CT quantification of the heterogeneity of fibrosis boundaries in idiopathic pulmonary fibrosis

被引:10
作者
Park, Junghoan [1 ,2 ]
Jung, Julip [3 ]
Yoon, Soon Ho [1 ,2 ]
Hong, Helen [3 ]
Kim, Hyungjin [1 ,2 ]
Kim, Heekyung [4 ]
Yoon, Jeong-Hwa [5 ]
Goo, Jin Mo [1 ,2 ,6 ]
机构
[1] Seoul Natl Univ Hosp, Dept Radiol, 101 Daehak Ro, Seoul 03080, South Korea
[2] Seoul Natl Univ, Dept Radiol, Coll Med, Seoul, South Korea
[3] Seoul Womens Univ, Dept Software Convergence, Seoul, South Korea
[4] Eulji Univ, Eulji Med Ctr, Sch Med, Dept Radiol, Daejeon, South Korea
[5] Seoul Natl Univ, Interdisciplinary Program Med Informat, Coll Med, Seoul, South Korea
[6] Seoul Natl Univ, Inst Radiat Med, Med Res Ctr, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
Tomography; X-ray computed; Lung; Idiopathic pulmonary fibrosis; Quantitative evaluation; USUAL INTERSTITIAL PNEUMONIA; QUANTITATIVE COMPUTED-TOMOGRAPHY; DIAGNOSIS; SURVIVAL; VARIABILITY; FEATURES;
D O I
10.1007/s00330-020-07594-y
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objectives To quantify the heterogeneity of fibrosis boundaries in idiopathic pulmonary fibrosis (IPF) using the Gaussian curvature analysis for evaluating disease severity and predicting survival. Methods We retrospectively included 104 IPF patients and 52 controls who underwent baseline chest CT scans. Normal lungs below - 500 HU were segmented, and the boundary was three-dimensionally reconstructed using in-house software. Gaussian curvature analysis provided histogram features on the heterogeneity of the fibrosis boundary. We analyzed the correlations between histogram features and the gender-age-physiology (GAP) and CT fibrosis scores. We built a regression model to predict diffusing capacity of carbon monoxide (DLCO) using the histogram features and calculated the modified GAP (mGAP) score by replacing DLCO with the predicted DLCO. The performances of the GAP, CT-GAP, and mGAP scores were compared using 100 repeated random-split sets. Results Patients with moderate-to-severe IPF had more numerous Gaussian curvatures at the fibrosis boundary, lower uniformity, and lower 10th to 30th percentiles of Gaussian curvature than controls or patients with mild IPF (all p < 0.0033). The 20th percentile was most significantly correlated with the GAP score (r = - 0.357; p < 0.001) and the CT fibrosis score (r = - 0.343; p = 0.001). More numerous Gaussian curvatures, higher entropy, lower uniformity, and 10th to 30th percentiles (p < 0.001-0.041) were associated with mortality. The mGAP score was comparable to the GAP and CT-GAP scores for survival prediction (mean C-indices, 0.76 vs. 0.79 vs. 0.77, respectively). Conclusions Gaussian curvatures of fibrosis boundaries became more heterogeneous as the disease progressed, and heterogeneity was negatively associated with survival in IPF.
引用
收藏
页码:5148 / 5159
页数:12
相关论文
共 37 条
[1]   Quantitative Computed Tomography Imaging of Interstitial Lung Diseases [J].
Bartholmai, Brian J. ;
Raghunath, Sushravya ;
Karwoski, Ronald A. ;
Moua, Teng ;
Rajagopalan, Srinivasan ;
Maldonado, Fabien ;
Decker, Paul A. ;
Robb, Richard A. .
JOURNAL OF THORACIC IMAGING, 2013, 28 (05) :298-307
[2]   Idiopathic pulmonary fibrosis: Physiologic tests, quantitative CT indexes, and CT visual scores as predictors of mortality [J].
Best, Alan C. ;
Meng, Jiangfeng ;
Lynch, Anne M. ;
Bozic, Carmen M. ;
Miller, David ;
Grunwald, Gary K. ;
Lynch, David A. .
RADIOLOGY, 2008, 246 (03) :935-940
[3]   Predicting Outcome in Idiopathic Pulmonary Fibrosis: Addition of Fibrotic Score at Thin-Section CT of the Chest to Gender, Age, and Physiology Score Improves the Prediction Model [J].
Chahal, Anurag ;
Sharif, Roozbeh ;
Watts, Jubal ;
de Andrade, Joao ;
Luckhardt, Tracy ;
Kim, Young-Il ;
Ramchandran, Rekha ;
Sonavane, Sushilkumar .
RADIOLOGY-CARDIOTHORACIC IMAGING, 2019, 1 (02)
[4]   Analysis of carotid lumen surface morphology using three-dimensional ultrasound imaging [J].
Chiu, Bernard ;
Beletsky, Vadim ;
Spence, J. David ;
Parraga, Grace ;
Fenster, Aaron .
PHYSICS IN MEDICINE AND BIOLOGY, 2009, 54 (05) :1149-1167
[5]   Intersession variability in single-breath diffusing capacity in diabetics without overt lung disease [J].
Drummond, Michael B. ;
Schwartz, Pamela F. ;
Duggan, William T. ;
Teeter, John G. ;
Riese, Richard J. ;
Ahrens, Richard C. ;
Crapo, Robert O. ;
England, Richard D. ;
MacIntyre, Neil R. ;
Jensen, Robert L. ;
Wise, Robert A. .
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2008, 178 (03) :225-232
[6]  
Graham BL, 2017, EUR RESPIR J, V49, DOI 10.1183/13993003.00016-2016
[7]  
Harrell FE, 2015, SPRINGER SER STAT, DOI 10.1007/978-3-319-19425-7
[8]   Contrast enhanced CT-scans are not comparable to non-enhanced scans in emphysema quantification [J].
Heussel, C. P. ;
Kappes, J. ;
Hantusch, R. ;
Hartlieb, S. ;
Weinheimer, O. ;
Kauczor, H. -U. ;
Eberhardt, R. .
EUROPEAN JOURNAL OF RADIOLOGY, 2010, 74 (03) :473-478
[9]   Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images [J].
Hu, SY ;
Hoffman, EA ;
Reinhardt, JM .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2001, 20 (06) :490-498
[10]   The importance of subpleural fibrosis in the prognosis of patients with idiopathic interstitial pneumonias [J].
Iwasawa, Tae ;
Takemura, Tamiko ;
Okudera, Koji ;
Gotoh, Toshiyuki ;
Iwao, Yuma ;
Kitamura, Hideya ;
Baba, Tomohisa ;
Ogura, Takashi ;
Oba, Mari S. .
EUROPEAN JOURNAL OF RADIOLOGY, 2017, 90 :106-113