Use of a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples: a prospective validation study

Genomic classifier: biomarker for progression in interstitial lung disease

Genomic classifier might serve as a biomarker for disease progression in fibrotic interstitial lung disease https://bit.ly/3YuGjoF.

Progression of interstitial lung disease after the Envisia Genomic Classifier

Background

Interstitial lung disease (ILD) represents a heterogenous group of diseases that have substantial morbidity and mortality. The Envisia Genomic Classifier (EGC) is a test that analyses RNA derived from transbronchial biopsy (TBBx) samples to make a positive or negative genomic usual interstitial pneumonitis (UIP) designation. Our study assesses the ability for the EGC to predict progression of disease, with a longer duration of follow-up than previous studies.

Methods

Patients referred for cryobiopsy for outpatient workup of ILD concurrently had TBBx and EGC testing performed. We performed a retrospective analysis to assess differences in progression of disease between EGC-positive and negative patients, applying Kaplan-Meier survival analysis and log-rank tests. Confidence in ILD diagnosis before and after the EGC result was also noted, and the difference in confidence levels was assessed by a Wilcoxon signed-rank test.

Results

82 patient cases were analysed. EGC-positive patients had a shorter progression-free survival (PFS) than EGC-negative patients, (p<0.0001), with 622 versus 1487 median PFS days respectively. EGC-positive patients also had worse progression in the subsets of patients with "indeterminate for UIP" computed tomography (CT) (p=0.0052), "alternative diagnosis" CT (p=0.0144) and non-idiopathic pulmonary fibrosis ILD diagnosis (p=0.0157). Additionally, EGC increased the diagnostic confidence level (p<0.0001).

Conclusion

EGC positivity predicts worse ILD progression over a sustained follow-up period. The ability to predict worse prediction early in the ILD course without the need for surgical biopsy would have significant clinical impact.

Updates in Diagnostic Tools for ILD

Interstitial lung disease (ILD) is a group of diffuse parenchymal disorders, which are diagnosed in many cases by multidisciplinary discussion (MDD). In some cases, diagnosis can be challenging, and the addition of histopathology can increase diagnostic confidence. The tools to obtain a histopathological sample to diagnose ILD are expanding. In this review, we will discuss the various modalities, their sensitivities and specificities, and procedural complication rates. In this review, we conducted a comprehensive review of literature focusing on emerging and established diagnostic tools for ILD. A systematic search of peer-reviewed publications was performed using PubMed with a focus on clinical trials, retrospective and prospective cohort studies, and systematic reviews. The key diagnostic modalities in focus were genomic classifier (GC), transbronchial cryobiopsy (TBLC), surgical lung biopsy (SLB), endobronchial ultrasound cryobiopsy (EBUS-C), genetic testing, and speckled transthoracic echocardiography (STE). Data extracted from these studies focused on diagnostic yield, specificity, sensitivity, and procedural complication rate. Genomic classifier, a gene-based molecular diagnostic tool, has a high specificity for histological usual interstitial pneumonia (UIP). However, in cases of a negative result, it often results in a need for further invasive sampling by TBLC or SLB. TBLC results in a larger histological sample, which can increase diagnostic yield and increase diagnostic confidence at MDD. Recent prospective trials have compared this modality with SLB and found 63-77% interobserver agreement between pathologists. SLB remains the gold standard with diagnostic yields reported to be more than 90%. EBUS-C has shown promising results increasing diagnostic yield in patients with suspected sarcoidosis or lymphoma. All diagnostic modalities have procedural complications with most common being pneumothorax, bleeding and, rarely, death. Advancements in diagnostic tools for interstitial lung disease (ILD) have significantly improved accuracy. Even though surgical lung biopsy remains the gold standard, the alternative modalities are promising and provide a promising yield with a lower procedural risk.

Cost-effectiveness of novel diagnostic tools for idiopathic pulmonary fibrosis in the United States

OBJECTIVES

Novel non-invasive machine learning algorithms may improve accuracy and reduce the need for biopsy when diagnosing idiopathic pulmonary fibrosis (IPF). We conducted a cost-effectiveness analysis of diagnostic strategies for IPF.

METHODS

We developed a decision analytic model to evaluate diagnostic strategies for IPF in the United States. To assess the full spectrum of costs and benefits, we compared four interventions: a machine learning diagnostic algorithm, a genomic classifier, a biopsy-all strategy, and a treat-all strategy. The analysis was conducted from the health sector perspective with a lifetime horizon. The primary outcome measures were costs, Quality-Adjusted Life-Years (QALYs) gained, and Incremental Cost-Effectiveness Ratios (ICERs) based on the average of 10,000 probabilistic runs of the model.

RESULTS

Compared to a biopsy-all strategy the machine learning algorithm and genomic classifer reduced diagnostic-related costs by $14,876 and $3,884, respectively. Use of the machine learning algorithm consistently reduced diagnostic costs. When including downstream treatment costs and benefits of anti-fibrotic treatment, the machine learning algorithm had an ICER of $331,069 per QALY gained compared to the biopsy-all strategy. The genomic classifier had a higher ICER of $390,043 per QALY gained, while the treat-all strategy had the highest ICER of $3,245,403 per QALY gained. Results were sensitive to changes in various input parameters including IPF treatment costs, sensitivity and specificity of novel screening tools, and the rate of additional diagnostics following inconclusive results. High treatment costs were found to drive overall cost regardless of the diagnostic method. As treatment costs lowered, the supplemental diagnostic tools became increasingly cost-effective.

CONCLUSIONS

Novel tools for diagnosing IPF reduced diagnostic costs, while overall incremental cost-effectiveness ratios were high due to treatment costs. New IPF diagnosis approaches may become more favourable with lower-cost treatments for IPF.

Advances in idiopathic pulmonary fibrosis diagnosis and treatment

Significant advances have been made in diagnosing and treating idiopathic pulmonary fibrosis (IPF) in the last decade. The incidence and prevalence of IPF are increasing, and morbidity and mortality remain high despite the two Food and Drug Administration (FDA)-approved medications, pirfenidone and nintedanib. Hence, there is an urgent need to develop new diagnostic tools and effective therapeutics to improve early, accurate diagnosis of IPF and halt or reverse the progression of fibrosis with a better safety profile. New diagnostic tools such as transbronchial cryobiopsy and genomic classifier require less tissue and generally have good safety profiles, and they have been increasingly utilized in clinical practice. Advances in artificial intelligence-aided diagnostic software are promising, but challenges remain. Both pirfenidone and nintedanib focus on growth factor-activated pathways to inhibit fibroblast activation. Novel therapies targeting different pathways and cell types (immune and epithelial cells) are being investigated. Biomarker-based personalized medicine approaches are also in clinical trials. This review aims to summarize recent diagnostic and therapeutic development in IPF.

Development and validation of a clinical, CT, genomic classifier and BAL scoring system for diagnosing idiopathic pulmonary fibrosis

BACKGROUND

The utility of incorporating a usual interstitial pneumonia (UIP) genomic classifier (GC) and bronchoalveolar lavage (BAL) cell count analysis alongside traditional clinical-imaging assessment in aiding in the multidisciplinary diagnosis of idiopathic pulmonary fibrosis (IPF) in patients with a non-definite high-resolution computed tomography (HRCT) UIP pattern is uncertain.

