Rationale Interstitial lung diseases (ILD) are a diverse group of conditions, often diagnosed using high-resolution chest computed tomography (HRCT), which is susceptible to subjective biases in interpretation. Objectives This study aims to develop and validate SPAIDNet (Spatial Pattern Analysis for ILD Diagnosis using a residual neural Network), a deep learning (DL) model for the automated classification of ILD, to reduce subjective biases and improve diagnostic consistency. Methods The study included 2901 ILD patients who underwent 5213 HRCT scans across multiple centers between July 2017 and June 2023. SPAIDNet, built upon the pre-trained residual neural network with 18 layers, utilizes multi-instance learning in three centers in China. Measurements and main results The model demonstrated exceptional performance, achieving macro-average area under the receiver operating characteristic curve (AUC) of over 0.999 in internal validation, 0.905 in external cohort I, and 0.870 in external cohort II for multiclass classification. SPAIDNet outperformed both a junior radiologist (AUC: 0.737) and a senior radiologist (AUC: 0.763). Furthermore, DL-assisted the two radiologists saw significant improvements in diagnostic accuracy, with AUCs rising to 0.817 and 0.787, respectively. Conclusions These results underscore SPAIDNet's potential to offer high accuracy, robustness, and generalizability in ILD diagnosis, providing a valuable tool to mitigate the subjectivity inherent in HRCT image interpretation.

Abstract Background Phase-resolved functional lung magnetic resonance imaging (PREFUL-MRI) enables simultaneous, free-breathing, radiation-free assessment of regional lung perfusion and ventilation. This study aimed to provide preliminary reference data for lung perfusion and ventilation using PREFUL-MRI in healthy adults, and to characterize the physiological dependencies of these metrics on two breathing patterns, sex, and age. Methods In this prospective observational study, 87 healthy adults underwent PREFUL-MRI at 1.5 T during both normal and deep-slow breathing. Perfusion- and ventilation-related metrics were quantified via an automated pipeline. Paired comparisons between breathing states were performed using Wilcoxon signed-rank tests; unpaired comparisons between sexes and age groups (< 45 vs. ≥45 years) used Mann–Whitney U tests, with Holm–Bonferroni and Benjamini–Hochberg false-discovery-rate corrections applied to control for multiple comparisons. Results Mean perfusion (7.7% vs. 6.0%, Holm-Bonferroni adjusted p < 0.001) and ventilation defects (8.6% vs. 5.1%, Holm-Bonferroni adjusted p = 0.010) were decreased, and mean ventilation (15.8% vs. 48.3%, Holm-Bonferroni adjusted p < 0.001) and perfusion defects (1.9% vs. 7.9%, Holm-Bonferroni adjusted p = 0.005) increased during deep breathing compared with normal breathing. Twenty-eight participants had increased lung perfusion while 59 had reduced perfusion during deep breathing relative to normal breathing. During normal breathing, men exhibited higher mean ventilation than women (20.2% vs. 14.2%, Holm-Bonferroni adjusted p = 0.018). During deep breathing, men demonstrated higher total perfusion defect percentage and matched ventilation-perfusion defects than women (FDR adjusted q < 0.05). Total perfusion defect percentage was lower in participants aged ≥ 45 years than in those aged < 45 years (1.8% vs. 2.7%, FDR adjusted q = 0.036). Mean flow-volume loop correlations were similar between breathing patterns, sexes, and age groups after multiple comparison correction ( p > 0.05). Conclusions PREFUL-MRI can captures physiological variations related to breathing pattern, sex, and age in healthy adults. These findings provide a framework for distinguishing normal physiological heterogeneity from pathological change in clinical PREFUL-MRI interpretation. Clinical trial number Not applicable.

