OBJECTIVES: The purpose of this study was to estimate the incidence of injuries and to identify their causes by classifying injuries according to various categories including age, sex, mechanism of injury, body parts injured, and place of injury. METHODS: This study used data from the Korea National Hospital Discharge In-depth Injury Survey (KNHDIS) from 2004 to 2016. The KNHDIS is conducted annually by the Korea Centers for Disease Control and Prevention, and its survey population includes all hospitalized patients discharged from medical institutions that have 100 or more beds, such as hospitals, general hospitals, and secondary community health centers. The number of injured cases is weighted and estimated using the mid-year estimated population of each year. RESULTS: The injury discharge rate steadily increased since 2004 (1,505 per 100,000 population in 2004, 2,007 per 100,000 population in 2016) and most injuries were unintentional (annual average of 94.7%). On average, during the 13-year study period, the injury rate for males was 1.5 times as high as for females. The 2 main causes of injury were consistently traffic accidents and falls. Notably, the rate of injuries resulting from falls rose by 1.7-fold from 463 to 792 per 100,000 people, and exceeded the rate of traffic accidents in 2016. CONCLUSIONS The incidence of injuries steadily increased after the survey was first conducted, whereas mortality resulting from injuries mostly remained unchanged. This suggests that effective strategies and interventions should be reinforced to reduce unintentional injuries.

PURPOSE: We investigated correlations between the findings of oral examinations and panoramic radiography in order to determine the efficacy of using panoramic radiographs in screening examinations. METHODS: This study included patients who visited dental clinics at National Health Insurance Service (NHIS) Ilsan Hospital for checkups during 2009–2015 and underwent panoramic radiographic examinations within 1 year prior to the oral examinations. Among the 48,006 patients who received checkups, 1,091 were included in this study. The data were evaluated using the Cohen kappa and interrater agreement coefficients. Accuracy, sensitivity, and specificity were calculated using data from the panoramic radiographs as true positive diagnoses. RESULTS: The interrater agreement coefficient for occlusal caries was 28.8%, and the Cohen kappa coefficient was 0.043 between the oral and panoramic radiographic examinations. Root caries and subgingival calculus were only found on the radiographs, while gingival inflammation was found only by the oral examinations. The oral examinations had a specificity for detecting occlusal dental caries of 100%, while their sensitivity for proximal dental caries and supragingival calculus was extremely low (14.0% and 18.3%, respectively) compared to the panoramic radiographic examinations. The oral examinations showed a relatively low sensitivity of 66.2% and a specificity of 43.7% in detecting tooth loss compared with panoramic radiography. CONCLUSIONS: Panoramic radiography can provide information that is difficult to obtain in oral examinations, such as root caries, furcation involvement, and subgingival calculus, which are factors that can directly affect the survival rate of teeth. It therefore seems reasonable and necessary to add panoramic radiography to large-scale health checkup programs such as that provided by the NHIS.
Calculi ; Dental Caries ; Dental Clinics ; Diagnosis ; Diagnosis, Oral ; Humans ; Inflammation ; Mass Screening ; National Health Programs ; Radiography, Dental ; Radiography, Panoramic ; Root Caries ; Sensitivity and Specificity ; Survival Rate ; Tooth ; Tooth Loss

OBJECTIVES: The purpose of this study was to estimate the incidence of injuries and to identify their causes by classifying injuries according to various categories including age, sex, mechanism of injury, body parts injured, and place of injury. METHODS: This study used data from the Korea National Hospital Discharge In-depth Injury Survey (KNHDIS) from 2004 to 2016. The KNHDIS is conducted annually by the Korea Centers for Disease Control and Prevention, and its survey population includes all hospitalized patients discharged from medical institutions that have 100 or more beds, such as hospitals, general hospitals, and secondary community health centers. The number of injured cases is weighted and estimated using the mid-year estimated population of each year. RESULTS: The injury discharge rate steadily increased since 2004 (1,505 per 100,000 population in 2004, 2,007 per 100,000 population in 2016) and most injuries were unintentional (annual average of 94.7%). On average, during the 13-year study period, the injury rate for males was 1.5 times as high as for females. The 2 main causes of injury were consistently traffic accidents and falls. Notably, the rate of injuries resulting from falls rose by 1.7-fold from 463 to 792 per 100,000 people, and exceeded the rate of traffic accidents in 2016. CONCLUSIONS The incidence of injuries steadily increased after the survey was first conducted, whereas mortality resulting from injuries mostly remained unchanged. This suggests that effective strategies and interventions should be reinforced to reduce unintentional injuries.

