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Lukhumaidze L, Hogg JC, Bourbeau J, Tan WC, Kirby M. Quantitative CT Imaging Features Associated with Stable PRISm using Machine Learning. Acad Radiol 2024:S1076-6332(24)00589-0. [PMID: 39191563 DOI: 10.1016/j.acra.2024.08.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Revised: 08/03/2024] [Accepted: 08/14/2024] [Indexed: 08/29/2024]
Abstract
RATIONALE AND OBJECTIVES The structural lung features that characterize individuals with preserved ratio impaired spirometry (PRISm) that remain stable overtime are unknown. The objective of this study was to use machine learning models with computed tomography (CT) imaging to classify stable PRISm from stable controls and stable COPD and identify discriminative features. MATERIALS AND METHODS A total of 596 participants that did not transition between control, PRISm and COPD groups at baseline and 3-year follow-up were evaluated: n = 274 with normal lung function (stable control), n = 22 stable PRISm, and n = 300 stable COPD. Investigated features included: quantitative CT (QCT) features (n = 34), such as total lung volume (%TLCCT) and percentage of ground glass and reticulation (%GG+Reticulationtexture), as well as Radiomic (n = 102) features, including varied intensity zone distribution grainy texture (GLDZMZDV). Logistic regression machine learning models were trained using various feature combinations (Base, Base+QCT, Base+Radiomic, Base+QCT+Radiomic). Model performances were evaluated using area under receiver operator curve (AUC) and comparisons between models were made using DeLong test; feature importance was ranked using Shapley Additive Explanations values. RESULTS Machine learning models for all feature combinations achieved AUCs between 0.63-0.84 for stable PRISm vs. stable control, and 0.65-0.92 for stable PRISm vs. stable COPD classification. Models incorporating imaging features outperformed those trained solely on base features (p < 0.05). Compared to stable control and COPD, those with stable PRISm exhibited decreased %TLCCT and increased %GG+Reticulationtexture and GLDZMZDV. CONCLUSION These findings suggest that reduced lung volumes, and elevated high-density and ground glass/reticulation patterns on CT imaging are associated with stable PRISm.
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Affiliation(s)
| | - James C Hogg
- Center for Heart, Lung Innovation, University of British Columbia, Vancouver, BC, Canada (J.C.H., W.C.T.)
| | - Jean Bourbeau
- Montreal Chest Institute of the Royal Victoria Hospital, McGill University Health Centre, Montreal, QC, Canada (J.B.); Respiratory Epidemiology and Clinical Research Unit, Research Institute of McGill University Health Centre, Montreal, QC, Canada (J.B.)
| | - Wan C Tan
- Center for Heart, Lung Innovation, University of British Columbia, Vancouver, BC, Canada (J.C.H., W.C.T.)
| | - Miranda Kirby
- Toronto Metropolitan University, Toronto, ON, Canada (L.L., M.K.).
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Genkin D, Zanette B, Grzela P, Benkert T, Subbarao P, Moraes TJ, Katz S, Ratjen F, Santyr G, Kirby M. Semiautomated Segmentation and Analysis of Airway Lumen in Pediatric Patients Using Ultra Short Echo Time MRI. Acad Radiol 2024; 31:648-659. [PMID: 37550154 DOI: 10.1016/j.acra.2023.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/06/2023] [Accepted: 07/10/2023] [Indexed: 08/09/2023]
Abstract
RATIONALE AND OBJECTIVES Ultra short echo time (UTE) magnetic resonance imaging (MRI) pulse sequences have shown promise for airway assessment, but the feasibility and repeatability in the pediatric lung are unknown. The purpose of this work was to develop a semiautomated UTE MRI airway segmentation pipeline from the trachea-to-tertiary airways in pediatric participants and assess repeatability and lumen diameter correlations to lung function. MATERIALS AND METHODS A total of 29 participants (n = 7 healthy, n = 11 cystic fibrosis, n = 6 asthma, and n = 5 ex-preterm), aged 7-18 years, were imaged using a 3D stack-of-spirals UTE examination at 3 T. Two independent observers performed airway segmentations using a pipeline developed in-house; observer 1 repeated segmentations 1 month later. Segmentations were extracted using region-growing with leak detection, then manually edited if required. The airway trees were skeletonized, pruned, and labeled. Airway lumen diameter measurements were extracted using ray casting. Intra- and interobserver variability was assessed using the Sørensen-Dice coefficient (DSC) and intra-class correlation coefficient (ICC). Correlations between lumen diameter and pulmonary function were assessed using Spearman's correlation coefficient. RESULTS For airway segmentations and lumen diameter, intra- and interobserver DSCs were 0.88 and 0.80, while ICCs were 0.95 and 0.89, respectively. The variability increased from the trachea-to-tertiary airways for intra- (DSC: 0.91-0.64; ICC: 0.91-0.49) and interobserver (DSC: 0.84-0.51; ICC: 0.89-0.21) measurements. Lumen diameter was significantly correlated with forced expiratory volume in 1 second and forced vital capacity (P < .05). CONCLUSION UTE MRI airway segmentation from the trachea-to-tertiary airways in pediatric participants across a range of diseases is feasible. The UTE MRI-derived lumen measurements were repeatable and correlated with lung function.