Background:Fibrotic interstitial lung disease (fILD) consists of a heterogeneous group of chronic, progressive interstitial lung diseases characterized by reduced lung elasticity and restrictive ventilatory impairment. Strain analysis based on dynamic ventilation computed tomography (DVCT) has emerged as a novel method for quantifying lung deformation during ventilation and thus monitoring the pathophysiological changes in lungs. This study aimed to quantitatively identify abnormal lung motion in patients with fILD through use of strain analysis and to determine the correlation of these values with spirometric indices. Methods:A total of 27 patients with fILD and 20 healthy controls were prospectively recruited. All participants underwent DVCT scanning on a 320-row computed tomography (CT) scanner. Strain metrics across the full respiratory cycle were computed with computational fluid dynamics software at nine axial levels spanning the upper, middle, and lower lungs. In patients, the percentage of fibrotic lung at the corresponding levels was also quantified. Group differences were assessed, and Pearson correlations were used to determine the associations between strain metrics, percentage fibrosis, and pulmonary function parameters. Results:During the respiratory cycle, lung strain exhibited heterogeneous temporal and spatial distributions. There were significant differences in maximum principal strain, mean principal strain, maximum displacement speed, and mean displacement speed between the upper, middle, and lower parts of both lungs, both in patients and controls (P<0.05). In both groups, peaks in strain were observed during the early expiration and mid-inspiration phases. Patients with fILD exhibited a distinct pattern, with consistently lower strain values across all metrics, while those of healthy controls were all significantly higher. The strain-related parameters were significantly correlated with forced expiratory volume at 1 second (r: 0.646-0.769; P≤0.001), forced vital capacity (r: 0.670-0.827; P≤0.001), and total lung capacity (r: 0.625-0.817; P≤0.001), whereas the percentage of lung fibrosis was not associated with any other parameters. Conclusions:DVCT-derived strain represents a quantitative measure of abnormal regional lung motion in patients with fILD and may complement spirometry by capturing local ventilatory mechanics. This technique shows promise for the evaluation of regional mechanical impairment in patients with fibrotic lung disease.

BACKGROUND:Cryptogenic organizing pneumonia (COP) is classified as a subtype of idiopathic interstitial pneumonia (IIP), which has a good prognosis. Relapse remains one of the most challenging and intriguing aspects of COP. This study aimed to characterize the clinical features, prognosis, and relapse patterns of COP. METHODS:In this prospective cohort study, patients diagnosed with COP between March 1, 2004 and June 30, 2022 were enrolled after a comprehensive multidisciplinary review. Patients were followed up through regular clinical visits every 3-6 months until October 30, 2023. Data collected included demographic characteristics, clinical presentation, laboratory findings, radiologic features, and prognostic outcomes. The primary outcome measure was relapse. Cox regression analyses were performed to explore factors related to the presence of relapse. RESULTS:This study included 268 patients with a final diagnosis of COP based on multidisciplinary discussion. After diagnosis, the one-year survival rate was 99.6%, decreasing to 97.7% at 3 years, 94.5% at 5 years, and 81.7% at 10 years. Relapses occurred in 20.9% (56/268) of patients, with a median time to relapse of 12 months. Of these relapses, 28.6% (16/56) occurred when prednisone was tapered to below 10 mg/day, and 62.5% (35/56) occurred after discontinuation of prednisone therapy; fewer than 10% of relapses occurred at prednisone doses above 15 mg/day. Ground-glass opacities (GGOs) (225/268, 84.0%) and consolidations (212/268, 79.1%), predominantly with bilateral lung distribution, were the most common computed tomography (CT) features at diagnosis. No patient developed residual lung fibrosis on high-resolution CT, regardless of relapse status. Furthermore, no deaths were attributable to COP progression or relapse, and all-cause mortality was unrelated to COP itself. CONCLUSION:This study indicated that patients with COP had a good prognosis with favorable survival outcomes. However, relapse was relatively common, occurring in more than 20% of patients. Therefore, close follow-up is essential for early detection of relapses, particularly during corticosteroid tapering or after treatment discontinuation.