METHODS

We reviewed consecutive adult patients presenting with fibrotic interstitial lung disease (fILD) and a non-definite HRCT UIP pattern who underwent BAL and GC. The initial fILD diagnoses were re-evaluated after bronchoscopy and a final multidisciplinary consensus diagnosis was provided. We created a clinical score by analysing fILD clinical characteristics, GC and BAL results from 139 National Jewish Health patients and validated it at the University of Arizona (n=52). A multivariable model was developed and assessed using receiver operating characteristic curves.

RESULTS

43/139 (31%) and 29/52 (56%) patients in the derivation and validation cohort, respectively, were diagnosed with IPF after bronchoscopy, and 85/139 (61%) and 32/52 (61%) had a change in treatment, respectively. Compared to non-IPF, IPF patients had a similar progression-free survival (hazard ratio 1.50, 95% CI 0.76-2.95). The final model assigned a score to eight predictors: age, sex, HRCT probable UIP pattern, exposures, connective tissue disease signs/symptoms, Velcro crackles, GC results and BAL lymphocyte and macrophage counts. The final score demonstrated an area under the curve of 0.90 (95% CI 0.85-0.95) in the derivation cohort and 0.91 (95% CI 0.83-0.99) in the validation cohort.

CONCLUSION

The clinical-HRCT-BAL-GC IPF score may accurately estimate the post-test probability of IPF in patients with a non-definite HRCT UIP pattern.

Spatially resolved gene expression profiles of fibrosing interstitial lung diseases

Fibrosing interstitial lung diseases (ILDs) encompass a diverse range of scarring disorders that lead to progressive lung failure. Previous gene expression profiling studies focused on idiopathic pulmonary fibrosis (IPF) and bulk tissue samples. We employed digital spatial profiling to gain new insights into the spatial resolution of gene expression across distinct lung microenvironments (LMEs) in IPF, chronic hypersensitivity pneumonitis (CHP) and non-specific interstitial pneumonia (NSIP). We identified differentially expressed genes between LMEs within each condition, and across histologically similar regions between conditions. Uninvolved regions in IPF and CHP were distinct from normal controls, and displayed potential therapeutic targets. Hallmark LMEs of each condition retained distinct gene signatures, but these could not be reproduced in matched lung tissue samples. Based on these profiles and unsupervised clustering, we grouped previously unclassified ILD cases into NSIP or CHP. Overall, our work uniquely dissects gene expression profiles between LMEs within and across different types of fibrosing ILDs.

Machine Learning of Plasma Proteomics Classifies Diagnosis of Interstitial Lung Disease

Rationale: Distinguishing connective tissue disease-associated interstitial lung disease (CTD-ILD) from idiopathic pulmonary fibrosis (IPF) can be clinically challenging. Objectives: To identify proteins that separate and classify patients with CTD-ILD and those with IPF. Methods: Four registries with 1,247 patients with IPF and 352 patients with CTD-ILD were included in analyses. Plasma samples were subjected to high-throughput proteomics assays. Protein features were prioritized using recursive feature elimination to construct a proteomic classifier. Multiple machine learning models, including support vector machine, LASSO (least absolute shrinkage and selection operator) regression, random forest, and imbalanced Random Forest, were trained and tested in independent cohorts. The validated models were used to classify each case iteratively in external datasets. Measurements and Main Results: A classifier with 37 proteins (proteomic classifier 37 [PC37]) was enriched in the biological process of bronchiole development and smooth muscle proliferation and immune responses. Four machine learning models used PC37 with sex and age score to generate continuous classification values. Receiver operating characteristic curve analyses of these scores demonstrated consistent areas under the curve of 0.85-0.90 in the test cohort and 0.94-0.96 in the single-sample dataset. Binary classification demonstrated 78.6-80.4% sensitivity and 76-84.4% specificity in the test cohort and 93.5-96.1% sensitivity and 69.5-77.6% specificity in the single-sample classification dataset. Composite analysis of all machine learning models confirmed 78.2% (194 of 248) accuracy in the test cohort and 82.9% (208 of 251) in the single-sample classification dataset. Conclusions: Multiple machine learning models trained with large cohort proteomic datasets consistently distinguished CTD-ILD from IPF. Many of the identified proteins are involved in immune pathways. We further developed a novel approach for single-sample classification, which could facilitate honing the differential diagnosis of ILD in challenging cases and improve clinical decision making.

Genetics and Genomics of Pulmonary Fibrosis: Charting the Molecular Landscape and Shaping Precision Medicine

Recent genetic and genomic advancements have elucidated the complex etiology of idiopathic pulmonary fibrosis (IPF) and other progressive fibrotic interstitial lung diseases (ILDs), emphasizing the contribution of heritable factors. This state-of-the-art review synthesizes evidence on significant genetic contributors to pulmonary fibrosis (PF), including rare genetic variants and common SNPs. The MUC5B promoter variant is unusual, a common SNP that markedly elevates the risk of early and established PF. We address the utility of genetic variation in enhancing understanding of disease pathogenesis and clinical phenotypes, improving disease definitions, and informing prognosis and treatment response. Critical research gaps are highlighted, particularly the underrepresentation of non-European ancestries in PF genetic studies and the exploration of PF phenotypes beyond usual interstitial pneumonia/IPF. We discuss the role of telomere length, often critically short in PF, and its link to progression and mortality, underscoring the genetic complexity involving telomere biology genes (TERT, TERC) and others like SFTPC and MUC5B. In addition, we address the potential of gene-by-environment interactions to modulate disease manifestation, advocating for precision medicine in PF. Insights from gene expression profiling studies and multiomic analyses highlight the promise for understanding disease pathogenesis and offer new approaches to clinical care, therapeutic drug development, and biomarker discovery. Finally, we discuss the ethical, legal, and social implications of genomic research and therapies in PF, stressing the need for sound practices and informed clinical genetic discussions. Looking forward, we advocate for comprehensive genetic testing panels and polygenic risk scores to improve the management of PF and related ILDs across diverse populations.

Functional Improvement at One Year in Fibrotic Interstitial Lung Diseases-Prognostic Value of Baseline Biomarkers and Anti-Inflammatory Therapies

BACKGROUND

The clinical spectrum of fibrotic interstitial lung diseases (ILDs) is highly heterogeneous. We aimed to evaluate the prognostic value of widely available baseline biomarkers for the improvement of lung function in patients with fibrotic ILDs.

METHODS

This registry-based study included 142 patients with fibrotic ILDs as defined by the presence of reticulation, traction bronchiectasis or honeycombing on initial high-resolution computed tomography (HRCT). Functional improvement at 1 year was defined as a relative increase of 5% in forced vital capacity (FVC) or of 10% in diffusion capacity for carbon monoxide (DLCO). The prognostic value of baseline biomarkers was evaluated for all patients and the subgroup with anti-inflammatory treatment.

RESULTS

At one year, 44 patients showed improvement while 73 showed disease progression. Multivariate analyses found prognostic significance for age < 60 years (OR 5.4; 95%CI 1.9-15.4; p = 0.002), lactate dehydrogenase (LDH) >250 U/L (OR 2.5; 95%CI 1.1-5.8; p = 0.043) and blood monocyte count < 0.8 G/L (OR 3.5; 95%CI 1.1-11.3; p = 0.034). In 84 patients undergoing anti-inflammatory treatment, multivariate analysis revealed age < 60 years (OR 8.5 (95%CI 2.1-33.4; p = 0.002) as the only significant variable.