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Affiliation(s)
- Daniel Genkin
- Department of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada (D.G.)
| | - Brandon Zanette
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.)
| | - Patrick Grzela
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.)
| | - Thomas Benkert
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (T.B.)
| | - Padmaja Subbarao
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.); Department of Pediatrics, University of Toronto, Toronto, ON, Canada (P.S., T.J.M., F.R.)
| | - Theo J Moraes
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.); Department of Pediatrics, University of Toronto, Toronto, ON, Canada (P.S., T.J.M., F.R.)
| | - Sherri Katz
- Department of Pediatrics, University of Ottawa, Ottawa, ON, Canada (S.K.); Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada (S.K.)
| | - Felix Ratjen
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.); Department of Pediatrics, University of Toronto, Toronto, ON, Canada (P.S., T.J.M., F.R.)
| | - Giles Santyr
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.); Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada (G.S.)
| | - Miranda Kirby
- Department of Physics, Toronto Metropolitan University, Kerr Hall South Bldg., Room KHS-344, 350 Victoria St., Toronto, ON M5B 2K3, Canada (M.K.).
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3
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Cheung WK, Pakzad A, Mogulkoc N, Needleman S, Rangelov B, Gudmundsson E, Zhao A, Abbas M, McLaverty D, Asimakopoulos D, Chapman R, Savas R, Janes SM, Hu Y, Alexander DC, Hurst JR, Jacob J. Automated airway quantification associates with mortality in idiopathic pulmonary fibrosis. Eur Radiol 2023; 33:8228-8238. [PMID: 37505249 PMCID: PMC10598186 DOI: 10.1007/s00330-023-09914-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 07/29/2023]
Abstract
OBJECTIVES The study examined whether quantified airway metrics associate with mortality in idiopathic pulmonary fibrosis (IPF). METHODS In an observational cohort study (n = 90) of IPF patients from Ege University Hospital, an airway analysis tool AirQuant calculated median airway intersegmental tapering and segmental tortuosity across the 2nd to 6th airway generations. Intersegmental tapering measures the difference in median diameter between adjacent airway segments. Tortuosity evaluates the ratio of measured segmental length against direct end-to-end segmental length. Univariable linear regression analyses examined relationships between AirQuant variables, clinical variables, and lung function tests. Univariable and multivariable Cox proportional hazards models estimated mortality risk with the latter adjusted for patient age, gender, smoking status, antifibrotic use, CT usual interstitial pneumonia (UIP) pattern, and either forced vital capacity (FVC) or diffusion capacity of carbon monoxide (DLco) if obtained within 3 months of the CT. RESULTS No significant collinearity existed between AirQuant variables and clinical or functional variables. On univariable Cox analyses, male gender, smoking history, no antifibrotic use, reduced DLco, reduced intersegmental tapering, and increased segmental tortuosity associated with increased risk of death. On multivariable Cox analyses (adjusted using FVC), intersegmental tapering (hazard ratio (HR) = 0.75, 95% CI = 0.66-0.85, p < 0.001) and segmental tortuosity (HR = 1.74, 95% CI = 1.22-2.47, p = 0.002) independently associated with mortality. Results were maintained with adjustment using DLco. CONCLUSIONS AirQuant generated measures of intersegmental tapering and segmental tortuosity independently associate with mortality in IPF patients. Abnormalities in proximal airway generations, which are not typically considered to be abnormal in IPF, have prognostic value. CLINICAL RELEVANCE STATEMENT Quantitative measurements of intersegmental tapering and segmental tortuosity, in proximal (second to sixth) generation airway segments, independently associate with mortality in IPF. Automated airway analysis can estimate disease severity, which in IPF is not restricted to the distal airway tree. KEY POINTS • AirQuant generates measures of intersegmental tapering and segmental tortuosity. • Automated airway quantification associates with mortality in IPF independent of established measures of disease severity. • Automated airway analysis could be used to refine patient selection for therapeutic trials in IPF.
