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Kathleen M. Capaccione Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA

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Hong Ma Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA

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Lyndon Luk Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA

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Mary M. Salvatore Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA

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Abstract

Background

The primary purpose of this study was to assess the interreader reliability of a grading system for UIP based on the quantification of normal lung. This grading system considers each of the following lung regions: right upper and middle lobes, right lower lobe, left upper lobe, and left lower lobe. Each is assigned a grade based on the following: 0: 0% normal lung; 1: 1–49% normal lung; 2: 50–74% normal lung; 3: 75–89% normal lung; 4: 90–99% normal lung; 5: 100% normal lung. The secondary purpose was to compare the grades rendered by non-cardiothoracic subspecialty trained radiologists to grades established by cardiothoracic radiologists, which were considered the gold standard.

Methods

Chest CT images of patients were obtained by searching the radiology record system for the terms “usual interstitial pneumonia” and “UIP”. Each case was confirmed by radiologist review; pathology was not assessed given the small fraction of cases that underwent biopsy due to the high risk of complications in patients with fibrotic lung disease. Two cardiothoracic radiologists evaluated each CT and reached a consensus grade. Two different radiologists who were not subspecialty trained in cardiothoracic radiology independently graded each case. Spearman correlation analysis was performed to compare the two reader's grades as well as each reader's grade independently to the gold standard score.

Results

Our analysis demonstrated a strongly positive statistically significant interreader correlation coefficient (RS) = 0.7062, P < 0.001. Our analysis of each reader compared to the gold standard demonstrated an Rs = 0.77559, P < 0.001 and an RS = 0.69958, P < 0.001 for readers 1 and 2, respectively, both representing statistically significant strongly positive correlations.

Conclusions

These results demonstrate strong interreader reproducibility and show that radiologists without subspecialty training in cardiothoracic radiology render grades that correlate strongly with those given by cardiothoracic radiologists. These findings support the use of this grading system for UIP both to monitor clinical progression and as a surrogate endpoint for antifibrotic drug trials.

Abstract

Background

The primary purpose of this study was to assess the interreader reliability of a grading system for UIP based on the quantification of normal lung. This grading system considers each of the following lung regions: right upper and middle lobes, right lower lobe, left upper lobe, and left lower lobe. Each is assigned a grade based on the following: 0: 0% normal lung; 1: 1–49% normal lung; 2: 50–74% normal lung; 3: 75–89% normal lung; 4: 90–99% normal lung; 5: 100% normal lung. The secondary purpose was to compare the grades rendered by non-cardiothoracic subspecialty trained radiologists to grades established by cardiothoracic radiologists, which were considered the gold standard.

Methods

Chest CT images of patients were obtained by searching the radiology record system for the terms “usual interstitial pneumonia” and “UIP”. Each case was confirmed by radiologist review; pathology was not assessed given the small fraction of cases that underwent biopsy due to the high risk of complications in patients with fibrotic lung disease. Two cardiothoracic radiologists evaluated each CT and reached a consensus grade. Two different radiologists who were not subspecialty trained in cardiothoracic radiology independently graded each case. Spearman correlation analysis was performed to compare the two reader's grades as well as each reader's grade independently to the gold standard score.

Results

Our analysis demonstrated a strongly positive statistically significant interreader correlation coefficient (RS) = 0.7062, P < 0.001. Our analysis of each reader compared to the gold standard demonstrated an Rs = 0.77559, P < 0.001 and an RS = 0.69958, P < 0.001 for readers 1 and 2, respectively, both representing statistically significant strongly positive correlations.

Conclusions

These results demonstrate strong interreader reproducibility and show that radiologists without subspecialty training in cardiothoracic radiology render grades that correlate strongly with those given by cardiothoracic radiologists. These findings support the use of this grading system for UIP both to monitor clinical progression and as a surrogate endpoint for antifibrotic drug trials.

Introduction

Usual interstitial pneumonia (UIP)/idiopathic pulmonary fibrosis (IFP) is a devastating pulmonary disease with relentless progression and mortality outcomes comparable to lung cancer [1]. It is one of over one hundred diseases that fall under the umbrella of interstitial lung disease, diseases that have varying known and unknown etiologies but progress down a final common pathway of pulmonary parenchymal scarring which ultimately results in decreased oxygen exchange and respiratory insufficiency [2–4]. Other common types of interstitial lung disease include nonspecific interstitial pneumonia (NSIP) and chronic hypersensitivity pneumonitis (CHP) [5]. Assessing progression of UIP/IPF is an important part of disease management because change over time has prognostic value and may trigger changes in treatment strategy.

