Imaging: how to recognise idiopathic pulmonary fibrosis

Devaraj, Anand

doi:10.1183/09059180.00001514

Cited by 42 publications

(33 citation statements)

References 13 publications

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“…Non-invasive imaging techniques remain unable to fully characterise the nature of fibrosis in the lung [8] and particularly the heart [9], resulting in a reliance upon ex vivo studies [10,11]. This has motivated in silico investigations, seeking to explain both the creation of different fibrotic patternings [12] and in the case of cardiac fibrosis, its pro-arrhythmic consequences [13,14,15,16,17].…”

Section: Introductionmentioning

confidence: 99%

Perlin Noise Generation of Physiologically Realistic Patterns of Fibrosis

Bueno‐Orovio

2019

Preprint

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Fibrosis, the pathological excess of fibroblast activity, is a significant health issue that hinders the function of many organs in the body, in some cases fatally. However, the severity of fibrosis-derived conditions depends on both the positioning of fibrotic affliction, and the microscopic patterning of fibroblast-deposited matrix proteins within afflicted regions. Variability in an individual's manifestation of a type of fibrosis is an important factor in explaining differences in symptoms, optimum treatment and prognosis, but a need for ex vivo procedures and a lack of experimental control over conflating factors has meant this variability remains poorly understood. In this work, we present a computational methodology for the generation of patterns of fibrosis microstructure, demonstrating the technique using histological images of four types of cardiac fibrosis. Our generator and automated tuning method prove flexible enough to capture each of these very distinct patterns, allowing for rapid generation of new realisations for high-throughput computational studies. We also demonstrate via simulation, using the generated fibrotic patterns, the importance of microscale variability by showing significant differences in electrophysiological impact even within a single class of fibrosis.

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Section: Introductionmentioning

confidence: 99%

Perlin Noise Generation of Physiologically Realistic Patterns of Fibrosis

Bueno‐Orovio

2019

Preprint

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“…With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in the reduced HRCT compared to standard HRCT. This finding may have been caused by the use of the small limited number of thin sliced sequential CT images, as even on standard HRCT the distinguishing of cystic change as honeycombing from bronchiectasis can be difficult (42). Since it is known that traction bronchiectasis is commonly associated with advanced fibrotic changes (43,44) and correlates with the amount of fibrosis (45), it can be assumed, that its detection rate may not influence the overall fibrosis assessment compared to other findings of advanced fibrosis such as honeycombing, coarse reticular pattern, and architectural distortion (43,44).…”

Section: Discussionmentioning

confidence: 97%

The impact of slice-reduced computed tomography on histogram-based densitometry assessment of lung fibrosis in patients with systemic sclerosis

Nguyen-Kim¹,

Maurer²,

Suliman³

et al. 2018

J. Thorac. Dis.

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Background: To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. Methods: From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. Results: With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051-0.073). All scores correlated significantly (P<0.001) to histogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both P<0.001). In contrast to standard HRCT histogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both P<0.001). Conclusions: Reduced HRCT is a robust method to assess lung fibrosis in SSc with minimal radiation dose with no difference in scoring assessment of lung fibrosis severity and extension in comparison to standard HRCT.In contrast to standard HRCT histogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients.Keywords: Interstitial lung disease (ILD); reduced high-resolution computed tomography of the lung (reduced HRCT of the lung); histogram parameters from reduced high-resolution computed tomography (histogram parameters from reduced HRCT); systemic sclerosis (SSc)

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“…Honeycombing, a common feature of IPF seen on HRCT, is crucial for an accurate diagnosis. Unfortunately, identification of honeycombing is not always straight forward, and there is some disagreement regarding its imaging features [5]. In the comorbidity was malignancy (10.8%) in patients with IPF and lung cancer with IPF was shown in Figure 7.…”

Section: Discussionmentioning

confidence: 99%

Giraffe Patterns in Idiopathic Pulmonary Fibrosis

Dirican¹,

Yildiz²,

Zorlu³

et al. 2020

Int J Respir Pulm Med

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Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung disease characterized by severe fibrosis and poor prognosis. We aimed to reveal to different radiological findings of IPF and to describe a different perspective on the complexity of diagnosis. We retrospectively evaluated patients with IPF between January 2015 and April 2019 in the Department of Pulmonary Medicine, VM Medical park Samsun Hospital, Samsun, Turkey. Totally 51 patients were included in this study; 35 (68.6%) were male and 16 (31.4%) were female. The mean age was 70.8 years (min, 50-max, 86). The mean FVC, FEV1 and FEV1/FVC were 1970 ml (53%), 1860 ml (63%) and 94.4%, respectively. The diagnostic efficacy of chest roentgenograph was 58.7% in patients with IPF. The number of cases with "propeller blade" distribution (PBD) (Figure 1 and Figure 2) was 32 (62.7%). The acute attack of IPF was observed in 10 (19.6%) patients. In conclusion; it should be kept in mind that the difference in HRCT findings in the diagnosis of IPF may vary depending on the environment in which patients live. Also, we think that the external environment affects not only the diagnosis, but also the course of the disease and the acute attack and it should be supported by other studies.

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Imaging: how to recognise idiopathic pulmonary fibrosis

Cited by 42 publications

References 13 publications

Perlin Noise Generation of Physiologically Realistic Patterns of Fibrosis

Perlin Noise Generation of Physiologically Realistic Patterns of Fibrosis

The impact of slice-reduced computed tomography on histogram-based densitometry assessment of lung fibrosis in patients with systemic sclerosis

Giraffe Patterns in Idiopathic Pulmonary Fibrosis

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