The pathophysiological changes of lung perfusion and ventilation in fibrosing interstitial lung diseases (F-ILD) remain inadequately characterized. This study aimed to analyze lung perfusion and ventilation characteristics in F-ILD patients using phase-resolved functional lung magnetic resonance imaging (PREFUL MRI) as well as their correlation with the severity of F-ILD. This cross-sectional study prospectively included 30 patients diagnosed with F-ILD (19 males, 64.6 ± 9.5 years) and 30 age- and sex-matched normal controls. All participants underwent PREFUL MRI as well as pulmonary function tests. High-resolution CT (HRCT) was performed for the patient cohort. Ventilation and perfusion-related parameters obtained from PREFUL MRI were analyzed and correlated with PFTs and fibrotic lesions identified on HRCT. Compared with normal controls, F-ILD patients showed significant differences in mean perfusion (7.55

Pneumoconiosis patients have a higher prevalence of chronic obstructive pulmonary disease (COPD). While age is a known associated factor, its impact across different populations is unclear. We included 9,964 pneumoconiosis patients from 27 Chinese provinces. Factors were identified using multivariable logistic regression, and the non-linear age–COPD association was examined with restricted cubic spline (RCS) modelling. Stratified analysis and interaction tests assessed sociodemographic heterogeneity. Sensitivity analyses comprised RCS models with varying knots and propensity score matching. The prevalence of COPD among patients with pneumoconiosis was 24.1

BACKGROUND:Checkpoint inhibitor pneumonitis (CIP) is the leading cause of treatment-related deaths for immune checkpoint inhibitor (ICI) combination therapies. CIP is problematic to diagnose and differentiate, particularly from radiation pneumonitis (RP), due to the lack of mechanistic distinctions between them. METHODS:Using single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor sequencing (scTCR-seq), we characterize the cellular landscape of bronchoalveolar lavage fluid (BALF) and peripheral blood from a discovery cohort (seven CIP, six RP, and six treatment-naive controls) and a validation cohort (five patients receiving combined ICI and radiotherapy who were diagnosed with RP). FINDINGS:We report a striking accumulation of alveolar CD8+ exhausted T cells (Texs) in CIP. The alveolar CD8+ Texs of CIP primarily differentiate from tissue-resident ZNF683hi CD8+ T cells, whereas those of RP predominantly originate from peripherally related GZMKhi CD8+ T cells. These findings were further validated in a prospectively enrolled validation cohort and ultimately guided successful clinical decisions regarding ICI rechallenge. CONCLUSIONS:These results highlight distinct cellular and molecular features in CIP and RP, thereby providing insights into clinical decision-making regarding ICI rechallenge in lung cancer patients. FUNDING:This study was supported by the National Natural Science Foundation of China.

To report a rare case of IgG4-related disease (IgG4-RD) with atypical predominant thoracic involvement mimicking lung cancer and sarcoidosis. A 74-year-old male with a history of heavy smoking presented with chronic cough and exertional dyspnea for 1 year. Chest high-resolution computed tomography (HRCT) revealed bronchovascular bundle thickening, a right parahilar mass, multiple perilymphatically distributed solid nodules, lymphadenopathy, and pleural effusion. Laboratory tests revealed marked elevations of serum IgG4 (6710 mg/dL) and IgE (2210 mg/dL). Histopathological examination of lung, pleural biopsy, and lymph node consistently demonstrated dense lymphoplasmacytic infiltration with abundant IgG4-positive plasma cells, without storiform fibrosis or obliterative phlebitis. The patient was definitively diagnosed with IgG4-RD via multidisciplinary team (MDT) consultation. Oral prednisone resulted in significant radiological improvement. IgG4-RD can mimic common thoracic disorders such as lung cancer and sarcoidosis. Early corticosteroid therapy is effective. An experienced MDT, integrating detailed clinical findings, serology, radiology, and histopathology, is essential for prompt diagnosis and timely intervention.

