Pulmonary disease identification and characterization are among the most intriguing research topics of recent years since they require an accurate and prompt diagnosis. Although pulmonary radiography has helped in lung disease diagnosis, the interpretation of the radiographic image has always been a major concern for doctors and radiologists to reduce diagnosis errors. Due to their success in image classification and segmentation tasks, cutting-edge artificial intelligence techniques like machine learning (ML) and deep learning (DL) are widely encouraged to be applied in the field of diagnosing lung disorders and identifying them using medical images, particularly radiographic ones. For this end, the researchers are concurring to build systems based on these techniques in particular deep learning ones. In this paper, we proposed three deep-learning models that were trained to identify the presence of certain lung diseases using thoracic radiography. The first model, named \"CovCXR-Net\", identifies the COVID-19 disease (two cases: COVID-19 or normal). The second model, named \"MDCXR3-Net\", identifies the COVID-19 and pneumonia diseases (three cases: COVID-19, pneumonia, or normal), and the last model, named \"MDCXR4-Net\", is destined to identify the COVID-19, pneumonia and the pulmonary opacity diseases (4 cases: COVID-19, pneumonia, pulmonary opacity or normal). These models have proven their superiority in comparison with the state-of-the-art models and reached an accuracy of 99,09 %, 97.74 %, and 90,37 % respectively with three benchmarks.

Thoracic radiography and abdominal ultrasonography are part of standard diagnostic investigations in cases of canine immune-mediated polyarthritis (IMPA). However, the clinical importance of thoracic and abdominal imaging towards the management of canine IMPA currently remains unknown. The primary aim of this study was to describe the findings documented on thoracic radiography and abdominal ultrasonography in dogs diagnosed with IMPA, and to evaluate the diagnostic utility of thoracic radiography and abdominal ultrasonography in the initial approach and management of these cases. Seventy-seven dogs diagnosed with IMPA who underwent thoracic radiography and abdominal ultrasonography at a single referral hospital between 2008 and 2022 were included. The diagnostic imaging studies of these 77 dogs were reviewed by one blinded board-certified diagnostic imaging specialist for quality assurance. The medical records, including the diagnostic imaging reports of these dogs, were then reviewed by three blinded board-certified internal medicine specialists. Using a modified version of a previous question and scoring system, the three internal medicine specialists then generated an answer for the overall diagnostic utility and a diagnostic utility score for thoracic radiography and abdominal ultrasonography for each case. The abnormal findings identified in radiography and ultrasonography were described. In the cases where the findings were considered significant enough to immediately affect the case management, the results of the further investigations that were subsequently performed were also described. No abnormalities were detected in thoracic radiography for 30 cases, and none were detected in abdominal ultrasound for 6. The majority of the internists considered thoracic radiography to be not useful in the overall case management at the time of IMPA diagnosis in 70 cases, and considered abdominal ultrasonography to be not useful in the overall case management in 57 cases. The majority of the internists agreed on the utility of thoracic radiography in 95% of the cases, and in 61% of the cases for abdominal ultrasonography. The most common finding in the thoracic radiography was a mild bronchial pulmonary pattern, and the most common in the abdominal ultrasonography was mild lymphadenomegaly. Therefore, although thoracic radiography and abdominal ultrasonography identified numerous abnormal findings in this population of dogs, in the majority of the cases, the findings were deemed not useful towards the overall case management at the time of the initial diagnosis of IMPA. Thus, the use of thoracic radiography and abdominal ultrasonography should be taken into careful consideration when considering initial diagnostic investigations for canine IMPA.

