2024 Consensus Statement on Coronary Stenosis and Plaque Evaluation in CT Angiography From the Asian Society of Cardiovascular Imaging-Practical Tutorial (ASCI-PT)

The Asian Society of Cardiovascular Imaging-Practical Tutorial (ASCI-PT) is an instructional initiative of the ASCI School designed to enhance educational standards. In 2021, the ASCI-PT was convened with the goal of formulating a consensus statement on the assessment of coronary stenosis and coronary plaque using coronary CT angiography (CCTA). Nineteen experts from four countries conducted thorough reviews of current guidelines and deliberated on eight key issues to refine the process and improve the clarity of reporting CCTA findings. The experts engaged in both online and on-site sessions to establish a unified agreement. This document presents a summary of the ASCI-PT 2021 deliberations and offers a comprehensive consensus statement on the evaluation of coronary stenosis and coronary plaque in CCTA.

Computed Tomography Radiomics for Preoperative Prediction of Spread Through Air Spaces in the Early Stage of Surgically Resected Lung Adenocarcinomas

PURPOSE

To assess the added value of radiomics models from preoperative chest CT in predicting the presence of spread through air spaces (STAS) in the early stage of surgically resected lung adenocarcinomas using multiple validation datasets.

MATERIALS AND METHODS

This retrospective study included 550 early-stage surgically resected lung adenocarcinomas in 521 patients, classified into training, test, internal validation, and temporal validation sets (n=211, 90, 91, and 158, respectively). Radiomics features were extracted from the segmented tumors on preoperative chest CT, and a radiomics score (Rad-score) was calculated to predict the presence of STAS. Diagnostic performance of the conventional model and the combined model, based on a combination of conventional and radiomics features, for the diagnosis of the presence of STAS were compared using the area under the curve (AUC) of the receiver operating characteristic curve.

RESULTS

Rad-score was significantly higher in the STAS-positive group compared to the STAS-negative group in the training, test, internal, and temporal validation sets. The performance of the combined model was significantly higher than that of the conventional model in the training set {AUC: 0.784 [95% confidence interval (CI): 0.722-0.846] vs. AUC: 0.815 (95% CI: 0.759-0.872), p=0.042}. In the temporal validation set, the combined model showed a significantly higher AUC than that of the conventional model (p=0.001). The combined model showed a higher AUC than the conventional model in the test and internal validation sets, albeit with no statistical significance.

CONCLUSION

A quantitative CT radiomics model can assist in the non-invasive prediction of the presence of STAS in the early stage of lung adenocarcinomas.

[Visualization of Borderline Coronary Artery Lesions by CT Angiography and Coronary Artery Disease Reporting and Data System]

Coronary artery disease (CAD) narrows vessel lumens at the sites of atherosclerosis, increasing the risk of myocardial ischemia or infarction. Early and accurate diagnosis of CAD is crucial to significantly improve prognosis and management. CT angiography (CTA) is a noninvasive imaging technique that enables assessment of vascular structure and stenosis with high resolution and contrast. Coronary CTA is useful in the diagnosis of CAD. Recently, the CAD-reporting and data system (CAD-RADS), a diagnostic classification system based on coronary CTA, has been developed to improve intervention efficacy in patients suspected of CAD. While the CAD-RAD is based on CTA, it includes borderline categories where interpreting the coronary artery status solely based on CTA findings may be challenging. This review introduces CTA findings that fall within the CAD-RADS categories that necessitate additional tests to decide to perform invasive coronary angiography and discusses appropriate management strategies.

Clinical predictors of polyps recurring in patients with chronic rhinosinusitis and nasal polyps: a systematic review and meta-analysis

BACKGROUND

Identification of perioperative risk factors for recurrent nasal polyps (RNPs) is important for selection of further treatment and determination of appropriate follow-up period. However, the relative prognostic significance of these risk factors has not been investigated.

METHODOLOGY

We compared the nasal symptoms, endoscopic polyp and Lund-Mackey computed tomography scores, and the laboratory and pathological findings of RNP and non-RNP patients. The risk of bias was assessed using the Newcastle-Ottawa scale.

RESULTS

Patients with poor nasal symptom scores and olfactory dysfunctions and high Lund-Mackey computed tomography scores were at higher risk of postoperative RNPs, as were those with allergic conditions and elevated tissue and serum eosinophil levels. The tissue neutrophil counts/percentages were significantly lower in the RNP than the other group. The tissue eosinophil level was of higher diagnostic utility than the serum eosinophil level. The RNP diagnostic odds ratio afforded by the tissue eosinophil count or percentage was 54.1247. The area under the receiver operating characteristic curve was 0.936. The sensitivity and specificity were 0.8809 and 0.8834, respectively.