Background:Primary Sjögren syndrome-associated interstitial lung disease (pSS-ILD) patients have a worse prognosis than pSS patients without pulmonary involvement. This study aims to establish a prediction nomogram for early prediction of lung transplantation (LTx)-free survival in pSS-ILD patients. Methods:The training cohort comprised 260 patients from China-Japan Friendship Hospital between 1 January 2016 and 30 June 2022, while the external validation cohort consisted of 135 patients from Beijing Chaoyang Hospital between 1 January 2007 and 31 December 2012. Univariable Cox regression analysis and least absolute shrinkage and selection operator were employed for variable selection, and a nomogram model was developed to predict the 1-, 3- and 5-year LTx-free survival. Discrimination and calibration of the nomogram were assessed using the concordance index (C-index), area under the curve, calibration curve and decision curve analysis. Results:Multivariable Cox regression demonstrated that elevated age, oxygenation index, carbohydrate antigen 125 and fibrosis score were independent risk factors for LTx-free survival in pSS-ILD patients. The C-index values for the training and validation cohorts were 0.812 and 0.809, respectively. The 1-, 3- and 5-year AUC values for the training cohort were 0.781, 0.874 and 0.909, respectively, while those for the validation cohort were 0.793, 0.826 and 0.863. The bias-corrected curve was close to the ideal curve and revealed a strong consistency between predicted and observed outcomes. Conclusions:We developed a nomogram capable of predicting the LTx-free survival probability at 1, 3 and 5 years in pSS-ILD patients. This model has the potential to be a useful tool for prediction of death or LTx in pSS-ILD.

This study aimed to investigate longitudinal change of idiopathic inflammatory myopathy-associated interstitial lung disease (IIM-ILD) on high-resolution computed tomography (HRCT). This prospective cohort study was undertaken involving 514 IIM-ILD patients (367 females; median age 54 years) from 2016 to 2022. Deep learning algorithms were employed to quantify interstitial lesions on HRCT, while clinical parameters including pulmonary function tests, serum biomarkers, and arterial blood gas analysis were also considered. The study identified anti-MDA5 antibody positivity (OR: 10.46, 95

Background Pulmonary vessel-related structural (PVRS) abnormalities have been implicated in usual interstitial pneumonia; however, their significance in idiopathic inflammatory myopathy-associated interstitial lung disease (IIM-ILD) remains unclear. In this two-centre study, we evaluated the associations between PVRS parameters on high-resolution computed tomography (HRCT) and rapid progression and prognosis in patients with IIM-ILD.Methods A total of 578 IIM-ILD patients (412 females; median age, 53 years) were included from retrospective ILD cohorts of two centres. Artificial intelligence (AI)-based quantification was performed on baseline HRCT to assess PVRS and interstitial lesions. The value of PVRS for rapid progression and prognosis was first evaluated in the cohort from the first centre using logistic regression, Kaplan-Meier analysis and Cox models. An independent cohort of 64 patients (43 female; median age, 54 years) from the second centre then served to validate the generalisability of the PVRS-based model of IIM-ILD progression.Results In the first-centre cohort, 249 patients with rapidly progressive ILD (RP-ILD) showed significantly elevated mean pulmonary vascular diameter (mPVD) (p<0.05), shorter vascular-pleural distances, greater PVRS volume and higher standard deviation of pulmonary vascular diameter (sdPVD) (p<0.001) compared with non-RP-ILD patients. Multivariate analysis identified age (HR 1.03, 95% CI 1.01 to 1.06), ground glass opacity percentage (HR 1.04, 95% CI 1.02 to 1.06) and sdPVD at 6 mm and 18 mm from the pleura as independent risk factors for poor prognosis in antisynthetase syndrome (ASS) patients (concordance index (C-index)=0.819). In contrast, for patients with antimelanoma differentiation-associated gene 5 antibody-positive dermatomyositis (MDA5+DM), the independent risk factors were age (HR 1.06, 95% CI 1.02 to 1.11), mPVD at 6 mm from the pleura and lactic dehydrogenase levels (C-index=0.835). When applied to the external validation cohort, the respective multivariate Cox models yielded C-indices of 0.841 for ASS and 0.814 for MDA5+DM, confirming their generalisability.Conclusions Our study demonstrates that baseline PVRS parameters on HRCT are robust imaging biomarkers associated with rapid progression and poor prognosis in IIM-ILD. These findings underscore the clinical relevance of PVRS assessment in risk stratification and management.

