Pulmonary manifestations of VEXAS syndrome with acute interstitial pneumonia and diffuse alveolar hemorrhage: a case report and literature review.

Vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome is an emerging adult-onset systemic autoinflammatory disorder affecting multiple organ systems. While lung involvement is common in this syndrome, literature regarding specific patterns is sparse. In this report, we present a case description of a patient with VEXAS syndrome who presented at the emergency department on two separate occasions with acute interstitial pneumonia (AIP) and diffuse alveolar hemorrhage (DAH). A literature review with a comparison of our observed findings to the general findings of VEXAS syndrome, AIP, and DAH is provided. This report underscores the rarity of specific pulmonary manifestations associated with VEXAS syndrome, contributing valuable insight to the limited literature available on this topic.

Imaging of Pulmonary Manifestations of Connective Tissue Disease.

The majority of connective tissue diseases (CTDs) are multisystem disorders that are often heterogeneous in their presentation and do not have a single laboratory, histologic, or radiologic feature that is defined as the gold standard to support a specific diagnosis. Given this challenging situation, the diagnosis of CTD is a process that requires the synthesis of multidisciplinary data which may include patient clinical symptoms, serologic evaluation, laboratory testing, and imaging. Pulmonary manifestations of connective tissue disease include interstitial lung disease as well as multicompartmental manifestations. These CT imaging patterns and features of specific diseases will be discussed in this article.

[Cerebral gas embolism as a complication of diffuse interstitial lung disease] / Embolismo gaseoso cerebral como complicación de una enfermedad pulmonar intersticial difusa.

Introduction: Cerebral gas embolism is an unusual but extremely serious condition that occurs when air is introduced into the arterial or venous circulation of the brain. Although rare, it can lead to significant neurological deficits and even the death of the patient. Clinical Case: 76-year-old patient with pre-existing diffuse interstitial lung disease, who experienced a massive stroke due to spontaneous pneumomediastinum. Her presentation included confusion, seizures, and motor weakness. Imaging tests revealed air bubbles in the cerebral sulci and hypodense areas in the cerebellum and parietooccipitals. In addition, pneumothorax and air in the upper mediastinum were noted on chest radiographs and chest CT scan. Despite therapeutic measures such as hyperbaric oxygen, the patient unfortunately died due to multiple organ failure. Discussion: The diagnosis of cerebral gas embolism generally involves performing a cerebral computed tomography, which is highly sensitive for detecting the presence of air in the cerebral vessels. Management includes monitoring of vital and neurological signs, as well as specific measures such as airway closure, venous catheter aspiration, Trendelenburg positioning, and hyperbaric oxygen. Conclusion: Cerebral gas embolism is a potentially fatal condition that requires a brain computed tomography for diagnosis and it is vitally important to know the prevention measures to avoid the appearance of this complication and also to know the general measures to adopt when it occurs.

Introducción: La embolia gaseosa cerebral es una afección inusual pero extremadamente grave que se produce cuando se introduce aire en la circulación arterial o venosa del cerebro. Aunque poco común, puede derivar en déficits neurológicos significativos e incluso la muerte del paciente. Caso Clínico: Paciente de 76 años con una enfermedad pulmonar intersticial difusa preexistente, que experimentó un ictus masivo debido a un neumomediastino espontáneo. Su presentación incluyó confusión, convulsiones y debilidad motora. Las pruebas de imagen revelaron burbujas de aire en los surcos cerebrales y áreas hipodensas en el cerebelo y parietooccipitales. Además, se observó neumotórax y aire en el mediastino superior en las radiografías de tórax y la tomografía torácica. A pesar de las medidas terapéuticas como el oxígeno hiperbárico, la paciente lamentablemente falleció debido al fallo multiorgánico. Discusión: El diagnóstico de embolia gaseosa cerebral generalmente implica la realización de una tomografía computarizada cerebral, que es altamente sensible para detectar la presencia de aire en los vasos cerebrales. El manejo incluye el control de las constantes vitales y neurológicas, así como medidas específicas como cierre de la entrada de aire, aspiración de catéteres venosos, posicionamiento de Trendelenburg y oxígeno hiperbárico. Conclusión: La embolia gaseosa cerebral es una afección potencialmente mortal que requiere una tomografía computarizada cerebral para el diagnóstico y de vital importancia conocer las medidas de prevención para evitar la aparición de esta complicación y así mismo conocer las medidas generales a adoptar cuando ésta se presenta.

