Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs. Materials and Methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (n = 23, 23%) and those who were not (n = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD. Results: Twenty-three patients (n = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both p < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28–24.21; p = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00–16.54; p = 0.050) were significant parameters for clinical diagnosis of ILD. Conclusion Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at followup chest CT can be predictors of clinically significant ILDs.

Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs. Materials and Methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (n = 23, 23%) and those who were not (n = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD. Results: Twenty-three patients (n = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both p < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28–24.21; p = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00–16.54; p = 0.050) were significant parameters for clinical diagnosis of ILD. Conclusion Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at followup chest CT can be predictors of clinically significant ILDs.

Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs. Materials and Methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (n = 23, 23%) and those who were not (n = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD. Results: Twenty-three patients (n = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both p < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28–24.21; p = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00–16.54; p = 0.050) were significant parameters for clinical diagnosis of ILD. Conclusion Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at followup chest CT can be predictors of clinically significant ILDs.

Background: Autoencoder (AE) is one of the deep learning techniques that uses an artificial neural network to reconstruct its input data in the output layer. We constructed a novel supervised AE model and tested its performance in the prediction of a co-existence of the disease of interest only using diagnostic codes. Methods: Diagnostic codes of one million randomly sampled patients listed in the Korean National Health Information Database in 2019 were used to train, validate, and test the prediction model. The first used AE solely for a feature engineering tool for an input of a classifier. Supervised Multi-Layer Perceptron (sMLP) was added to train a classifier to predict a binary level with latent representation as an input (AE + sMLP). The second model simultaneously updated the parameters in the AE and the connected MLP classifier during the learning process (End-to-End Supervised AE [EEsAE]). We tested the performances of these two models against baseline models, eXtreme Gradient Boosting (XGB) and naïve Bayes, in the prediction of co-existing gastric cancer diagnosis. Results: The proposed EEsAE model yielded the highest F1-score and highest area under the curve (0.86). The EEsAE and AE + sMLP gave the highest recalls. XGB yielded the highest precision. Ablation study revealed that iron deficiency anemia, gastroesophageal reflux disease, essential hypertension, gastric ulcers, benign prostate hyperplasia, and shoulder lesion were the top 6 most influential diagnoses on performance. Conclusion A novel EEsAE model showed promising performance in the prediction of a disease of interest.

Electronic cigarette (e-cigarette) or vaping product use-associated lung injury (EVALI) has emerged as a social issue as e-cigarette use is rapidly increasing worldwide and is related to many deaths in the United States. To our knowledge, this is the first case report of EVALI in South Korea of a 24-year-old man with acute respiratory symptoms and a history of e-cigarette use. Chest CT revealed diffuse bilateral ground-glass opacities with subpleural sparing, airspace consolidation, and centrilobular micronodules as typical patterns of EVALI with organizing pneumonia and diffuse alveolar damage. Infection was excluded with meticulous laboratory examinations, and the patients’ illnesses were not attributed to other causes. EVALI was diagnosed by meeting the diagnostic criteria with consistent clinico-radiologic findings through a multidisciplinary approach. Radiologists should have good knowledge of EVALI radiologic findings and play a cardinal role in the proper diagnosis and management of EVALI.

Purpose: This study aimed to evaluate the reproducibility and diagnostic performance of a quantitative parameter of superb microvascular imaging (SMI) in real-time breast ultrasonography (US) for differentiating benign from malignant breast masses. Methods: Eighty-seven breast masses in 75 patients who underwent both B-mode US and SMI before US-guided core needle biopsy were included in this study. Two radiologists performed B-mode US and measured the vascular index (VI) of SMI respectively for each lesion in real time. Intraobserver and interobserver agreements were analyzed for the VI of SMI. The diagnostic performance of B-mode US using the Breast Imaging Reporting and Database System lexicon and combined use with the VI of SMI was evaluated compared to pathology. Results: The median VI of malignant masses (n=32) was significantly higher than that of benign masses (n=55) (7.6% and 2.6%, respectively; P<0.001). The intraobserver agreement for VI was excellent regardless of the pathology, size, or depth of the lesion. The interobserver agreement for VI was excellent regardless of the presence of a measurement interval. The interobserver agreement for the final diagnostic decision was improved by combining B-mode US and VI (κ=0.883) in comparison with B-mode US only (κ=0.617). Adding VI led to significant improvements in the specificity (87.2% vs. 52.7%, 83.6% vs. 49.0%), accuracy (89.7% vs. 69.3%, 84.0% vs. 65.9%) and positive predictive value (81.5% vs. 55.1%, 75.6% vs. 52.6%) of B-mode US for both observers compared with B-mode US alone (all, P=0.001). Conclusion The VI of SMI for real-time breast US is highly reproducible and leads to improved diagnostic performance for differentiating between benign and malignant breast lesions in combination with B-mode US.