CONCLUSION

Younger age, a higher LDH and lower blood monocyte count predicted functional improvement in fibrotic ILD patients, while in those treated with anti-inflammatory drugs, only age had significant implications.

Disorders of fatty acid metabolism and imbalance in the ratio of monounsaturated fatty acids promote the development of pulmonary fibrosis

OBJECTIVE

Although some studies suggested that metabolic abnormalities may contribute to the development of pulmonary fibrosis, there are no studies that have reported a clear causal relationship between them, and the aim of this study was to explore the causal relationship between plasma metabolites and pulmonary fibrosis using Mendelian randomization (MR) combined with metabolomics analysis.

METHODS

Firstly, we explored the causal relationship between 1400 metabolites and pulmonary fibrosis using MR analysis, and detected plasma metabolites in mice with pulmonary fibrosis using metabolomics technology, thus validating the results of MR analysis. In addition, we again used MR to explore the causal relationship between the results of the differential metabolite KEGG in metabolomics and pulmonary fibrosis.

RESULTS

A total of 52 metabolites were screened for association with pulmonary fibrosis in the MR analysis of 1400 plasma metabolites with pulmonary fibrosis, based on P < 0.05 for the IVW method, with consistent OR directions for all methods. Four of them were validated in the plasma of mice with pulmonary fibrosis, namely carnitine c18:2 levels (negative correlation), Glutamine degradant levels (positive correlation), Propionylcarnitine (c3) levels (negative correlation), carnitine to palmitoylcarnitine (c16) ratio (negative correlation). In addition, KEGG analysis of plasma differential metabolites revealed that the signaling pathway of biosynthetic of unsaturated fatty acids was most affected in mice with pulmonary fibrosis, and MR analysis showed that imbalance in the ratio of monounsaturated fatty acids was significantly associated with pulmonary fibrosis.

CONCLUSIONS

Our study suggests that abnormal fatty acid levels due to reduced levels of carnitine-like metabolites, and an imbalance in the ratio of monounsaturated, promote the development of pulmonary fibrosis. This study reveals the marker metabolites and metabolic pathways affecting the development of pulmonary fibrosis to provide a basis for the development of new drugs for the treatment of pulmonary fibrosis.

Impact of surgical lung biopsy on lung function and survival in patients with idiopathic pulmonary fibrosis in a multi-centre registry cohort

BACKGROUND AND OBJECTIVE

Establishing an accurate and timely diagnosis of idiopathic pulmonary fibrosis (IPF) is essential for appropriate management and prognostication. In some cases, surgical lung biopsy (SLB) is performed but carries non-negligible risk. The objective of this retrospective study was to determine if SLB is associated with accelerated lung function decline in patients with IPF using the Canadian Registry for Pulmonary Fibrosis.

METHODS

Linear mixed models and Cox proportional hazards regression models were used to compare decline in forced vital capacity (FVC)%, diffusion capacity of the lung (DLCO%) and risk of death or lung transplantation between SLB and non-SLB patients. Adjustments were made for baseline age, sex, smoking history, antifibrotic use, and lung function. A similar analysis compared lung function changes 12 months pre- and post-SLB.

RESULTS

A total of 81 SLB patients and 468 non-SLB patients were included. In the SLB group, the post-biopsy annual FVC% decline was 2.0% (±0.8) in unadjusted, and 2.1% (±0.8) in adjusted models. There was no difference in FVC% decline, DLCO% decline, or time to death or lung transplantation between the two groups, in adjusted or unadjusted models (all p-values >0.07). In the pre-post SLB group, no differences were identified in FVC% decline in unadjusted or adjusted models (p = 0.07 for both).

CONCLUSION

No association between SLB and lung function decline or risk of death or lung transplantation was identified in this multi-centre study of patients with IPF.

Relationship between idiopathic interstitial pneumonias (IIPs) and connective tissue disease-related interstitial lung disease (CTD-ILD): A narrative review

While idiopathic interstitial pneumonia (IIP) centering on idiopathic pulmonary fibrosis (IPF) is the most prevalent interstitial lung disease (ILD), especially in the older adult population, connective tissue disease (CTD)-related ILD is the second most prevalent ILD. The pathogenesis of IPF is primarily fibrosis, whereas that of other ILDs, particularly CTD-ILD, is mainly inflammation. Therefore, a precise diagnosis is crucial for selecting appropriate treatments, such as antifibrotic or immunosuppressive agents. In addition, some patients with IIP have CTD-related features, such as arthritis and skin eruption, but do not meet the criteria for any CTD, this is referred to as interstitial pneumonia with autoimmune features (IPAF). IPAF is closely associated with idiopathic nonspecific interstitial pneumonia (iNSIP) and cryptogenic organizing pneumonia (COP). Furthermore, patients with iNSIP or those with NSIP with OP overlap frequently develop polymyositis/dermatomyositis after the diagnosis of IIP. Acute exacerbation of ILD, the most common cause of death, occurs more frequently in patients with IPF than in those with other ILDs. Although acute exacerbation of CTD-ILD occurs at a low rate of incidence, patients with rheumatoid arthritis, microscopic polyangiitis, or systemic sclerosis experience more acute exacerbation of CTD-ILD than those with other CTD. In this review, the features of each IIP, focusing on CTD-related signatures, are summarized, and the pathogenesis and appropriate treatments to improve the prognoses of patients with various ILDs are discussed.

A Machine Learning System to Indicate Diagnosis of Idiopathic Pulmonary Fibrosis Non-Invasively in Challenging Cases

Radiologic usual interstitial pneumonia (UIP) patterns and concordant clinical characteristics define a diagnosis of idiopathic pulmonary fibrosis (IPF). However, limited expert access and high inter-clinician variability challenge early and pre-invasive diagnostic sensitivity and differentiation of IPF from other interstitial lung diseases (ILDs). We investigated a machine learning-driven software system, Fibresolve, to indicate IPF diagnosis in a heterogeneous group of 300 patients with interstitial lung disease work-up in a retrospective analysis of previously and prospectively collected registry data from two US clinical sites. Fibresolve analyzed cases at the initial pre-invasive assessment. An Expert Clinical Panel (ECP) and three panels of clinicians with varying experience analyzed the cases for comparison. Ground Truth was defined by separate multi-disciplinary discussion (MDD) with the benefit of surgical pathology results and follow-up. Fibresolve met both pre-specified co-primary endpoints of sensitivity superior to ECP and significantly greater specificity (p = 0.0007) than the non-inferior boundary of 80.0%. In the key subgroup of cases with thin-slice CT and atypical UIP patterns (n = 124), Fibresolve's diagnostic yield was 53.1% [CI: 41.3-64.9] (versus 0% pre-invasive clinician diagnostic yield in this group), and its specificity was 85.9% [CI: 76.7-92.6%]. Overall, Fibresolve was found to increase the sensitivity and diagnostic yield for IPF among cases of patients undergoing ILD work-up. These results demonstrate that in combination with standard clinical assessment, Fibresolve may serve as an adjunct in the diagnosis of IPF in a pre-invasive setting.

