[Visualization of Borderline Coronary Artery Lesions by CT Angiography and Coronary Artery Disease Reporting and Data System]. / 관상동맥 질환 íŒë ê³¼ 자료 체계와 CT í˜ˆê´€ì¡°ì˜ìˆ ì—ì„œì˜ 경계성 관상동맥 병변.

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.

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.

Longitudinal long term follow up investigation on the carcinogenic impact of polyhexamethylene guanidine phosphate in rat models.

Polyhexamethylene guanidine phosphate (PHMG-p) is a major component in humidifier disinfectants, which cause life-threatening lung injuries. However, to our knowledge, no published studies have investigated associations between PHMG-p dose and lung damage severity with long-term follow-up. Therefore, we evaluated longitudinal dose-dependent changes in lung injuries using repeated chest computed tomography (CT). Rats were exposed to low (0.2 mg/kg, n = 10), intermediate (1.0 mg/kg, n = 10), and high (5.0 mg/kg, n = 10) doses of PHMG-p. All rats underwent repeated CT scans after 10 and 40 weeks following the first exposure. All CT images were quantitatively analyzed using commercial software. Inflammation/fibrosis and tumor counts underwent histopathological evaluation. In both radiological and histopathologic results, the lung damage severity increased as the PHMG-p dose increased. Moreover, the number, size, and malignancy of the lung tumors increased as the dose increased. Bronchiolar-alveolar hyperplasia developed in all groups. During follow-up, there was intergroup variation in bronchiolar-alveolar hyperplasia progression, although bronchiolar-alveolar adenomas or carcinomas usually increase in size over time. Thirty-three carcinomas were detected in the high-dose group in two rats. Overall, lung damage from PHMG-p and the number and malignancy of lung tumors were shown to be dose-dependent in a rat model using repeated chest CT scans during a long-term follow-up.

Thoracic Aortic Calcium Density and Area in Long-Term Atherosclerotic Cardiovascular Disease Risk Among Men Versus Women.

BACKGROUND: The development of thoracic aortic calcium (TAC) temporally precedes coronary artery calcium more often in women versus men. Whether TAC density and area confer sex-specific differences in atherosclerotic cardiovascular disease (ASCVD) risk is unknown. METHODS: We studied 5317 primary prevention patients who underwent coronary artery calcium scoring on noncontrast cardiac gated computed tomography with TAC >0. The Agatston TAC score (Agatston units), density (Hounsfield units), and area (mm2) were compared between men and women. Cox proportional hazards regression calculated adjusted hazard ratios for TAC density-area groups with ASCVD mortality, adjusting for traditional risk factors, coronary artery calcium, and TAC. Multinomial logistic regression calculated adjusted odds ratios for the association between traditional risk factors and TAC density-area groups. RESULTS: The mean age was 60.7 years, 38% were women, and 163 ASCVD deaths occurred over a median of 11.7-year follow-up. Women had higher median TAC scores (97 versus 84 Agatston units; P=0.004), density (223 versus 210 Hounsfield units; P<0.001), and area (37 versus 32 mm2; P=0.006) compared with men. There was a stepwise higher incidence of ASCVD deaths across increasing TAC density-area groups in men though women with low TAC density relative to TAC area (3.6 per 1000 person-years) had survival probability commensurate with the high-density-high-area group (4.8 per 1000 person-years). Compared with low TAC density-area, low TAC density/high TAC area conferred a 3.75-fold higher risk of ASCVD mortality in women (adjusted hazard ratio, 3.75 [95% CI, 1.13-12.44]) but not in men (adjusted hazard ratio, 1.16 [95% CI, 0.48-2.84]). Risk factors most strongly associated with low TAC density/high TAC area differed in women (diabetes: adjusted odds ratio, 2.61 [95% CI, 1.34-5.07]) versus men (hypertension: adjusted odds ratio, 1.45 [95% CI, 1.11-1.90]). CONCLUSIONS: TAC density-area phenotypes do not consistently associate with ASCVD mortality though low TAC density relative to area may be a marker of increased ASCVD risk in women.

Utilities and Limitations of Cardiac Magnetic Resonance Imaging in Dilated Cardiomyopathy.

