Lateral Position With Gantry Tilt Further Improves Computed Tomography Image Quality Reconstructed Using Single-Energy Metal Artifact Reduction Algorithm in the Oral Cavity

Techniques, Tricks, and Stratagems of Oral Cavity Computed Tomography and Magnetic Resonance Imaging

The oral cavity constitutes a complex anatomical area that can be affected by many developmental, inflammatory, and tumoural diseases. MultiSlice Computed Tomography (MSCT) and Magnetic Resonance Imaging (MRI) currently represent the essential and complementary imaging techniques for detecting oral cavity abnormalities. Advanced MRI with diffusion-weighted imaging (DWI) and dynamic contrast-enhanced perfusion-weighted imaging (DCE-PWI) has recently increased the ability to characterise oral lesions and distinguish disease recurrences from post therapy changes. The analysis of the oral cavity area via imaging techniques is also complicated both by mutual close appositions of different mucosal surfaces and metal artifacts from dental materials. Nevertheless, an exact identification of oral lesions is made possible thanks to dynamic manoeuvres and specific stratagems applicable on MSCT and MRI acquisitions. This study summarises the currently available imaging techniques for oral diseases, with particular attention to the role of DWI, DCE-PWI, and dynamic manoeuvres. We also propose MSCT and MRI acquisition protocols for an accurate study of the oral cavity area.

Reduction of metal artifacts from knee tumor prostheses on CT images: value of the single energy metal artifact reduction (SEMAR) algorithm

Background

To evaluate the effect of the single energy metal artifact reduction (SEMAR) algorithm with a multidetector CT (MDCT) for knee tumor prostheses.

Methods

First, a phantom of knee tumor prosthesis underwent a MDCT scan. The raw data was reconstructed by iterative reconstruction (IR) alone and IR plus SEMAR. The mean value of the CT number and the image noise were measured around the prosthesis at the stem level and articular level. Second, 95 consecutive patients with knee tumor prostheses underwent MDCT scans. The raw data were also reconstructed by the two methods. Periprosthetic structures were selected at the similar two levels. Four radiologists visually graded the image quality on a scale from 0 to 5. Additionally, the readers also assessed the presence of prosthetic complication and tumor recurrence on a same scale.

Results

In the phantom, when the SEMAR was used, the CT numbers were closer to normal value and the noise of images using soft and sharper kernel were respectively reduced by up to 77.1% and 43.4% at the stem level, and by up to 82.2% and 64.5% at the articular level. The subjective scores increased 1 ~ 3 points and 1 ~ 4 points at the two levels, respectively. Prosthetic complications and tumor recurrence were diagnosed in 66 patients. And the SEMAR increased the diagnostic confidence of prosthetic complications and tumor recurrence (4 ~ 5 vs. 1 ~ 1.5).

Conclusions

The SEMAR algorithm can significantly reduce the metal artifacts and increase diagnostic confidence of prosthetic complications and tumor recurrence in patients with knee tumor prostheses.