UNASSIGNED: In Thailand, epidemiological data on silicosis in the ceramic sector is lacking and the underdiagnosis of silicosis remains an extensive concern. Therefore, this study aimed to determine the prevalence of silicosis and the extent of underdiagnosis among Thai ceramic workers by reinterpreting chest radiographs previously taken by a health check-up unit.
UNASSIGNED: This retrospective cross-sectional study was conducted on ceramic workers undergoing health surveillance using chest radiographs in one ceramic factory in September 2018. All chest radiographs were done retrospectively, then were reinterpreted by professional readers specially trained in using the ILO International Classification of Radiograph of Pneumoconioses (ILO/ICRP). Chest radiographs with a profusion of 1/1 or greater were suggestive of silicosis.
UNASSIGNED: Out of the 244 participants undergoing chest radiography, the prevalence of silicosis was 2.9%. Overall, the mean age of the participants was 41 years, and 72.1% were female. Among individuals with silicosis, the median age was 43 years; 71.4% were male; the average employment duration was 26.9 years; while the male sex was the significant variable associated with silicosis with an odds ratio of 7.01 (95% confidence interval 1.31 to 37.4). Regarding the underdiagnosis, the health check-up unit failed to recognize all individuals with silicosis, and could not detect any radiographic chest abnormalities in 57.1% of those with silicosis.
UNASSIGNED: Despite the low prevalence of silicosis among Thai ceramic workers, this finding indicates ongoing exposure to silica in the ceramic industry. In addition, a significant proportion of the silicosis cases were underrecognized. Future efforts to prevent underdiagnosis and improve an occupational health surveillance service in Thailand are needed.

BACKGROUND: Severe courses and high hospitalization rates were ubiquitous during the first pandemic SARS-CoV-2 waves. Thus, we aimed to examine whether integrative diagnostics may aid in identifying vulnerable patients using crucial data and materials obtained from COVID-19 patients hospitalized between 2020 and 2021 (n = 52). Accordingly, we investigated the potential of laboratory biomarkers, specifically the dynamic cell decay marker cell-free DNA and radiomics features extracted from chest CT.
METHODS: Separate forward and backward feature selection was conducted for linear regression with the Intensive-Care-Unit (ICU) period as the initial target. Three-fold cross-validation was performed, and collinear parameters were reduced. The model was adapted to a logistic regression approach and verified in a validation naïve subset to avoid overfitting.
RESULTS: The adapted integrated model classifying patients into \"ICU/no ICU demand\" comprises six radiomics and seven laboratory biomarkers. The models\' accuracy was 0.54 for radiomics, 0.47 for cfDNA, 0.74 for routine laboratory, and 0.87 for the combined model with an AUC of 0.91.
CONCLUSIONS: The combined model performed superior to the individual models. Thus, integrating radiomics and laboratory data shows synergistic potential to aid clinic decision-making in COVID-19 patients. Under the need for evaluation in larger cohorts, including patients with other SARS-CoV-2 variants, the identified parameters might contribute to the triage of COVID-19 patients.

Description Lung cavitation as a complication of COVID-19 is rare. A 56-year-old male presented with lung cavitation, small volume hemoptysis, and violaceous discoloration of the right great toe, 5 weeks after diagnosis with COVID-19 pneumonia. The digital changes were consistent with previously described microvascular changes called \"COVID toe.\" CT angiography of the chest was negative for pulmonary embolism but showed a 2.5 x 3.1 x 2.2 cm cavitation within the right lung. Extensive evaluation for commonly implicated infectious and autoimmune causes was negative. We concluded that the cavitary lung lesions were likely a complication of COVID-19 pneumonia and may implicate microangiopathy as an important component of pathogenesis. This case highlights a rare complication of COVID-19 of which clinicians should be aware.