Given the poor outcomes for patients with UIP/IPF, there have been extensive efforts to develop and test antifibrotic agents to slow or ideally arrest the progression of the disease. Two antifibrotic agents have been approved clinically to slow the progression of UIP, pirfenidone and nintedanib [6–9]. Numerous agents are in various stages of preclinical development, including phosphodiesterase inhibitor BI1015550 [10] and pamrevlumab, a first-in-class anti-connective tissue growth factor (CTGF) antibody [11]. These and other agents have the potential to transform the treatment landscape for patients with UIP/IPF. However, the establishment of clinically meaningful surrogate endpoints for pulmonary fibrosis drug trials has been a significant challenge to the field.

The diagnosis of UIP is made radiographically by the presence of specific radiographic features. According to an official ATS/ERS/JRS/ALAT clinical practice guideline, the diagnosis of UIP is made with the findings of basilar predominant subpleural reticulation, traction bronchiectasis and/or bronchiolectasis, and honeycombing. In the absence of honeycombing, the pattern is called “probable UIP” [1213]. A subsequent statement defined that progressive pulmonary fibrosis can be diagnosed when at least two of the following three criteria are met: worsening symptoms, radiological progression, and physiological progression [14]. Therefore, the ability to accurately diagnose radiological progression has significant implications for patient care.

We have previously developed a grading system for UIP based on the quantity of remaining normal lung and validated that it correlates with PFTs [15] (Fig. 1). This grading system considers two regions: “normal lung”, and “pathologically affected lung”, which can include regions of fibrosis, ground glass, mosaic attenuation, consolidation, emphysematous change, cysts, and other lung parenchymal abnormalities. The reasoning for this is that pathologically affected lung from any causes will result in diminution of pulmonary function, therefore the overall lung score should reflect the amount of healthy lung. We demonstrated that this grading system correlates with patient mortality [16]. Our system has several advantages: 1) CT imaging is highly reproducible and is not patient or operator dependent; 2) it is based on quantitating normal lung, which is similar to the way that PFTs are reported; 3) it can account for multiple lung diseases that occur concurrently; 4) it does not require special software or machines as do some of the other proposed UIP grading systems [17–19].

Fig. 1.
Fig. 1.

Demonstrates representative examples of each grade in our system: (A) Grade 0, (B) Grade 1, (C) Grade 2, (D) Grade 3, (E) Grade 4, (F) Grade 5

Citation: Imaging 16, 1; 10.1556/1647.2024.00190

An outstanding question in our prior work was the degree of reproducibility of our system by radiologists who were not subspecialty trained in cardiothoracic radiology, as were the readers in prior studies. Given the significant amount of medical care occurs outside of the subspecialty setting, in order for a system to reach widespread adoption, it is important that a grading system be reproducible by general radiologists. We hypothesized that our system would be reproducible by non-cardiothoracic fellowship trained radiologists, and tested this hypothesis by evaluating the correlation of the CT grades of patients with UIP on chest CT rendered by these radiologists compared to grades established by cardiothoracic radiologists. Demonstration of a strong correlation would validate the widespread use of this system by general radiologists and those trained in other subspecialties.

Patients and methods

Grading system

We employed the grading system for normal lung as previously published [15]. Briefly, the system considers 4 regions (right upper and middle, right lower, left upper, left lower) and gives an individual grade based on percentage of normal lung. Percentage scores are as follows: 0: 0% normal lung; 1: 1–49% normal lung; 2: 50–74% normal lung; 3: 75–89% normal lung; 4: 90–99% normal lung; 5: 100% normal lung. Scores were summed to generate a single score representing total amount of normal lung.

CT scans used for grading

This study was conducted under Columbia University IRB-approved HIPAA-compliant protocol (AAAT6351, approved 03/31/2021). The requirement for consent was waived given the retrospective nature of this study. CT scans used for grading in this study were obtained by searching the radiology record system MModal for the search terms “UIP” and “usual interstitial pneumonia”. This cohort was used previously to assess mortality, and inclusion criteria were patients that were deceased at the time of review and had a date of death could be identified. The first 100 patients by serial medical record number were reviewed and ultimately 94 met inclusion criteria. CT scans analyzed in this study were performed on a variety of different machines both within our department and on scanners at outside hospitals brought to our institution for review. The parameters were variable mimicking real life conditions. A minimum of 5 mm slices were used for image review, and in the majority of cases image slice thickeness of 1.25 mm was available and used for review.