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Affiliation(s)
- Wing Keung Cheung
- Satsuma Lab, Centre for Medical Image Computing, University College London, 1st Floor, 90 High Holborn, London, WC1V6LJ, UK
- Department of Computer Science, University College London, London, UK
| | - Ashkan Pakzad
- Satsuma Lab, Centre for Medical Image Computing, University College London, 1st Floor, 90 High Holborn, London, WC1V6LJ, UK
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Nesrin Mogulkoc
- Department of Respiratory Medicine, Ege University Hospital, Izmir, Turkey
| | - Sarah Needleman
- Satsuma Lab, Centre for Medical Image Computing, University College London, 1st Floor, 90 High Holborn, London, WC1V6LJ, UK
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Bojidar Rangelov
- Satsuma Lab, Centre for Medical Image Computing, University College London, 1st Floor, 90 High Holborn, London, WC1V6LJ, UK
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Eyjolfur Gudmundsson
- Satsuma Lab, Centre for Medical Image Computing, University College London, 1st Floor, 90 High Holborn, London, WC1V6LJ, UK
- Department of Computer Science, University College London, London, UK
| | - An Zhao
- Satsuma Lab, Centre for Medical Image Computing, University College London, 1st Floor, 90 High Holborn, London, WC1V6LJ, UK
- Department of Computer Science, University College London, London, UK
| | - Mariam Abbas
- Department of Computer Science, University College London, London, UK
| | | | | | - Robert Chapman
- Interstitial Lung Disease Service, Department of Respiratory Medicine, University College London Hospitals NHS Foundation Trust, London, UK
| | - Recep Savas
- Department of Radiology, Ege University Hospital, Izmir, Turkey
| | - Sam M Janes
- Lungs for Living Research Centre, UCL, London, UK
- UCL Respiratory, University College London, London, UK
| | - Yipeng Hu
- Satsuma Lab, Centre for Medical Image Computing, University College London, 1st Floor, 90 High Holborn, London, WC1V6LJ, UK
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Daniel C Alexander
- Satsuma Lab, Centre for Medical Image Computing, University College London, 1st Floor, 90 High Holborn, London, WC1V6LJ, UK
- Department of Computer Science, University College London, London, UK
| | - John R Hurst
- UCL Respiratory, University College London, London, UK
- Respiratory Medicine, Royal Free London NHS Foundation Trust, London, UK
| | - Joseph Jacob
- Satsuma Lab, Centre for Medical Image Computing, University College London, 1st Floor, 90 High Holborn, London, WC1V6LJ, UK.
- Lungs for Living Research Centre, UCL, London, UK.
- UCL Respiratory, University College London, London, UK.
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Nicolas N, Dinet V, Roux E. 3D imaging and morphometric descriptors of vascular networks on optically cleared organs. iScience 2023; 26:108007. [PMID: 37810224 PMCID: PMC10551892 DOI: 10.1016/j.isci.2023.108007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2023] Open
Abstract
The vascular system is a multi-scale network whose functionality depends on its structure, and for which structural alterations can be linked to pathological shifts. Though biologists use multiple 3D imaging techniques to visualize vascular networks, the 3D image processing methodologies remain sources of biases, and the extraction of quantitative morphometric descriptors remains flawed. The article, first, reviews the current 3D image processing methodologies, and morphometric descriptors of vascular network images mainly obtained by light-sheet microscopy on optically cleared organs, found in the literature. Second, it proposes operator-independent segmentation and skeletonization methodologies using the freeware ImageJ. Third, it gives more extractable network-level (density, connectivity, fractal dimension) and segment-level (length, diameter, tortuosity) 3D morphometric descriptors and how to statistically analyze them. Thus, it can serve as a guideline for biologists using 3D imaging techniques of vascular networks, allowing the production of more comparable studies in the future.
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Affiliation(s)
- Nabil Nicolas
- University Bordeaux, INSERM, Biologie des maladies cardiovasculaires, U1034, F-33600 Pessac, France
| | - Virginie Dinet
- University Bordeaux, INSERM, Biologie des maladies cardiovasculaires, U1034, F-33600 Pessac, France
| | - Etienne Roux
- University Bordeaux, INSERM, Biologie des maladies cardiovasculaires, U1034, F-33600 Pessac, France
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Zeng X, Guo Y, Zaman A, Hassan H, Lu J, Xu J, Yang H, Miao X, Cao A, Yang Y, Chen R, Kang Y. Tubular Structure Segmentation via Multi-Scale Reverse Attention Sparse Convolution. Diagnostics (Basel) 2023; 13:2161. [PMID: 37443556 DOI: 10.3390/diagnostics13132161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 06/17/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023] Open
Abstract
Cerebrovascular and airway structures are tubular structures used for transporting blood and gases, respectively, providing essential support for the normal activities of the human body. Accurately segmenting these tubular structures is the basis of morphology research and pathological detection. Nevertheless, accurately segmenting these structures from images presents great challenges due to their complex morphological and topological characteristics. To address this challenge, this paper proposes a framework UARAI based on the U-Net multi-scale reverse attention network and sparse convolution network. The framework utilizes a multi-scale structure to effectively extract the global and deep detail features of vessels and airways. Further, it enhances the extraction ability of fine-edged features by a joint reverse attention module. In addition, the sparse convolution structure is introduced to improve the features' expression ability without increasing the model's complexity. Finally, the proposed training sample cropping strategy reduces the influence of block boundaries on the accuracy of tubular structure segmentation. The experimental findings demonstrate that the UARAI-based metrics, namely Dice and IoU, achieve impressive scores of 90.31% and 82.33% for cerebrovascular segmentation and 93.34% and 87.51% for airway segmentation, respectively. Compared to commonly employed segmentation techniques, the proposed method exhibits remarkable accuracy and robustness in delineating tubular structures such as cerebrovascular and airway structures. These results hold significant promise in facilitating medical image analysis and clinical diagnosis, offering invaluable support to healthcare professionals.