Defining Optimal Settings for Lung Cryobiopsy in End-Stage Pulmonary Disease. A Human, Ex Vivo, Diseased Lung Clinical Trial

BACKGROUND

To evaluate optimal settings of probe size, freezing time, and distance to the pleura that influence the size and quality of biopsy specimens during transbronchial lung cryobiopsies in ESPD.

METHODS

We prospectively recruited 17 patients undergoing lung transplantation. We created a nonperfused ex vivo bronchoscopy setting to perform multiple cryobiopsies with different probe sizes (1.7, 1.9, and 2.4 mm), freezing times (3, 5, 7, 10, 20, 30 seconds), and probe distance from pleura (5, 10, and 20 mm). Alveolated pulmonary parenchyma area≥50% in histology was considered a good quality biopsy, with a minimum procedural artifact. We used logistic regression to identify independent parameters as risk factors for histologic adequacy.

RESULTS

A total of 545 cryobiopsies were obtained from 34 explanted lungs after pneumonectomy for lung transplantation. The mean maximum diameter of the specimen achieved with the 1.7 probe was larger (13.5 mm) than those obtained with 1.9 and 2.4 mm probes (11.3 and 10.7 mm, P= 0.07). More pleural macroscopic damage and pleural tissue in histology occurred with the 2.4 mm probe ( P <0.001). There was no difference in the quality of specimens between the different freezing times and the distance from the pleura.

CONCLUSIONS

Freezing time and distance from the pleura did not affect the histologic quality for diagnosing ESPD in severely damaged lungs. Smaller cryoprobe size did not negatively affect sample adequacy.

Multidisciplinary Approach to the Diagnosis of Idiopathic Interstitial Pneumonias: Focus on the Pathologist's Key Role

Idiopathic Interstitial Pneumonias (IIPs) are a heterogeneous group of the broader category of Interstitial Lung Diseases (ILDs), pathologically characterized by the distortion of lung parenchyma by interstitial inflammation and/or fibrosis. The American Thoracic Society (ATS)/European Respiratory Society (ERS) international multidisciplinary consensus classification of the IIPs was published in 2002 and then updated in 2013, with the authors emphasizing the need for a multidisciplinary approach to the diagnosis of IIPs. The histological evaluation of IIPs is challenging, and different types of IIPs are classically associated with specific histopathological patterns. However, morphological overlaps can be observed, and the same histopathological features can be seen in totally different clinical settings. Therefore, the pathologist's aim is to recognize the pathologic-morphologic pattern of disease in this clinical setting, and only after multi-disciplinary evaluation, if there is concordance between clinical and radiological findings, a definitive diagnosis of specific IIP can be established, allowing the optimal clinical-therapeutic management of the patient.

Transbronchial Lung Cryobiopsy Performed with Cone Beam Computed Tomography Guidance Versus Fluoroscopy: A Retrospective Cohort Review

PURPOSE

Determining the cause of interstitial lung disease (ILD) remains challenging. While surgical lung biopsy remains the gold standard approach, risks associated with it may be prohibitive. Transbronchial lung cryobiopsy (TBLC) is a minimally invasive alternative with an improved safety profile and acceptable diagnostic accuracy. We retrospectively assessed whether the use of Cone Beam computed tomography guidance for TBLC (TBLC-CBCT) improves safety and diagnostic yield compared to performing TBLC with fluoroscopic guidance (TBLC-F).

METHODS

A retrospective cohort review of 120 patients presenting for evaluation of newly diagnosed ILD was performed. Demographic data, pulmonary function test values, chest imaging pattern, procedural information, and final multidisciplinary discussion (MDD) diagnosis were recorded.

RESULTS

62 patients underwent TBLC-F and 58 underwent TBLC-CBCT. Patients undergoing TBLC-CBCT were older (67.86 ± 10.97 vs 61.45 ± 12.77 years, p = 0.004) and had a higher forced vital capacity percent predicted (73.80 ± 17.32% vs 66.00 ± 17.45%, p = 0.03) compared to the TBLC-F group. The average probe-to-pleura distance was 5.1 ± 2.3 mm in the TBLC-CBCT group with 4.0 ± 0.3 CBCT spins performed. Pneumothorax occurred more often in the TBLC-F group (n = 6, 9.7%) compared to the TBLC-CBCT group (n = 1, 1.7%, p = 0.06). Grade 2 bleeding only occurred in the TBLC-F group (n = 4, 6.5%). A final MDD diagnosis was obtained in 89% (n = 57) of TBLC-F patients and 95% (n = 57) of TBLC-CBCT patients.

CONCLUSIONS

TBLC-CBCT appears to be safer compared to TBLC-F with both approaches facilitating an MDD diagnosis. Further studies from multiple institutions randomizing patients to each modality are needed to confirm these findings.

Pulmonary Pathology Society Survey on Practice Approaches in the Histologic Diagnosis of Fibrotic Interstitial Lung Disease: Consensus and Opportunities

CONTEXT.—

The pathologic diagnosis of usual interstitial pneumonia (UIP) remains a challenging area, and application of histologic UIP guidelines has proved difficult.

OBJECTIVE.—

To understand current practice approaches by pulmonary pathologists for the histologic diagnosis of UIP and other fibrotic interstitial lung diseases (ILDs).

DESIGN.—

The Pulmonary Pathology Society (PPS) ILD Working Group developed and sent a 5-part survey on fibrotic ILD electronically to the PPS membership.

RESULTS.—

One hundred sixty-one completed surveys were analyzed. Of the respondents, 89% reported using published histologic features in clinical guidelines for idiopathic pulmonary fibrosis (IPF) in their pathologic diagnosis; however, there was variability in reporting terminology, quantity and quality of histologic features, and the use of guideline categorization. Respondents were very likely to have access to pulmonary pathology colleagues (79%), pulmonologists (98%), and radiologists (94%) to discuss cases. Half of respondents reported they may alter their pathologic diagnosis based on additional clinical and radiologic history if it is pertinent. Airway-centered fibrosis, granulomas, and types of inflammatory infiltrates were considered important, but there was poor agreement on how these features are defined.

CONCLUSIONS.—

There is significant consensus among the PPS membership on the importance of histologic guidelines/features of UIP. There are unmet needs for (1) consensus and standardization of diagnostic terminology and incorporation of recommended histopathologic categories from the clinical IPF guidelines into pathology reports, (2) agreement on how to incorporate into the report relevant clinical and radiographic information, and (3) defining the quantity and quality of features needed to suggest alternative diagnoses.

Interventional Pulmonology: Extending the Breadth of Thoracic Care

Interventional pulmonary medicine has developed as a subspecialty focused on the management of patients with complex thoracic disease. Leveraging minimally invasive techniques, interventional pulmonologists diagnose and treat pathologies that previously required more invasive options such as surgery. By mitigating procedural risk, interventional pulmonologists have extended the reach of care to a wider pool of vulnerable patients who require therapy. Endoscopic innovations, including endobronchial ultrasound and robotic and electromagnetic bronchoscopy, have enhanced the ability to perform diagnostic procedures on an ambulatory basis. Therapeutic procedures for patients with symptomatic airway disease, pleural disease, and severe emphysema have provided the ability to palliate symptoms. The combination of medical and procedural expertise has made interventional pulmonologists an integral part of comprehensive care teams for patients with oncologic, airway, and pleural needs. This review surveys key areas in which interventional pulmonologists have impacted the care of thoracic disease through bronchoscopic intervention.