Dilated cardiomyopathy (DCM) is one of the most common types of non-ischemic cardiomyopathy. DCM is characterized by left ventricle (LV) dilatation and systolic dysfunction without coronary artery disease or abnormal loading conditions. DCM is not a single disease entity and has a complex historical background of revisions and updates to its definition because of its diverse etiology and clinical manifestations. In cases of LV dilatation and dysfunction, conditions with phenotypic overlap should be excluded before establishing a DCM diagnosis. The differential diagnoses of DCM include ischemic cardiomyopathy, valvular heart disease, burned-out hypertrophic cardiomyopathy, arrhythmogenic cardiomyopathy, and non-compaction. Cardiac magnetic resonance (CMR) imaging is helpful for evaluating DCM because it provides precise measurements of cardiac size, function, mass, and tissue characterization. Comprehensive analyses using various sequences, including cine imaging, late gadolinium enhancement imaging, and T1 and T2 mapping, may help establish differential diagnoses, etiological work-up, disease stratification, prognostic determination, and follow-up procedures in patients with DCM phenotypes. This article aimed to review the utilities and limitations of CMR in the diagnosis and assessment of DCM.

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.

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.

Evaluation of fully automated commercial software for Agatston calcium scoring on non-ECG-gated low-dose chest CT with different slice thickness.

OBJECTIVES: To evaluate commercial deep learning-based software for fully automated coronary artery calcium (CAC) scoring on non-electrocardiogram (ECG)-gated low-dose CT (LDCT) with different slice thicknesses compared with manual ECG-gated calcium-scoring CT (CSCT). METHODS: This retrospective study included 567 patients who underwent both LDCT and CSCT. All LDCT images were reconstructed with a 2.5-mm slice thickness (LDCT2.5-mm), and 453 LDCT scans were reconstructed with a 1.0-mm slice thickness (LDCT1.0-mm). Automated CAC scoring was performed on CSCT (CSCTauto), LDCT1.0-mm, and LDCT2.5-mm images. The reliability of CSCTauto, LDCT1.0-mm, and LDCT2.5-mm was compared with manual CSCT scoring (CSCTmanual) using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. Agreement, in CAC severity category, was analyzed using weighted kappa statistics. Diagnostic performance at various Agatston score cutoffs was also calculated. RESULTS: CSCTauto, LDCT1.0-mm, and LDCT2.5-mm demonstrated excellent agreement with CSCTmanual (ICC [95% confidence interval, CI]: 1.000 [1.000, 1.000], 0.937 [0.917, 0.952], and 0.955 [0.946, 0.963], respectively). The mean difference with 95% limits of agreement was lower with LDCT1.0-mm than with LDCT2.5-mm (19.94 [95% CI, -244.0, 283.9] vs. 45.26 [-248.2, 338.7]). Regarding CAC severity, LDCT1.0-mm achieved almost perfect agreement, and LDCT2.5-mm achieved substantial agreement (kappa [95% CI]: 0.809 [0.776, 0.838], 0.776 [0.740, 0.809], respectively). Diagnostic performance for detecting Agatston score ≥ 400 was also higher with LDCT1.0-mm than with LDCT2.5-mm (F1 score, 0.929 vs. 0.855). CONCLUSIONS: Fully automated CAC-scoring software with both CSCT and LDCT yielded excellent reliability and agreement with CSCTmanual. LDCT1.0-mm yielded more accurate Agatston scoring than LDCT2.5-mm using fully automated commercial software. KEY POINTS: • Total Agatston scores and all vessels of CSCTauto, LDCT1.0-mm, and LDCT2.5-mm demonstrated excellent agreement with CSCTmanual (all ICC > 0.85). • The diagnostic performance for detecting all Agatston score cutoffs was better with LDCT1.0-mm than with LDCT2.5-mm. • This automated software yielded a lower degree of underestimation compared with methods described in previous studies, and the degree of underestimation was lower with LDCT1.0-mm than with LDCT2.5-mm.

Fully automatic coronary calcium scoring in non-ECG-gated low-dose chest CT: comparison with ECG-gated cardiac CT.

