Imaging of the inferior alveolar nerve using dental-dedicated MRI at 0.55 T: Comparison of a deep learning-based accelerated sequence with a conventional sequence

The aim of this study was to investigate the feasibility of low-field dental MRI in the evaluation of the inferior alveolar nerve (IAN) and the acceleration of image acquisition with a deep learning (DL)-based sequence. Therefore, overall image quality (OIQ), image artefacts and delineation of the IAN were investigated.

In this single-centre retrospective study, we enrolled 39 patients who underwent dental MRI using a dedicated dental coil on a 0.55 T MRI system. A conventional T1-weighted gradient-echo 3D sequence and a T1-weighted gradient-echo 3D sequence with advanced DL-based reconstruction were acquired. Both sequences were evaluated for OIQ, image artefacts in and conspicuity of the IAN using a Likert scale from 1 to 5. Interrater agreement was assessed using weighted Cohen's κ coefficients. As quantitative measurements, the apparent signal-to-noise ratio (aSNR) and the diameter of the IAN were determined.

Thirty-three examinations were included, OIQ was rated higher for the accelerated sequence compared with the conventional sequence for both readers (p < 0.01). Image artefacts were lower in the accelerated sequence for both readers (p < 0.001). Accordingly, the delineation of the IAN was improved for both sides (p < 0.001) in the accelerated sequence. Interrater agreement between readers was substantial/good to almost perfect/excellent across all measures. aSNR was increased in the accelerated sequence (p < 0.001), whereas IAN diameter did not differ.

This study demonstrates that a DL-accelerated T1-weighted gradient-echo 3D sequence for dental-dedicated MRI is feasible for imaging of the IAN with improved image quality while reducing acquisition time by 50%.

Reduction of scan time and superior image quality could help establish dental-dedicated MRI as a radiation-free alternative for dentomaxillofacial imaging.