Background:Anti-MDA5 antibody-positive dermatomyositis (anti-MDA5 Ab+ DM) is increasingly recognized to involve the heart, yet the prevalence and phenotype of cardiac involvement remain insufficiently characterized. This study aimed to determine the utility of cardiac magnetic resonance (CMR) for detecting myocardial involvement (MI) in patients with anti-MDA5+ DM. Methods:We prospectively included 42 anti-MDA5+ DM patients (male: 23, median age: 45 years) and 29 age- and gender-matched healthy controls (HCs). All participants underwent CMR to evaluate left ventricular function, native T1 and T2 value, and late gadolinium enhancement (LGE). Results:Patients with anti-MDA5+ DM exhibited significantly reduced left ventricular ejection fraction (LVEF) compared to HCs (P<0.001). They also had elevated myocardial T1 (P<0.001) and T2 (P<0.001) values. LGE was detected in 35.7% of patients. Compared to the LGE-negative group, patients with LGE-positive findings had higher creatine kinase myocardial band (CK-MB) levels (P<0.001) and lower cardiac index (CI, P<0.05). We stratified anti-MDA5+ DM patients into subgroups according to predefined thresholds for the biomarkers. The inflammatory marker-positive subgroup showed significantly increased left ventricular end-diastolic volume index (LVEDVI) and reduced CI compared to the negative subgroup (LVEDVI: 64.0±17.1 vs. 54.8±10.1 mL/m2, P=0.047; CI: 2.6±0.5 vs. 3.0±0.6 L/min/m2, P=0.006). LVEDVI (r=0.520, P<0.001) correlated with ferritin (FER) levels and LVEF demonstrated a moderate negative correlation with FER levels (r=-0.492, P<0.001). Conclusions:Left ventricular involvement is highly prevalent in anti-MDA5+ DM patients, as evidenced by CMR. The study reinforces CMR as a valuable diagnostic tool for MI in anti-MDA5+ DM patients.

Objective:To comprehensively analyze the relevant factors influencing the treatment efficacy of Nocardia farcinica pneumonia, construct and validate a prediction model to provide a scientific basis for clinical treatment, and realize visual prediction using a nomogram. Methods:The clinical data of 150 patients with Nocardia farcinica pneumonia collected from January 2020 to December 2024 were selected and divided into a training set (n = 105) and a validation set (n = 45) at a ratio of 7:3. The data covered patients' basic information, laboratory examination indicators, imaging features, and treatment regimens. Risk factors were screened by univariate and multivariate logistic regression in the training set to construct a nomogram model. The receiver operating characteristic curve (ROC) and calibration curve were plotted to evaluate the model's efficacy and were validated in the validation set. Decision curve analysis (DCA) was used to evaluate the clinical value. Results:In the training set, 26 cases (24.32%) exhibited poor treatment response, while 11 cases (25.25%) were identified in the validation set. Multivariate analysis identified serum albumin levels, empyema, cavitary lesions, and antibiotic regimens (sulfonamides/cephalosporins/carbapenems) as independent factors influencing the therapeutic efficacy of Nocardia farcinica pneumonia. In the training and validation sets, the model achieved C-index values of 0.849 and 0.831, with areas under the ROC curve (AUC) of 0.849 (95% CI: 0.764-0.935) and 0.831 (95% CI: 0.580-1.000), respectively. The sensitivity and specificity were 0.772 and 0.895 in the training set, and 0.773 and 0.857 in the validation set, indicating predictive capability for treatment outcomes. The nomogram model exhibited excellent predictive accuracy upon calibration curve analysis. Decision curve analysis (DCA) further confirmed its high clinical utility. Conclusion:Beyond confirming the role of host immunity and inflammation, this study develops and validates the first nomogram that integrates baseline albumin, empyema, cavitation, and antibiotic choice to quantitatively predict individual treatment failure risk in Nocardia farcinica pneumonia. This tool provides an immediately applicable visual guide for early risk stratification and personalized therapy selection, addressing a significant gap in the management of this complex infection.