OBJECTIVES: To validate an artificial intelligence (AI)-based fully automatic coronary artery calcium (CAC) scoring system on non-electrocardiogram (ECG)-gated low-dose chest computed tomography (LDCT) using multi-institutional datasets with manual CAC scoring as the reference standard. METHODS: This retrospective study included 452 subjects from three academic institutions, who underwent both ECG-gated calcium scoring computed tomography (CSCT) and LDCT scans. For all CSCT and LDCT scans, automatic CAC scoring (CAC_auto) was performed using AI-based software, and manual CAC scoring (CAC_man) was set as the reference standard. The reliability and agreement of CAC_auto was evaluated and compared with that of CAC_man using intraclass correlation coefficients (ICCs) and Bland-Altman plots. The reliability between CAC_auto and CAC_man for CAC severity categories was analyzed using weighted kappa (κ) statistics. RESULTS: CAC_auto on CSCT and LDCT yielded a high ICC (0.998, 95% confidence interval (CI) 0.998-0.999 and 0.989, 95% CI 0.987-0.991, respectively) and a mean difference with 95% limits of agreement of 1.3 ± 37.1 and 0.8 ± 75.7, respectively. CAC_auto achieved excellent reliability for CAC severity (κ = 0.918-0.972) on CSCT and good to excellent but heterogenous reliability among datasets (κ = 0.748-0.924) on LDCT. CONCLUSIONS: The application of an AI-based automatic CAC scoring software to LDCT shows good to excellent reliability in CAC score and CAC severity categorization in multi-institutional datasets; however, the reliability varies among institutions. KEY POINTS: • AI-based automatic CAC scoring on LDCT shows excellent reliability with manual CAC scoring in multi-institutional datasets. • The reliability for CAC score-based severity categorization varies among datasets. • Automatic scoring for LDCT shows a higher false-positive rate than automatic scoring for CSCT, and most common causes of a false-positive are image noise and artifacts for both CSCT and LDCT.

Hematotoxic Effect of Respiratory Exposure to PHMG-p and Its Integrated Genetic Analysis.

Polyhexamethylene guanidine phosphate (PHMG-p), the main ingredient of humidifier disinfectants, circulates systemically through the lungs; however, its toxicological assessment has been primarily limited to pulmonary disease. Herein, we investigated the possible abnormalities in hematopoietic function 20 weeks after intratracheal instillation of PHMG-p in a rat model. Notable abnormalities were found out in the peripheral blood cell count and bone marrow (BM) biopsy, while RNA sequencing of BM tissue revealed markedly altered gene expression. Furthermore, signaling involved in hematopoietic dysfunction was predicted by analyzing candidate genes through Ingenuity Pathway Analysis (IPA) program. Respiratory PHMG-p exposure significantly decreased monocyte and platelet (PLT) counts and total protein, while significantly increasing hemoglobin and hematocrit levels in peripheral blood. Histopathological analysis of the BM revealed a reduced number of megakaryocytes, with no significant differences in spleen and liver weight to body weight. Moreover, PHMG-p exposure significantly activated estrogen receptor signaling and RHOA signaling, and inhibited RHOGDI signaling. In IPA analysis, candidate genes were found to be strongly related to 'hematological system development and function' and 'hematological disease.' Accordingly, our results suggest that PHMG-p could affect hematopoiesis, which participates in monocyte differentiation and PLT production, and may induce hematologic diseases via the respiratory tract.

Erratum: Differential Diagnosis of Thick Myocardium according to Histologic Features Revealed by Multiparametric Cardiac Magnetic Resonance Imaging.

This corrects the article on p. 581 in vol. 23, PMID: 35555885.

Accuracy of two deep learning-based reconstruction methods compared with an adaptive statistical iterative reconstruction method for solid and ground-glass nodule volumetry on low-dose and ultra-low-dose chest computed tomography: A phantom study.

No published studies have evaluated the accuracy of volumetric measurement of solid nodules and ground-glass nodules on low-dose or ultra-low-dose chest computed tomography, reconstructed using deep learning-based algorithms. This is an important issue in lung cancer screening. Our study aimed to investigate the accuracy of semiautomatic volume measurement of solid nodules and ground-glass nodules, using two deep learning-based image reconstruction algorithms (Truefidelity and ClariCT.AI), compared with iterative reconstruction (ASiR-V) in low-dose and ultra-low-dose settings. We performed computed tomography scans of solid nodules and ground-glass nodules of different diameters placed in a phantom at four radiation doses (120 kVp/220 mA, 120 kVp/90 mA, 120 kVp/40 mA, and 80 kVp/40 mA). Each scan was reconstructed using Truefidelity, ClariCT.AI, and ASiR-V. The solid nodule and ground-glass nodule volumes were measured semiautomatically. The gold-standard volumes could be calculated using the diameter since all nodule phantoms are perfectly spherical. Subsequently, absolute percentage measurement errors of the measured volumes were calculated. Image noise was also calculated. Across all nodules at all dose settings, the absolute percentage measurement errors of Truefidelity and ClariCT.AI were less than 11%; they were significantly lower with Truefidelity or ClariCT.AI than with ASiR-V (all P<0.05). The absolute percentage measurement errors for the smallest solid nodule (3 mm) reconstructed by Truefidelity or ClariCT.AI at all dose settings were significantly lower than those of this nodule reconstructed by ASiR-V (all P<0.05). Furthermore, the lowest absolute percentage measurement errors for ground-glass nodules were observed with Truefidelity or ClariCT.AI at all dose settings. The absolute percentage measurement errors for ground-glass nodules reconstructed with Truefidelity at ultra-low-dose settings were significantly lower than those of all sizes of ground-glass nodules reconstructed with ASiR-V (all P<0.05). Image noise was lowest with Truefidelity (all P<0.05). In conclusion, the deep learning-based algorithms were more accurate for volume measurements of both solid nodules and ground-glass nodules than ASiR-V at both low-dose and ultra-low-dose settings.