Diagnosis of interstitial lung diseases: from Averill A. Liebow to artificial intelligence

Histopathologic criteria of usual interstitial pneumonia (UIP)/idiopathic pulmonary fibrosis (IPF) were defined over the years and endorsed by leading organizations decades after Dr. Averill A. Liebow first coined the term UIP in the 1960s as a distinct pathologic pattern of fibrotic interstitial lung disease. Novel technology and recent research on interstitial lung diseases with genetic component shed light on molecular pathogenesis of UIP/IPF. Two antifibrotic agents introduced in the mid-2010s opened a new era of therapeutic approaches to UIP/IPF, albeit contentious issues regarding their efficacy, side effects, and costs. Recently, the concept of progressive pulmonary fibrosis was introduced to acknowledge additional types of progressive fibrosing interstitial lung diseases with the clinical and pathologic phenotypes comparable to those of UIP/IPF. Likewise, some authors have proposed a paradigm shift by considering UIP as a stand-alone diagnostic entity to encompass other fibrosing interstitial lung diseases that manifest a relentless progression as in IPF. These trends signal a pendulum moving toward the tendency of lumping diagnoses, which poses a risk of obscuring potentially important information crucial to both clinical and research purposes. Recent advances in whole slide imaging for digital pathology and artificial intelligence technology could offer an unprecedented opportunity to enhance histopathologic evaluation of interstitial lung diseases. However, current clinical practice trends of moving away from surgical lung biopsies in interstitial lung disease patients may become a limiting factor in this endeavor as it would be difficult to build a large histopathologic database with correlative clinical data required for artificial intelligence models.

Inhaled pulmonary surfactant biomimetic liposomes for reversing idiopathic pulmonary fibrosis through synergistic therapeutic strategy

Idiopathic pulmonary fibrosis (IPF) stands as a highly heterogeneous and deadly lung disease, yet the available treatment options remain limited. Combining myofibroblast inhibition with ROS modulation in damaged AECs offers a comprehensive strategy to halt IPF progression, but delivering drugs separately to these cell types is challenging. Inspired by the successful application of pulmonary surfactant (PS) replacement therapy in lung disease treatment, we have developed PS nano-biomimetic liposomes (PSBs) to utilize its natural transport pathway for targeting AECs while reducing lung tissue clearance. In this collaborative pulmonary drug delivery system, PSBs composed of DPPC/POPG/DPPG/CHO (20:9:5:4) were formulated for inhalation. These PSBs loaded with ROS-scavenger astaxanthin (AST) and anti-fibrosis drug pirfenidone (PFD) were aerosolized for precise quantification and mimicking patient inhalation. Through aerosol inhalation, the lipid membrane of PSBs gradually fused with natural PS, enabling AST delivery to AECs by hitchhiking with PS circulation. Simultaneously, PFD was released within the PS barrier, effectively penetrating lung tissue to exert therapeutic effects. In vivo results have shown that PSBs offer numerous therapeutic advantages in mice with IPF, particularly in terms of lung function recovery. This approach addresses the challenges of drug delivery to specific lung cells and offers potential benefits for IPF patients.

Emerging opportunities to treat idiopathic pulmonary fibrosis: Design, discovery, and optimizations of small-molecule drugs targeting fibrogenic pathways

Idiopathic pulmonary fibrosis (IPF) is the most common fibrotic form of idiopathic diffuse lung disease. Due to limited treatment options, IPF patients suffer from poor survival. About ten years ago, Pirfenidone (Shionogi, 2008; InterMune, 2011) and Nintedanib (Boehringer Ingelheim, 2014) were approved, greatly changing the direction of IPF drug design. However, limited efficacy and side effects indicate that neither can reverse the process of IPF. With insights into the occurrence of IPF, novel targets and agents have been proposed, which have fundamentally changed the treatment of IPF. With the next-generation agents, targeting pro-fibrotic pathways in the epithelial-injury model offers a promising approach. Besides, several next-generation IPF drugs have entered phase II/III clinical trials with encouraging results. Due to the rising IPF treatment requirements, there is an urgent need to completely summarize the mechanisms, targets, problems, and drug design strategies over the past ten years. In this review, we summarize known mechanisms, target types, drug design, and novel technologies of IPF drug discovery, aiming to provide insights into the future development and clinical application of next-generation IPF drugs.

The potential role of artificial intelligence in the clinical practice of interstitial lung disease

Artificial intelligence (AI) is being widely applied in the field of medicine, in areas such as drug discovery, diagnostic support, and assistance with medical practice. Among these, medical imaging is an area where AI is expected to make a significant contribution. In Japan, as of November 2022, 23 AI medical devices have received regulatory approval; all these devices are related to image analysis. In interstitial lung diseases, technologies have been developed that use AI to analyze high-resolution computed tomography and pathological images, and gene expression patterns in tissue taken from transbronchial lung biopsies to assist in the diagnosis of idiopathic pulmonary fibrosis. Some of these technologies are already being used in clinical practice in the United States. AI is expected to reduce the burden on physicians, improve reproducibility, and advance personalized medicine. Obtaining sufficient data for diseases with a small number of patients is difficult. Additionally, certain issues must be addressed in order for AI to be applied in healthcare. These issues include taking responsibility for the AI results output, updating software after the launch of technology, and adapting to new imaging technologies. Establishing research infrastructures such as large-scale databases and common platforms is important for the development of AI technology: their use requires an understanding of the characteristics and limitations of the systems. CLINICAL TRIAL REGISTRATION: Not applicable.

Walking the path of treatable traits in interstitial lung diseases

Interstitial lung diseases (ILDs) are complex and heterogeneous diseases. The use of traditional diagnostic classification in ILD can lead to suboptimal management, which is worsened by not considering the molecular pathways, biological complexity, and disease phenotypes. The identification of specific "treatable traits" in ILDs, which are clinically relevant and modifiable disease characteristics, may improve patient's outcomes. Treatable traits in ILDs may be classified into four different domains (pulmonary, aetiological, comorbidities, and lifestyle), which will facilitate identification of related assessment tools, treatment options, and expected benefits. A multidisciplinary care team model is a potential way to implement a "treatable traits" strategy into clinical practice with the aim of improving patients' outcomes. Multidisciplinary models of care, international registries, and the use of artificial intelligence may facilitate the implementation of the "treatable traits" approach into clinical practice. Prospective studies are needed to test potential therapies for a variety of treatable traits to further advance care of patients with ILD.