Angiography ; Bias (Epidemiology) ; Constriction, Pathologic ; Coronary Angiography ; Fractional Flow Reserve, Myocardial ; Humans ; Ischemia ; Patient-Specific Modeling ; Sensitivity and Specificity

Purpose: To compare image quality in selective intracoronary contrast-injected computed tomography angiography (SelectiveCTA) with that in conventional intravenous contrast-injected CTA (IV-CTA). Materials and Methods: Six pigs (35 to 40 kg) underwent both IV-CTA using an intravenous injection (60 mL) and Selective-CTA using an intracoronary injection (20 mL) through a guide-wire during/after percutaneous coronary intervention. Images of the common coronary artery were acquired. Scans were performed using a combined machine comprising an invasive coronary angiography suite and a 320-channel multi-slice CT scanner. Quantitative image quality parameters of CT attenuation, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), mean lumen diameter (MLD), and mean lumen area (MLA) were measured and compared. Qualitative analysis was performed using intraclass correlation coefficient (ICC), which was calculated for analysis of interobserver agreement. Results: Quantitative image quality, determined by assessing the uniformity of CT attenuation (399.06 vs. 330.21, p<0.001), image noise (24.93 vs. 18.43, p<0.001), SNR (16.43 vs. 18.52, p=0.005), and CNR (11.56 vs. 13.46, p=0.002), differed significantly between IV-CTA and Selective-CTA. MLD and MLA showed no significant difference overall (2.38 vs. 2.44, p=0.068, 4.72 vs. 4.95, p=0.078).The density of contrast agent was significantly lower for selective-CTA (13.13 mg/mL) than for IV-CTA (400 mg/mL). Agreement between observers was acceptable (ICC=0.79±0.08). Conclusion Our feasibility study in swine showed that compared to IV-CTA, Selective-CTA provides better image quality and requires less iodine contrast medium.

Objective: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction methods. Materials and Methods: We collected contrast-enhanced dual-energy CT of the abdomen that was obtained using various reconstruction methods, including filtered back projection, iterative reconstruction, optimum contrast, and monoenergetic images with 40, 60, and 80 keV. A deep learning based image conversion algorithm was developed to standardize the CT images using 142 CT examinations (128 for training and 14 for tuning). A separate set of 43 CT examinations from 42 patients (mean age, 10.1 years) was used as the test data. A commercial software program (MEDIP PRO v2.0.0.0, MEDICALIP Co. Ltd.) based on 2D U-NET was used to create liver segmentation masks with liver volume. The original 80 keV images were used as the ground truth. We used the paired t-test to compare the segmentation performance in the Dice similarity coefficient (DSC) and difference ratio of the liver volume relative to the ground truth volume before and after image standardization. The concordance correlation coefficient (CCC) was used to assess the agreement between the segmented liver volume and ground-truth volume. Results: The original CT images showed variable and poor segmentation performances. The standardized images achieved significantly higher DSCs for liver segmentation than the original images (DSC [original, 5.40%–91.27%] vs. [standardized, 93.16%–96.74%], all P < 0.001). The difference ratio of liver volume also decreased significantly after image conversion (original, 9.84%–91.37% vs. standardized, 1.99%–4.41%). In all protocols, CCCs improved after image conversion (original, -0.006–0.964 vs. standardized, 0.990–0.998). Conclusion Deep learning-based CT image standardization can improve the performance of automated hepatic segmentation using CT images reconstructed using various methods. Deep learning-based CT image conversion may have the potential to improve the generalizability of the segmentation network.

Purpose: In a preclinical study using a swine myocardial infarction (MI) model, a delayed enhancement (DE)-multi-detector computed tomography (MDCT) scan was performed using a hybrid system alongside diagnostic invasive coronary angiography (ICA) without the additional use of a contrast agent, and demonstrated an excellent correlation in the infarct area compared with histopathologic specimens. In the present investigation, we evaluated the feasibility and diagnostic accuracy of a myocardial viability assessment by DE-MDCT using a hybrid system comprising ICA and MDCT alongside diagnostic ICA without the additional use of a contrast agent. Materials and Methods: We prospectively enrolled 13 patients (median age: 67 years) with a previous MI (>6 months) scheduled to undergo ICA. All patients underwent cardiac magnetic resonance (CMR) imaging before diagnostic ICA. MDCT viability scans were performed concurrently with diagnostic ICA without the use of additional contrast. The total myocardial scar volume per patient and average transmurality per myocardial segment measured by DE-MDCT were compared with those from DE-CMR. Results: The DE volume measured by MDCT showed an excellent correlation with the volume measured by CMR (r=0.986, p<0.0001). The transmurality per segment by MDCT was well-correlated with CMR (r=0.900, p<0.0001); the diagnostic performance of MDCT in differentiating non-viable from viable myocardium using a 50% transmurality criterion was good with a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 87.5%, 99.5%, 87.5%, 99.5%, and 99.1%, respectively. Conclusion The feasibility of the DE-MDCT viability assessment acquired simultaneously with conventional ICA was proven in patients with chronic MI using DE-CMR as the reference standard.