The role of lung ultrasound and ultrasound elastography in diagnosis of interstitial lung diseases.

Introduction: Ultrasound elastography (US-E) is a novel, tissue stiffness-sensitive imaging method. We aimed to investigate whether lung ultrasound (US) and US-E can play a role in diagnosing interstitial lung diseases (ILDs) in which lung elasticity is affected due to fibrosis. Materials and Methods: A prospective cohort study. Patients with ILD were defined as ''ILD group'' and with other pulmonary diseases as ''control group". All subjects were examined and compared by lung US in B and elastography modes. Besides, the relationship between ultrasonography and high-resolution computerized tomography (HRCT) and chest X-ray findings was evaluated. Result: A total of 109 patients, 55 in ILD and 54 in the control group, with a mean age of 62 ± 14 years, were included. A positive correlation was found between the Warrick score (calculated from HRCT to determine the severity of ILD) and the number of B-lines (discrete vertical reverberation artifacts, indicating interstitial lung syndrome) in lung US (p= 0.001, r= 0.550) in the ILD group. In US-E, blue color (meaning more rigid tissue) dominated in the ILD group, and green color (indicating medium tissue stiffness) dominated in the control group (p= 0.001). Lung US diagnosed the ILD with 69% accuracy, 80% sensitivity, and 60% specificity compared to HRCT. Combined with chest X-ray, diagnostic accuracy was 74%, sensitivity 60%, and specificity 89%. Conclusions: Although lung US and US-E are not superior to gold standard HRCT in diagnosing ILDs, they can still be accepted as promising, novel, noninvasive tools, especially when combined with chest X-rays. Their role still needs to be clarified with further studies.

The heterogeneity of lung involvement in vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic syndrome: a case of hypersensitivity pneumonitis-like pattern.

Vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome is a recently characterized disease associated with somatic mutations in the UBA1 gene, which cause dysregulation of ubiquitin-mediated processes. This case describes a 71-year-old male patient with VEXAS syndrome who presented with refractory lung inflammation with a pattern similar to computed tomography hypersensitivity pneumonitis, a novel finding in VEXAS syndrome. The presented clinical case highlights the protean involvement of the lung in VEXAS syndrome and emphasizes the importance of considering interstitial lung disease in the differential diagnosis.

Radiomics based on HRCT can predict RP-ILD and mortality in anti-MDA5 + dermatomyositis patients: a multi-center retrospective study.

OBJECTIVES: To assess the effectiveness of HRCT-based radiomics in predicting rapidly progressive interstitial lung disease (RP-ILD) and mortality in anti-MDA5 positive dermatomyositis-related interstitial lung disease (anti-MDA5 + DM-ILD). METHODS: From August 2014 to March 2022, 160 patients from Institution 1 were retrospectively and consecutively enrolled and were randomly divided into the training dataset (n = 119) and internal validation dataset (n = 41), while 29 patients from Institution 2 were retrospectively and consecutively enrolled as external validation dataset. We generated four Risk-scores based on radiomics features extracted from four areas of HRCT. A nomogram was established by integrating the selected clinico-radiologic variables and the Risk-score of the most discriminative radiomics model. The RP-ILD prediction performance of the models was evaluated by using the area under the receiver operating characteristic curves, calibration curves, and decision curves. Survival analysis was conducted with Kaplan-Meier curves, Mantel-Haenszel test, and Cox regression. RESULTS: Over a median follow-up time of 31.6 months (interquartile range: 12.9-49.1 months), 24 patients lost to follow-up and 46 patients lost their lives (27.9%, 46/165). The Risk-score based on bilateral lungs performed best, attaining AUCs of 0.869 and 0.905 in the internal and external validation datasets. The nomogram outperformed clinico-radiologic model and Risk-score with AUCs of 0.882 and 0.916 in the internal and external validation datasets. Patients were classified into low- and high-risk groups with 50:50 based on nomogram. High-risk group patients demonstrated a significantly higher risk of mortality than low-risk group patients in institution 1 (HR = 4.117) and institution 2 cohorts (HR = 7.515). CONCLUSION: For anti-MDA5 + DM-ILD, the nomogram, mainly based on radiomics, can predict RP-ILD and is an independent predictor of mortality.

Rheumatoid arthritis disease activity significantly impacts on the severity of interstitial lung disease.

