher correlation with the reference standard in the CBCT. Observers’ certainty for fracture detection and classification were higher in the CBCT. CBCT shows a higher diagnostic accuracy for scaphoid fractures than radiography.

Contrast agent‐enhanced magnetic resonance (MR) mammography is a highly sensitive method in breast cancer detection. The inflow of contrast agent is tracked to classify tissue as malignant or benign. In this article, we introduce approaches to overcome two of the most prominent problems in MR mammography: (a) variability in contrast agent dynamics, and (b) motion of the patient during data acquisition. The variability of contrast agent dynamics is considered using data‐driven analysis based on self‐organizing maps. Motion during data acquisition is handled by means of a fast local elastic matching algorithm. © 1999 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 10, 199–206, 1999

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