CONCLUSION

The tissue eosinophil level reliably predicts RNP after endoscopic sinus surgery.

Changes in total volatile organic compound concentration in Seoul subway stations before (2019) and after (2021) the COVID-19 outbreak

Volatile organic compounds (VOCs) are major air pollutants often designated as specific hazardous or toxic. This study analyzed the trends in concentration changes and influencing factors of VOCs in underground subway stations in the Seoul Metro before (2019) and after (2021) the COVID-19 pandemic. A total of 506 samples were collected from 253 stations on lines 1-8 between May 2019 and September 2021. Total VOC concentrations in Seoul Metro increased after the COVID-19 pandemic 3.8 times over. The deeper the underground station platform, the greater the difference in the VOC concentrations between 2019 and 2021, which was positively related. Average VOC concentration was the highest (52.8 µg/m3) at a depth of 25-30 m and the lowest (23.9 µg/m3) at a depth of < 10 m in 2019. In conclusion, excessive disinfection during the COVID-19 pandemic resulted in increased VOC concentrations in the Seoul Metro, especially in the deeper underground stations. Less frequent quarantine disinfection is recommended to improve air quality.

Aortic Annulus Detection Based on Deep Learning for Transcatheter Aortic Valve Replacement Using Cardiac Computed Tomography

BACKGROUND

To propose a deep learning architecture for automatically detecting the complex structure of the aortic annulus plane using cardiac computed tomography (CT) for transcatheter aortic valve replacement (TAVR).

METHODS

This study retrospectively reviewed consecutive patients who underwent TAVR between January 2017 and July 2020 at a tertiary medical center. Annulus Detection Permuted AdaIN network (ADPANet) based on a three-dimensional (3D) U-net architecture was developed to detect and localize the aortic annulus plane using cardiac CT. Patients (N = 72) who underwent TAVR between January 2017 and July 2020 at a tertiary medical center were enrolled. Ground truth using a limited dataset was delineated manually by three cardiac radiologists. Training, tuning, and testing sets (70:10:20) were used to build the deep learning model. The performance of ADPANet for detecting the aortic annulus plane was analyzed using the root mean square error (RMSE) and dice similarity coefficient (DSC).

RESULTS

In this study, the total dataset consisted of 72 selected scans from patients who underwent TAVR. The RMSE and DSC values for the aortic annulus plane using ADPANet were 55.078 ± 35.794 and 0.496 ± 0.217, respectively.

CONCLUSION

Our deep learning framework was feasible to detect the 3D complex structure of the aortic annulus plane using cardiac CT for TAVR. The performance of our algorithms was higher than other convolutional neural networks.

Reliability of synthetic diffusion-weighted imaging with a high b-value for paediatric abdominal MRI

AIM

To evaluate the reliability of synthetic diffusion-weighted imaging (DWI) using a high b-value in comparison to conventional DWI for paediatric abdominal MRI.

MATERIALS AND METHODS

Paediatric patients (<19 years old) who underwent liver or pancreatobiliary MRI with DWI using 10 b-values (b = 0, 25, 50, 75, 100, 200, 400, 600, 800, 1,500 s/mm2) from March to October 2021 were included in this retrospective study. Using the software, synthetic DWI using b = 1,500 s/mm2 was generated automatically by selecting the b-value required as output. Conventional and synthetic DWI values for b = 1,500 s/mm2 were measured at the liver, spleen, paraspinal muscle, and mass lesions, if present, and apparent diffusion coefficient (ADC) values were calculated using the mono-exponential model. Intraclass correlation coefficients (ICCs) were calculated to assess the reliability of conventional and synthetic DWI and ADC values with b = 1,500 s/mm2.

RESULTS

Thirty paediatric patients (M:F = 22:8, mean 10.8 ± 3.1 years old) were included and four had tumours on abdominal MRI. ICC values were 0.906-0.995 between conventional and synthetic DWI and ADC with b = 1,500 s/mm2 in the liver, spleen and muscle. For mass lesions, ICC values were 0.997-0.999 for both synthetic DWI and ADC images.

CONCLUSIONS

Synthetic DWI and ADC values obtained using a high b-value showed excellent agreement with conventional DWI for the liver, spleen, muscle, and mass in paediatric MRI.