OBJECTIVES: Rheumatoid arthritis (RA) related interstitial lung disease (ILD) impacts on the treatment strategy and its prognosis in patients with RA. However, the relationship between RA disease activity and the severity of comorbid ILD has not been fully investigated. This study aimed to investigate the impact of RA disease activity on the severity of comorbid ILD in detail based on currently established visual scoring method along with physiological severity. METHODS: Consecutive patients with RA visiting to our Rheumatology Centre between December 2020 and December 2023 were analysed. The radiological severity of ILD was evaluated by averaging the extent of the combined lesion of ground glass opacity, reticulation and honeycombing in 5% increments in six representative high-resolution computed tomography slices ranging from 0% (no involvement) to 100% (all lung fields affected) according to Goh and Walsh's method. Associations between the radiological and physiological severity of ILD and patients' features were investigated using linear regression analysis. RESULTS: Among 124 patients (32 men, 92 women), the median age was 70 years, and the median disease duration was 2.92 years. Radiological severity of ILD was 0% (without ILD) in 107 (86.2%), ILD with extent < 10% in nine (7.2%), ILD with extent ≥10% and < 20% in three (2.4%), ILD with extent ≥20% in five (4.0%). Both disease activity score (DAS)28-erythrocyte sedimentation rate (ESR) (standardized coefficient = 0.199, P = 0.03) and rheumatoid factor titre (standardized coefficient = 0.247, P = 0.01) were significantly associated with the radiological quantitative severity of ILD in multivariate analysis adjusted for age, sex, disease duration, smoking status and anti-citrullinated peptide antibody titre. DAS28-ESR was significantly associated with forced vital capacity% predicted (standardized coefficient = -0.230, P = 0.047). CONCLUSIONS: Disease activity of RA was significantly associated with the severity of RA-ILD both radiologically and physiologically.

Interstitial Lung Abnormalities: Current Understanding.

Interstitial lung abnormalities (ILAs) are incidental findings on computed tomography scans, characterized by nondependent abnormalities affecting more than 5% of any lung zone. They are associated with factors such as age, smoking, genetic variants, worsened clinical outcomes, and increased mortality. Risk stratification based on clinical and radiological features of ILAs is crucial in clinical practice, particularly for identifying cases at high risk of progression to pulmonary fibrosis. Traction bronchiectasis/bronchiolectasis index has emerged as a promising imaging biomarker for prognostic risk stratification in ILAs. These findings suggest a spectrum of fibrosing interstitial lung diseases, encompassing from ILAs to pulmonary fibrosis.

Computed tomography machine learning classifier correlates with mortality in interstitial lung disease.

BACKGROUND: A machine learning classifier system, Fibresolve, was designed and validated as an adjunct to non-invasive diagnosis in idiopathic pulmonary fibrosis (IPF). The system uses a deep learning algorithm to analyze chest computed tomography (CT) imaging. We hypothesized that Fibresolve is a useful predictor of mortality in interstitial lung diseases (ILD). METHODS: Fibresolve was previously validated in a multi-site >500-patient dataset. In this analysis, we assessed the usefulness of Fibresolve to predict mortality in a subset of 228 patients with IPF and other ILDs in whom follow up data was available. We applied Cox regression analysis adjusting for the Gender, Age, and Physiology (GAP) score and for other known predictors of mortality in IPF. We also analyzed the role of Fibresolve as tertiles adjusting for GAP stages. RESULTS: During a median follow-up of 2.8 years (range 5 to 3434 days), 89 patients died. After adjusting for GAP score and other mortality risk factors, the Fibresolve score significantly predicted the risk of death (HR: 7.14; 95% CI: 1.31-38.85; p = 0.02) during the follow-up period, as did forced vital capacity and history of lung cancer. After adjusting for GAP stages and other variables, Fibresolve score split into tertiles significantly predicted the risk of death (p = 0.027 for the model; HR 1.37 for 2nd tertile; 95% CI: 0.77-2.42. HR 2.19 for 3rd tertile; 95% CI: 1.22-3.93). CONCLUSIONS: The machine learning classifier Fibresolve demonstrated to be an independent predictor of mortality in ILDs, with prognostic performance equivalent to GAP based solely on CT images.

Can FDG-PET/CT imaging be used to predict decline in quality of life in interstitial lung disease? A prospective study of the relationship between FDG uptake and quality of life in a UK outpatient setting.