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Affiliation(s)
- Xueqiang Zeng
- School of Applied Technology, Shenzhen University, Shenzhen 518060, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
| | - Yingwei Guo
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China
| | - Asim Zaman
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China
| | - Haseeb Hassan
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
| | - Jiaxi Lu
- School of Applied Technology, Shenzhen University, Shenzhen 518060, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
| | - Jiaxuan Xu
- State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, First Affiliated Hospital, Guangzhou Medical University, Guangzhou 510120, China
| | - Huihui Yang
- School of Applied Technology, Shenzhen University, Shenzhen 518060, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
| | - Xiaoqiang Miao
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China
| | - Anbo Cao
- School of Applied Technology, Shenzhen University, Shenzhen 518060, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
| | - Yingjian Yang
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China
| | - Rongchang Chen
- Shenzhen Institute of Respiratory Diseases, Shenzhen People's Hospital, Shenzhen 518001, China
- The Second Clinical Medical College, Jinan University, Guangzhou 518001, China
- The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen 518001, China
| | - Yan Kang
- School of Applied Technology, Shenzhen University, Shenzhen 518060, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China
- Engineering Research Centre of Medical Imaging and Intelligent Analysis, Ministry of Education, Shenyang 110169, China
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Bumgarner JR, Nelson RJ. Open-source analysis and visualization of segmented vasculature datasets with VesselVio. CELL REPORTS METHODS 2022; 2:100189. [PMID: 35497491 PMCID: PMC9046271 DOI: 10.1016/j.crmeth.2022.100189] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 01/10/2022] [Accepted: 03/02/2022] [Indexed: 05/11/2023]
Abstract
Vascular networks are fundamental components of biological systems. Quantitative analysis and observation of the features of these networks can improve our understanding of their roles in health and disease. Recent advancements in imaging technologies have enabled the generation of large-scale vasculature datasets, but barriers to analyzing these datasets remain. Modern analysis options are mainly limited to paid applications or open-source terminal-based software that requires programming knowledge with high learning curves. Here, we describe VesselVio, an open-source application developed to analyze and visualize pre-binarized vasculature datasets and pre-constructed vascular graphs. Vasculature datasets and graphs can be loaded with annotations and processed with custom parameters. Here, the program is tested on ground-truth datasets and is compared with current pipelines. The utility of VesselVio is demonstrated by the analysis of multiple formats of 2D and 3D datasets acquired with several imaging modalities, including annotated mouse whole-brain vasculature volumes.
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Affiliation(s)
- Jacob R. Bumgarner
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26505, USA
| | - Randy J. Nelson
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26505, USA
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7
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Hoffman EA. Origins of and lessons from quantitative functional X-ray computed tomography of the lung. Br J Radiol 2022; 95:20211364. [PMID: 35193364 PMCID: PMC9153696 DOI: 10.1259/bjr.20211364] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/20/2022] [Accepted: 01/27/2022] [Indexed: 12/16/2022] Open
Abstract
Functional CT of the lung has emerged from quantitative CT (qCT). Structural details extracted at multiple lung volumes offer indices of function. Additionally, single volumetric images, if acquired at standardized lung volumes and body posture, can be used to model function by employing such engineering techniques as computational fluid dynamics. With the emergence of multispectral CT imaging including dual energy from energy integrating CT scanners and multienergy binning using the newly released photon counting CT technology, function is tagged via use of contrast agents. Lung disease phenotypes have previously been lumped together by the limitations of spirometry and plethysmography. QCT and its functional embodiment have been imbedded into studies seeking to characterize chronic obstructive pulmonary disease, severe asthma, interstitial lung disease and more. Reductions in radiation dose by an order of magnitude or more have been achieved. At the same time, we have seen significant increases in spatial and density resolution along with methodologic validations of extracted metrics. Together, these have allowed attention to turn towards more mild forms of disease and younger populations. In early applications, clinical CT offered anatomic details of the lung. Functional CT offers regional measures of lung mechanics, the assessment of functional small airways disease, as well as regional ventilation-perfusion matching (V/Q) and more. This paper will focus on the use of quantitative/functional CT for the non-invasive exploration of dynamic three-dimensional functioning of the breathing lung and beating heart within the unique negative pressure intrathoracic environment of the closed chest.