Differential Diagnosis of Thick Myocardium according to Histologic Features Revealed by Multiparametric Cardiac Magnetic Resonance Imaging.

Left ventricular (LV) wall thickening, or LV hypertrophy (LVH), is common and occurs in diverse conditions including hypertrophic cardiomyopathy (HCM), hypertensive heart disease, aortic valve stenosis, lysosomal storage disorders, cardiac amyloidosis, mitochondrial cardiomyopathy, sarcoidosis and athlete's heart. Cardiac magnetic resonance (CMR) imaging provides various tissue contrasts and characteristics that reflect histological changes in the myocardium, such as cellular hypertrophy, cardiomyocyte disarray, interstitial fibrosis, extracellular accumulation of insoluble proteins, intracellular accumulation of fat, and intracellular vacuolar changes. Therefore, CMR imaging may be beneficial in establishing a differential diagnosis of LVH. Although various diseases share LV wall thickening as a common feature, the histologic changes that underscore each disease are distinct. This review focuses on CMR multiparametric myocardial analysis, which may provide clues for the differentiation of thickened myocardium based on the histologic features of HCM and its phenocopies.

Analysis of lung cancer-related genetic changes in long-term and low-dose polyhexamethylene guanidine phosphate (PHMG-p) treated human pulmonary alveolar epithelial cells.

BACKGROUND: Lung injury elicited by respiratory exposure to humidifier disinfectants (HDs) is known as HD-associated lung injury (HDLI). Current elucidation of the molecular mechanisms related to HDLI is mostly restricted to fibrotic and inflammatory lung diseases. In our previous report, we found that lung tumors were caused by intratracheal instillation of polyhexamethylene guanidine phosphate (PHMG-p) in a rat model. However, the lung cancer-related genetic changes concomitant with the development of these lung tumors have not yet been fully defined. We aimed to discover the effect of long-term exposure of PHMG-p on normal human lung alveolar cells. METHODS: We investigated whether PHMG-p could increase distorted homeostasis of oncogenes and tumor-suppressor genes, with long-term and low-dose treatment, in human pulmonary alveolar epithelial cells (HPAEpiCs). Total RNA sequencing was performed with cells continuously treated with PHMG-p and harvested after 35 days. RESULTS: After PHMG-p treatment, genes with transcriptional expression changes of more than 2.0-fold or less than 0.5-fold were identified. Within 10 days of exposure, 2 protein-coding and 5 non-coding genes were selected, whereas in the group treated for 27-35 days, 24 protein-coding and 5 non-coding genes were identified. Furthermore, in the long-term treatment group, 11 of the 15 upregulated genes and 9 of the 14 downregulated genes were reported as oncogenes and tumor suppressor genes in lung cancer, respectively. We also found that 10 genes of the selected 24 protein-coding genes were clinically significant in lung adenocarcinoma patients. CONCLUSIONS: Our findings demonstrate that long-term exposure of human pulmonary normal alveolar cells to low-dose PHMG-p caused genetic changes, mainly in lung cancer-associated genes, in a time-dependent manner.

Clinical findings, viral load, and outcomes of COVID-19: Comparison of patients with negative and positive initial chest computed tomography.