OBJECTIVE: To compare the visibility of anatomical structures and overall quality of the attenuation images obtained with a dark-field X-ray radiography prototype with those from a commercial radiography system.
METHODS: Each of the 65 patients recruited for this study obtained a thorax radiograph at the prototype and a reference radiograph at the commercial system. Five radiologists independently assessed the visibility of anatomical structures, the level of motion artifacts, and the overall image quality of all attenuation images on a five-point scale, with 5 points being the highest rating. The average scores were compared between the two image types. The differences were evaluated using an area under the curve (AUC) based z-test with a significance level of p ≤ 0.05. To assess the variability among the images, the distributions of the average scores per image were compared between the systems.
RESULTS: The overall image quality was rated high for both devices, 4.2 for the prototype and 4.6 for the commercial system. The rating scores varied only slightly between both image types, especially for structures relevant to lung assessment, where the images from the commercial system were graded slightly higher. The differences were statistically significant for all criteria except for the bronchial structures, the cardiophrenic recess, and the carina.
CONCLUSIONS: The attenuation images acquired with the prototype were assigned a high diagnostic quality despite a lower resolution and the presence of motion artifacts. Thus, the attenuation-based radiographs from the prototype can be used for diagnosis, eliminating the need for an additional conventional radiograph.
CONCLUSIONS: • Despite a low tube voltage (70 kVp) and comparably long acquisition time, the attenuation images from the dark-field chest radiography system achieved diagnostic quality for lung assessment. • Commercial chest radiographs obtained a mean rating score regarding their diagnostic quality of 4.6 out of 5, and the grating-based images had a slightly lower mean rating score of 4.2 out of 5. • The difference in rating scores for anatomical structures relevant to lung assessment is below 5%.

OBJECTIVE: A cardiothoracic ratio ≥0.50 is widely used as an indicator of cardiomegaly, but associations between the cardiothoracic ratio and left ventricular systolic dysfunction (LVSD) have not been investigated previously. We conducted this study to investigate the relationship between cardiothoracic ratio measured using computed tomography (CT) and left ventricular ejection fraction (LVEF), and to determine the optimal cardiothoracic ratio for predicting left ventricular systolic dysfunction (LVSD).
METHODS: A retrospective cross-sectional study was performed using data from patients who underwent both chest CT and echocardiography at the emergency department from January 1 to December 31, 2021. The patients were classified as normal, or having mild, moderate, and severe LVSD based on their LVEF, and the cardiothoracic ratios of each group were compared. The receiver operating characteristic (ROC) curve analyses were used to identify the optimal cardiothoracic ratio for prediction of mild, moderate, and severe LVSD.
RESULTS: The final study population included 444 patients. The median CT-measured cardiothoracic ratio was 0.54 for patients with normal LVEF, and 0.60 for patients with LVSD (P<0.001). The optimal CT-measured cardiothoracic ratios for predicting mild, moderate, and severe LVSD were 0.56, 0.59, and 0.60, and their areas under the ROC curve were 0.653, 0.690, and 0.680, and negative predictive values were 90%, 94%, and 98%, respectively.
CONCLUSIONS: The best cutoff value for a CT-measured cardiothoracic ratio suggestive of LVSD was 0.56, which is very different from the 0.50 value typically considered an abnormal cardiothoracic ratio. The CT-measured cardiothoracic ratio ≥0.56 can be used as a rough indicator of mild LVSD, and a ratio <0.60 can exclude severe LVSD with a high degree of confidence.

UNASSIGNED: To report values of the chest radiographic thoracic area (CRTA) in ventilated, term-born infants without respiratory disease and to evaluate whether CRTA is related to demographic data at birth.
UNASSIGNED: Retrospective, observational cohort study in a tertiary neonatal unit at King\'s College Hospital NHS Foundation Trust, London, UK.Newborn infants born after 36 completed weeks of gestation, ventilated for poor perinatal adaptation or hypoxic ischaemic encephalopathy without respiratory disease and admitted in a recent eight-year period (2014-2022).The CRTA was assessed by free-hand tracing of the perimeter of the thoracic area as outlined by the diaphragm and the rib cage excluding the mediastinal structures and was calculated using the Sectra PACS software.
UNASSIGNED: One hundred and twenty-one infants (75 male) were included with a median (IQR) gestation of 40 (38-41) weeks and birth weight of 3.41 (3.04-3.75) kg. The median (IQR) CRTA was 2,589 (2,167-2,943) mm2 and was significantly related to birth weight (r = 0.316, p = 0.003), gestation at birth (r = 0.193, p = 0.032) and birth weight z-score (r = 0.187, p = 0.038).
UNASSIGNED: We report values of the chest radiographic thoracic area in ventilated term-born infants which could be used as reference for determining respiratory disease severity.