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Affiliation(s)
- Eric A Hoffman
- Departments of Radiology, Internal Medicine and Biomedical Engineering University of Iowa, Iowa, United States
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Au RC, Tan WC, Bourbeau J, Hogg JC, Kirby M. Impact of image pre-processing methods on computed tomography radiomics features in chronic obstructive pulmonary disease. Phys Med Biol 2021; 66. [PMID: 34847536 DOI: 10.1088/1361-6560/ac3eac] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 11/30/2021] [Indexed: 01/06/2023]
Abstract
Computed tomography (CT) imaging texture-based radiomics analysis can be used to assess chronic obstructive pulmonary disease (COPD). However, different image pre-processing methods are commonly used, and how these different methods impact radiomics features and lung disease assessment, is unknown. The purpose of this study was to develop an image pre-processing pipeline to investigate how various pre-processing combinations impact radiomics features and their use for COPD assessment. Spirometry and CT images were obtained from the multi-centered Canadian Cohort of Obstructive Lung Disease study. Participants were divided based on assessment site and were further dichotomized as No COPD or COPD within their participant groups. An image pre-processing pipeline was developed, calculating 32 grey level co-occurrence matrix radiomics features. The pipeline included lung segmentation, airway segmentation or no segmentation, image resampling or no resampling, and either no pre-processing, binning, edgmentation, or thresholding pre-processing techniques. A three-way analysis of variance was used for method comparison. A nested 10-fold cross validation using logistic regression and multiple linear regression models were constructed to classify COPD and assess correlation with lung function, respectively. Logistic regression performance was evaluated using the area under the receiver operating characteristic curve (AUC). A total of 1210 participants (Sites 1-8: No COPD:n = 447, COPD:n = 413; and Site 9: No COPD:n = 155, COPD:n = 195) were evaluated. Between the two participant groups, at least 16/32 features were different between airway segmentation/no segmentation (P ≤ 0.04), at least 29/32 features were different between no resampling/resampling (P ≤ 0.04), and 32/32 features were different between the pre-processing techniques (P < 0.0001). Features generated using the resampling/edgmentation and resampling/thresholding pre-processing combinations, regardless of airway segmentation, performed the best in COPD classification (AUC ≥ 0.718), and explained the most variance with lung function (R2 ≥ 0.353). Therefore, the image pre-processing methods completed prior to CT radiomics feature extraction significantly impacted extracted features and their ability to assess COPD.
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Affiliation(s)
- Ryan C Au
- Department of Physics, Ryerson University, Toronto, ON, M5B 2K3, Canada
| | - Wan C Tan
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Jean Bourbeau
- McGill University Health Centre, McGill University, Montreal, QC, H3A 0G4, Canada
| | - James C Hogg
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Miranda Kirby
- Department of Physics, Ryerson University, Toronto, ON, M5B 2K3, Canada.,Institute for Biomedical Engineering, Science and Technology, St. Michael's Hospital, Toronto, ON, M5B 1T8, Canada
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9
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Guggenberger K, Krafft AJ, Ludwig U, Raithel E, Forman C, Meckel S, Hennig J, Bley TA, Vogel P. Intracranial vessel wall imaging framework - Data acquisition, processing, and visualization. Magn Reson Imaging 2021; 83:114-124. [PMID: 34403760 DOI: 10.1016/j.mri.2021.08.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 07/09/2021] [Accepted: 08/12/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVE Assessment of vessel walls is an integral part in diagnosis and disease monitoring of vascular diseases such as vasculitis. Vessel wall imaging (VWI), in particular of intracranial arteries, is the domain of Magnetic Resonance Imaging (MRI) - but still remains a challenge. The tortuous anatomy of intracranial arteries and the need for high resolution within clinically acceptable scan times require special technical conditions regarding the hardware and software environments. MATERIALS AND METHODS In this work a dedicated framework for intracranial VWI is presented offering an optimized, black-blood 3D T1-weighted post-contrast Compressed Sensing (CS)-accelerated MRI sequence prototype combined with dedicated 3D-GUI supported post-processing tool for the CPR visualization of tortuous arbitrary vessel structures. RESULTS Using CS accelerated MRI sequence, the scanning time for high-resolution 3D black-blood CS-space data could be reduced to under 10 min. These data are adequate for a further processing to extract straightened visualizations (curved planar reformats - CPR). First patient data sets could be acquired in clinical environment. CONCLUSION A highly versatile framework for VWI visualization was demonstrated utilizing a post-processing tool to extract CPR reformats from high-resolution 3D black-blood CS-SPACE data, enabling simplified and optimized assessment of intracranial arteries in intracranial vascular disorders, especially in suspected intracranial vasculitis, by stretching their tortuous course. The processing time from about 15-20 min per patient (data acquisition and further processing) allows the integration into clinical routine.
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Affiliation(s)
- Konstanze Guggenberger
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany
| | - Axel J Krafft
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Ute Ludwig
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | | | | | - Stephan Meckel
- Department of Neuroradiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jürgen Hennig
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Thorsten A Bley
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany
| | - Patrick Vogel
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany; Department of Experimental Physics 5 (Biophysics), University of Würzburg, Würzburg, Germany.