Treatable Traits in Systemic Sclerosis

Systemic sclerosis (SSc) is a chronic systemic disease within the spectrum of connective tissue diseases, specifically characterized by vascular abnormalities and inflammatory and fibrotic involvement of the skin and internal organs resulting in high morbidity and mortality. The clinical phenotype of SSc is heterogeneous, and serum autoantibodies together with the extent of skin involvement have a predictive value in the risk stratification. Current recommendations include an organ-based management according to the predominant involvement with only limited individual factors included in the treatment algorithm. Similar to what has been proposed for other chronic diseases, we hypothesize that a "treatable trait" approach based on relevant phenotypes and endotypes could address the unmet needs in SSc stratification and treatment to maximize the outcomes. We provide herein a comprehensive review and a critical discussion of the literature regarding potential treatable traits in SSc, focusing on established and candidate biomarkers, with the purpose of setting the bases for a precision medicine-based approach. The discussion, structured based on the organ involvement, allows to conjugate the pathogenetic mechanisms of tissue injury with the proposed predictors, particularly autoantibodies and other serum biomarkers. Ultimately, we are convinced that precision medicine is the ideal guide to manage a complex condition such as SSc for which available treatments are largely unsatisfactory.

Precision medicine advances in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a highly heterogeneous, unpredictable and ultimately lethal chronic lung disease. Over the last decade, two anti-fibrotic agents have been shown to slow disease progression, however, both drugs are administered uniformly with minimal consideration of disease severity and inter-individual molecular, genetic, and genomic differences. Advances in biological understanding of disease endotyping and the emergence of precision medicine have shown that "a one-size-fits-all approach" to the management of chronic lung diseases is no longer appropriate. While precision medicine approaches have revolutionized the management of other diseases such as lung cancer and asthma, the implementation of precision medicine in IPF clinical practice remains an unmet need despite several reports demonstrating a large number of diagnostic, prognostic and theragnostic biomarker candidates in IPF. This review article aims to summarize our current knowledge of precision medicine in IPF and highlight barriers to translate these research findings into clinical practice.

The Evolving Concept of the Multidisciplinary Approach in the Diagnosis and Management of Interstitial Lung Diseases

BACKGROUND

Interstitial lung diseases (ILDs) are a group of heterogeneous diseases characterized by inflammation and/or fibrosis of the lung interstitium, leading to a wide range of clinical manifestations and outcomes. Over the years, the literature has demonstrated the increased diagnostic accuracy and confidence associated with a multidisciplinary approach (MDA) in assessing diseases involving lung parenchyma. This approach was recently emphasized by the latest guidelines from the American Thoracic Society, European Respiratory Society, Japanese Respiratory Society, and Latin American Thoracic Association for the diagnosis of ILDs.

METHODS

In this review, we will discuss the role, composition, and timing of multidisciplinary diagnosis (MDD) concerning idiopathic pulmonary fibrosis, connective tissue disease associated with ILDs, hypersensitive pneumonia, and idiopathic pneumonia with autoimmune features, based on the latest recommendations for their diagnosis.

RESULTS

The integration of clinical, radiological, histopathological, and, often, serological data is crucial in the early identification and management of ILDs, improving patient outcomes. Based on the recent endorsement of transbronchial cryo-biopsy in idiopathic pulmonary fibrosis guidelines, an MDA helps guide the choice of the sampling technique, obtaining the maximum diagnostic performance, and avoiding the execution of more invasive procedures such as a surgical lung biopsy. A multidisciplinary team should include pulmonologists, radiologists, pathologists, and, often, rheumatologists, being assembled regularly to achieve a consensus diagnosis and to review cases in light of new features.

CONCLUSIONS

The literature highlighted that an MDA is essential to improve the accuracy and reliability of ILD diagnosis, allowing for the early optimization of therapy and reducing the need for invasive procedures. The multidisciplinary diagnosis of ILDs is an ongoing and dynamic process, often referred to as a "working diagnosis", involving the progressive integration and re-evaluation of clinical, radiological, and histological features.

Hypersensitivity Pneumonitis: Updates in Evaluation, Management, and Ongoing Dilemmas

Hypersensitivity pneumonitis (HP) is a heterogenous disease entity characterized by an aberrant immune response to inhalational antigens. Disease modification hinges on early antigen remediation with a goal to attenuate immune dysregulation. Disease severity and progression are mediated by an interface between degree, type and chronicity of exposure, genetic predisposition, and biochemical properties of the inducing agent. Guidelines have provided a standardized approach; however, decision-making remains with many clinical dilemmas. The delineation of fibrotic and nonfibrotic HP is crucial to identify the differences in clinical trajectories, and further clinical trials are needed to understand optimal therapeutic strategies.

Interstitial lung disease progression after genomic usual interstitial pneumonia testing

BACKGROUND

A genomic classifier for usual interstitial pneumonia (gUIP) has been shown to predict histological UIP with high specificity, increasing diagnostic confidence for idiopathic pulmonary fibrosis (IPF). Whether those with positive gUIP classification exhibit a progressive, IPF-like phenotype remains unknown.

METHODS

A pooled, retrospective analysis of patients who underwent clinically indicated diagnostic bronchoscopy with gUIP testing at seven academic medical centres across the USA was performed. We assessed the association between gUIP classification and 18-month progression-free survival (PFS) using Cox proportional hazards regression. PFS was defined as the time from gUIP testing to death from any cause, lung transplant, ≥10% relative decline in forced vital capacity (FVC) or censoring at the time of last available FVC measure. Longitudinal change in FVC was then compared between gUIP classification groups using a joint regression model.

RESULTS

Of 238 consecutive patients who underwent gUIP testing, 192 had available follow-up data and were included in the analysis, including 104 with positive gUIP classification and 88 with negative classification. In multivariable analysis, positive gUIP classification was associated with reduced PFS (hazard ratio 1.58, 95% CI 0.86-2.92; p=0.14), but this did not reach statistical significance. Mean annual change in FVC was -101.8 mL (95% CI -142.7- -60.9 mL; p<0.001) for those with positive gUIP classification and -73.2 mL (95% CI -115.2- -31.1 mL; p<0.001) for those with negative classification (difference 28.7 mL, 95% CI -83.2-25.9 mL; p=0.30).

CONCLUSIONS

gUIP classification was not associated with differential rates of PFS or longitudinal FVC decline in a multicentre interstitial lung disease cohort undergoing bronchoscopy as part of the diagnostic evaluation.

[Consensus guideline on the interdisciplinary diagnosis of interstitial lung diseases]

The evaluation of a patient with interstitial lung disease (ILD) includes assessment of clinical, radiological, and often histopathological data. As there were no specific recommendations to guide the evaluation of patients under the suspicion of an ILD within the German practice landscape, this position statement from an interdisciplinary panel of ILD experts provides guidance related to the diagnostic modalities which should be used in the evaluation of ILD. This includes clinical assessment rheumatological evaluation, radiological examinations, histopathologic sampling and the need for a final discussion in a multidisciplinary team.

Diagnosis and Pharmacologic Management of Fibrotic Interstitial Lung Disease

Interstitial lung disease is an umbrella term that encompasses a spectrum of parenchymal lung pathologies affecting the gas exchanging part of the lung. While many of these disease entities are not fibrotic in nature, a number can lead to pulmonary fibrosis which may or may not progress over time. Idiopathic pulmonary fibrosis is the prototypical, progressive fibrotic interstitial lung disease, which can lead to worsening hypoxemic respiratory failure and mortality within a number of years from the time of diagnosis. The importance of an accurate and timely diagnosis of interstitial lung diseases, which is needed to inform prognosis and guide clinical management, cannot be overemphasized. Developing a consensus diagnosis requires the incorporation of a variety of factors by a multidisciplinary team, which then may or may not determine a need for tissue sampling. Clinical management can be challenging given the heterogeneity of disease behavior and the paucity of controlled trials to guide decision making. This review addresses current paradigms and recent updates in the diagnosis and pharmacologic management of these fibrotic interstitial lung diseases.

