Diagnostic Protocol for Detecting Otosclerosis on High-Resolution Temporal Bone CT

Ultra-high-resolution CT of the temporal bone: Comparison between deep learning reconstruction and hybrid and model-based iterative reconstruction

PURPOSE

The purpose of this study was to evaluate the ability of ultra-high-resolution computed tomography (UHR-CT) to assess stapes and chorda tympani nerve anatomy using a deep learning (DLR), a model-based, and a hybrid iterative reconstruction algorithm compared to simulated conventional CT.

MATERIALS AND METHODS

CT acquisitions were performed with a Mercury 4.0 phantom. Images were acquired with a 1024 × 1024 matrix and a 0.25 mm slice thickness and reconstructed using DLR, model-based, and hybrid iterative reconstruction algorithms. To simulate conventional CT, images were also reconstructed with a 512 × 512 matrix and a 0.5 mm slice thickness. Spatial resolution, noise power spectrum, and objective high-contrast detectability were compared. Three radiologists evaluated the clinical acceptability of these algorithms by assessing the thickness and image quality of the stapes footplate and superstructure elements, as well as the image quality of the chorda tympani nerve bony and tympanic segments using a 5-point confidence scale on 13 temporal bone CT examinations reconstructed with the four algorithms.

RESULTS

UHR-CT provided higher spatial resolution than simulated conventional CT at the penalty of higher noise. DLR and model-based iterative reconstruction provided better noise reduction than hybrid iterative reconstruction, and DLR had the highest detectability index, regardless of the dose level. All stapedial structure thicknesses were thinner using UHR-CT by comparison with conventional simulated CT (P < 0.009). DLR showed the best visualization scores compared to the other reconstruction algorithms (P < 0.032).

CONCLUSION

UHR-CT with DLR results in less noise than UHR-CT with hybrid iterative reconstruction and significantly improves stapes and tympanic chorda tympani nerve depiction compared to simulated conventional CT and UHR-CT with iterative reconstruction.

Utility of machine learning for identifying stapes fixation on ultra-high-resolution CT

PURPOSE

Imaging diagnosis of stapes fixation (SF) is challenging owing to a lack of definite evidence. We developed a comprehensive machine learning (ML) model to identify SF on ultra-high-resolution CT.

MATERIALS AND METHODS

We retrospectively enrolled 109 participants (143 ears) and divided them into the training set (115 ears) and test set (28 ears). Stapes mobility (SF or non-SF) was determined by surgical inspection. In the ML analysis, rectangular regions of interest were placed on consecutive axial slices in the training set. Radiomic features were extracted and fed into the training session. The test set was analyzed using 7 ML models (support vector machine, k nearest neighbor, decision tree, random forest, extra trees, eXtreme Gradient Boosting, and Light Gradient Boosting Machine) and by 2 dedicated neuroradiologists. Diagnostic performance (sensitivity, specificity and accuracy, with surgical findings as the reference) was compared between the radiologists and the optimal ML model by using the McNemar test.

RESULTS

The mean age of the participants was 42.3 ± 17.5 years. The Light Gradient Boosting Machine (LightGBM) model showed the highest sensitivity (0.83), specificity (0.81), accuracy (0.82) and area under the curve (0.88) for detecting SF among the 7 ML models. The neuroradiologists achieved good sensitivities (0.75 and 0.67), moderate-to-good specificities (0.63 and 0.56) and good accuracies (0.68 and 0.61). This model showed no statistical differences with the neuroradiologists (P values 0.289-1.000).

CONCLUSIONS

Compared to the neuroradiologists, the LightGBM model achieved competitive diagnostic performance in identifying SF, and has the potential to be a supportive tool in clinical practice.

Do CT values change over time and correlate with hearing in the non-surgical ears of otosclerosis patients?

BACKGROUND

High-resolution computed tomography (HRCT) is often used to diagnose otosclerosis.

