No abstract available.

No abstract available.
Meningitis*

PURPOSE: The purpose of this study was to evaluate computed tomographic (CT) findings of deep neck space infection(DNSI) with particular attention to the differences in the spaces involved and in complications between odontogenic and nonodontogenic groups. MATERIALS AND METHODS: Forty-four patients(21 odontogenic and 23 nonodontogenic) were included in this study. Among odontogenic DNSls, 15 had the dental infection in the second or third mandibular molar. We compared the CT features between odontogenic and nonodontogenic DNSIs with special emphasis on the differences in the spaces involved and in the rate and type of complications. RESULTS: In all patients, CT clearly differentiated abscess from cellulitis. The most common spaces involved in 21 patients with odontogenic DNSl were the parapharyngeal(n=18), the submandibular(n=18), the anterior visceral(n=13), the masticator(n=9), and the sublingual(n=7) spaces. In contrast, in 23 patients with nonodontogenic DNSI, the anterior visceral space(n=14) was most frequently involved. The parapharyngeal, the submandibular, and the masticator spaces were statistically more frequently involved in odontogenic than in nonodontogenic DNSI(p<.05). Twenty-two patients had one or more complications shown by CT, of which airway compromise was more frequent and severe in odontogenicthan in nonodontogenic DNSI. CONCLUSION: We conclude that the parapharyngeal, the submandibular, and the masticator spaces are more significantly vulnerable in odontogenic DNSl than in nonodontogenic DNSl. The predilection for certain spaces of the neck in odontogenic DNSl seems to originate from the intimate relationship of the mandibular molars to the adjacent deep neck spaces.
Abscess ; Cellulitis ; Humans ; Molar ; Neck*

PURPOSE: The purpose of this study was to evaluate computed tomographic (CT) findings of deep neck space infection(DNSI) with particular attention to the differences in the spaces involved and in complications between odontogenic and nonodontogenic groups. MATERIALS AND METHODS: Forty-four patients(21 odontogenic and 23 nonodontogenic) were included in this study. Among odontogenic DNSls, 15 had the dental infection in the second or third mandibular molar. We compared the CT features between odontogenic and nonodontogenic DNSIs with special emphasis on the differences in the spaces involved and in the rate and type of complications. RESULTS: In all patients, CT clearly differentiated abscess from cellulitis. The most common spaces involved in 21 patients with odontogenic DNSl were the parapharyngeal(n=18), the submandibular(n=18), the anterior visceral(n=13), the masticator(n=9), and the sublingual(n=7) spaces. In contrast, in 23 patients with nonodontogenic DNSI, the anterior visceral space(n=14) was most frequently involved. The parapharyngeal, the submandibular, and the masticator spaces were statistically more frequently involved in odontogenic than in nonodontogenic DNSI(p<.05). Twenty-two patients had one or more complications shown by CT, of which airway compromise was more frequent and severe in odontogenicthan in nonodontogenic DNSI. CONCLUSION: We conclude that the parapharyngeal, the submandibular, and the masticator spaces are more significantly vulnerable in odontogenic DNSl than in nonodontogenic DNSl. The predilection for certain spaces of the neck in odontogenic DNSl seems to originate from the intimate relationship of the mandibular molars to the adjacent deep neck spaces.
Abscess ; Cellulitis ; Humans ; Molar ; Neck*

We report a rare case of pleomorphic adenoma arising from heterotopic salivary gland tissue in the upper neck. Although it is difficult to differentiate this condition from lymph node diseases-including metastasis- on the basis of radiologic findings alone, it should be included in the differential diagnosis of a solitary unilateral solid cervical mass, particularly one in the upper neck.
Adenoma, Pleomorphic* ; Diagnosis, Differential ; Lymph Nodes ; Neck* ; Salivary Glands*

No abstract available.
Cushing Syndrome*

No abstract available.
Dermatoglyphics* ; Humans*

No abstract available.
Sinusitis*

Chest X-ray radiography and computed tomography, the two mainstay modalities in thoracic radiology, are under activeinvestigation with deep learning technology, which has shown promising performance in various tasks, including detection,classification, segmentation, and image synthesis, outperforming conventional methods and suggesting its potential forclinical implementation. However, the implementation of deep learning in daily clinical practice is in its infancy and facingseveral challenges, such as its limited ability to explain the output results, uncertain benefits regarding patient outcomes, andincomplete integration in daily workflow. In this review article, we will introduce the potential clinical applications of deeplearning technology in thoracic radiology and discuss several challenges for its implementation in daily clinical practice.

Artificial intelligence (AI) technology is actively being applied for the interpretation of medical imaging, such as chest X-rays. AI-based software medical devices, which automatically detect various types of abnormal findings in chest X-ray images to assist physicians in their interpretation, are actively being commercialized and clinically implemented in Korea. Several important issues need to be considered for AI-based detection assistant tools to be applied in clinical practice: the evaluation of performance and efficacy prior to implementation; the determination of the target application, range, and method of delivering results; and monitoring after implementation and legal liability issues. Appropriate decision making regarding these devices based on the situation in each institution is necessary. Radiologists must be engaged as medical assessment experts using the software for these devices as well as in medical image interpretation to ensure the safe and efficient implementation and operation of AIbased detection assistant tools.