Small-molecule-mediated OGG1 inhibition attenuates pulmonary inflammation and lung fibrosis in a murine lung fibrosis model

Interstitial lung diseases such as idiopathic pulmonary fibrosis (IPF) are caused by persistent micro-injuries to alveolar epithelial tissues accompanied by aberrant repair processes. IPF is currently treated with pirfenidone and nintedanib, compounds which slow the rate of disease progression but fail to target underlying pathophysiological mechanisms. The DNA repair protein 8-oxoguanine DNA glycosylase-1 (OGG1) has significant roles in the modulation of inflammation and metabolic syndromes. Currently, no pharmaceutical solutions targeting OGG1 have been utilized in the treatment of IPF. In this study we show Ogg1-targeting siRNA mitigates bleomycin-induced pulmonary fibrosis in male mice, highlighting OGG1 as a tractable target in lung fibrosis. The small molecule OGG1 inhibitor, TH5487, decreases myofibroblast transition and associated pro-fibrotic gene expressions in fibroblast cells. In addition, TH5487 decreases levels of pro-inflammatory mediators, inflammatory cell infiltration, and lung remodeling in a murine model of bleomycin-induced pulmonary fibrosis conducted in male C57BL6/J mice. OGG1 and SMAD7 interact to induce fibroblast proliferation and differentiation and display roles in fibrotic murine and IPF patient lung tissue. Taken together, these data suggest that TH5487 is a potentially clinically relevant treatment for IPF but further study in human trials is required.

Real-world utility of a genomic classifier in establishing a diagnosis of newly identified interstitial lung disease

BACKGROUND

Diagnosing interstitial lung disease (ILD) remains challenging. Guidelines recommend utilizing a multidisciplinary discussion (MDD) to review clinical and radiographic data and if diagnostic uncertainty persists, then to obtain histopathology. Surgical lung biopsy and transbronchial lung cryobiopsy (TBLC) are acceptable methods, but risks of complications may be prohibitive. The Envisia genomic classifier (EGC) represents another option to determine a molecular usual interstitial pneumonia (UIP) signature to facilitate an ILD diagnosis at MDD with high sensitivity and specificity. We evaluated the concordance between TBLC and EGC at MDD and the safety of this procedure.

METHODS

Demographic data, pulmonary function values, chest imaging pattern, procedural information, and MDD diagnosis were recorded. Concordance was defined as agreement between the molecular EGC results and histopathology from TBLC in the context of the patient's High Resolution CT pattern.

RESULTS

49 patients were enrolled. Imaging demonstrated a probable (n = 14) or indeterminate (n = 7) UIP pattern in 43% and an alternative pattern in 57% (n = 28). EGC results were positive for UIP in 37% (n = 18) and negative in 63% (n = 31). MDD diagnosis was obtained in 94% (n = 46) with fibrotic hypersensitivity pneumonitis (n = 17, 35%) and IPF (n = 13, 27%) most common. The concordance between EGC and TBLC at MDD was 76% (37/49) with discordant results seen in 24% (12/49) of patients.

CONCLUSIONS

There appears to be reasonable concordance between EGC and TBLC results at MDD. Efforts clarifying the contributions of these tools to an ILD diagnosis may help identify specific patient populations that may benefit from a tailored diagnostic approach.

Novel diagnostic techniques in interstitial lung disease

Research into novel diagnostic techniques and targeted therapeutics in interstitial lung disease (ILD) is moving the field toward increased precision and improved patient outcomes. An array of molecular techniques, machine learning approaches and other innovative methods including electronic nose technology and endobronchial optical coherence tomography are promising tools with potential to increase diagnostic accuracy. This review provides a comprehensive overview of the current evidence regarding evolving diagnostic methods in ILD and to consider their future role in routine clinical care.

Immune cell profiles and patient clustering in complex cases of interstitial lung disease

Interstitial lung disease comprises numerous clinical entities posing significant challenges towards a prompt and accurate diagnosis. Amongst the contributing factors are intricate pathophysiological mechanisms, an overlap between conditions, and interobserver disagreement. We developed a model for patient clustering offering an additional approach to such complex clinical cases. The model is based on surface phenotyping of over 40 markers on immune cells isolated from bronchoalveolar lavage in combination with clinical data. Based on the marker expression pattern we constructed an individual immune cell profile, then merged these to create a global profile encompassing various pathologies. The contribution of each participant to the global profile was assessed through dimensionality reduction tools and the ensuing similarity between samples was calculated. Our model enables two approaches. First, assessing the immune cell population landscape similarity between patients within a diagnostic group allows rapid identification of divergent profiles, which is particularly helpful for cases with uncertain diagnoses. Second, sample clustering is based exclusively on the calculated similarity of the immune cell profiles, thereby removing physician bias and relying on cellular nearest neighbors.

Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies

Despite its wide-ranging benefits, whole-transcriptome or RNA exome profiling is challenging to implement in a clinical diagnostic setting. The Unified Assay is a comprehensive workflow wherein exome-enriched RNA-sequencing (RNA-Seq) assays are performed on clinical samples and analyzed by a series of advanced machine learning-based classifiers. Gene expression signatures and rare and/or novel genomic events, including fusions, mitochondrial variants, and loss of heterozygosity were assessed using RNA-Seq data generated from 120,313 clinical samples across three clinical indications (thyroid cancer, lung cancer, and interstitial lung disease). Since its implementation, the data derived from the Unified Assay have allowed significantly more patients to avoid unnecessary diagnostic surgery and have played an important role in guiding follow-up decisions regarding treatment. Collectively, data from the Unified Assay show the utility of RNA-Seq and RNA expression signatures in the clinical laboratory, and their importance to the future of precision medicine.

Screening for idiopathic pulmonary fibrosis using comorbidity signatures in electronic health records

Idiopathic pulmonary fibrosis (IPF) is a lethal fibrosing interstitial lung disease with a mean survival time of less than 5 years. Nonspecific presentation, a lack of effective early screening tools, unclear pathobiology of early-stage IPF and the need for invasive and expensive procedures for diagnostic confirmation hinder early diagnosis. In this study, we introduce a new screening tool for IPF in primary care settings that requires no new laboratory tests and does not require recognition of early symptoms. Using subtle comorbidity signatures identified from the history of medical encounters of individuals, we developed an algorithm, called the zero-burden comorbidity risk score for IPF (ZCoR-IPF), to predict the future risk of an IPF diagnosis. ZCoR-IPF was trained on a national insurance claims database and validated on three independent databases, comprising a total of 2,983,215 participants, with 54,247 positive cases. The algorithm achieved positive likelihood ratios greater than 30 at a specificity of 0.99 across different cohorts, for both sexes, and for participants with different risk states and history of confounding diseases. The area under the receiver-operating characteristic curve for ZCoR-IPF in predicting IPF exceeded 0.88 and was approximately 0.84 at 1 and 4 years before a conventional diagnosis, respectively. Thus, if adopted, ZCoR-IPF can potentially enable earlier diagnosis of IPF and improve outcomes of disease-modifying therapies and other interventions.