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Wang M, Jin R, Jiang N, Liu H, Jiang S, Li K, Zhou X. Automated labeling of the airway tree in terms of lobes based on deep learning of bifurcation point detection. Med Biol Eng Comput 2020; 58:2009-2024. [PMID: 32613598 DOI: 10.1007/s11517-020-02184-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Accepted: 05/01/2020] [Indexed: 12/19/2022]
Abstract
This paper presents an automatic lobe-based labeling of airway tree method, which can detect the bifurcation points for reconstructing and labeling the airway tree from a computed tomography image. A deep learning-based network structure is designed to identify the four key bifurcation points. Then, based on the detected bifurcation points, the entire airway tree is reconstructed by a new region-growing method. Finally, with the basic airway tree anatomy and topology knowledge, individual branches of the airway tree are classified into different categories in terms of pulmonary lobes. There are several advantages in our method such as the detection of the bifurcation points does not depend on the segmentation of airway tree and only four bifurcation points need to be manually labeled for each sample to prepare the training dataset. The segmentation of airway tree is guided by the detected points, which overcomes the difficulty of manual seed selection of conventional region-growing algorithm. In addition, the bifurcation points can help analyze the tree structure, which provides a basis for effective airway tree labeling. Experimental results show that our method is fast, stable, and the accuracy of our method is 97.85%, which is higher than that of the traditional skeleton-based method. Graphical Abstract The pipeline of our proposed lobe-based airway tree labeling method. Given a raw CT volume, a neural network structure is designed to predict major bifurcation points of airway tree. Based on the detected points, airway tree is reconstructed and labeled in terms of lobes.
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Affiliation(s)
- Manyang Wang
- School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.,Key Laboratory of Education Ministry for Image Processing and Intelligence Control, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Renchao Jin
- School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China. .,Key Laboratory of Education Ministry for Image Processing and Intelligence Control, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
| | - Nanchuan Jiang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.,Hubei Province Key Laboratory of Molecular Imaging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Hong Liu
- School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.,Key Laboratory of Education Ministry for Image Processing and Intelligence Control, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Shan Jiang
- School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.,Key Laboratory of Education Ministry for Image Processing and Intelligence Control, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Kang Li
- School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.,Key Laboratory of Education Ministry for Image Processing and Intelligence Control, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - XueXin Zhou
- School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.,Key Laboratory of Education Ministry for Image Processing and Intelligence Control, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
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11
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Jiang F, Hirano T, Ohgi J, Chen X. A voxel image-based pulmonary airflow simulation method with an automatic detection algorithm for airway outlets. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2020; 36:e3305. [PMID: 31913573 DOI: 10.1002/cnm.3305] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 01/01/2020] [Accepted: 01/03/2020] [Indexed: 06/10/2023]
Abstract
Investigations of pulmonary airflows in respiratory systems are important for the diagnostics and treatment of pulmonary diseases. For accurate prediction of the flow field in an airway, a numerical simulation must be conducted using the true geometry from computed tomography (CT) data. Flow simulation is still a difficult task because of the mesh generation process and preprocessing setup procedures. In this study, we developed a voxel image-based simulation method using an automatic detection algorithm for airway outlets to simplify the simulation process and improve its applicability in the medical field. Our approach is based on the lattice Boltzmann method with a topology analysis algorithm, which can preserve all raw information from the original CT images and give an accurate flow field inside the airways. Our method can reproduce the essential flow features inside airways, is highly efficient, and decreases the overall processing time. Thus, it has a great potential for future real-time airflow analyses to provide airflow information to medical experts. HIGHLIGHTS: This paper proposed a voxel image-based simulation method with a novel automatic outlet-selecting algorithm to calculate the velocity and pressure of physiological flows in multi-generation-branched airways. Our approach simplifies the simulation process by automatically applying the boundary conditions to large numbers of outlets and minimizes the time-consuming mesh generation process. Our proposed method has considerable potential for real-time simulations improving the applicability to patient-specific medical diagnostics and treatments.
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Affiliation(s)
- Fei Jiang
- Department of Mechanical Engineering, Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Yamaguchi, Japan
- Biomedical Engineering Center (YUBEC), Yamaguchi University, Ube, Japan
- International Institute for Carbon-Neutral Energy Research (WPI-I2CNER), Kyushu University, Fukuoka, Japan
- Blue Energy Center for SGE Technology (BEST), Yamaguchi University, Ube, Japan
| | - Tsunahiko Hirano
- Department of Respiratory Medicine and Infectious Disease, Graduate School of Medicine, Yamaguchi University, Yamaguchi, Japan
| | - Junji Ohgi
- Department of Mechanical Engineering, Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Yamaguchi, Japan
- Biomedical Engineering Center (YUBEC), Yamaguchi University, Ube, Japan
| | - Xian Chen
- Department of Mechanical Engineering, Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Yamaguchi, Japan
- Biomedical Engineering Center (YUBEC), Yamaguchi University, Ube, Japan
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12
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Duan HH, Gong J, Sun XW, Nie SD. Region growing algorithm combined with morphology and skeleton analysis for segmenting airway tree in CT images. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2020; 28:311-331. [PMID: 32039883 DOI: 10.3233/xst-190627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
BACKGROUND Automatic segmentation of pulmonary airway tree is a challenging task in many clinical applications, including developing computer-aided detection and diagnosis schemes of lung diseases. OBJECTIVE To segment the pulmonary airway tree from the computed tomography (CT) chest images using a novel automatic method proposed in this study. METHODS This method combines a two-pass region growing algorithm with gray-scale morphological reconstruction and leakage elimination. The first-pass region growing is implemented to obtain a rough airway tree. The second-pass region growing and gray-scale morphological reconstruction are used to detect the distal airways. Finally, leakage detection is performed to remove leakage and refine the airway tree. RESULTS Our methods were compared with the gold standards. Forty-five clinical CT lung image scan cases were used in the experiments. Statistics on tree division order, branch number, and airway length were adopted for evaluation. The proposed method detected up to 12 generations of bronchi. On average, 148.85 branches were extracted with a false positive rate of 0.75%. CONCLUSIONS The results show that our method is accurate for pulmonary airway tree segmentation. The strategy of separating the leakage detection from the segmenting process is feasible and promising for ensuring a high branch detected rate with a low leakage volume.