Objective:To assess imaging quantitative markers on baseline High-resolution computed tomography (HRCT) for predicting rapid progression (RP) and adverse events in anti-synthetase syndrome associated interstitial lung disease (ASS-ILD) and anti-MDA5-positive dermatomyositis-associated interstitial lung disease (MDA5-ILD). Methods:This retrospective study analyzed 511 patients (ASS-ILD: n=356, median age=56 years; MDA5-ILD: n=155, median age=50 years) between Jan 2016 and Dec 2021. RP was defined as pulmonary function, image, or symptom aggravation within 3 months of initial presentation. Adverse events (death/intensive care) were recorded. Deep learning quantified ground-glass opacity (GGO) and consolidation volumes/percentages on baseline HRCT. Multivariable logistic and Cox regression adjusted for confounders (age, gender, smoking status, body mass index, fibrosis, and treatment). No multiple comparisons were conducted since this is an explorable study. Results:RP occurred in 34.8% (124/356) of ASS-ILD and 44.5% (69/155) of MDA5-ILD patients. Elevated GGO/consolidation volumes and percentages independently predicted RP in patients with ASS-ILD (adjusted odd ratio=1.63, 95% confidence interval:1.25-2.12, P<0.001), but not in patients with MDA5-ILD. During median follow-up (ASS-ILD: 4.45 years; MDA5-ILD: 4.05 years), RP patients showed higher mortality versus patients without RP (hazard ratio=4.12, P<0.001). Increased baseline GGO/consolidation metrics predicted adverse events in patients with ASS-ILD or MDA5-ILD (P<0.01). Conclusion:GGO and consolidation quantification on baseline HRCT can provide clinically actionable predictors to identify patients with ASS-ILD at high-risk for RP, and to stratify adverse event risks across ASS/MDA5-ILD regardless of RP status, enabling early intervention.

Idiopathic pulmonary fibrosis (IPF) is more likely to occur in the elderly population, and these patients often become depressed. It has been recognized that psychological disorders are not conducive to the control of many diseases. Thus, this study aims to determine whether alleviating depression can delay the progression of IPF and frailty in elderly patients with IPF. IPF patients over 60 years old were included in the study. None had a prior history of psychological disorders. All developed depression after being diagnosed with IPF. During the 12-month follow-up, some patients received anti-depression interventions and the rest didn’t. Depression, IPF, frailty and peripheral inflammation at baseline and after follow-up were evaluated by indicators and scales such as BDI-II, FVC

BACKGROUND:Usual interstitial pneumonia (UIP) indicates a poor prognosis, and there is significant heterogeneity in the diagnosis of UIP, necessitating an auxiliary diagnostic tool. RESEARCH QUESTION:Can a machine learning (ML) classifier using radiomics features and clinical data accurately identify UIP from patients with interstitial lung disease (ILD)? STUDY DESIGN AND METHODS:This data from a prospective cohort includes 5,321 sets of high-resolution CT (HRCT) images from 2,901 patients with ILD (male, 63.5%; mean age ± SD, 61.7 ± 10.8 years) across 3 medical centers. Multimodal data, including whole-lung radiomics features on HRCT scan, demographics, smoking status, pulmonary function, and comorbidity data, were extracted. An XGBoost and logistic regression were used to design a nomogram predicting UIP or not. The area under the receiver operating characteristic curve (AUC) and Cox regression for all-cause mortality were used to assess the diagnostic performance and prognostic value of models, respectively. RESULTS:A total of 5,213 HRCT images were divided into the training group (n = 3,639), the internal testing group (n = 785), and the external validation group (n = 789). UIP prevalence was 43.7% across the whole data set, with 42.7% and 41.3% for the internal validation set and external validation set, respectively. The radiomics-based classifier had an AUC of 0.790 in the internal testing set and 0.786 for the external validation data set. Integrating multimodal data improved AUCs to 0.802 and 0.794, respectively. The performance of the integration model was comparable with a pulmonologist with > 10 years of experience in ILD. Within 522 patients deceased during a median follow-up period of 3.37 years, the multimodal-based ML model-predicted UIP pattern was associated with high all-cause mortality risk (hazard ratio, 2.52; P < .001). INTERPRETATION:The classifier combining radiomics and clinical features showed strong diagnostic performance across varied UIP prevalence. This multimodal-based ML model could serve as an adjunct in the diagnosis of UIP. CLINICAL TRIAL REGISTRATION:ClinicalTrials.gov; No.: NCT04370158; URL: www. CLINICALTRIALS:gov.

