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Background and purposeThe complex anatomy of the temporal bone is difficult to understand and constitutes a challenge in the daily diagnostic routine even for experienced neuroradiologists. In the context of otoneurological (oVEMP) and preoperative diagnostics, the diagnosis of superior semicircular canal dehiscence (SSCD) is of great importance for Ear, Nose, and Throat (ENT) specialists. The gold standard for this diagnosis is a high-resolution CT (HRCT) of the temporal bone. In order to correctly diagnose SSCD, special oblique reconstructions are necessary in addition to standard (axial, coronal, sagittal) reconstructions. We evaluated the frequency of diagnosis and its location in HRCT in correlation with otoneurological examination. From this analysis, we present a new SSCD classification. This classification yields the potential of a differentiated analysis of the patient's clinical symptoms with correlation to the cross-sectional anatomy and may lead to a differentiated therapy approach.Study design and settingWe evaluated 1370 temporal bone scans of patients with residual hearing and verified 343 superior semicircular canal dehiscence (SSCD). We conducted a subgroup analysis of these 343 HRCT scans displaying a SSCD and used them as a basis to create a classification.ResultsThree location types of SSCD were identified. These were anterior type 1, superior type 2 and posterior type 3. Type 2 were significantly more frequent in both sexes. SSCD at this location can be overlooked if diagnosis is performed only in the standard axial plane, since it can only be visualized by means of double oblique reconstruction. We present a standardized reconstruction algorithm.ConclusionIn total, three types of SSCD with differing incidences can be extrapolated from the locations. Superior type 2 is the most frequent one. Both sexes are affected with roughly equal incidence. The use of standardized double oblique reconstruction algorithm ensures that all three types are diagnosed in the HRCT.

BackgroundThe postoperative imaging assessment of Cochlear Implant (CI) patients is imperative. The main obstacle is that Magnetic Resonance imaging (MR) is contraindicated or hindered by significant artefacts in most cases with CIs. This study describes an automatic cochlear image registration and fusion method that aims to help radiologists and surgeons to process pre-and postoperative 3D multimodal imaging studies in cochlear implant (CI) patients.Methods and findingsWe propose a new registration method, Automatic Cochlea Image Registration (ACIR-v3), which uses a stochastic quasi-Newton optimiser with a mutual information metric to find 3D rigid transform parameters for registration of preoperative and postoperative CI imaging. The method was tested against a clinical cochlear imaging dataset that contains 131 multimodal 3D imaging studies of 41 CI patients with preoperative and postoperative images. The preoperative images were MR, Multidetector Computed Tomography (MDCT) or Cone Beam Computed Tomography (CBCT) while the postoperative were CBCT. The average root mean squared error of ACIR-v3 method was 0.41 mm with a standard deviation of 0.39 mm. The results were evaluated quantitatively using the mean squared error of two 3D landmarks located manually by two neuroradiology experts in each image and compared to other previously known registration methods, e.g. Fast Preconditioner Stochastic Gradient Descent, in terms of accuracy and speed.ConclusionsOur method, ACIR-v3, produces high resolution images in the postoperative stage and allows for visualisation of the accurate anatomical details of the MRI with the absence of significant metallic artefacts. The method is implemented as an open-source plugin for 3D Slicer tool.

OBJECTIVES: To utilize a novel objective approach combining a software phantom and an image quality metric to systematically evaluate the influence of sinogram affirmed iterative reconstruction (SAFIRE) of multidetector computed tomography (MDCT) data on image noise characteristics and low-contrast detectability (LCD). MATERIALS AND METHODS: A low-contrast and a high-contrast phantom were examined on a 128-slice scanner at different dose levels. The datasets were reconstructed using filtered back projection (FBP) and SAFIRE and virtual low-contrast lesions (-20HU) were inserted. LCD was evaluated using the multiscale structural similarity index (MS-SIM*). Image noise texture and spatial resolution were objectively evaluated. RESULTS: The use of SAFIRE led to an improvement of LCD for all dose levels and lesions sizes. The relative improvement of LCD was inversely related to the dose level, declining from 208%(±37%), 259%(±30%) and 309%(±35%) at 25mAs to 106%(±6%), 119%(±9%) and 123%(±8%) at 200mAs for SAFIRE filter strengths of 1, 3 and 5 (p