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Affiliation(s)
- Hui-Hong Duan
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Jing Gong
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Xi-Wen Sun
- Department of Radiology of Shanghai Pulmonary Hospital, ZhengMin Road, YangPu District, Shanghai, China
| | - Sheng-Dong Nie
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
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13
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Auto-generation of centerline graphs from geometrically complex roadmaps of real-world traffic systems using hierarchical quadtrees for cellular automata simulations. Inf Sci (N Y) 2019. [DOI: 10.1016/j.ins.2019.07.049] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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14
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Quan K, Tanno R, Shipley RJ, Brown JS, Jacob J, Hurst JR, Hawkes DJ. Reproducibility of an airway tapering measurement in computed tomography with application to bronchiectasis. J Med Imaging (Bellingham) 2019; 6:034003. [PMID: 31548977 PMCID: PMC6745534 DOI: 10.1117/1.jmi.6.3.034003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 08/23/2019] [Indexed: 11/14/2022] Open
Abstract
We propose a pipeline to acquire a scalar tapering measurement from the carina to the most distal point of an individual airway visible on computed tomography (CT). We show the applicability of using tapering measurements on clinically acquired data by quantifying the reproducibility of the tapering measure. We generate a spline from the centerline of an airway to measure the area and arclength at contiguous intervals. The tapering measurement is the gradient of the linear regression between area in log space and arclength. The reproducibility of the measure was assessed by analyzing different radiation doses, voxel sizes, and reconstruction kernel on single timepoint and longitudinal CT scans and by evaluating the effect of airway bifurcations. Using 74 airways from 10 CT scans, we show a statistical difference, p = 3.4 × 10 - 4 , in tapering between healthy airways ( n = 35 ) and those affected by bronchiectasis ( n = 39 ). The difference between the mean of the two populations is 0.011 mm - 1 , and the difference between the medians of the two populations was 0.006 mm - 1 . The tapering measurement retained a 95% confidence interval of ± 0.005 mm - 1 in a simulated 25 mAs scan and retained a 95% confidence of ± 0.005 mm - 1 on simulated CTs up to 1.5 times the original voxel size. We have established an estimate of the precision of the tapering measurement and estimated the effect on precision of the simulated voxel size and CT scan dose. We recommend that the scanner calibration be undertaken with the phantoms as described, on the specific CT scanner, radiation dose, and reconstruction algorithm that are to be used in any quantitative studies.
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Affiliation(s)
- Kin Quan
- University College London, Center for Medical Image Computing, London, United Kingdom
| | - Ryutaro Tanno
- University College London, Center for Medical Image Computing, London, United Kingdom
| | - Rebecca J. Shipley
- University College London, Department of Mechanical Engineering, London, United Kingdom
| | - Jeremy S. Brown
- University College London, UCL Respiratory, London, United Kingdom
| | - Joseph Jacob
- University College London, Center for Medical Image Computing, London, United Kingdom
- University College London, UCL Respiratory, London, United Kingdom
| | - John R. Hurst
- University College London, UCL Respiratory, London, United Kingdom
| | - David J. Hawkes
- University College London, Center for Medical Image Computing, London, United Kingdom
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Veiga C, Landau D, Devaraj A, Doel T, White J, Ngai Y, Hawkes DJ, McClelland JR. Novel CT-Based Objective Imaging Biomarkers of Long-Term Radiation-Induced Lung Damage. Int J Radiat Oncol Biol Phys 2018; 102:1287-1298. [PMID: 29908943 DOI: 10.1016/j.ijrobp.2018.06.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 05/07/2018] [Accepted: 06/05/2018] [Indexed: 12/25/2022]
Abstract
PURPOSE Recent improvements in lung cancer survival have spurred an interest in understanding and minimizing long-term radiation-induced lung damage (RILD). However, there are still no objective criteria to quantify RILD, leading to variable reporting across centers and trials. We propose a set of objective imaging biomarkers for quantifying common radiologic findings observed 12 months after lung cancer radiation therapy. METHODS AND MATERIALS Baseline and 12-month computed tomography (CT) scans of 27 patients from a phase 1/2 clinical trial of isotoxic chemoradiation were included in this study. To detect and measure the severity of RILD, 12 quantitative imaging biomarkers were developed. The biomarkers describe basic CT findings, including parenchymal change, volume reduction, and pleural change. The imaging biomarkers were implemented as semiautomated image analysis pipelines and were assessed against visual assessment of the occurrence of each change. RESULTS Most of the biomarkers were measurable in each patient. The continuous nature of the biomarkers allows objective scoring of severity for each patient. For each imaging biomarker, the cohort was split into 2 groups according to the presence or absence of the biomarker by visual assessment, testing the hypothesis that the imaging biomarkers were different in the 2 groups. All features were statistically significant except for rotation of the main bronchus and diaphragmatic curvature. Most of the biomarkers were not strongly correlated with each other, suggesting that each of the biomarkers is measuring a separate element of RILD pathology. CONCLUSIONS We developed objective CT-based imaging biomarkers that quantify the severity of radiologic lung damage after radiation therapy. These biomarkers are representative of typical radiologic findings of RILD.