Diagnosing interstitial lung disease by multidisciplinary discussion: A review

The multidisciplinary meeting (MDM) has been endorsed in current international consensus guidelines as the gold standard method for diagnosis of interstitial lung disease (ILD). In the absence of an accurate and reliable diagnostic test, the agreement between multidisciplinary meetings has been used as a surrogate marker for diagnostic accuracy. Although the ILD MDM has been shown to improve inter-clinician agreement on ILD diagnosis, result in a change in diagnosis in a significant proportion of patients and reduce unclassifiable diagnoses, the ideal form for an ILD MDM remains unclear, with constitution and processes of ILD MDMs varying greatly around the world. It is likely that this variation of practice contributes to the lack of agreement seen between MDMs, as well as suboptimal diagnostic accuracy. A recent Delphi study has confirmed the essential components required for the operation of an ILD MDM. The ILD MDM is a changing entity, as it incorporates new diagnostic tests and genetic markers, while also adapting in its form in response to the obstacles of the COVID-19 pandemic. The aim of this review was to evaluate the current evidence regarding ILD MDM and their role in the diagnosis of ILD, the practice of ILD MDM around the world, approaches to ILD MDM standardization and future directions to improve diagnostic accuracy in ILD.

[French practical guidelines for the diagnosis and management of IPF - 2021 update, full version]

BACKGROUND

Since the previous French guidelines were published in 2017, substantial additional knowledge about idiopathic pulmonary fibrosis has accumulated.

METHODS

Under the auspices of the French-speaking Learned Society of Pulmonology and at the initiative of the coordinating reference center, practical guidelines for treatment of rare pulmonary diseases have been established. They were elaborated by groups of writers, reviewers and coordinators with the help of the OrphaLung network, as well as pulmonologists with varying practice modalities, radiologists, pathologists, a general practitioner, a head nurse, and a patients' association. The method was developed according to rules entitled "Good clinical practice" in the overall framework of the "Guidelines for clinical practice" of the official French health authority (HAS), taking into account the results of an online vote using a Likert scale.

RESULTS

After analysis of the literature, 54 recommendations were formulated, improved, and validated by the working groups. The recommendations covered a wide-ranging aspects of the disease and its treatment: epidemiology, diagnostic modalities, quality criteria and interpretation of chest CT, indication and modalities of lung biopsy, etiologic workup, approach to familial disease entailing indications and modalities of genetic testing, evaluation of possible functional impairments and prognosis, indications for and use of antifibrotic therapy, lung transplantation, symptom management, comorbidities and complications, treatment of chronic respiratory failure, diagnosis and management of acute exacerbations of fibrosis.

CONCLUSION

These evidence-based guidelines are aimed at guiding the diagnosis and the management in clinical practice of idiopathic pulmonary fibrosis.

The role of precision medicine in interstitial lung disease

The management of interstitial lung disease (ILD) may benefit from a conceptual shift. Increased understanding of this complex and heterogeneous group of disorders over the past 20 years has highlighted the need for individualised treatment strategies that encompass diagnostic classification and disease behaviour. Biomarker-based approaches to precision medicine hold the greatest promise. Robust, large-scale biomarker-based technologies supporting ILD diagnosis have been developed, and future applications relating to staging, prognosis and assessment of treatment response are emerging. Artificial intelligence may redefine our ability to base prognostic evaluation on both diagnosis and underlying disease processes, sharpening individualised treatment algorithms to a level not previously achieved. Compared with therapeutic areas such as oncology, precision medicine in ILD is still in its infancy. However, the heterogeneous nature of ILD suggests that many relevant molecular, environmental and behavioural targets may serve as useful biomarkers if we are willing to invest in their identification and validation.

Idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis is defined as a chronic progressive fibrosing interstitial pneumonia of unknown etiology. There are intrinsic and extrinsic risk factors that could favor the development of the disease in individuals with a genetic predisposition. The diagnosis is made by characteristic radiological and/or histological findings on high-resolution computed tomography and lung biopsy, respectively, in the absence of a specific identifiable cause. The median survival of the disease for patients without treatment is 3-5years from the onset of symptoms, although its natural history is variable and unpredictable. Currently, there are two antifibrotic drugs that reduce disease progression. The multidisciplinary approach will consider the nutritional and emotional status, physical conditioning, and treatment of comorbidities, as well as lung transplantation and palliative care in advanced stages. The following article reviews the fundamental aspects for the diagnosis and treatment of idiopathic pulmonary fibrosis.

Interstitial lung disease detection using template matching combined sparse coding and blended multi class support vector machine

Interstitial lung disease (ILD), representing a collection of disorders, is considered to be the deadliest one, which increases the mortality rate of humans. In this paper, an automated scheme for detection and classification of ILD patterns is presented, which eliminates low inter-class feature variation and high intra-class feature variation in patterns, caused by translation and illumination effects. A novel and efficient feature extraction method named Template-Matching Combined Sparse Coding (TMCSC) is proposed, which extracts features invariant to translation and illumination effects, from defined regions of interest (ROI) within lung parenchyma. The translated image patch is compared with all possible templates of the image using template matching process. The corresponding sparse matrix for the set of translated image patches and their nearest template is obtained by minimizing the objective function of the similarity matrix of translated image patch and the template. A novel Blended-Multi Class Support Vector Machine (B-MCSVM) is designed for tackling high-intra class feature variation problems, which provides improved classification accuracy. Region of interests (ROIs) of five lung tissue patterns (healthy, emphysema, ground glass, micronodule, and fibrosis) selected from an internal multimedia database that contains high-resolution computed tomography (HRCT) image series are identified and utilized in this work. Performance of the proposed scheme outperforms most of the state-of-art multi-class classification algorithms.

French practical guidelines for the diagnosis and management of idiopathic pulmonary fibrosis - 2021 update. Full-length version

BACKGROUND

Since the latest 2017 French guidelines, knowledge about idiopathic pulmonary fibrosis has evolved considerably.

METHODS

Practical guidelines were drafted on the initiative of the Coordinating Reference Center for Rare Pulmonary Diseases, led by the French Language Pulmonology Society (SPLF), by a coordinating group, a writing group, and a review group, with the involvement of the entire OrphaLung network, pulmonologists practicing in various settings, radiologists, pathologists, a general practitioner, a health manager, and a patient association. The method followed the "Clinical Practice Guidelines" process of the French National Authority for Health (HAS), including an online vote using a Likert scale.

RESULTS

After a literature review, 54 guidelines were formulated, improved, and then validated by the working groups. These guidelines addressed multiple aspects of the disease: epidemiology, diagnostic procedures, quality criteria and interpretation of chest CT scans, lung biopsy indication and procedures, etiological workup, methods and indications for family screening and genetic testing, assessment of the functional impairment and prognosis, indication and use of antifibrotic agents, lung transplantation, management of symptoms, comorbidities and complications, treatment of chronic respiratory failure, diagnosis and management of acute exacerbations of fibrosis.

CONCLUSION

These evidence-based guidelines are intended to guide the diagnosis and practical management of idiopathic pulmonary fibrosis.