BACKGROUND: 18Fluorine-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) CT imaging has been used in many inflammatory and infectious conditions to differentiate areas of increased metabolic activity. FDG uptake differs between areas of normal lung parenchyma and interstitial lung disease (ILD). OBJECTIVES: In this study, we investigated whether FDG-PET/CT parameters were associated with a change in the quality of life (QoL) in patients with ILD over 4 years of follow-up. METHODS: Patients underwent PET-CT imaging at diagnosis and were followed up with annual QoL assessment using the St George's Respiratory Questionnaire (SGRQ) until death or 4 years of follow-up. Maximum standard uptake value (SUVmax) and Tissue-to-Background Ratio (TBR) were assessed against SGRQ overall and subscale scores. RESULTS: 193 patients (94 patients in the idiopathic pulmonary fibrosis (IPF) subgroup and 99 patients in the non-IPF subgroup) underwent baseline FDG-PET/CT imaging and QoL assessment. Weak-to-moderate correlation was observed between baseline SUVmax and SGRQ scores in both ILD subgroups. No relationship was observed between baseline SUVmax or TBR and change in SGRQ scores over 4 years of follow-up. In the IPF subgroup, surviving patients reported a decline in QoL at 4 years post diagnosis whereas an improvement in QoL was seen in surviving patients with non-IPF ILD. CONCLUSIONS: Weak-to-moderate positive correlation between baseline SUVmax and SGRQ scores was observed in both ILD subgroups (IPF:rs=0.187, p=0.047, non-IPF: rs=0.320, p=0.001). However, baseline SUVmax and TBR were not associated with change in QoL in patients with IPF and non-IPF ILD over 4 years of follow-up. At 4 years post diagnosis, surviving patients with IPF reported declining QoL whereas improvement was seen in patients with ILD who did not have IPF.

Prognostic and predictive value of interstitial lung abnormalities and EGFR mutation status in patients with non-small cell lung cancer.

BACKGROUND: To determine the predictive value of interstitial lung abnormalities (ILA) for epidermal growth factor receptor (EGFR) mutation status and assess the prognostic significance of EGFR and ILA in patients with non-small cell lung cancer (NSCLC). METHODS: We reviewed 797 consecutive patients with a histologically proven diagnosis of primary NSCLC from January 2013 to October 2018. Of these, 109 patients with NSCLC were found to have concomitant ILA. Multivariate logistic regression analysis was used to identify the significant clinical and computed tomography (CT) findings in predicting EGFR mutations. Cox proportional hazard models were used to identify significant prognostic factors. RESULTS: EGFR mutations were identified in 22 of 109 tumors (20.2%). Multivariate analysis showed that the models incorporating clinical, tumor CT and ILA CT features yielded areas under the receiver operating characteristic curve (AUC) values of 0.749, 0.838, and 0.849, respectively. When combining the three models, the independent predictive factors for EGFR mutations were non-fibrotic ILA, female sex, and small tumor size, with an AUC value of 0.920 (95% confidence interval[CI]: 0.861-0.978, p < 0.001). In the multivariate Cox model, EGFR mutations (hazard ratio = 0.169, 95% CI = 0.042-0.675, p = 0.012; 692 days vs. 301 days) were independently associated with extended overall survival compared to the wild-type. CONCLUSION: Non-fibrotic ILA independently predicts the presence of EGFR mutations, and the presence of EGFR mutations rather than non-fibrotic ILA serves as an independent good prognostic factor for patients with NSCLC.

Screening value of lung ultrasound and pleural shear wave elastography in connective tissue disease-related interstitial lung disease: a preliminary study.