UNASSIGNED: To develop and validate a deep learning-based screening tool for the early diagnosis of scoliosis using chest radiographs with a semi-supervised generative adversarial network (GAN).
UNASSIGNED: Using a semi-supervised learning framework with a GAN, a screening tool for diagnosing scoliosis was developed and validated through the chest PA radiographs of patients at two different tertiary hospitals. Our proposed method used training GAN with mild to severe scoliosis only in a semi-supervised manner, as an upstream task to learn scoliosis representations and a downstream task to perform simple classification for differentiating between normal and scoliosis states sensitively.
UNASSIGNED: The area under the receiver operating characteristic curve, negative predictive value (NPV), positive predictive value, sensitivity, and specificity were 0.856, 0.950, 0.579, 0.985, and 0.285, respectively.
UNASSIGNED: Our deep learning-based artificial intelligence software in a semi-supervised manner achieved excellent performance in diagnosing scoliosis using the chest PA radiographs of young individuals; thus, it could be used as a screening tool with high NPV and sensitivity and reduce the burden on radiologists for diagnosing scoliosis through health screening chest radiographs.
UNASSIGNED: 흉부 X선 사진에서 척추측만증을 조기진단 할 수 있는 딥러닝 기반의 스크리닝 소프트웨어를 준지도학습(semi-supervised generative adversarial network; 이하 GAN) 방법을 이용하여 개발하고자 하였다.
UNASSIGNED: 두 곳의 상급종합병원에서 촬영된 흉부 X선 사진에서 척추측만증을 조기진단할 수 있는 스크리닝 소프트웨어를 개발하기 위하여 GAN 방법이 이용되었다. GAN의 훈련과정에서 경증에서 중증의 척추측만증을 보이는 흉부 X선 사진들을 사용하였으며 upstream task에서 척추측만증의 특징을 학습하고, downstream task에서 정상과 척추측만증을 분류하도록 훈련하였다.
UNASSIGNED: 수신자 조작 특성 곡선의 곡선하면적(area under the receiver operating characteristic curve), 음성예측도, 양성예측도, 민감도 및 특이도는 각각 0.856, 0.950, 0.579, 0.985, 0.285이었다.
UNASSIGNED: 우리가 GAN 방법을 이용하여 개발한 딥러닝 기반의 스크리닝 소프트웨어는 청소년의 흉부 X선에서 척추측만증을 진단하는데 있어서 높은 음성예측도와 민감도를 보였다. 이 소프트웨어가 건강검진을 목적으로 촬영한 청소년의 흉부 X선 사진에 진단 스크리닝 도구로써 이용된다면 영상의학과 의사의 부담을 덜어주며, 척추측만증의 조기진단에 기여할 것으로 생각된다.

UNASSIGNED: Thoracic ultrasonography (TUS) is widely used in equine practice but comparison to radiography is limited in horses.
UNASSIGNED: To validate a novel, objective scoring system for TUS in adult horses and to compare ultrasonographic and radiographic findings.
UNASSIGNED: 13 healthy horses and 9 with confirmed bacterial pneumonia.
UNASSIGNED: Prospective study in which TUS and radiography were performed on healthy horses and those with bacterial pneumonia confirmed by clinical signs and results of transtracheal wash analysis. Ultrasonography was scored utilizing a novel scoring system evaluating number of comet tail lesions, the presence or absence of pleural effusion and/or pulmonary consolidation in each intercostal space. Eighteen horses had thoracic radiographs taken that were scored by a board-certified radiologist utilizing a previously described system. Total scores were recorded and compared between control and diseased patients.
UNASSIGNED: Ultrasonographic scores were significantly higher in the diseased group (median= 126) than in the control group (median = 20, p = 0.01). Receiver operating characteristics (ROC) analysis identified a sensitivity of 66.7% (95% CI 0.417-1) and specificity of 92.3% (95% CI 0.462-1) for the ability of ultrasonography to identify bacterial pneumonia utilizing a TUS score cutoff of 37.
UNASSIGNED: TUS had moderate sensitivity and high specificity for identification of bacterial pneumonia in adult horses. TUS appears to be an acceptable stand-alone imaging modality for diagnosis of bacterial pneumonia in horses when radiography is not practical.