Assessment of Prognosis of Patients With Idiopathic Pulmonary Fibrosis by Computer-aided Analysis of CT Images

Iwasawa, Tae; Asakura, Akira; Sakai, Fumikazu; Kanauchi, Tetu; Gotoh, Toshiyuki; Ogura, Takashi; Yazawa, Takuya; Nishimura, Jun-ichi; Inoue, Tomio

doi:10.1097/rti.0b013e3181a6527d

Cited by 56 publications

(45 citation statements)

References 18 publications

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“…Correlation of quantitative estimates of pulmonary fibrosis by automated analysis to mortality has been the object of few reports [1,18,19]. This line of research has been hampered by the lack of validation methodology and poor access to high-quality HRCT allowing for volumetric assessment of the lung parenchyma.…”

Section: Discussionmentioning

confidence: 99%

“…An accurate and reproducible method allowing monitoring of fibrosis progression on HRCT would be a valuable surrogate marker of disease. Unfortunately, assessment of fibrosis volumes by expert radiologists has been hampered by substantial intra-and interobserver variability, and quantitative CT indices using fractal analysis and global histogram-based methods have not been validated or found helpful in clinical practice thus far [1,4,[19][20][21][22][23][24]. CALIPER is based on a texture-sensitive volumetric analysis that allows automated classification of lung parenchyma according to a database of HRCT volumes of interest validated by radiologists using data from the LTRC [9].…”

Section: Discussionmentioning

confidence: 99%

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Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis

Maldonado

Moua

Rajagopalan³

et al. 2013

Eur Respir J

207

139

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Accurate assessment of prognosis in idiopathic pulmonary fibrosis remains elusive due to significant individual radiological and physiological variability. We hypothesised that short-term radiological changes may be predictive of survival.We explored the use of CALIPER (Computer-Aided Lung Informatics for Pathology Evaluation and Rating), a novel software tool developed by the Biomedical Imaging Resource Laboratory at the Mayo Clinic Rochester (Rochester, MN, USA) for the analysis and quantification of parenchymal lung abnormalities on high-resolution computed tomography. We assessed baseline and follow-up (time-points 1 and 2, respectively) high-resolution computed tomography scans in 55 selected idiopathic pulmonary fibrosis patients and correlated CALIPER-quantified measurements with expert radiologists' assessments and clinical outcomes.Findings of interval change (mean 289 days) in volume of reticular densities (hazard ratio 1.91, p50.006), total volume of interstitial abnormalities (hazard ratio 1.70, p50.003) and per cent total interstitial abnormalities (hazard ratio 1.52, p50.017) as quantified by CALIPER were predictive of survival after a median follow-up of 2.4 years. Radiologist interpretation of short-term global interstitial lung disease progression, but not specific radiological features, was also predictive of mortality.These data demonstrate the feasibility of quantifying interval short-term changes on high-resolution computed tomography and their possible use as independent predictors of survival in idiopathic pulmonary fibrosis. @ERSpublications Short-term quantified CT changes are predictive of survival in IPF

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis

Maldonado

Moua

Rajagopalan³

et al. 2013

Eur Respir J

207

139

View full text Add to dashboard Cite

show abstract

“…A visual inspection of the results of the segmentation procedure (i.e., the lung mask) is mandatory and, in case of failure, a manual correction is essential in order to prevent the inclusion in the lung mask of non-lung regions or the exclusion of lung regions, e.g., because of image artefacts. Lung densitometry can be performed on a circumscribed lung area (48,49), but evaluation of diffuse lung diseases is usually performed in inspiratory scans on the entire cross-sectional area of the lung in selected sections or on the whole lung. In the latter case, once the lung mask is considered valid, the lung volume can be computed.…”