[Expert Opinion Questionnaire About Chest CT Scan Using A Negative Pressure Isolation Strecher in COVID-19 Patients: Image Quality and Infection Risk]

PURPOSE

To survey perceptions of certified physicians on the protocol of chest CT in patients with coronavirus (COVID-19) using a negative pressure isolation stretcher (NPIS).

MATERIALS AND METHODS

This study collected questionnaire responses from a total of 27 certified physicians who had previously performed chest CT with NPIS in COVID-19 isolation hospitals.

RESULTS

The nine surveyed hospitals performed an average of 116 chest CT examinations with NPIS each year. Of these, an average of 24 cases (21%) were contrast chest CT. Of the 9 pulmonologists we surveyed, 5 (56%) agreed that patients who showed abnormalities in serum D-dimer required contrast chest CT. All 9 surveyed radiologists agreed that the image quality of the chest CT with NPIS was sufficient for CT image interpretation regarding pneumonia or pulmonary embolism. Furthermore, in our 9 surveyed infectionologists, 5 (56%) agreed that a risk of secondary infection in the CT room after temporary opening of NPIS could be prevented through a process of disinfection.

CONCLUSION

Experienced physicians considered that the effects of NIPS on chest CT image quality was minimal in patients with COVID-19, and the risk of CT room contamination was easily controlled.

Two Years of Experience and Methodology of Korean COVID-19 Living Clinical Practice Guideline Development

BACKGROUND

In Korea, during the early phase of the coronavirus disease 2019 (COVID-19) pandemic, we responded to the uncertainty of treatments under various conditions, consistently playing catch up with the speed of evidence updates. Therefore, there was high demand for national-level evidence-based clinical practice guidelines for clinicians in a timely manner. We developed evidence-based and updated living recommendations for clinicians through a transparent development process and multidisciplinary expert collaboration.

METHODS

The National Evidence-based Healthcare Collaborating Agency (NECA) and the Korean Academy of Medical Sciences (KAMS) collaborated to develop trustworthy Korean living guidelines. The NECA-supported methodological sections and 8 professional medical societies of the KAMS worked with clinical experts, and 31 clinicians were involved annually. We developed a total of 35 clinical questions, including medications, respiratory/critical care, pediatric care, emergency care, diagnostic tests, and radiological examinations.

RESULTS

An evidence-based search for treatments began in March 2021 and monthly updates were performed. It was expanded to other areas, and the search interval was organized by a steering committee owing to priority changes. Evidence synthesis and recommendation review was performed by researchers, and living recommendations were updated within 3-4 months.

CONCLUSION

We provided timely recommendations on living schemes and disseminated them to the public, policymakers and various stakeholders using webpages and social media. Although the output was successful, there were some limitations. The rigor of development issues, urgent timelines for public dissemination, education for new developers, and spread of several new COVID-19 variants have worked as barriers. Therefore, we must prepare systematic processes and funding for future pandemics.

Association between levels of radon and bioaerosols (bacteria and fungi) by living conditions

This study aimed to measure the levels of airborne radon Rn and bioaerosols - culturable airborne bacteria (CAB) and culturable airborne fungi (CAF)-in South Korea's residential environments, considering living conditions such as the number of ventilations, number of windows, floors, temperature, and relative humidity. . The range of Rn levels was 0.43-7.439 pCi/L with a median of 0.70 pCi/L. The CAB levels were 239-488 colony-forming unit (CFU)/m³ with a median of 309 CFU/m³, and CAF levels were 174-366 CFU/m³ with a median of 233 CFU/m³. Thus, this study found that semi-basement residential indoor environments negatively affected Rn and bioaerosol levels, and living in such residences resulted in high health condition scores on the bad side. Given the correlation between airborne Rn and bioaerosol levels, further large-scale studies are needed to identify more reliable and representative of research.

Multicentre external validation of a commercial artificial intelligence software to analyse chest radiographs in health screening environments with low disease prevalence

OBJECTIVES

To externally validate the performance of a commercial AI software program for interpreting CXRs in a large, consecutive, real-world cohort from primary healthcare centres.

METHODS

A total of 3047 CXRs were collected from two primary healthcare centres, characterised by low disease prevalence, between January and December 2018. All CXRs were labelled as normal or abnormal according to CT findings. Four radiology residents read all CXRs twice with and without AI assistance. The performances of the AI and readers with and without AI assistance were measured in terms of area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity.