CT grading

All studies were initially reviewed by two cardiothoracic radiologists (M.M.S and K.M.C) with 28- and 6-years experience, respectively. CT grade for each lobe was obtained by consensus. Readers were blinded to all other clinical and mortality data during the time of CT review.

All cases were subsequently reviewed and graded independently by two radiologists who were not subspecialty trained in cardiothoracic radiology (H.M. and L.L.), with 11- and 9- years' experience, respectively. Both were subspecialty trained in abdominal imaging and had general radiology experience reading cross sectional imaging including cardiothoracic studies, however received no additional training in this grading system beyond a general introduction, as explained in the introduction of this manuscript. Readers scored each of the four regions as described above to generate a composite score.

Statistical analysis

Statistical analysis was performed using Spearman correlation using an online calculator [20]. First, correlation was performed between the two readers to establish the inter-reader reproducibility of the grading system score. Subsequently, each reader's score was correlated to the scores established by the cardiothoracic trained radiologists who developed the system, which was taken as the gold standard grade. For all analyses, a two-tailed p value less than or equal to 0.05 was considered significant.

Results

Radiologists display strong interreader reliability using this grading system

We first sought to evaluate the interreader reproducibility of our grading system. Results of the two readers' grades were analyzed using Spearman correlation to assess for the degree of interreader reliability as measured by correlation coefficient. The interreader correlation coefficient (RS) = 0.7062, P < 0.001 representing a statistically significant strong positive correlation (Fig. 2). A small number of outliers were present, for example a single case rated by one reader as 20 and the second reader as 6. Similarly, when evaluating the reader's grades compared to the established gold standard, a small number of outliers were present in each case. These were included in the comparison because there was no systematic disagreement among readers, and occasional disagreement in final reports closely mirrors the real practice setting. Despite these few outliers, correlations were strong between readers and between each reader and the gold standard.

Fig. 2.
Fig. 2.

Demonstrates the interreader reliability of the grading system, with a strong positive correlation, (RS) = 0.7062, P < 0.001

Citation: Imaging 16, 1; 10.1556/1647.2024.00190

Non-subspecialty trained radiologists demonstrate strong correlation with gold standard grading performed by cardiothoracic radiologists

We next sought to determine whether the grades rendered by radiologists not subspecialty-trained in cardiothoracic radiology were comparable to those given by cardiothoracic radiologists, which were considered the gold standard for this study. We performed Spearman correlation analysis between the gold standard cardiothoracic radiologist consensus score and the scores from each of the readers. Our analysis demonstrated an Rs = 0.77559, P < 0.001 and RS = 0.69958, P < 0.001 for readers 1 and 2, respectively, both representing strong positive correlations (Fig. 3).

Fig. 3.
Fig. 3.

Demonstrates the correlation of individual readers compared to the gold standard score established by consensus agreement of two cardiothoracic radiologists in (A) and (B) for readers 1 and 2, respectively

Citation: Imaging 16, 1; 10.1556/1647.2024.00190

Discussion

The development of a reproducible grading system to monitor radiologic progression of UIP/IPF represents a major advance both for clinical decision making and use in clinical trials. Here, we demonstrate that our grading system is highly reproducible by radiologists who are not subspecialty trained in cardiothoracic radiology. The results support the use of this system to monitor clinical progression as well as in clinical trials given that it provides a quantitative measure that is neither patient nor operator dependent, and is highly reproducible among readers.

While other groups have tried to develop grading systems for interstitial lung disease, many of them involve artificial intelligence and the use of complex computer systems [17–19]. These software programs may be unavailable to many clinicians limiting their utility particularly in the context of general radiology settings. An advantage of this highly reproducible system is that it does not require any special programs or systems and could be implemented across medical systems to standardize the assessment of progression of pulmonary fibrosis. Many patients who are ultimately diagnosed with UIP/IPF are initially treated in the community setting and are eventually referred to a center of excellence for management of their fibrotic lung disease. Use of this quantitative grade could help them transition from one practice setting to the other with quantitative radiologic data so that the monitoring of their disease would be continuous.