OBJECTIVE: To explore the diagnostic value of lung ultrasound (LUS) and pleural shear wave elastography (SWE) for connective tissue disease-interstitial lung disease (CTD-ILD). METHODS: We selected 104 patients diagnosed with connective tissue disease (CTD) at our hospital. All patients underwent LUS, SWE, and high-resolution computed tomography (HRCT). With HRCT as the imaging gold standard for diagnosis, patients were categorized into CTD-ILD and CTD-non-ILD groups. We employed paired chi-square tests to compare the diagnostic differences between HRCT and LUS for ILD. Receiver operating characteristic (ROC) curves were used to assess the diagnostic value of pleural SWE for ILD. Correlation analysis was performed between pleural elasticity values and lung ultrasound scores. RESULTS: The sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of LUS for diagnosing CTD-ILD were 93.3%, 86.2%, 6.761, and 0.078, respectively. There was no statistically significant difference in the results between HRCT and LUS (P = 1.000), with a kappa value of 0.720 (P < 0.001). There was a statistically significant difference in the pleural elasticity in the bilateral lower back region between the case and control groups (P < 0.001). The area under the receiver operating characteristic (ROC) curve (AUC) for pleural SWE in diagnosing CTD-ILD was 0.685. In CTD-ILD patients, there was no significant correlation between pleural elasticity values and LUS scores (P > 0.05). CONCLUSION: The LUS can serve as an important imaging method for screening for CTD-ILD and assessing the severity of the disease. However, pleural SWE has been shown to demonstrate lower diagnostic efficacy for CTD-ILD, and its ability to assess disease severity is limited.

Prevalence and prognostic meaning of interstitial lung abnormalities in remote CT scans of patients with interstitial lung disease treated with antifibrotic therapy.

OBJECTIVES: To describe the prevalence and characteristics of interstitial lung abnormalities (ILA) in CT scans performed prior to the initiation of antifibrotics in a series of patients with interstitial lung disease (ILD), and to identify characteristics apparent on early CT scans that could help to predict outcomes. METHODS: We conducted a retrospective observational study. The original cohort consisted of 101 patients diagnosed with ILD and treated with antifibrotics in a tertiary hospital. Patients were included if they had a thoracic CT scan performed at least one year before initiation of therapy. They were classified radiologically in three groups: without ILA, with radiological ILA and extensive abnormalities. ILA were classified as subpleural fibrotic, subpleural non-fibrotic and non-subpleural. The initial scan and the latest CT scan performed before treatment were read for assessing progression. The relationship between CT findings of fibrosis and the radiological progression rate and mortality were analyzed. RESULTS: We included 50 patients. Only 1 (2%) had a normal CT scan, 25 (50%) had extensive alterations and 24 (48%) had radiological criteria for ILA, a median of 98.2 months before initiation of antifibrotics, of them 18 (75%) had a subpleural fibrotic pattern. Significant bronchiectasis and obvious honeycombing in the lower zones were associated with shorter survival (p = 0.04). Obvious honeycombing in the lower zones was also significantly (p < 0.05) associated with a faster progression rate. CONCLUSIONS: Fibrotic ILAs are frequent in remote scans of patients with clinically relevant ILD, long before they require antifibrotics. Findings of traction bronchiectasis and honeycombing in the earliest scans, even in asymptomatic patients, are related to mortality and progression later on.

Longitudinal assessment of interstitial lung abnormalities on CT in patients with COPD using artificial intelligence-based segmentation: a prospective observational study.

BACKGROUND: Interstitial lung abnormalities (ILAs) on CT may affect the clinical outcomes in patients with chronic obstructive pulmonary disease (COPD), but their quantification remains unestablished. This study examined whether artificial intelligence (AI)-based segmentation could be applied to identify ILAs using two COPD cohorts. METHODS: ILAs were diagnosed visually based on the Fleischner Society definition. Using an AI-based method, ground-glass opacities, reticulations, and honeycombing were segmented, and their volumes were summed to obtain the percentage ratio of interstitial lung disease-associated volume to total lung volume (ILDvol%). The optimal ILDvol% threshold for ILA detection was determined in cross-sectional data of the discovery and validation cohorts. The 5-year longitudinal changes in ILDvol% were calculated in discovery cohort patients who underwent baseline and follow-up CT scans. RESULTS: ILAs were found in 32 (14%) and 15 (10%) patients with COPD in the discovery (n = 234) and validation (n = 153) cohorts, respectively. ILDvol% was higher in patients with ILAs than in those without ILA in both cohorts. The optimal ILDvol% threshold in the discovery cohort was 1.203%, and good sensitivity and specificity (93.3% and 76.3%) were confirmed in the validation cohort. 124 patients took follow-up CT scan during 5 ± 1 years. 8 out of 124 patients (7%) developed ILAs. In a multivariable model, an increase in ILDvol% was associated with ILA development after adjusting for age, sex, BMI, and smoking exposure. CONCLUSION: AI-based CT quantification of ILDvol% may be a reproducible method for identifying and monitoring ILAs in patients with COPD.