RESULTS

The prevalence of clinically significant lesions was 2.2% (68 of 3047). The AUROC, sensitivity, and specificity of the AI were 0.648 (95% confidence interval [CI] 0.630-0.665), 35.3% (CI, 24.7-47.8), and 94.2% (CI, 93.3-95.0), respectively. AI detected 12 of 41 pneumonia, 3 of 5 tuberculosis, and 9 of 22 tumours. AI-undetected lesions tended to be smaller than true-positive lesions. The readers' AUROCs ranged from 0.534-0.676 without AI and 0.571-0.688 with AI (all p values < 0.05). For all readers, the mean reading time was 2.96-10.27 s longer with AI assistance (all p values < 0.05).

CONCLUSIONS

The performance of commercial AI in these high-volume, low-prevalence settings was poorer than expected, although it modestly boosted the performance of less-experienced readers. The technical prowess of AI demonstrated in experimental settings and approved by regulatory bodies may not directly translate to real-world practice, especially where the demand for AI assistance is highest.

KEY POINTS

• This study shows the limited applicability of commercial AI software for detecting abnormalities in CXRs in a health screening population. • When using AI software in a specific clinical setting that differs from the training setting, it is necessary to adjust the threshold or perform additional training with such data that reflects this environment well. • Prospective test accuracy studies, randomised controlled trials, or cohort studies are needed to examine AI software to be implemented in real clinical practice.

Identifying fragile calcifications of the aortic valve in transcatheter aortic valve replacement: iodine concentration of aortic valvular calcification by spectral CT

OBJECTIVE

To demonstrate the relationship between spectral computed tomography (CT) measured iodine concentration and strength of aortic valvular calcification (AVC) in patients with aortic valve stenosis (AVS).

METHODS

A retrospective study was performed on patients who underwent transcatheter aortic valve replacement (TAVR) for symptomatic AVS and underwent both pre and postprocedural electrocardiogram gated CT scans using a spectral CT system. Preprocedural CT was used to evaluate the volume and iodine concentration (IC) in the AVC. Postprocedural CT data were used to calculate the volume reduction percentage (VRP) of AVC. Multiple linear regression analysis was used to identify the independent variables related to the VRP in AVCs.

RESULTS

A total of 94 AVCs were selected from 22 patients. The mean volume and IC of the AVCs before TAVR were 0.37 mL ± 0.15 mL and 7 mg/mL ± 10.5 mg/mL, respectively. After TAVR, a median VRP of all 94 AVCs was 18.5%. Multiple linear regression analysis showed that the IC was independently associated with the VRP (coefficient = 1.64, p < 0.001). When an optimal IC cutoff point was set at 4 mg/mL in the assessment of a fragile AVC which showed the VRP was > 18.5%, the sensitivity was 63%; specificity, 91%; positive predictive value, 88%; and negative predictive value, 71%.

CONCLUSIONS

When using spectral CT to prepare the TAVR, measuring the IC of the AVC may be useful to assess the probability of AVC deformity after TAVR.

KEY POINTS

• A dual-layer detector-based spectral CT enables quantifying iodine of contrast media in the aortic valve calcification (AVC) on contrast-enhanced CT images. • The AVC including iodine of contrast media on contrast-enhanced CT image may have loose compositions, associated with the deformity of AVC after TAVR. • Measuring the iodine concentration in AVC may have the potential to assess the probability of AVC deformity, which may be associated with the outcome and complications after TAVR.2.

Indoor exposure assessment for levels of dust mite and total volatile organic compounds (TVOCs) in living houses

The purpose of this study is to measure the levels of dust mites (Dermatophagoides farina group 1 [Der f1] and Dermatophagoides pteronyssinus group 1 [Der p1]) and total volatile organic compounds (TVOCs) in the resident environments with living conditions such as the number of ventilation; the number of window, floor, and temperature; and relative humidity (RH) from vulnerable class in South Korea. Information on residents is designed to be prepared by residents on their general characteristics (daily residence time, heating and cooking type, and cleaning on the day of sampling). Dust mites levels ranged from 24.0 to 1087.5 ng/g with a mean of 215.4 ng/g for Der f1 and from 0.6 to 489.9 ng/g with a mean of 489.9 ng/g for Der p1. Total TVOC levels ranged from 15.3 to 1642.1 μg/m³ with a mean of 219.7 μg/m³. The correlation analysis showed a positive association between Der f1 levels and xylene levels in fall (r = 0.49, r < 0.05) of this study.

