A non-invasive AI-based system for precise grading of anosmia in COVID-19 using neuroimaging.

COVID-19 (Coronavirus), an acute respiratory disorder, is caused by SARS-CoV-2 (coronavirus severe acute respiratory syndrome). The high prevalence of COVID-19 infection has drawn attention to a frequent illness symptom: olfactory and gustatory dysfunction. The primary purpose of this manuscript is to create a Computer-Assisted Diagnostic (CAD) system to determine whether a COVID-19 patient has normal, mild, or severe anosmia. To achieve this goal, we used fluid-attenuated inversion recovery (FLAIR) Magnetic Resonance Imaging (FLAIR-MRI) and Diffusion Tensor Imaging (DTI) to extract the appearance, morphological, and diffusivity markers from the olfactory nerve. The proposed system begins with the identification of the olfactory nerve, which is performed by a skilled expert or radiologist. It then proceeds to carry out the subsequent primary steps: (i) extract appearance markers (i.e., 1 s t and 2 n d order markers), morphology/shape markers (i.e., spherical harmonics), and diffusivity markers (i.e., Fractional Anisotropy (FA) & Mean Diffusivity (MD)), (ii) apply markers fusion based on the integrated markers, and (iii) determine the decision and corresponding performance metrics based on the most-promising classifier. The current study is unusual in that it ensemble bags the learned and fine-tuned ML classifiers and diagnoses olfactory bulb (OB) anosmia using majority voting. In the 5-fold approach, it achieved an accuracy of 94.1%, a balanced accuracy (BAC) of 92.18%, precision of 91.6%, recall of 90.61%, specificity of 93.75%, F1 score of 89.82%, and Intersection over Union (IoU) of 82.62%. In the 10-fold approach, stacking continued to demonstrate impressive results with an accuracy of 94.43%, BAC of 93.0%, precision of 92.03%, recall of 91.39%, specificity of 94.61%, F1 score of 91.23%, and IoU of 84.56%. In the leave-one-subject-out (LOSO) approach, the model continues to exhibit notable outcomes, achieving an accuracy of 91.6%, BAC of 90.27%, precision of 88.55%, recall of 87.96%, specificity of 92.59%, F1 score of 87.94%, and IoU of 78.69%. These results indicate that stacking and majority voting are crucial components of the CAD system, contributing significantly to the overall performance improvements. The proposed technology can help doctors assess which patients need more intensive clinical care.

Clinical and Imaging Evaluation of COVID-19-Related Olfactory Dysfunction.

BACKGROUND: Olfactory dysfunction has been reported in 47.85% of COVID patients. It can be broadly categorized into conductive or sensorineural olfactory loss. Conductive loss occurs due to impaired nasal air flow, while sensorineural loss implies dysfunction of the olfactory epithelium or central olfactory pathways. OBJECTIVES: The aim of this study was to analyze the clinical and imaging findings in patients with COVID-related olfactory dysfunction. Additionally, the study aimed to investigate the possible mechanisms of COVID-related olfactory dysfunction. METHODS: The study included 110 patients with post-COVID-19 olfactory dysfunction, and a control group of 50 COVID-negative subjects with normal olfactory function. Endoscopic nasal examination was performed for all participants with special focus on the olfactory cleft. Smell testing was performed for all participants by using a smell diskettes test. Olfactory pathway magnetic resonance imaging (MRI) was done to assess the condition of the olfactory cleft and the dimensions and volume of the olfactory bulb. RESULTS: Olfactory dysfunction was not associated with nasal symptoms in 51.8% of patients. MRI showed significantly increased olfactory bulb dimensions and volume competed to controls. Additionally, it revealed olfactory cleft edema in 57.3% of patients. On the other hand, radiological evidence of sinusitis was detected in only 15.5% of patients. CONCLUSION: The average olfactory bulb volumes were significantly higher in the patients' group compared to the control group, indicating significant edema and swelling in the olfactory bulb in patients with COVID-related olfactory dysfunction. Furthermore, in most patients, no sinonasal symptoms such as nasal congestion or rhinorrhea were reported, and similarly, no radiological evidence of sinusitis was detected. Consequently, the most probable mechanism of COVID-related olfactory dysfunction is sensorineural loss through virus spread and damage to the olfactory epithelium and pathways.