Reports detailing the clinical characteristics, viral load, and outcomes of patients with normal initial chest CT findings are lacking. We sought to compare the differences in clinical findings, viral loads, and outcomes between patients with confirmed COVID-19 who initially tested negative on chest CT (CT negative) with patients who tested initially positive on chest CT (CT positive). The clinical data, viral loads, and outcomes of initial CT-positive and CT-negative patients examined between January 2020 and April 2020 were retrospectively compared. The efficacy of viral load (cyclic threshold value [Ct value]) in predicting pneumonia was evaluated using receiver operating characteristic (ROC) curve and area under the curve (AUC). In total, 128 patients underwent initial chest CT (mean age, 54.3 ± 19.0 years, 50% male). Of those, 36 were initially CT negative, and 92 were CT positive. The CT-positive patients were significantly older (P < .001) than the CT-negative patients. Only age was significantly associated with the initial presence of pneumonia (odds ratio, 1.060; confidence interval (CI), 1.020-1-102; P = .003). In addition, age (OR, 1.062; CI, 1.014-1.112; P = .011), fever at diagnosis (OR, 6.689; CI, 1.715-26.096; P = .006), and CRP level (OR, 1.393; CI, 1.150-1.687; P = .001) were significantly associated with the need for O2 therapy. Viral load was significantly higher in the CT-positive group than in the CT-negative group (P = .017). The cutoff Ct value for predicting the presence of pneumonia was 27.71. Outcomes including the mean hospital stay, intensive care unit admission, and O2 therapy were significantly worse in the CT-positive group than in the CT-negative group (all P < .05). In conclusion, initially CT-negative patients showed better outcomes than initially CT-positive patients. Age was significantly associated with the initial presence of pneumonia, and viral load may help in predicting the initial presence of pneumonia.

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.

A deep learning-based automatic analysis of cardiovascular borders on chest radiographs of valvular heart disease: development/external validation.

OBJECTIVES: Cardiovascular border (CB) analysis is the primary method for detecting and quantifying the severity of cardiovascular disease using posterior-anterior chest radiographs (CXRs). This study aimed to develop and validate a deep learning-based automatic CXR CB analysis algorithm (CB_auto) for diagnosing and quantitatively evaluating valvular heart disease (VHD). METHODS: We developed CB_auto using 816 normal and 798 VHD CXRs. For validation, 640 normal and 542 VHD CXRs from three different hospitals and 132 CXRs from a public dataset were assigned. The reliability of the CB parameters determined by CB_auto was evaluated. To evaluate the differences between parameters determined by CB_auto and manual CB drawing (CB_hand), the absolute percentage measurement error (APE) was calculated. Pearson correlation coefficients were calculated between CB_hand and echocardiographic measurements. RESULTS: CB parameters determined by CB_auto yielded excellent reliability (intraclass correlation coefficient > 0.98). The 95% limits of agreement for the cardiothoracic ratio were 0.00 ± 0.04% without systemic bias. The differences between parameters determined by CB_auto and CB_hand as defined by the APE were < 10% for all parameters except for carinal angle and left atrial appendage. In the public dataset, all CB parameters were successfully drawn in 124 of 132 CXRs (93.9%). All CB parameters were significantly greater in VHD than in normal controls (all p < 0.05). All CB parameters showed significant correlations (p < 0.05) with echocardiographic measurements. CONCLUSIONS: The CB_auto system empowered by deep learning algorithm provided highly reliable CB measurements that could be useful not only in daily clinical practice but also for research purposes. KEY POINTS: • A deep learning-based automatic CB analysis algorithm for diagnosing and quantitatively evaluating VHD using posterior-anterior chest radiographs was developed and validated. • Our algorithm (CB_auto) yielded comparable reliability to manual CB drawing (CB_hand) in terms of various CB measurement variables, as confirmed by external validation with datasets from three different hospitals and a public dataset. • All CB parameters were significantly different between VHD and normal control measurements, and echocardiographic measurements were significantly correlated with CB parameters measured from normal control and VHD CXRs.

Differentiating pulmonary metastasis from benign lung nodules in thyroid cancer patients using dual-energy CT parameters.