[Diffuse cystic lung disease]. / Cystische Lungenerkrankungen.

INTRODUCTION: Diffuse cystic lung disease (DCLD) represents a heterogeneous group of conditions, typically characterized by the presence of multiple thin-walled, predominantly round parenchymal lucencies. The increased accessibility of computed tomography (CT) underscores the growing relevance of a relatively rare group of diseases as more clinicians are confronted with the presence of multiple lung cysts on the chest CT scan. Although the etiology of these conditions is very diverse, the focus of the differential diagnosis revolves around four primary causative factors - Lymphangioleiomyomatosis (LAM), Pulmonary Langerhanscell histiocytosis (PLCH), Birt-Hogg-Dubé (BHD) and lymphoid interstitial pneumonia (LIP). Achieving an accurate diagnosis poses a challenge and typically necessitates lung biopsies; however, it is crucial for ensuring proper management.

The Value of Ultrasound for Detecting and Following Subclinical Interstitial Lung Disease in Systemic Sclerosis.

BACKGROUND: Interstitial lung disease (ILD) is a complication in patients with systemic sclerosis (SSc). Accurate strategies to identify its presence in early phases are essential. We conducted the study aiming to determine the validity of ultrasound (US) in detecting subclinical ILD in SSc, and to ascertain its potential in determining the disease progression. METHODS: 133 patients without respiratory symptoms and 133 healthy controls were included. Borg scale, Rodnan skin score (RSS), auscultation, chest radiographs, and respiratory function tests (RFT) were performed. A rheumatologist performed the lung US. High-resolution CT (HRCT) was also performed. The patients were followed every 12 weeks for 48 weeks. RESULTS: A total of 79 of 133 patients (59.4%) showed US signs of ILD in contrast to healthy controls (4.8%) (p = 0.0001). Anti-centromere antibodies (p = 0.005) and RSS (p = 0.004) showed an association with ILD. A positive correlation was demonstrated between the US and HRCT findings (p = 0.001). The sensitivity and specificity of US in detecting ILD were 91.2% and 88.6%, respectively. In the follow-up, a total of 30 patients out of 79 (37.9%) who demonstrated US signs of ILD at baseline, showed changes in the ILD score by US. CONCLUSIONS: US showed a high prevalence of subclinical ILD in SSc patients. It proved to be a valid, reliable, and feasible tool to detect ILD in SSc and to monitor disease progression.

Clinical utility, reproducibility, and radiologist acceptance of ILD-RADS.

PURPOSE: To investigate the clinical utility, reproducibility, and radiologists' acceptance of the Interstitial Lung Disease Imaging-Reporting and Data System (ILD-RADS). METHOD: In this single-institutional retrospective study, three radiologists independently reviewed the chest high-resolution CT (HRCT) scans of 111 consecutive patients diagnosed with ILDs. They assessed the HRCT pulmonary features using the ILD-RADS template and assigned an ILD-RADS category (1-4) to each scan based on the identified imaging pattern. Patients were classified into idiopathic pulmonary fibrosis (IPF) (n = 14) and non-IPF ILD (n = 97) groups based on clinical diagnoses determined by multidisciplinary discussion. Association between ILD-RADS categories and clinical diagnoses was assessed using the Chi-square test for trend. Reproducibility was evaluated using kappa (k) scores, and radiologists' acceptance of the ILD-RADS was evaluated with a questionnaire. RESULTS: We found a significant association between the ILD-RADS categories and patients' clinical diagnoses (P ≤ 0.0001) for the three readers, with a trend toward increased assignment of ILD-RADS-1 to IPF patients (50 %-57.1 %), and ILD-RADS-4 to non-IPF patients (46.4 %-49.5 %). The ILD-RADS categories showed excellent intra-reader agreement (k = 0.873) and moderate inter-reader agreement (k = 0.440). ILD-RADS-1 and -4 categories showed the highest inter-reader agreement (k = 0.681 and 0.481, respectively). Radiologists gave a positive response to using the ILD-RADS in daily practice. CONCLUSIONS: The clinical utility of the ILD-RADS was demonstrated by the significant association between the ILD-RADS categories and patients' clinical diagnoses, particularly the ILD-RADS-1 and -4 categories. Excellent intra-reader and moderate inter-reader reproducibility was observed. ILD-RADS has the potential to be widely accepted for standardized HRCT reporting among radiologists.