Establishing surrogate endpoints in clinical trials for pulmonary fibrosis is important to drive forward the development of new antifibrotic agents [21, 22]. Given the high reproducibility of this system demonstrated herein, in conjunction with its correlation with gold standard mortality [16] and PFTs [15], this grading system is an excellent candidate. We propose its incorporation into clinical trials monitoring followed by comparison with current standard of care endpoints to prove its utility in this context.

Limitations of this study included that all of the cases were drawn from a single institution, which was a tertiary care center with extensive expertise in interstitial lung disease. Although the readers were not subspecialty trained in cardiothoracic radiology, they had exposure to a greater number of cases of interstitial lung disease than a radiologist in general practice. The “gold standard” grade was established by consensus of two cardiothoracic radiologists. The use of a computerized method to generate a score could potentially have resulted in a more standardized measure. Finally, the additional inclusion of a non-radiologist with clinical expertise in interstitial lung disease as a reader may have demonstrated even more expanded reproducibility of this system if results were concordant with the gold standard reads, however such a reader was not included at this time. Despite these limitations, these data establish this grading system based on radiologic quantification of normal lung as highly reproducible among radiologists without cardiothoracic radiology subspecialty training.

Conclusion

Here, we validate the interreader reproducibly of this grading system for normal lung, as well as demonstrate that there is strong correlation between individual readers and the gold standard grades. This provides support for the use of this system as a surrogate endpoint in clinical trials and as a clinical metric to follow progression of UIP/IFP over time.

Authors' contributions

Conceptualization: KMC, MMS; Data collection: KMC, HYM, LL, MMS; Data analysis: KMC; Manuscript-writing: KMC; Manuscript-editing: KMC, HYM, LL, MMS. All authors reviewed the final version of the manuscript and agreed to submit it to IMAGING for publication.

Funding sources

No financial support was received for this study.

Conflict of interest

Dr. Mary Salvatore has received grant support from Boehringer Ingelheim and Genentech and has served as a consultant for AbbVie, Bioclinica, and LungLife AI. Dr. Capaccione has served as an advisor for Cardinal Health. The remaining authors have no conflicts of interest to disclose.

Ethical statement

This work was conducted under an IRB-approved, HIPAA-compliant protocol (Columbia University, AAAS1829) to study patients with pulmonary fibrosis.

References

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    Plönes T, Osei-Agyemang T, Elze M, Palade E, Wagnetz D, Loop T, et al.: Morbidity and mortality in patients with usual interstitial pneumonia (UIP) pattern undergoing surgery for lung biopsy. Respir Med 2013; 107: 629632.

    • Search Google Scholar
    • Export Citation
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    Wallis A, Spinks K: The diagnosis and management of interstitial lung diseases. BMJ : British Medical Journal 2015; 350: h2072.

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    Fainberg HP, Oldham JM, Molyneaux PL, Allen RJ, Kraven LM, Fahy WA, et al.: Forced vital capacity trajectories in patients with idiopathic pulmonary fibrosis: A secondary analysis of a multicentre, prospective, observational cohort. The Lancet Digital Health 2022; 4: e862e72.

    • Search Google Scholar
    • Export Citation
  • [4]

    Schott CA, Ascoli C, Huang Y, Perkins DL, Finn PW: Declining pulmonary function in interstitial lung disease Linked to lymphocyte dysfunction. American Journal of Respiratory and Critical Care Medicine 2020; 201: 610-613.

    • Search Google Scholar
    • Export Citation
  • [5]

    Salvatore M, Henschke CI, Yip R, Jacobi A, Eber C, Padilla M, et al.: Journal club: evidence of interstitial lung disease on low-dose chest CT images: prevalence, patterns, and progression. AJR Am J Roentgenol 2016; 206: 487494.

    • Search Google Scholar
    • Export Citation
  • [6]

    Richeldi L, du Bois RM, Raghu G, Azuma A, Brown KK, Costabel U, et al.: Efficacy and safety of nintedanib in idiopathic pulmonary fibrosis. New England Journal of Medicine 2014; 370: 20712082.

    • Search Google Scholar
    • Export Citation
  • [7]

    Lancaster L, Crestani B, Hernandez P, Inoue Y, Wachtlin D, Loaiza L, et al.: Safety and survival data in patients with idiopathic pulmonary fibrosis treated with nintedanib: Pooled data from six clinical trials. BMJ Open Respiratory Research 2019; 6: e000397.