Background: The postoperative imaging assessment of Cochlear Implant (CI) patients is imperative. The main obstacle is that Magnetic Resonance imaging (MR) is contraindicated or hindered by significant artefacts in most cases with CIs. This study describes an automatic cochlear image registration and fusion method that aims to help radiologists and surgeons to process pre-and postoperative 3D multimodal imaging studies in cochlear implant (CI) patients. Methods and findings: We propose a new registration method, Automatic Cochlea Image Registration (ACIR-v3), which uses a stochastic quasi-Newton optimiser with a mutual information metric to find 3D rigid transform parameters for registration of preoperative and postoperative CI imaging. The method was tested against a clinical cochlear imaging dataset that contains 131 multimodal 3D imaging studies of 41 CI patients with preoperative and postoperative images. The preoperative images were MR, Multidetector Computed Tomography (MDCT) or Cone Beam Computed Tomography (CBCT) while the postoperative were CBCT. The average root mean squared error of ACIR-v3 method was 0.41 mm with a standard deviation of 0.39 mm. The results were evaluated quantitatively using the mean squared error of two 3D landmarks located manually by two neuroradiology experts in each image and compared to other previously known registration methods, e.g. Fast Preconditioner Stochastic Gradient Descent, in terms of accuracy and speed. Conclusions: Our method, ACIR-v3, produces high resolution images in the postoperative stage and allows for visualisation of the accurate anatomical details of the MRI with the absence of significant metallic artefacts. The method is implemented as an open-source plugin for 3D Slicer tool. [ABSTRACT FROM AUTHOR]

Background and purpose: The complex anatomy of the temporal bone is difficult to understand and constitutes a challenge in the daily diagnostic routine even for experienced neuroradiologists. In the context of otoneurological (oVEMP) and preoperative diagnostics, the diagnosis of superior semicircular canal dehiscence (SSCD) is of great importance for Ear, Nose, and Throat (ENT) specialists. The gold standard for this diagnosis is a high-resolution CT (HRCT) of the temporal bone. In order to correctly diagnose SSCD, special oblique reconstructions are necessary in addition to standard (axial, coronal, sagittal) reconstructions. We evaluated the frequency of diagnosis and its location in HRCT in correlation with otoneurological examination. From this analysis, we present a new SSCD classification. This classification yields the potential of a differentiated analysis of the patient's clinical symptoms with correlation to the cross-sectional anatomy and may lead to a differentiated therapy approach. Study design and setting: We evaluated 1370 temporal bone scans of patients with residual hearing and verified 343 superior semicircular canal dehiscence (SSCD). We conducted a subgroup analysis of these 343 HRCT scans displaying a SSCD and used them as a basis to create a classification. Results: Three location types of SSCD were identified. These were anterior type 1, superior type 2 and posterior type 3. Type 2 were significantly more frequent in both sexes. SSCD at this location can be overlooked if diagnosis is performed only in the standard axial plane, since it can only be visualized by means of double oblique reconstruction. We present a standardized reconstruction algorithm. Conclusion: In total, three types of SSCD with differing incidences can be extrapolated from the locations. Superior type 2 is the most frequent one. Both sexes are affected with roughly equal incidence. The use of standardized double oblique reconstruction algorithm ensures that all three types are diagnosed in the HRCT. [ABSTRACT FROM AUTHOR]

Objectives: To utilize a novel objective approach combining a software phantom and an image quality metric to systematically evaluate the influence of sinogram affirmed iterative reconstruction (SAFIRE) of multidetector computed tomography (MDCT) data on image noise characteristics and low-contrast detectability (LCD). Materials and Methods: A low-contrast and a high-contrast phantom were examined on a 128-slice scanner at different dose levels. The datasets were reconstructed using filtered back projection (FBP) and SAFIRE and virtual low-contrast lesions (-20HU) were inserted. LCD was evaluated using the multiscale structural similarity index (MS-SIM*). Image noise texture and spatial resolution were objectively evaluated. Results: The use of SAFIRE led to an improvement of LCD for all dose levels and lesions sizes. The relative improvement of LCD was inversely related to the dose level, declining from 208%(±37%), 259%(±30%) and 309%(±35%) at 25mAs to 106%(±6%), 119%(±9%) and 123%(±8%) at 200mAs for SAFIRE filter strengths of 1, 3 and 5 (p<0.05). SAFIRE reached at least the LCD of FBP at a relative dose of 50%. There was no statistically significant difference in spatial resolution. The use of SAFIRE led to coarser image noise granularity. Conclusion: A novel objective approach combining a software phantom and the MS-SSIM* image quality metric was used to analyze the detectability of virtual low-contrast lesions against the background of image noise as created using SAFIRE in comparison to filtered back-projection. We found, that image noise characteristics using SAFIRE at 50% dose were comparable to the use of FBP at 100% dose with respect to lesion detectability. The unfamiliar imaging appearance of iteratively reconstructed datasets may in part be explained by a different, coarser noise characteristic as demonstrated by a granulometric analysis. [ABSTRACT FROM AUTHOR]