OBJECTIVES: To explore the importance of quantitative characteristics of dual-energy CT (DECT) between pulmonary metastasis and benign lung nodules in thyroid cancer. METHODS: In this retrospective study, we identified 63 patients from our institution's database with pathologically proven thyroid cancer who underwent DECT to assess pulmonary metastasis. Among these patients, 22 had 55 pulmonary metastases, and 41 had 97 benign nodules. If nodules showed increased iodine uptake on I-131 single-photon emission computed tomography-computed tomography or increased size in follow-up CT, they were considered metastatic. We compared the clinical findings and DECT parameters of both groups and performed a receiver operating characteristic analysis to evaluate the optimal cutoff values of the DECT parameters. RESULTS: Patients with metastases were significantly older than patients with benign nodules (p = 0.048). The DECT parameters of the metastatic nodules were significantly higher than those of the benign nodules (iodine concentration [IC], 5.61 ± 2.02 mg/mL vs. 1.61 ± 0.98 mg/mL; normalized IC [NIC], 0.60 ± 0.20 vs. 0.16 ± 0.11; NIC using pulmonary artery [NICPA], 0.60 ± 0.44 vs. 0.15 ± 0.11; slope of the spectral attenuation curves [λHU], 5.18 ± 2.54 vs. 2.12 ± 1.39; and Z-effective value [Zeff], 10.0 ± 0.94 vs. 8.79 ± 0.75; all p < 0.001). In the subgroup analysis according to nodule size, all DECT parameters of the metastatic nodules in all subgroups were significantly higher than those of the benign nodules (all p < 0.05). The cutoff values for IC, NIC, λHU, NICPA, and Zeff for diagnosing metastases were 3.10, 0.29, 3.57, 0.28, and 9.34, respectively (all p < 0.001). CONCLUSIONS: DECT parameters can help to differentiate metastatic and benign lung nodules in thyroid cancer. KEY POINTS: • DECT parameters can help to differentiate metastatic and benign lung nodules in patients with thyroid cancer. • DECT parameters showed a significant difference between benign lung nodules and lung metastases, even for nodules with diameters ≥ 3 mm and < 5 mm. • Among the DECT parameters, the highest diagnostic accuracy for differentiating pulmonary metastases from benign lung nodules was achieved with the NIC and IC, followed by the NICPA and λHU, and their cutoff values were 0.29, 3.10, 0.28, and 3.57, respectively.

New formulas to predict the length of a peripherally inserted central catheter based on anteroposterior chest radiographs.

PURPOSE: To develop formulas that predict the optimal length of a peripherally inserted central catheter (PICC) from variables measured on anteroposterior (AP) chest radiography (CXR). MATERIALS AND METHODS: A total of 134 patients who underwent PICC insertion at the angiography suites were included. Clinical information such as patient height, weight, sex, age, cubital crease to inferior carina border length (CCL), and approach side were recorded. The following variables via measurement on AP-CXR were also collected: (1) distance from the T1 to T12 vertebra (DTV), (2) maximal horizontal thoracic diameter (MHTD), and (3) clavicle length (CL). RESULTS: Significant correlations between CCL and the following variables were identified in linear regression analyses: approach side, height, weight, sex, DTV, MHTD, and CL. Multiple regression results motivated the following two formulas: (1) with height data, estimated CCL (cm) = 12.429 + 0.113 × Height + 0.377 × MHTD (if left side, add 2.933 cm, if female, subtract 0.723 cm); (2) without height data, estimated CCL = 19.409 + 0.424 × MHTD + 0.287 × CL + 0.203 × DTV (if left side, add 3.063 cm, if female, subtract 0.997 cm). Estimated final PICC length can be calculated as (Estimated CCL, cm) + 4.0 (distance from inferior carina border to about 2.0 vertebra body unit, cm) - (distance from set cubital crease to designated puncture point, cm). CONCLUSION: This study suggests new formulas to predict the appropriate PICC length for bedside insertion using previous AP-CXRs. With this formula, ideal positioning of the catheter's tip can be achieved in the clinical practice, avoiding or minimalizing the exposed catheter out of skin. These formulas may be helpful for patients who cannot undergo intra-hospital transport due to hemodynamic instability or who are concerned about isolation precautions due to any infectious-related contamination.

Evaluation of the effect of filtered ultrafine particulate matter on bleomycin-induced lung fibrosis in a rat model using computed tomography, histopathologic analysis, and RNA sequencing.

We aimed to investigate the effect of chronic particulate matter (PM) exposure on bleomycin-induced lung fibrosis in a rat model using chest CT, histopathologic evaluation, and RNA-sequencing. A bleomycin solution was intratracheally administrated to 20 male rats. For chronic PM exposure, after four weeks of bleomycin treatment to induce lung fibrosis, PM suspension (experimental group) or normal saline (control group) was intratracheally administrated for 10 weeks. Chest CT was carried out in all rats, and then both lungs were extracted for histopathologic evaluation. One lobe from three rats in each group underwent RNA sequencing, and one lobe from five rats in each group was evaluated by western blotting. Inflammation and fibrosis scores in both chest CT and pathologic analysis were significantly more aggravated in rats with chronic PM exposure than in the control group. Several genes associated with inflammation and immunity were also upregulated with chronic PM exposure. Our study revealed that chronic PM exposure in a bleomycin-induced lung fibrosis rat model aggravated pulmonary fibrosis and inflammation, proven by chest CT, pathologic analysis, and RNA sequencing.