Electronic Cigarette or Vaping-Associated Lung Injury Manifested as Acute Eosinophilic Pneumonia: A Case Report

Electronic cigarette or vaping-associated lung injury (EVALI) is a disease defined by lung injuries caused by e-cigarette use. It predominantly manifests in forms of organized pneumonia or diffuse alveolar damage but rarely as acute eosinophilic pneumonia (AEP). This report describes a 34-year-old male with acute respiratory symptoms and a vaping history of only nicotine. Chest CT revealed peripheral distributing multiple patchy consolidations and ground-glass opacities dominant in both lower lobes, bilateral diffuse interlobular septal thickening, and bilateral pleural effusion without cardiomegaly. Bronchoalveolar lavage fluids showed increased eosinophilia levels, while infectious laboratory results were all negative, enabling the diagnosis of both AEP and EVALI. Herein, we report a rare case of only-nicotine vaping EVALI manifested as AEP.

Artificial Intelligence-Based Identification of Normal Chest Radiographs: A Simulation Study in a Multicenter Health Screening Cohort

Objective

This study aimed to investigate the feasibility of using artificial intelligence (AI) to identify normal chest radiography (CXR) from the worklist of radiologists in a health-screening environment.

Materials and Methods

This retrospective simulation study was conducted using the CXRs of 5887 adults (mean age ± standard deviation, 55.4 ± 11.8 years; male, 4329) from three health screening centers in South Korea using a commercial AI (Lunit INSIGHT CXR3, version 3.5.8.8). Three board-certified thoracic radiologists reviewed CXR images for referable thoracic abnormalities and grouped the images into those with visible referable abnormalities (identified as abnormal by at least one reader) and those with clearly visible referable abnormalities (identified as abnormal by at least two readers). With AI-based simulated exclusion of normal CXR images, the percentages of normal images sorted and abnormal images erroneously removed were analyzed. Additionally, in a random subsample of 480 patients, the ability to identify visible referable abnormalities was compared among AI-unassisted reading (i.e., all images read by human readers without AI), AI-assisted reading (i.e., all images read by human readers with AI assistance as concurrent readers), and reading with AI triage (i.e., human reading of only those rendered abnormal by AI).

Results

Of 5887 CXR images, 405 (6.9%) and 227 (3.9%) contained visible and clearly visible abnormalities, respectively. With AI-based triage, 42.9% (2354/5482) of normal CXR images were removed at the cost of erroneous removal of 3.5% (14/405) and 1.8% (4/227) of CXR images with visible and clearly visible abnormalities, respectively. In the diagnostic performance study, AI triage removed 41.6% (188/452) of normal images from the worklist without missing visible abnormalities and increased the specificity for some readers without decreasing sensitivity.

Conclusion

This study suggests the feasibility of sorting and removing normal CXRs using AI with a tailored cut-off to increase efficiency and reduce the workload of radiologists.

Efficient Segmentation for Left Atrium With Convolution Neural Network Based on Active Learning in Late Gadolinium Enhancement Magnetic Resonance Imaging

BACKGROUND

To propose fully automatic segmentation of left atrium using active learning with limited dataset in late gadolinium enhancement in cardiac magnetic resonance imaging (LGE-CMRI).

METHODS

An active learning framework was developed to segment the left atrium in cardiac LGE-CMRI. Patients (n = 98) with atrial fibrillation from the Korea University Anam Hospital were enrolled. First, 20 cases were delineated for ground truths by two experts and used for training a draft model. Second, the 20 cases from the first step and 50 new cases, corrected in a human-in-the-loop manner after predicting using the draft model, were used to train the next model; all 98 cases (70 cases from the second step and 28 new cases) were trained. An additional 20 LGE-CMRI were evaluated in each step.

RESULTS

The Dice coefficients for the three steps were 0.85 ± 0.06, 0.89 ± 0.02, and 0.90 ± 0.02, respectively. The biases (95% confidence interval) in the Bland-Altman plots of each step were 6.36% (-14.90-27.61), 6.21% (-9.62-22.03), and 2.68% (-8.57-13.93). Deep active learning-based annotation times were 218 ± 31 seconds, 36.70 ± 18 seconds, and 36.56 ± 15 seconds, respectively.

CONCLUSION

Deep active learning reduced annotation time and enabled efficient training on limited LGE-CMRI.