BackgroundAnti-melanoma differentiation-associated gene 5 dermatomyositis (anti-MDA5 Ab+ DM) is characterized by amyopathic DM with interstitial lung disease. Its impact on the right ventricle remains unclear. We aim to evaluate RV involvement in anti-MDA5 Ab+ DM patients using cardiovascular magnetic resonance (CMR).MethodsThis single-center, prospective cohort study included 43 anti-MDA5 Ab+ DM patients (24 males, mean age = 44.7 ± 11.1 years) and 30 age- and gender-matched healthy controls (18 males, mean age = 44.8 ± 10.4 years). All patients underwent CMR before treatment. RV functional parameters, including ejection fraction (RVEF), end-diastolic/end-systolic remodeling index (RVEDRI/RVESRI), and right ventricular long-axis strain (RV-LAS), and RV and LV T1 and T2 mapping were analyzed. Differences between the two groups were evaluated, and correlations with clinical data were explored.ResultsAnti-MDA5 Ab+ DM patients exhibited a significant decrease in RVEF (45.7 ± 5.9% vs. 52.7 ± 6.6%, P < 0.001) and RV-LAS across all techniques. Increased RVESRI (1.38 ± 0.14 vs. 1.29 ± 0.14, P = 0.031) indicated RV subclinical dysfunction. The RV and LV blood pool T2 ratio was elevated in patients (0.96 ± 0.02 vs. 0.94 ± 0.03, P = 0.007). Patients in the inflammatory marker-positive group exhibited significantly worse RV-LAS compared with the negative group. RV-LASIns/mid negatively correlated with hsTnl levels (r = −0.34, P = 0.026), and ferritin (FER) is moderately positively correlated with RV-LASLVapex/peri (r = 0.487, P < 0.001).ConclusionRV subclinical dysfunction is common in patients with anti-MDA5 Ab+ DM. RV parameters on CMR such as RV-LAS and RVESRI serve as valuable imaging markers for early detection and risk stratification. These findings underscore the importance of routine cardiac evaluation in anti-MDA5 Ab+ DM.

Respiratory muscle dysfunction in patients with idiopathic pulmonary fibrosis (IPF) is a big challenge for treatment and rehabilitation. To quantitatively assess diaphragm and chest wall dysfunction using dynamic Magnetic Resonance Imaging (Dyn-MRI) in patients with IPF. Ninety-six patients with IPF and 50 gender- and age-matched controls were prospectively included and underwent D-MRI with a dynamic fast spoiled gradient-recalled echo sequence. Respiratory muscles function were assessed with thoracic anterior-posterior (AP), left-right (LR), cranial-caudal (CC) metrics. Moreover, lung area ratios, height (DH), and area (DA) of diaphragm curvature between end-inspiration and end-expiration during both quiet and deep breathing. During quiet breathing, the functional metrics of the diaphragm and chest wall were comparable between IPF patients and controls. However, during deep breathing, IPF patients exhibited significantly reduced ratios of AP, CC, and lung area compared to controls. Moreover, the median ratios of DH and DA were higher in IPF patients than in controls (DH: 0.96 vs. 0.81, p < 0.001; DA: 1.00 vs. 0.90, p < 0.001). Furthermore, the ratios of AP, CC, and lung area during deep breathing were found to correlate with pulmonary function, total lung volume, and 6-minute walk distance. D-MRI demonstrated dysfunction in the diaphragm and chest wall among IPF patients, with respiratory muscle dysfunction showing a correlation with the severity of disease. This article presents a prospective observational study that does not include the outcomes of any healthcare interventions on human participants. The study was registered on September 11, 2018, under the registration number NCT03666234.