AIMS/OBJECTIVES

To investigate whether CT values change over time and correlate with hearing in the non-surgical ears of otosclerosis patients.

MATERIALS AND METHODS

32 patients with bilateral otosclerosis who had undergone unilateral stapedectomy were enrolled in the study. HRCT examination and pure tone audiometry were performed before and after the surgery. CT values of different regions of interest (ROIs) were measured manually and the data were collected for analysis.

RESULTS

The CT value of anterior to the inner auditory meatus (AIAM) decreased by 88.5 HU (p < .05), and the changes in CT values in other ROIs showed no statistical difference. Regarding hearing, the value of air bone gap (ABG) increased by 3.6 dB (p = .020), and the average hearing deterioration rate of ABG was 3.1 dB/year. The CT value of the mid-point of the stapes footplate (MPSF) showed a certain correlation with the change of ABG (p < .05).

CONCLUSIONS AND SIGNIFICANCE

The CT value of AIAM may change over time. The overall hearing of non-surgical ears in otosclerosis patients shows a deteriorating trend. Moreover, the changes in the CT value of MPSF may be related to the hearing, which needs further research.

Does otosclerosis affect the dimensions of the facial canal and cochlear aquaduct?

PURPOSE

Our aim was to evaluate the relationship of the dimensions of the facial canal (FC) and cochlear aqueduct (CA) in otosclerosis (OS) with the type and severity of OS.

METHODS

Two radiologists retrospectively evaluated temporal bone high-resolution computed tomography (HRCT) images obtained from 48 healthy individuals and 94 OS patients between January 2015 and July 2020. In the study group, the CA width, funnel base width, and funnel length, in addition to the FC transverse length, were measured in the axial plane. The CA length was measured in the coronal plane on HRCT images. The FC craniocaudal length was measured in the same plane as the fissula ante fenestram (FAF) in coronal reformatted HRCT images. Grading of OS was based on otosclerotic plaque density and new bone formation extending toward the tympanic cavity at the FAF level.

RESULTS

In the OS patients, the CA width and FC craniocaudal and FC transverse diameters were significantly decreased on both sides compared to those in the control group (p < 0.001). In fenestral OS, the FC craniocaudal and transverse widths on both sides were statistically significantly lower than the FC widths in the control group (p < 0.0001). A statistically negative correlation was found in the FC craniocaudal (r = - 0.831/- 0.818) and transverse (r = - 0.742/- 0.750) measurements on both sides in accordance with an increase in the otosclerotic plaque density (p < 0.0001).

CONCLUSION

The presence of narrowing in the FC and CA adjacent to the FAF supports the role of autoimmunity theory in the etiology of OS.

Imaging Studies in Otosclerosis: An Up-to-date Comprehensive Review

Introduction  Otosclerosis is a primary osteodystrophy of the otic capsule, frequently responsible for acquired hearing loss in adults. Although the diagnostic value of imaging investigations in otosclerosis is debatable, they might still be employed with different goals within the context of the disease.

Objectives  The present paper aims to review the most recent literature on the use of imaging studies in otosclerosis for the most varied purposes, from routine application and differential diagnosis to prognostic prediction and investigation of surgical failure.

Data Synthesis  The diagnosis of otosclerosis is usually clinical, but computed tomography (CT) is paramount in particular cases for the differential diagnosis. The routine use, however, is not supported by strong evidence. Even so, there is growing evidence of the role of this method in surgical planning and prediction of postoperative prognosis. In specific scenarios, for example when superior semicircular canal dehiscence (SSCD) syndrome is suspected or in surgical failure, CT is crucial indeed. Magnetic resonance imaging (MRI), however, has limited – although important – indications in the management of individuals with otosclerosis, especially in the evaluation of postoperative complications and in the follow-up of medical treatment in active ostosclerosis.

Conclusion  Imaging studies have a broad range of well-established indications in otosclerosis. Besides, although the routine use of CT remains controversial, the most recent papers have shed light into new potential benefits of imaging prior to surgery.