Review of Inhalation Health Risks Involving Chloromethylisothiazolinone (CMIT) and Methylisothiazolinone (MIT) Used as Disinfectants in Household Humidifiers

The association between lung injury and exposure to humidifier disinfectant (HD) containing a mixture of chloromethylisothiazolinone (CMIT) and methylisothiazolinone (MIT) has been controversial in South Korea. This study conducts a literature review in order to evaluate the likelihood of CMIT/MIT reaching the lower part of the respiratory tract and causing lung injury. A literature review focused on the inhalation risk of HD containing a mixture of CMIT and MIT. The major contents included the physicochemical properties of CMIT and MIT contained in HDs and methodological reviews on substance analysis, toxicity tests and clinical cases. HD products marketed in South Korea have been reported to contain approximately 1-2% CMIT and 0.2-0.6% MIT along with magnesium nitrate (20-25%), magnesium chloride (0.2-1.0%), and water (70-75%). The types of CMIT and MIT dispersed into the air and deposited in the respiratory tract are assumed to be either gaseous substances or nanoparticles mixed with magnesium salts. The result of the literature review including clinical cases of lung injury among CMIT/MIT HD product users, demonstrated that these chemicals likely reach the lower respiratory tract and accordingly cause lung injury. A number of humidifier disinfectant-associated lung injury cases with clinical evidence should be prioritized in risk assessment of HD containing CMIT and MIT, even though there might be insufficient evidence in all related areas, including inhalation exposure assessment studies, animal testing, and epidemiological studies.

[Korean Clinical Imaging Guidelines for Justification of Diagnostic Imaging Study for COVID-19]

To develop Korean coronavirus disease (COVID-19) chest imaging justification guidelines, eight key questions were selected and the following recommendations were made with the evidence-based clinical imaging guideline adaptation methodology. It is appropriate not to use chest imaging tests (chest radiograph or CT) for the diagnosis of COVID-19 in asymptomatic patients. If reverse transcription-polymerase chain reaction testing is not available or if results are delayed or are initially negative in the presence of symptoms suggestive of COVID-19, chest imaging tests may be considered. In addition to clinical evaluations and laboratory tests, chest imaging may be contemplated to determine hospital admission for asymptomatic or mildly symptomatic unhospitalized patients with confirmed COVID-19. In hospitalized patients with confirmed COVID-19, chest imaging may be advised to determine or modify treatment alternatives. CT angiography may be considered if hemoptysis or pulmonary embolism is clinically suspected in a patient with confirmed COVID-19. For COVID-19 patients with improved symptoms, chest imaging is not recommended to make decisions regarding hospital discharge. For patients with functional impairment after recovery from COVID-19, chest imaging may be considered to distinguish a potentially treatable disease.

Comparison of melt-blown and glass-fiber HEPA asbestos filters based on ISO filter classes, filtration efficiency, power consumption, and face velocity

The purpose of this study was to determine the most efficient airborne asbestos filter for use in an HEPA negative air machines through filter performance testing. The filter classes applied conformed with ISO and European standard (EN 1822) regarding fractional efficiency by dust loading amount for filters, fractional efficiency for negative air machines, and consumption of electrical power at filter size 0.3 μm. Class H13 had the highest fractional efficiency among the three experimental filter classes by particle size, at face velocity of (1, 2, and 3) m/s. Melt-blown (MB) filters exhibited higher fractional performance than did glass-fiber filters at all particle sizes tested (0.3, 0.5, and 1.0 µm). The power consumption of glass-fiber filters was higher (at 10 m³/min) than that of melt-blown filters. Therefore, melt blown filters would be more cost-effective than glass fiber filters for use in HEPA negative air machines, for protection against airborne asbestos.Implications: Air cleaner and related systems were developed to control a variety of airborne pollutants in general indoor environments, but there was no certified system for focusing on asbestos fractional efficiency using filter tests. Class H13 had the highest fractional efficiency among the three experimental filter classes by particle size, at face velocity of (1, 2, and 3) m/s. Melt-blown filters exhibited higher fractional performance than did glass-fiber filters at all particle sizes tested (0.3, 0.5, and 1.0 µm). The power consumption of glass-fiber filters was higher (at 10 m³/min) than that of melt-blown filters.