BACKGROUND: Postoperative nausea and vomiting (PONV) frequently occurs following bimaxillary orthognathic surgeries. Compared to opioids, Nefopam is associated with lower incidences of PONV, and does not induce gastrointestinal tract injury, coagulopathy, nephrotoxicity, or fracture healing dysfunction, which are common side effects of Nonsteroidal anti-inflammatory drugs. We compared nefopam- and fentanyl-induced incidence of PONV in patients with access to patient-controlled analgesia (PCA) following bimaxillary orthognathic surgeries. METHODS: Patients undergoing bimaxillary orthognathic surgeries were randomly divided into nefopam and fentanyl groups. Nefopam 120 mg or fentanyl 700 µg was mixed with normal saline to a final volume of 120 mL. Patients were given access to nefopam or fentanyl via PCA. Postoperative pain intensity and PONV were measured at 30 minutes and 1 hour after surgery in the recovery room and at 8, 24, 48, and 72 hours after surgery in the ward. The frequency of bolus delivery was compared at each time point. RESULTS: Eighty-nine patients were enrolled in this study, with 48 in the nefopam (N) group and 41 in the fentanyl (F) group. PONV occurred in 13 patients (27.7%) in the N group and 7 patients (17.1%) in the F group at 8 hours post-surgery (P = 0.568), and there were no significant differences between the two groups at any of the time points. VAS scores were 4.4 ± 2.0 and 3.7 ± 1.9 in the N and F groups, respectively, at 8 hours after surgery (P = 0.122), and cumulative bolus delivery was 10.7 ± 13.7 and 8.6 ± 8.5, respectively (P = 0.408). There were no significant differences in pain or bolus delivery at any of the remaining time points. CONCLUSION: Patients who underwent bimaxillary orthognathic surgery and were given nefopam via PCA did not experience a lower rate of PONV compared to those that received fentanyl via PCA. Furthermore, nefopam and fentanyl did not provide significantly different postoperative pain control.
Analgesia, Patient-Controlled ; Analgesics, Opioid ; Fentanyl ; Fracture Healing ; Gastrointestinal Tract ; Humans ; Incidence ; Nefopam ; Orthognathic Surgery ; Pain, Postoperative ; Passive Cutaneous Anaphylaxis ; Postoperative Nausea and Vomiting ; Prospective Studies ; Recovery Room

PURPOSE: This study examined the diagnostic accuracy of an imaging study to find the factors that affect the presence of residual tumors after an unplanned excision of sarcomas. MATERIALS AND METHODS: Ninety-eight patients, who underwent a re-excision after unplanned surgery between January 2008 and December 2014, were enrolled in this study. Magnetic resonance imaging (MRI) was performed before reoperation in all patients. Positron emission tomography (PET)-computed tomography was performed on 54 patients. A wide re-excision and histology diagnosis were performed in all cases. The clinical variables were evaluated using univariate logistic regression and multivariate logistic regression. RESULTS: The presence of a deep-seated tumor increases the risk of remnant tumors (odds ratio: 3.21, p=0.02, 95% confidence interval: 1.25–8.30). The sensitivity for detecting residual tumors is high in MRI (sensitivity 0.79). CONCLUSION: Deep-seated tumors have a significantly higher risk of remnant tumors. Because the negative predictive value of MRI and PET scans is very low, reoperation should be performed regardless of a negative result.
Diagnosis ; Humans ; Logistic Models ; Magnetic Resonance Imaging ; Neoplasm, Residual ; Positron-Emission Tomography ; Reoperation ; Risk Factors ; Sarcoma

Yolk sac tumors are rare malignant germ cell neoplasms that usually arise from the gonads. Extragonadal yolk sac tumors (EGYSTs) frequently occur in the mediastinum in post-pubertal females. EGYSTs in the pelvis are extremely rare, and to date, only thirteen cases have been reported in the English literature. Among them, the primary EGYST of the pelvic peritoneum in post-pubertal females has only been reported in ten cases. The present case describes a 26-year-old female diagnosed with primary peritoneal yolk sac tumor located in the rectouterine pouch. We report clinical and tumor imaging features, including ultrasound, computed tomography (CT), magnetic resonance images (MRI), positron emission tomography-computed tomography (PET-CT), and present a review of the literature.
Adult ; Douglas' Pouch ; Electrons ; Endodermal Sinus Tumor ; Female ; Gonads ; Humans ; Magnetic Resonance Imaging ; Mediastinum ; Neoplasms, Germ Cell and Embryonal ; Pelvis ; Peritoneum ; Ultrasonography ; Yolk Sac

PURPOSE: This study aimed to determine the relationships between particulate matter risk perception, knowledge, and perceived barriers and health-promoting behaviors among college students. METHODS: Data for this cross-sectional study were collected from September 1 to 30, 2017. The study sample consisted of 85 students from a university, Seoul. Students not living in the Seoul metropolitan area during the spring 2017 semester were excluded from participation. Pearson's correlation coefficient was used to identify relationships among study variables. RESULTS: A significant positive correlation existed between particulate matter risk perception and health-promoting behaviors related to particulate matter (r=.51, p < .001). Among the risk perception subdomains, attention (r=.47, p < .001) and health effect (r=.55, p < .001) showed strong positive relationships with health-promoting behaviors. No significant relationships were found between knowledge (r=.12, p=.288) or perceived barriers (r=−.12, p=.264) and health-promoting behaviors related to particulate matter. CONCLUSION: Based on the study results, strategies for enhancing particulate matter risk perception are needed to increase the level of health-promoting behaviors related to particulate matter among college students.
Cross-Sectional Studies ; Health Promotion ; Humans ; Particulate Matter ; Seoul