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.

Endoscopic transcanal coblation excision of glomus tympanicum: a novel technique.

OBJECTIVE: To evaluate the feasibility of coblation in excision of glomus tympanicum tumors. PATIENTS AND METHODS: A retrospective study carried out over 28 patients with types I and II glomus tympanicum tumors according to GLASSCOCK-JACKSON classification. Preoperative radiological and endocrinal evaluation were performed. All patients underwent endoscopic transcanal excision of their glomus tympanicum tumors using coblation. RESULTS: None of the patients developed recurrence during the 1-year follow up period proved radiologically. None of the patients developed facial palsy postoperatively. Differences between preoperative and postoperative dizziness and taste disturbance were statistically non-significant. Tinnitus disappeared completely in 22 patients postoperatively. A statistically significant reduction in Tinnitus Handicap Inventory (THI) after surgery was found. Statistically significant reductions in postoperative air conduction (AC) threshold and air bone gap (ABG) were recorded while bone conduction (BC) threshold showed statistically non-significant change. CONCLUSION: Coblation is an effective and safe tool in excision of glomus tympanicum tumors. Further studies comparing coblation with laser and piezosurgery are strongly recommended.

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.

Role of Imaging and AI in the Evaluation of COVID-19 Infection: A Comprehensive Survey.

Coronavirus disease 2019 (COVID-19) is a respiratory illness that started and rapidly became the pandemic of the century, as the number of people infected with it globally exceeded 253.4 million. Since the beginning of the pandemic of COVID-19, over two years have passed. During this hard period, several defies have been coped by the scientific society to know this novel disease, evaluate it, and treat affected patients. All these efforts are done to push back the spread of the virus. This article provides a comprehensive review to learn about the COVID-19 virus and its entry mechanism, its main repercussions on many organs and tissues of the body, identify its symptoms in the short and long terms, in addition to recognize the role of diagnosis imaging in COVID-19. Principally, the quick evolution of active vaccines act an exceptional accomplishment where leaded to decrease rate of death worldwide. However, some hurdels still have to be overcome. Many proof referrers that infection with CoV-19 causes neurological dis function in a substantial ratio of influenced patients, where these symptoms appear severely during the infection and still less is known about the potential long term consequences for the brain, where Loss of smell is a neurological sign and rudimentary symptom of COVID-19. Hence, we review the causes of olfactory bulb dysfunction and Anosmia associated with COVID-19, the latest appropriate therapeutic strategies for the COVID-19 treatment (e.g., the ACE2 strategy and the Ang II receptor), and the tests through the follow-up phases. Additionally, we discuss the long-term complications of the virus and thus the possibility of improving therapeutic strategies. Moreover, the main steps of artificial intelligence that have been used to foretell and early diagnose COVID-19 are presented, where Artificial intelligence, especially machine learning is emerging as an effective approach for diagnostic image analysis with performance in the discriminate diagnosis of injuries of COVID-19 on multiple organs, comparable to that of human practitioners. The followed methodology to prepare the current survey is to search the related work concerning the mentioned topic from different journals, such as Springer, Wiley, and Elsevier. Additionally, different studies have been compared, the results are collected and then reported as shown. The articles are selected based on the year (i.e., the last three years). Also, different keywords were checked (e.g., COVID-19, COVID-19 Treatment, COVID-19 Symptoms, and COVID-19 and Anosmia).

Screening for Subclinical Interstitial Lung Disease in Rheumatoid Arthritis Patients: Functional and Radiological Methods.

OBJECTIVE: Interstitial lung disease is the most frequent lung symptom of rheumatoid arthritis and is a significant contributor to morbid- ity. As a result, the target of this research was to measure the frequency of radiological and functional abnormalities in rheumatoid arthritis patients who did not have any respiratory symptoms. MATERIAL AND METHODS: This study consists of 30 patients diagnosed with rheumatoid arthritis. All involved cases were exposed to entire history taking and clinical examination. All patients were examined by high-resolution computed tomography and pulmonary function tests. RESULTS: According to the computed tomography visual score, 73.3% showed interstitial lung disease. The most common abnormalities were reticular patterns (46.7%) followed by nodular patterns (40%) and septal lines (23.3%). However, 36% of the patients had a normal pulmonary function, while 32% had a small airway affection, 20% had restrictive lung disease, and 12% had obstructive lung disease. A significant association was found between supine expiratory volume and computed tomography visual score. Results showed no associa- tion between interstitial lung disease and all lung function test parameters. CONCLUSION: Subclinical interstitial lung disease is frequent among rheumatoid arthritis patents. A combination of pulmonary func- tion tests with computed tomography is essential to enhance the recognition of subclinical interstitial lung disease as normal pulmonary function alone cannot exclude its presence.