Semi-Quantitative Scoring of Late Gadolinium Enhancement of the Left Ventricle in Patients with Ischemic Cardiomyopathy: Improving Interobserver Reliability and Agreement Using Consensus Guidance from the Asian Society of Cardiovascular Imaging-Practical Tutorial (ASCI-PT) 2020

Objective

This study aimed to evaluate the effect of implementing the consensus statement from the Asian Society of Cardiovascular Imaging-Practical Tutorial 2020 (ASCI-PT 2020) on the reliability of cardiac MR with late gadolinium enhancement (CMR-LGE) myocardial viability scoring between observers in the context of ischemic cardiomyopathy.

Materials and Methods

A total of 17 cardiovascular imaging experts from five different countries evaluated CMR obtained in 26 patients (male:female, 23:3; median age [interquartile range], 55.5 years [50–61.8]) with ischemic cardiomyopathy. For LGE scoring, based on the 17 segments, the extent of LGE in each segment was graded using a five-point scoring system ranging from 0 to 4 before and after exposure according to the consensus statement. All scoring was performed via web-based review. Scores for slices, vascular territories, and total scores were obtained as the sum of the relevant segmental scores. Interobserver reliability for segment scores was assessed using Fleiss’ kappa, while the intraclass correlation coefficient (ICC) was used for slice score, vascular territory score, and total score. Inter-observer agreement was assessed using the limits of agreement from the mean (LoA).

Results

Interobserver reliability (Fleiss’ kappa) in each segment ranged 0.242–0.662 before the consensus and increased to 0.301–0.774 after the consensus. The interobserver reliability (ICC) for each slice, each vascular territory, and total score increased after the consensus (slice, 0.728–0.805 and 0.849–0.884; vascular territory, 0.756–0.902 and 0.852–0.941; total score, 0.847 and 0.913, before and after implementing the consensus statement, respectively. Interobserver agreement in scoring also improved with the implementation of the consensus for all slices, vascular territories, and total score. The LoA for the total score narrowed from ± 10.36 points to ± 7.12 points.

Conclusion

The interobserver reliability and agreement for CMR-LGE scoring for ischemic cardiomyopathy improved when following guidance from the ASCI-PT 2020 consensus statement.

Standardization of 129I using the movable 4πβ(LS)-X(NaI(Tl)) system

The ¹²⁹I standardization, using the movable 4πβ(LS)-X(NaI(Tl)) coincidence system, was performed for two ¹²⁹I radioactive sources - one was dissolved in 0.1M NaOH solution and the other in 0.1M HNO₃ solution. The system incorporates three movable PM tubes for a β-counter placed on a plane and a X-ray detector that can be moved up to the bottom of the vial. The β-efficiency depending on the amount of radioactive solution was investigated with 14 liquid scintillation samples prepared by gravimetrically dispensing 4.4-145 mg of ¹²⁹I radioactive solution. The β-efficiencies above 90% were observed at less than 56 mg, but it was at most 70% at 145 mg. This occurred regardless of the activity of the sample or the type of chemical solution used to dissolve ¹²⁹I source. The activity concentration of each ¹²⁹I source was determined by efficiency-extrapolation method for samples with an activity range of 0.28-4.5 kBq. The β-efficiency points were derived over 10 intervals by moving 3-PM tubes in fine steps of about 1 mm from the sample. The highest value for β-efficiency was 95%. The combined uncertainty were 0.25% and 0.26%, respectively. The stated precision obtained using the system is better than that previously reported in the literature obtained by the triple to double coincidence ratio (TDCR) or the CIEMAT/NIST efficiency tracing method.

Deep convolution neural networks to differentiate between COVID-19 and other pulmonary abnormalities on chest radiographs: Evaluation using internal and external datasets

We aimed to evaluate the performance of convolutional neural networks (CNNs) in the classification of coronavirus disease 2019 (COVID-19) disease using normal, pneumonia, and COVID-19 chest radiographs (CXRs). First, we collected 9194 CXRs from open datasets and 58 from the Korea University Anam Hospital (KUAH). The number of normal, pneumonia, and COVID-19 CXRs were 4580, 3884, and 730, respectively. The CXRs obtained from the open dataset were randomly assigned to the training, tuning, and test sets in a 70:10:20 ratio. For external validation, the KUAH (20 normal, 20 pneumonia, and 18 COVID-19) dataset, verified by radiologists using computed tomography, was used. Subsequently, transfer learning was conducted using DenseNet169, InceptionResNetV2, and Xception to identify COVID-19 using open datasets (internal) and the KUAH dataset (external) with histogram matching. Gradient-weighted class activation mapping was used for the visualization of abnormal patterns in CXRs. The average AUC and accuracy of the multiscale and mixed-COVID-19Net using three CNNs over five folds were (0.99 ± 0.01 and 92.94% ± 0.45%), (0.99 ± 0.01 and 93.12% ± 0.23%), and (0.99 ± 0.01 and 93.57% ± 0.29%), respectively, using the open datasets (internal). Furthermore, these values were (0.75 and 74.14%), (0.72 and 68.97%), and (0.77 and 68.97%), respectively, for the best model among the fivefold cross-validation with the KUAH dataset (external) using domain adaptation. The various state-of-the-art models trained on open datasets show satisfactory performance for clinical interpretation. Furthermore, the domain adaptation for external datasets was found to be important for detecting COVID-19 as well as other diseases.

