- Accuracy of Preoperative Imaging in Detecting Nodal Extracapsular Spread in Oral Cavity Squamous Cell Carcinoma
A group of 111 consecutive patients with untreated oral cavity squamous cell carcinoma and available preoperative imaging and subsequent lymph node dissection was studied. Twenty nine subjects had radiographically determined extracapsular spread. Imaging sensitivity and specificity for extracapsular spread were 68% and 88%, respectively. Necrosis, irregular borders, and gross invasion were independently correlated with pathologically proved extracapsular spread.
- Temporal Bone CT: Improved Image Quality and Potential for Decreased Radiation Dose Using an Ultra-High-Resolution Scan Mode with an Iterative Reconstruction Algorithm
Patients with baseline temporal bone CT scans acquired by using a z-axis ultra-high-resolution protocol and a follow-up scan by using the ultra-high-resolution–iterative reconstruction technique were identified. Images of left and right temporal bones were reconstructed in the axial, coronal, and Poschl planes. Spatial resolution was comparable (Poschl) or slightly better (axial and coronal planes) with ultra-high-resolution–iterative reconstruction than with z-axis ultra-high-resolution. Paired t test indicated that noise was significantly lower with ultra-high-resolution–iterative reconstruction than with z-axis ultra-high-resolution.
- Acute Invasive Fungal Rhinosinusitis: A Comprehensive Update of CT Findings and Design of an Effective Diagnostic Imaging Model
Two blinded neuroradiologists retrospectively graded 23 prespecified imaging abnormalities in the craniofacial region on CT examinations from 42 patients with pathology-proven acute invasive fungal rhinosinusitis and 42 control patients. A 7-variable model (periantral fat, bone dehiscence, orbital invasion, septal ulceration, pterygopalatine fossa, nasolacrimal duct, and lacrimal sac) was synthesized on the basis of multivariate analysis. The presence of abnormality involving a single variable in the model had an 87% positive predictive value, 95% negative predictive value, 95% sensitivity, and 86% specificity.
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