    • Search Google Scholar
    • Export Citation
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    Noble PW, Albera C, Bradford WZ, Costabel U, Glassberg MK, Kardatzke D, et al.: Pirfenidone in patients with idiopathic pulmonary fibrosis (CAPACITY): Two randomised trials. Lancet 2011; 377: 17601769.

    • Search Google Scholar
    • Export Citation
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    Taniguchi H, Ebina M, Kondoh Y, Ogura T, Azuma A, Suga M, et al.: Pirfenidone in idiopathic pulmonary fibrosis. European Respiratory Journal 2010; 35: 821829.

    • Search Google Scholar
    • Export Citation
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    Richeldi L, Azuma A, Cottin V, Hesslinger C, Stowasser S, Valenzuela C, et al.: Trial of a preferential phosphodiesterase 4B inhibitor for idiopathic pulmonary fibrosis. New England Journal of Medicine 2022; 386: 21782187.

    • Search Google Scholar
    • Export Citation
  • [11]

    Richeldi L, Fernández Pérez ER, Costabel U, Albera C, Lederer DJ, Flaherty KR, et al.: Pamrevlumab, an anti-connective tissue growth factor therapy, for idiopathic pulmonary fibrosis (PRAISE): A phase 2, randomised, double-blind, placebo-controlled trial. The Lancet Respiratory Medicine 2020; 8: 2533.

    • Search Google Scholar
    • Export Citation
  • [12]

    Raghu G, Collard HR, Egan JJ, Martinez FJ, Behr J, Brown KK, et al.: An official ATS/ERS/JRS/ALAT statement: Idiopathic pulmonary fibrosis: Evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med 2011; 183: 788824.

    • Search Google Scholar
    • Export Citation
  • [13]

    Raghu G, Remy-Jardin M, Myers JL, Richeldi L, Ryerson CJ, Lederer DJ, et al.: Diagnosis of idiopathic pulmonary fibrosis. An official ATS/ERS/JRS/ALAT clinical practice guideline. American Journal of Respiratory and Critical Care Medicine 2018; 198: e44e68.

    • Search Google Scholar
    • Export Citation
  • [14]

    Raghu G, Remy-Jardin M, Richeldi L, Thomson CC, Inoue Y, Johkoh T, et al.: Idiopathic pulmonary fibrosis (an update) and progressive pulmonary fibrosis in adults: an official ATS/ERS/JRS/ALAT clinical practice guideline. American Journal of Respiratory and Critical Care Medicine 2022; 205: e18e47.

    • Search Google Scholar
    • Export Citation
  • [15]

    Capaccione KM, Wang A, Lee SM, Patel N, Austin JHM, Maino P, et al.: Quantifying normal lung in pulmonary fibrosis: CT analysis and correlation with %DLCO. Clin Imaging 2021; 77: 287290.

    • Search Google Scholar
    • Export Citation
  • [16]

    Capaccione KM, Salvatore MM: Radiographic grading system for usual interstitial pneumonia correlates with mortality and may serve as a surrogate endpoint in clinical trials. Clinical Imaging 2023; 102: 3741.

    • Search Google Scholar
    • Export Citation
  • [17]

    Rosas IO, Yao J, Avila NA, Chow CK, Gahl WA, Gochuico BR: Automated quantification of high-resolution CT scan findings in individuals at risk for pulmonary fibrosis. Chest 2011; 140: 15901597.

    • Search Google Scholar
    • Export Citation
  • [18]

    Maldonado F, Moua T, Rajagopalan S, Karwoski RA, Raghunath S, Decker PA, et al.: Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis. Eur Respir J 2014; 43: 204212.

    • Search Google Scholar
    • Export Citation
  • [19]

    Kim HJ, Brown MS, Elashoff R, Li G, Gjertson DW, Lynch DA, et al.: Quantitative texture-based assessment of one-year changes in fibrotic reticular patterns on HRCT in scleroderma lung disease treated with oral cyclophosphamide. Eur Radiol 2011; 21: 24552465.

    • Search Google Scholar
    • Export Citation
  • [21]

    Raghu G, Collard HR, Anstrom KJ, Flaherty KR, Fleming TR, King TE, Jr., et al.: Idiopathic pulmonary fibrosis: Clinically meaningful primary endpoints in phase 3 clinical trials. Am J Respir Crit Care Med 2012; 185: 10441048.

