Infective endocarditis (IE) is an uncommon but potentially devastating disease. Recently published data have revealed a significant increase in the incidence of IE following the restriction on indications for antibiotic prophylaxis as recommended by the revised guidelines. This study aims to reexamine the basic assumption behind the rationale of prophylaxis that dental procedures increase the risk of IE.Using the Longitudinal Health Insurance Database of Taiwan, we retrospectively analyzed a total of 739 patients hospitalized for IE between 1999 and 2012. A case-crossover design was conducted to compare the odds of exposure to dental procedures within 3 months preceding hospitalization with that during matched control periods when no IE developed.In the unadjusted model, the odds ratio (OR) was 0.93 for tooth extraction (95% confidence interval [CI] 0.54-1.59), 1.64 for surgery (95% CI 0.61-4.42), 0.92 for dental scaling (95% CI 0.59-1.42), 1.69 for periodontal treatment (95% CI 0.88-3.21), and 1.29 for endodontic treatment (95% CI 0.72-2.31). The association between dental procedures and the risk of IE remained insignificant after adjustment for antibiotic use, indicating that dental procedures did not increase the risk of IE.Therefore, this result may argue against the conventional assumption on which the recommended prophylaxis for IE is based.

The purpose of this work was to evaluate the performance of an existing commercially available artificial intelligence (AI) software system in differentiating malignant and benign lung nodules. The AI tool consisted of a vessel-suppression function and a deep-learning-based computer-aided-detection (VS-CAD) analyzer. Fifty patients (32 females, mean age 52 years) with 75 lung nodules (47 malignant and 28 benign) underwent low-dose computed tomography (LDCT) followed by surgical excision and the pathological analysis of their 75 nodules within a 3 month time frame. All 50 cases were then processed by the AI software to generate corresponding VS images and CAD outcomes. All 75 pathologically proven lung nodules were well delineated by vessel-suppressed images. Three (6.4%) of the 47 lung cancer cases, and 11 (39.3%) of the 28 benign nodules were ignored and not detected by the AI without showing a CAD analysis summary. The AI system/radiologists produced a sensitivity and specificity (shown in %) of 93.6/89.4 and 39.3/82.1 in distinguishing malignant from benign nodules, respectively. AI sensitivity was higher than that of radiologists, though not statistically significant (p = 0.712). Specificity obtained by the radiologists was significantly higher than that of the VS-CAD AI (p = 0.003). There was no significant difference between the malignant and benign lesions with respect to age, gender, pure ground-glass pattern, the diameter and location of the nodules, or nodules <6 vs. ≥6 mm. However, more part-solid nodules were proven to be malignant than benign (90.9% vs. 9.1%), and more solid nodules were proven to be benign than malignant (86.7% vs. 13.3%) with statistical significance (p = 0.001 and <0.001, respectively). A larger cohort and prospective study are required to validate the AI performance.

Congenital tuberculosis is rare, even where tuberculosis (TB) is endemic. A 14-day-old girl presented with a 3-day history of fever and respiratory distress. Her mother was diagnosed with a disseminated TB infection immediately after the delivery which was confirmed by a positive TB-polymerase chain reaction (TB-PCR) and subsequent culture from ascites and sputum. The infant was separated from her mother at birth. Her chest radiograph showed bilateral miliary nodules. Congenital TB was strongly suspected because of the symptoms, signs and maternal TB history, and was confirmed by TB-PCR and culture from the gastric lavage. Timely administration of standard anti-TB therapy resulted in a good outcome. The case highlights the importance of maternal TB history and typical miliary pattern on chest radiography for early diagnosis of congenital or neonatal TB which in turn facilitates prompt treatment and the prognosis.

Coronary computed tomography angiography (CCTA) is a widely used imaging modality for diagnosing coronary artery disease (CAD) but is limited by a high false positive rate when evaluating coronary arteries with stents and heavy calcifications. Virtual intravascular endoscopy (VIE) images generated from CCTA can be used to qualitatively assess the vascular lumen and might be helpful for overcoming this challenge. In this study, one hundred subjects with coronary stents underwent both CCTA and invasive coronary angiography (ICA). A total of 902 vessel segments were analyzed using CCTA and VIE. The vessel segments were first analyzed on CCTA alone. Then, using VIE, the segments were classified qualitatively as either negative or positive for in-stent restenosis (ISR) or CAD. These results were compared, using ICA as the reference, to determine the added diagnostic value of VIE. Of the 902 analyzed vessel segments, CCTA/VIE had sensitivity, specificity, accuracy, positive predictive value, and negative predictive value (shown in %) of 93.9/90.2, 96.2/98.2, 96.0/97.7, 70.0/83.1, and 99.4/99.0, respectively, in diagnosing ISR or CAD, with significantly improved specificity (p = 0.025), accuracy (p = 0.046), and positive predictive value (p = 0.047). VIE can be a helpful addition to CCTA when evaluating coronary arteries.

Background: Low-dose computed tomography (LDCT) techniques can reduce exposure to radiation. Several previous studies have shown that radiation dose reduction in LDCT does not decrease the diagnostic performance for appendicitis among attending radiologists. But, the LDCT diagnostic performance for acute appendicitis in radiology residents with variable training levels has not been well discussed. Objectives: To compare inter-observer and intra-observer differences of diagnostic performance on non-enhanced LDCT (NE-LDCT) and contrast-enhanced standard dose CT (CE-SDCT) for acute appendicitis among attending and resident radiologists. Patients and Methods: This retrospective study included 101 patients with suspected acute appendicitis who underwent NE-LDCT and CE-SDCT. The CT examinations were interpreted and recorded on a five-point scale independently by three attending radiologists and three residents with 4, 1 and 1 years of training. Diagnostic performance for acute appendicitis of all readers on both examinations was represented by area under receiver operating characteristic (ROC) curves. Inter-observer and intra-observer AUC values were compared using Jackknife FROC software on both modalities. The diagnostic accuracy of each reader on NE-LDCT was compared with body mass index (BMI) subgroups and noise using independent T test. Results: Diagnostic performances for acute appendicitis were not statistically different for attending radiologists at both examinations. Better performance was noted on the CE-SDCT with a borderline significant difference (P = 0.05) for senior radiology resident. No statistical difference of AUC values was observed between attending radiologists and fourth year resident on both examinations. Statistically significant differences of AUC values were observed between attending radiologists and first year residents (P = 0.001 ~ 0.018) on NE-LDCT. Diagnostic accuracies of acute appendicitis on NE-LDCT for each reader were not significantly related to BMI or noise. Conclusion: Attending radiologists could diagnose acute appendicitis accurately on NE-LDCT. Performance of senior residents on NE-LDCT is better than junior residents and comparable to attending radiologists. Keywords: Radiation Dose; Computed Tomography; Appendicitis; Emergencies; Education