Development of a movable 4πβ(LS)-γ coincidence counting system for activity standardization of β-γ emitters

A new movable 3PM-γ coincidence system, based on 4πβ(LS)-γ coincidence counting, for activity measurement of β-γ emitters has been designed at the Korea Research Institute of Standards and Science (KRISS). The system incorporates 3 PM tubes on the plane and two detectors placed above and below the center of the plane. The 3 PM tubes for β-counters in the plane are movable up to 100 mm from a liquid scintillation vial, thus enabling the variation of β-detection efficiencies by a geometrical technique. A NaI(Tl) γ-counter was set above for the present work. The β-event is determined by counting the logical sum of three double coincidences. All the necessary electronics, i.e., logical sum, adjusting the duration of dead-time of each counting channel and coincidence resolving times, and analyzing coincidence relation, were specially designed to be fabricated in an integrated circuit. Details of the detectors, the electronics, the overall movable 3PM-γ coincidence system are presented, as well as the results of investigations to assess its operating characteristics. Validation measurements have been performed with ⁶⁰Co and ⁵⁷Co sources. The highest β-detection efficiency achieved with ⁶⁰Co and ⁵⁷Co was 97% and 95%, respectively. The activity concentration determined with a new system agreed with calibrated values within the uncertainty range. Further results from validation measurements and the corresponding uncertainty budgets are presented.

Observation of Coulomb-Assisted Nuclear Bound State of Ξ^{-}-^{14}N System

In an emulsion-counter hybrid experiment performed at J-PARC, a Ξ^{-} absorption event was observed which decayed into twin single-Λ hypernuclei. Kinematic calculations enabled a unique identification of the reaction process as Ξ^{-}+^{14}N→_{Λ}^{10}Be+_{Λ}^{5}He. For the binding energy of the Ξ^{-} hyperon in the Ξ^{-}-^{14}N system a value of 1.27±0.21  MeV was deduced. The energy level of Ξ^{-} is likely a nuclear 1p state which indicates a weak ΞN-ΛΛ coupling.

Predictive factors of recurrence after resection of subsolid clinical stage IA lung adenocarcinoma

BACKGROUND

Ongoing studies are currently investigating the extent of surgical resection required for subsolid cancers. This study aimed to investigate the predictive factors related to recurrence in patients with clinical stage IA subsolid cancer who underwent either lobectomy or sublobar resection.

METHODS

This was a prospective multicenter observational study conducted in eight qualifying university teaching hospitals between April 2014 and December 2016. A total of 173 patients with subsolid nodules pathologically confirmed to have primary lung adenocarcinoma and stage IA disease were included in the final analysis. All patients underwent lobectomy, segmentectomy, or wedge resection performed by experienced thoracoscopic surgeons at each site. The surgical procedure was chosen based on the decision of the surgeons involved. The primary endpoint was time to recurrence (TTR).

RESULTS

The study population was 43.9% (76 of 173) male with a mean age of 60.7 years. During the median follow-up period of 5.01 years, nine patients (5%) experienced disease recurrence. In the multivariable analysis, tumor size (size ≥2 cm) (hazard ratio: 73.717, 95% confidence interval [CI]: 3.635-895.036; p < 0.001) and stage IA3 (hazard ratio: 62.010, 95% CI: 2.837-855.185; p < 0.001) were independent predictors of tumor recurrence. When analyzing the recurrence outcome in patients according to surgical procedure, no significant difference was found in TTR among the three groups (i.e., lobectomy, segmentectomy, and wedge resection; p = 0.99).

CONCLUSIONS

Patients with radiologically subsolid lung adenocarcinoma measuring <3 cm could be candidates for sublobar resection instead of lobectomy.