    • Search Google Scholar
    • Export Citation
  • [22]

    Aronson JK: Biomarkers and surrogate endpoints. Br J Clin Pharmacol 2005; 59: 491494.

  • [1]

    Plönes T, Osei-Agyemang T, Elze M, Palade E, Wagnetz D, Loop T, et al.: Morbidity and mortality in patients with usual interstitial pneumonia (UIP) pattern undergoing surgery for lung biopsy. Respir Med 2013; 107: 629632.

    • Search Google Scholar
    • Export Citation
  • [2]

    Wallis A, Spinks K: The diagnosis and management of interstitial lung diseases. BMJ : British Medical Journal 2015; 350: h2072.

  • [3]

    Fainberg HP, Oldham JM, Molyneaux PL, Allen RJ, Kraven LM, Fahy WA, et al.: Forced vital capacity trajectories in patients with idiopathic pulmonary fibrosis: A secondary analysis of a multicentre, prospective, observational cohort. The Lancet Digital Health 2022; 4: e862e72.

    • Search Google Scholar
    • Export Citation
  • [4]

    Schott CA, Ascoli C, Huang Y, Perkins DL, Finn PW: Declining pulmonary function in interstitial lung disease Linked to lymphocyte dysfunction. American Journal of Respiratory and Critical Care Medicine 2020; 201: 610-613.

    • Search Google Scholar
    • Export Citation
  • [5]

    Salvatore M, Henschke CI, Yip R, Jacobi A, Eber C, Padilla M, et al.: Journal club: evidence of interstitial lung disease on low-dose chest CT images: prevalence, patterns, and progression. AJR Am J Roentgenol 2016; 206: 487494.

    • Search Google Scholar
    • Export Citation
  • [6]

    Richeldi L, du Bois RM, Raghu G, Azuma A, Brown KK, Costabel U, et al.: Efficacy and safety of nintedanib in idiopathic pulmonary fibrosis. New England Journal of Medicine 2014; 370: 20712082.

    • Search Google Scholar
    • Export Citation
  • [7]

    Lancaster L, Crestani B, Hernandez P, Inoue Y, Wachtlin D, Loaiza L, et al.: Safety and survival data in patients with idiopathic pulmonary fibrosis treated with nintedanib: Pooled data from six clinical trials. BMJ Open Respiratory Research 2019; 6: e000397.

    • Search Google Scholar
    • Export Citation
  • [8]

    Noble PW, Albera C, Bradford WZ, Costabel U, Glassberg MK, Kardatzke D, et al.: Pirfenidone in patients with idiopathic pulmonary fibrosis (CAPACITY): Two randomised trials. Lancet 2011; 377: 17601769.

    • Search Google Scholar
    • Export Citation
  • [9]

    Taniguchi H, Ebina M, Kondoh Y, Ogura T, Azuma A, Suga M, et al.: Pirfenidone in idiopathic pulmonary fibrosis. European Respiratory Journal 2010; 35: 821829.

    • Search Google Scholar
    • Export Citation
  • [10]

    Richeldi L, Azuma A, Cottin V, Hesslinger C, Stowasser S, Valenzuela C, et al.: Trial of a preferential phosphodiesterase 4B inhibitor for idiopathic pulmonary fibrosis. New England Journal of Medicine 2022; 386: 21782187.

    • Search Google Scholar
    • Export Citation
  • [11]

    Richeldi L, Fernández Pérez ER, Costabel U, Albera C, Lederer DJ, Flaherty KR, et al.: Pamrevlumab, an anti-connective tissue growth factor therapy, for idiopathic pulmonary fibrosis (PRAISE): A phase 2, randomised, double-blind, placebo-controlled trial. The Lancet Respiratory Medicine 2020; 8: 2533.

    • Search Google Scholar
    • Export Citation
  • [12]

    Raghu G, Collard HR, Egan JJ, Martinez FJ, Behr J, Brown KK, et al.: An official ATS/ERS/JRS/ALAT statement: Idiopathic pulmonary fibrosis: Evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med 2011; 183: 788824.

    • Search Google Scholar
    • Export Citation
  • [13]

    Raghu G, Remy-Jardin M, Myers JL, Richeldi L, Ryerson CJ, Lederer DJ, et al.: Diagnosis of idiopathic pulmonary fibrosis. An official ATS/ERS/JRS/ALAT clinical practice guideline. American Journal of Respiratory and Critical Care Medicine 2018; 198: e44e68.

