Automated diagnosis of COVID-19 using radiological modalities and Artificial Intelligence functionalities: A retrospective study based on chest HRCT database.

Background and Objective: The spread of coronavirus has been challenging for the healthcare system's proper management and diagnosis during the rapid spread and control of the infection. Real-time reverse transcription-polymerase chain reaction (RT-PCR), though considered the standard testing measure, has low sensitivity and is time-consuming, which restricts the fast screening of individuals. Therefore, computer tomography (CT) is used to complement the traditional approaches and provide fast and effective screening over other diagnostic methods. This work aims to appraise the importance of chest CT findings of COVID-19 and post-COVID in the diagnosis and prognosis of infected patients and to explore the ways and means to integrate CT findings for the development of advanced Artificial Intelligence (AI) tool-based predictive diagnostic techniques. Methods: The retrospective study includes a 188 patient database with COVID-19 infection confirmed by RT-PCR testing, including post-COVID patients. Patients underwent chest high-resolution computer tomography (HRCT), where the images were evaluated for common COVID-19 findings and involvement of the lung and its lobes based on the coverage region. The radiological modalities analyzed in this study may help the researchers in generating a predictive model based on AI tools for further classification with a high degree of reliability. Results: Mild to moderate ground glass opacities (GGO) with or without consolidation, crazy paving patterns, and halo signs were common COVID-19 related findings. A CT score is assigned to every patient based on the severity of lung lobe involvement. Conclusion: Typical multifocal, bilateral, and peripheral distributions of GGO are the main characteristics related to COVID-19 pneumonia. Chest HRCT can be considered a standard method for timely and efficient assessment of disease progression and management severity. With its fusion with AI tools, chest HRCT can be used as a one-stop platform for radiological investigation and automated diagnosis system.

Evaluation of Tongue Cancer Using High-Resolution Sonography: Comparison With Magnetic Resonance Imaging.

OBJECTIVES: To evaluate the role of sonography in assessing tongue cancer compared with magnetic resonance imaging (MRI). METHODS: A randomized prospective study was performed on 40 cases of tongue cancer. Magnetic resonance imaging and sonography of the tongue were performed, tumor spreading to particular sites was recorded in all cases. Sonographic and MRI findings were correlated with histopathologic findings in 18 operable cases. In 22 inoperable cases, sonography was compared only with MRI. RESULTS: In operable patients, sonography achieved sensitivity of 61.1%, whereas MRI achieved sensitivity of 94.4%. The difference was statistically significant (P < .05). The results for detection of individual site involvement on sonography and MRI were as follows: intrinsic muscles only, 0 and 6, respectively; tongue base, 5 and 5; genioglossus muscle, 34 and 34; mylohyoid muscle, 9 and 8; sublingual space, 12 and 14; sublingual neurovascular bundle, 12 and 12; submandibular gland, 3 and 3; spread across the lingual septum, 17 and 17; and alveolar involvement, 0 and 1. There was no significant difference (P> .05) between sonography and MRI in detecting involvement of the above-mentioned sites except for cases with only intrinsic muscles and alveolar involvement. Tumors involving intrinsic tongue muscles only were not visualized on sonography. They all underwent surgery, resulting in reduced sensitivity of sonography in operable cases. CONCLUSIONS: Even though small tumors were difficult to visualize, sonography can play an important role in assessment of tumor extension in large growths, especially when MRI is unavailable, contraindicated, or unaffordable, and for posttreatment follow-up.

Evaluation of hypopharyngeal carcinoma using high-resolution ultrasound: comparison with CT.

BACKGROUND: To evaluate the role of sonography (US) in assessing hypopharyngeal carcinoma when compared with CT. METHODS: A randomized prospective study was performed on 40 biopsy-proven cases of hypopharyngeal carcinoma.Contrast-enhanced CT of the neck was performed in all patients, followed by US. Sonographic identification of any tumor extension into the extralaryngeal soft tissues, postcricoid space, subglottis, thyroid gland, esophagus, and across the midline was recorded. US observations and CT findings were compared and then correlated with the histopathologic findings in 14 operative cases. In the remaining 26 inoperable cases, US was compared only with CT. RESULTS: Our cohort was composed of 38 men and 2 women ranging in age from 36 to 59 years. In a subset of 14 operative patients, US had a sensitivity of 71.4% (10/14), while CT achieved a sensitivity of 92.8% (13/14), and the difference was not statistically significant (p > 0.05). US and CT findings concurred in 67.5% (27/40) of cases. CONCLUSIONS: Even though small tumors are difficult to visualize, US can play a significant role in the assessment of tumor extension within and beyond the larynx, especially when cross-sectional imaging is either unavailable or unaffordable.

Adenoid cystic carcinoma of the upper trachea: a rare neoplasm.

Primary malignant tracheal tumors are not common and adenoid cystic carcinoma (ACC) of trachea is rare. We report an extremely rare case of ACC of proximal trachea, which was diagnosed in a 42-year-old male who presents with 6-month history of dyspnea. Lateral skiagram of neck, computed tomography, and magnetic resonance imaging revealed a broad-based polypoidal soft tissue mass arising from posterior wall of the proximal trachea. Biopsy confirmed the diagnosis of ACC. The patient was treated by surgical resection followed by radiotherapy and is on regular follow-up. Follow-up at 18 months post-treatment showed no local recurrence or distant metastases. The literature on tracheal ACC is reviewed. Image findings are briefly discussed.