Section: Lung Segmentationmentioning

confidence: 99%

Lung densitometry: why, how and when

Mascalchi¹,

Camiciottoli²,

Diciotti

2017

J. Thorac. Dis.

102

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Lung densitometry assesses with computed tomography (CT) the X-ray attenuation of the pulmonary tissue which reflects both the degree of inflation and the structural lung abnormalities implying decreased attenuation, as in emphysema and cystic diseases, or increased attenuation, as in fibrosis. and with pulmonary fibrosis. It has also been applied to assess prevalence of smoking-related emphysema and to monitor progression of smoking-related emphysema, alpha1 antitrypsin deficiency emphysema, and pulmonary fibrosis. Finally, it is recommended as end-point in pharmacological trials of emphysema and lung fibrosis.

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“…[17][18][19] This value was calculated using a three-dimensional image analysis system (SYNAPSE VINCENT TM ; Fujifilm, Tokyo, Japan) in order to quantify the GGO. We calculated the mean %GGO of six images obtained from each scan.…”

mentioning

confidence: 99%

Low-dose CT screening using hybrid iterative reconstruction: confidence ratings of diagnoses of simulated lesions other than lung cancer

Sakai

Yabuuchi

Kondo

et al. 2015

BJR

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Objective: To evaluate the confidence ratings of diagnoses of simulated lesions other than lung cancer on low-dose screening CT with hybrid iterative reconstruction (IR). Methods: Simulated lesions (emphysema, mediastinal masses and interstitial pneumonia) in a chest phantom were scanned by a 320-row area detector CT. The scans were performed by 64-row and 160-row helical scans at various dose levels and were reconstructed by filtered back projection (FBP) and IR. Emphysema, honeycombing and reticular opacity were visually scored on a four-point scale by six thoracic radiologists. The ground-glass opacity as a percentage of total lung volume (%GGO), CT value and contrast-to-noise ratio (CNR) of mediastinal masses were calculated. These scores and values were compared between FBP and IR. Wilcoxon's signed-rank test was used (p , 0.05). Interobserver agreements were evaluated by k statistics.Results: There were no significant differences in visual assessment. Interobserver agreement was almost perfect. CT values were almost equivalent between FBP and IR, whereas CNR with IR was significantly higher than that with FBP. %GGO significantly increased at low-dose levels with FBP; however, IR suppressed the elevation. Conclusion: The confidence ratings of diagnoses of simulated lesions other than lung cancer on low-dose CT screening were not degraded with hybrid IR compared with FBP. Advances in knowledge: Hybrid IR did not degrade the confidence ratings of diagnoses on visual assessment and differential diagnoses based on CT value of mediastinal masses, and it showed the advantage of higher GGO conspicuity at low-dose level. Radiologists can analyse images of hybrid IR alone on low-dose CT screening for lung cancer. INTRODUCTIONRecently, there have been discussions regarding the efficacy of lung cancer screening using low-dose CT. For example, the National Lung Screening Trial research team's 1 randomized clinical trial comparing the efficacies of chest radiographs and low-dose CT. They found that lung cancer screening using low-dose CT reduces lung cancer-related mortality in groups at high risk of lung cancer. With regard to dose-reduction techniques in CT, a new method of image reconstruction, iterative reconstruction (IR), has been developed and is now widely used for various clinical purposes. This technique has an advantage over the filtered back projection (FBP) method of image reconstruction in that FBP contains quantum noise; IR reduces this quantum noise by repeatedly comparing projection data, including quantum noise or primary reconstruction image data, with ideal anatomical and statistical models.

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Assessment of Prognosis of Patients With Idiopathic Pulmonary Fibrosis by Computer-aided Analysis of CT Images

Abstract: The GHNC provides automatic measurement of volume of fibrosis. The F2-pattern on CT can predict prognosis of patients with IPF.

Cited by 56 publications

References 18 publications

Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis

Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis

Lung densitometry: why, how and when

Low-dose CT screening using hybrid iterative reconstruction: confidence ratings of diagnoses of simulated lesions other than lung cancer

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