    • Search Google Scholar
    • Export Citation
  • [14]

    Raghu G, Remy-Jardin M, Richeldi L, Thomson CC, Inoue Y, Johkoh T, et al.: Idiopathic pulmonary fibrosis (an update) and progressive pulmonary fibrosis in adults: an official ATS/ERS/JRS/ALAT clinical practice guideline. American Journal of Respiratory and Critical Care Medicine 2022; 205: e18e47.

    • Search Google Scholar
    • Export Citation
  • [15]

    Capaccione KM, Wang A, Lee SM, Patel N, Austin JHM, Maino P, et al.: Quantifying normal lung in pulmonary fibrosis: CT analysis and correlation with %DLCO. Clin Imaging 2021; 77: 287290.

    • Search Google Scholar
    • Export Citation
  • [16]

    Capaccione KM, Salvatore MM: Radiographic grading system for usual interstitial pneumonia correlates with mortality and may serve as a surrogate endpoint in clinical trials. Clinical Imaging 2023; 102: 3741.

    • Search Google Scholar
    • Export Citation
  • [17]

    Rosas IO, Yao J, Avila NA, Chow CK, Gahl WA, Gochuico BR: Automated quantification of high-resolution CT scan findings in individuals at risk for pulmonary fibrosis. Chest 2011; 140: 15901597.

    • Search Google Scholar
    • Export Citation
  • [18]

    Maldonado F, Moua T, Rajagopalan S, Karwoski RA, Raghunath S, Decker PA, et al.: Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis. Eur Respir J 2014; 43: 204212.

    • Search Google Scholar
    • Export Citation
  • [19]

    Kim HJ, Brown MS, Elashoff R, Li G, Gjertson DW, Lynch DA, et al.: Quantitative texture-based assessment of one-year changes in fibrotic reticular patterns on HRCT in scleroderma lung disease treated with oral cyclophosphamide. Eur Radiol 2011; 21: 24552465.

    • Search Google Scholar
    • Export Citation
  • [21]

    Raghu G, Collard HR, Anstrom KJ, Flaherty KR, Fleming TR, King TE, Jr., et al.: Idiopathic pulmonary fibrosis: Clinically meaningful primary endpoints in phase 3 clinical trials. Am J Respir Crit Care Med 2012; 185: 10441048.

    • Search Google Scholar
    • Export Citation
  • [22]

    Aronson JK: Biomarkers and surrogate endpoints. Br J Clin Pharmacol 2005; 59: 491494.

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Chair of the Editorial Board:
Béla MERKELY (Semmelweis University, Budapest, Hungary)

Editor-in-Chief:
Pál MAUROVICH-HORVAT (Semmelweis University, Budapest, Hungary)

Deputy Editor-in-Chief:
Viktor BÉRCZI (Semmelweis University, Budapest, Hungary)

Executive Editor:
Charles S. WHITE (University of Maryland, USA)

Deputy Editors:
Gianluca PONTONE (Department of Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy)
Michelle WILLIAMS (University of Edinburgh, UK)

Senior Associate Editors:
Tamás Zsigmond KINCSES (University of Szeged, Hungary)
Hildo LAMB (Leiden University, The Netherlands)
Denisa MURARU (Istituto Auxologico Italiano, IRCCS, Milan, Italy)
Ronak RAJANI (Guy’s and St Thomas’ NHS Foundation Trust, London, UK)