Diagnostic performance of chest computed tomography for COVID-19 in children: a systematic review and meta-analysis of clinical and computed tomography features in 987 patients.

Purpose: The outbreak of a new coronavirus is still spreading worldwide, affecting children and adults. However, COVID-19 in children shows distinctive characteristics in clinical and radiological presentation. We aimed to assess the diagnostic performance of chest CT and clarify the clinicoradiological CT features of COVID-19 among children with COVID-19. Material and methods: Adhering to PRISMA-DTA guidelines, we searched databases (PubMed, Google Scholar, and Web of Science) to identify relevant articles. The search keywords were: "Chest CT" AND "COVID-19" OR "coronavirus" OR "SARS-COV-2" AND "Children" OR "Pediatric". Published reports providing clinical and imaging findings of paediatric COVID-19 were included. Results: Twenty-eight studies were included, with 987 patients. Most of the patients were symptomatic (76.9%; 95% CI: 69.2-84.7%), with fever being the most frequent manifestation (64%; 95% CI: 58.0-71.2%). Only 2.3% of the cases were critical, and mortality was reported in one case. The proportion of COVID-19 detected by chest CT among children is relatively high (658/987), with ground-glass opacity (GGO) being the most prevalent feature (52.5%; 95% CI: 40.5-64.7%). The pooled sensitivity of chest CT in all patients was 67%; however, it was different between symptomatic and asymptomatic patients (71% and 33%, respectively). The pooled specificity was (67%), which was calculated after considering the symptomatic PCR-positive patients as the gold standard. Conclusions: Chest CT showed moderate pooled sensitivity and specificity among symptomatic children with COVID-19 and low sensitivity among asymptomatic children. This means that CT is not to be used as a screening tool or for confirmation of the diagnosis in children and should be reserved for specific clinical situations.

Combined preoperative HRCT parameters for prediction of round window visibility in pediatric cochlear implant patient.

OBJECTIVE: To evaluate the add value of combined analysis of high resolution computed tomography (HRCT) temporal bone parameters in accurate prediction of round window (RW) visibility through posterior tympanotomy. PATIENTS AND METHODS: a retrospective observational study was held in a tertiary center, conducted on 45 cochlear implant pediatric candidates between January 2017 and September 2019. Candidates were referred for CT temporal bone. They were classified into fully visible RW cases and partially or non-visible RW cases. Radiological measurements were compared between the two groups for prediction of RW visibility separate and in combination. RESULTS: 45 patients were included in the study (26 males (57.8%) and 19 females (42.2%)). Their median age was 4 years (2-12 years). There were 38 (84.4%) fully visible and 7 (15.6%) partially or non-visible RW cases. Kashio posterior line (n:32/3), fascial recess width (FRW) (mean: 4.9 (3.5-7.5)/4.2 (4-4.7) mm) and round window location (RWL) (3 (1-4)/2.8 (1-3)mm) measurements significantly differentiated between the two groups; (P value 0.034, 0.012 & 0.025 respectively). Posterior kashio line and cut off values of ≥4.75 mm of FRW & 2.95 mm of RWL were showed sensitivity 84.2%, 63.2% & 65.8%, and accuracy 80%, 68.9% &68.9% in prediction of RW visibility respectively. Combination of Kashio prediction line with cut off value ≥ 7.45 mm (sum of FRW & RWL) showed P value 0.003 with further improve in the sensitivity and overall accuracy in prediction of RW visibility from 84.2% to 80% up to 91.4% and 88.6% respectively. CONCLUSION: combined parameters using Kashio line with FRW and RWL increases sensitivity and overall accuracy in prediction of RW visibility rather than single parameter.