The purpose of this study was to develop a diagnostic tool to automatically detect temporomandibular joint osteoarthritis (TMJOA) from cone beam computed tomography (CBCT) images with artificial intelligence. CBCT images of patients diagnosed with temporomandibular disorder were included for image preparation. Single-shot detection, an object detection model, was trained with 3,514 sagittal CBCT images of the temporomandibular joint that showed signs of osseous changes in the mandibular condyle. The region of interest (condylar head) was defined and classified into 2 categories—indeterminate for TMJOA and TMJOA—according to image analysis criteria for the diagnosis of temporomandibular disorder. The model was tested with 2 sets of 300 images in total. The average accuracy, precision, recall, and F1 score over the 2 test sets were 0.86, 0.85, 0.84, and 0.84, respectively. Automated detection of TMJOA from sagittal CBCT images is possible by using a deep neural networks model. It may be used to support clinicians with diagnosis and decision making for treatments of TMJOA.

Inflammatory skin diseases, such as rosacea and acne, are major causes of facial erythema and accompanying skin barrier dysfunction. Several methods to restore the impaired skin barrier and improve facial erythema, such as medication, radiofrequency, laser, and ultrasound therapy were attempted. This study evaluated the efficacy and safety of dual-frequency ultrasound with impulse mode, for improving skin hydration and erythema in Asian subjects with rosacea and acne. Twenty-six subjects with facial erythema received an ultrasound treatment once per week, for 4 weeks, over both cheeks. The erythema index and transepidermal water loss (TEWL) were measured at each visit. Clinicians assessed the erythema improvement and patients evaluated their satisfaction level. The average decrease in TEWL and erythema index at 6 weeks was 5.37 ± 13.22 g·h−1·m−2 (p = 0.020) and 39.73 ± 44.21 (p = 0.010), respectively. The clinician’s erythema assessment and the subject satisfaction questionnaire score significantly improved at final follow-up (p < 0.001; p = 0.003, respectively). No serious adverse effects were observed during the treatment and follow-up periods. The dual-frequency ultrasound with impulse mode appears to be effective and safe for improving skin hydration and erythema in patients with rosacea and acne.

Higher PD-1 positivity is associated with small-cell-predominant cutaneous ENKTL. However, PD-1 expression has no prognostic value in cutaneous ENKTL.

Background Becker's nevus (BN) presents as a hairy patch or plaque with or without

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Telangiectasia macularis eruptiva perstans (TMEP) is a rare subtype of cutaneous mastocytosis, characterized by telangiectatic tan to brown macules on the trunk and extremities. Although TMEP has been descried as an uncommon disease in the literature, we often encounter patients with TMEP lesions in the outpatient clinic. We aimed to assess the clinical and histopathological characteristics of acquired bilateral TMEP, and the pathophysiological mechanism of acquired bilateral TMEP among these patients. We retrospectively reviewed 30 patients (28 men and 2 women) with acquired bilateral TMEP; multiple telangiectatic dark red to brown macules that were symmetrically distributed. The clinical characteristics and general histopathological findings of lesional skin were investigated. The number of mast cells was evaluated using immunohistochemical analysis with an antibody directed against c-kit (CD117). Acquired bilateral TMEP was predominantly localized on the sun-exposed area: the upper arm in 30 patients (100%), forearm in 19 patients (63.3%) and anterior chest in 15 patients (50%). A total of 16 patients (53.3%) showed at least one aggravating factor, including UV irradiation, alcohol use and heat exposure. Compared with the mast cell numbers in 19 age- and biopsy site-matched healthy controls (91 ± 29.0/mm ), the number of mast cells in the papillary dermal skin of acquired bilateral TMEP patients was significantly increased (159 ± 37.2/mm , P < 0.01). In addition, a significant difference in vessel numbers in the papillary dermis was observed between acquired bilateral TMEP patients and healthy controls (10.5 ± 1.9 vs 5.4 ± 1.0/mm , P < 0.01). Acquired bilateral TMEP is a relatively common disorder in middle-aged Asian men. An increased number of mast cells and dilated vessels might be a photoaging-related reactive process of chronic sun-exposure, which consequently leads to the formation of characteristic telangiectatic hyperpigmentary macules through certain melanogenic mediators.

Background Although deep neural networks have shown promising results in the diagnosis of skin cancer, a prospective evaluation in a real-world setting could confirm these results. This study aimed to evaluate whether an algorithm (http://b2019.modelderm.com) improves the accuracy of nondermatologists in diagnosing skin neoplasms. Methods A total of 285 cases (random series) with skin neoplasms suspected of malignancy by either physicians or patients were recruited in two tertiary care centers located in South Korea. An artificial intelligence (AI) group (144 cases, mean [SD] age, 57.0 [17.7] years; 62 [43.1%] men) was diagnosed via routine examination with photographic review and assistance by the algorithm, whereas the control group (141 cases, mean [SD] age, 61.0 [15.3] years; 52 [36.9%] men) was diagnosed only via routine examination with a photographic review. The accuracy of the nondermatologists before and after the interventions was compared. Results Among the AI group, the accuracy of the first impression (Top-1 accuracy; 58.3%) after the assistance of AI was higher than that before the assistance (46.5%, P = .008). The number of differential diagnoses of the participants increased from 1.9 ± 0.5 to 2.2 ± 0.6 after the assistance (P < .001). In the control group, the difference in the Top-1 accuracy between before and after reviewing photographs was not significant (before, 46.1%; after, 51.8%; P = .19), and the number of differential diagnoses did not significantly increase (before, 2.0 ± 0.4; after, 2.1 ± 0.5; P = .57). Conclusions In real-world settings, AI augmented the diagnostic accuracy of trainee doctors. The limitation of this study is that the algorithm was tested only for Asians recruited from a single region. Additional international randomized controlled trials involving various ethnicities are required.

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