Associate Editors:
Andrea BAGGIANO (Department of Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy)
Fabian BAMBERG (Department of Radiology, University Hospital Freiburg, Germany)
Péter BARSI (Semmelweis University, Budapest, Hungary)
Theodora BENEDEK (University of Medicine, Pharmacy, Sciences and Technology, Targu Mures, Romania)
Ronny BÜCHEL (University Hospital Zürich, Switzerland)
Filippo CADEMARTIRI (SDN IRCCS, Naples, Italy) Matteo CAMELI (University of Siena, Italy)
Csilla CELENG (University of Utrecht, The Netherlands)
Edit DÓSA (Semmelweis University, Budapest, Hungary)
Marco FRANCONE (La Sapienza University of Rome, Italy)
Viktor GÁL (OrthoPred Ltd., Győr, Hungary)
Alessia GIMELLI (Fondazione Toscana Gabriele Monasterio, Pisa, Italy)
Tamás GYÖRKE (Semmelweis Unversity, Budapest)
Fabian HYAFIL (European Hospital Georges Pompidou, Paris, France)
György JERMENDY (Bajcsy-Zsilinszky Hospital, Budapest, Hungary)
Pál KAPOSI (Semmelweis University, Budapest, Hungary)
Mihaly KÁROLYI (University of Zürich, Switzerland)
Lajos KOZÁK (Semmelweis University, Budapest, Hungary)
Mariusz KRUK (Institute of Cardiology, Warsaw, Poland)
Zsuzsa LÉNARD (Semmelweis University, Budapest, Hungary)
Erica MAFFEI (ASUR Marche, Urbino, Marche, Italy)
Robert MANKA (University Hospital, Zürich, Switzerland)
Saima MUSHTAQ (Cardiology Center Monzino (IRCCS), Milan, Italy)
Gábor RUDAS (Semmelweis University, Budapest, Hungary)
Balázs RUZSICS (Royal Liverpool and Broadgreen University Hospital, UK)
Christopher L SCHLETT (Unievrsity Hospital Freiburg, Germany)
Bálint SZILVESZTER (Semmelweis University, Budapest, Hungary)
Richard TAKX (University Medical Centre, Utrecht, The Netherlands)
Ádám TÁRNOKI (National Institute of Oncology, Budapest, Hungary)
Dávid TÁRNOKI (National Institute of Oncology, Budapest, Hungary)
Ákos VARGA-SZEMES (Medical University of South Carolina, USA)
Hajnalka VÁGÓ (Semmelweis University, Budapest, Hungary)
Jiayin ZHANG (Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China)

International Editorial Board:

Gergely ÁGOSTON (University of Szeged, Hungary)
Anna BARITUSSIO (University of Padova, Italy)
Bostjan BERLOT (University Medical Centre, Ljubljana, Slovenia)
Edoardo CONTE (Centro Cardiologico Monzino IRCCS, Milan)
Réka FALUDI (University of Szeged, Hungary)
Andrea Igoren GUARICCI (University of Bari, Italy)
Marco GUGLIELMO (Department of Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy)
Kristóf HISRCHBERG (University of Heidelberg, Germany)
Dénes HORVÁTHY (Semmelweis University, Budapest, Hungary)
Julia KARADY (Harvard Unversity, MA, USA)
Attila KOVÁCS (Semmelweis University, Budapest, Hungary)
Riccardo LIGA (Cardiothoracic and Vascular Department, Università di Pisa, Pisa, Italy)
Máté MAGYAR (Semmelweis University, Budapest, Hungary)
Giuseppe MUSCOGIURI (Centro Cardiologico Monzino IRCCS, Milan, Italy)
Anikó I NAGY (Semmelweis University, Budapest, Hungary)
Liliána SZABÓ (Semmelweis University, Budapest, Hungary)
Özge TOK (Memorial Bahcelievler Hospital, Istanbul, Turkey)
Márton TOKODI (Semmelweis University, Budapest, Hungary)

Managing Editor:
Anikó HEGEDÜS (Semmelweis University, Budapest, Hungary)

Pál Maurovich-Horvat, MD, PhD, MPH, Editor-in-Chief

Semmelweis University, Medical Imaging Centre
2 Korányi Sándor utca, Budapest, H-1083, Hungary
Tel: +36-20-663-2485
E-mail: maurovich-horvat.pal@med.semmelweis-univ.hu

Indexing and Abstracting Services:

  • WoS Emerging Science Citation Index
  • Scopus
  • DOAJ

2023  
Web of Science  
Journal Impact Factor 0.7
Rank by Impact Factor Q3 (Medicine, General & Internal)
Journal Citation Indicator 0.09
Scopus  
CiteScore 0.7
CiteScore rank Q4 (Medicine miscellaneous)
SNIP 0.151
Scimago  
SJR index 0.181
SJR Q rank Q4

Imaging
Publication Model Gold Open Access
Submission Fee none
Article Processing Charge none
Subscription Information Gold Open Access

Imaging
Language English
Size A4
Year of
Foundation
2020 (2009)
Volumes
per Year
1
Issues
per Year
2
Founder Akadémiai Kiadó
Founder's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2732-0960 (Online)

Monthly Content Usage

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Jun 2024 0 87 11
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