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Affiliation(s)
- Catarina Veiga
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.
| | - David Landau
- Department of Oncology, Guy's & St. Thomas' NHS Trust, London, United Kingdom; Department of Oncology, University College London Hospital, London, United Kingdom
| | - Anand Devaraj
- Department of Radiology, Royal Brompton Hospital, London, United Kingdom
| | - Tom Doel
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Jared White
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Yenting Ngai
- Cancer Research UK and UCL Cancer Trials Centre, University College London, London, United Kingdom
| | - David J Hawkes
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Jamie R McClelland
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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16
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Zhang W, Wang X, Li X, Chen J. 3D skeletonization feature based computer-aided detection system for pulmonary nodules in CT datasets. Comput Biol Med 2017; 92:64-72. [PMID: 29154123 DOI: 10.1016/j.compbiomed.2017.11.008] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Revised: 10/24/2017] [Accepted: 11/08/2017] [Indexed: 11/17/2022]
Abstract
Pulmonary nodule detection has a significant impact on early diagnosis of lung cancer. To effectively detect pulmonary nodules from interferential vessels in chest CT datasets, this paper proposes a novel 3D skeletonization feature, named as voxels remove rate. Based on this feature, a computer-aided detection system is constructed to validate its performance. The system mainly consists of five stages. Firstly, the lung tissues are segmented by a global optimal active contour model, which can extract all structures (including juxta-pleural nodules) in the lung region. Secondly, thresholding, 3D binary morphological operations, and 3D connected components labeling are utilized to extract candidates of pulmonary nodules. Thirdly, combining the voxels remove rate with other nine existing 3D features (including gray features and shape features), the extracted candidates are characterized. Then, prior anatomical knowledge is utilized for preliminary screening of numerous invalid nodule candidates. Finally, false positives are reduced by support vector machine. Our system is evaluated on early stage lung cancer subjects obtained from the publicly available LIDC-IDRI database. The result shows the proposed 3D skeletonization feature is a useful indicator that efficiently differentiates lung nodules from the other suspicious structures. The computer-aided detection system based on this feature can detect various types of nodules, including solitary, juxta-pleural and juxta-vascular nodules.
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Affiliation(s)
- Weihang Zhang
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Xue Wang
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China.
| | - Xuanping Li
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Junfeng Chen
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
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17
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Grélard F, Baldacci F, Vialard A, Domenger JP. New methods for the geometrical analysis of tubular organs. Med Image Anal 2017; 42:89-101. [PMID: 28780175 DOI: 10.1016/j.media.2017.07.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Revised: 06/08/2017] [Accepted: 07/27/2017] [Indexed: 11/28/2022]
Abstract
This paper presents new methods to study the shape of tubular organs. Determining precise cross-sections is of major importance to perform geometrical measurements, such as diameter, wall-thickness estimation or area measurement. Our first contribution is a robust method to estimate orthogonal planes based on the Voronoi Covariance Measure. Our method is not relying on a curve-skeleton computation beforehand. This means our orthogonal plane estimator can be used either on the skeleton or on the volume. Another important step towards tubular organ characterization is achieved through curve-skeletonization, as skeletons allow to compare two tubular organs, and to perform virtual endoscopy. Our second contribution is dedicated to correcting common defects of the skeleton by new pruning and recentering methods. Finally, we propose a new method for curve-skeleton extraction. Various results are shown on different types of segmented tubular organs, such as neurons, airway-tree and blood vessels.
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Affiliation(s)
- Florent Grélard
- Univ. Bordeaux, LaBRI, UMR 5800, F-33400 Talence, France; CNRS, LaBRI, UMR 5800, F-33400 Talence, France.
| | - Fabien Baldacci
- Univ. Bordeaux, LaBRI, UMR 5800, F-33400 Talence, France; CNRS, LaBRI, UMR 5800, F-33400 Talence, France
| | - Anne Vialard
- Univ. Bordeaux, LaBRI, UMR 5800, F-33400 Talence, France; CNRS, LaBRI, UMR 5800, F-33400 Talence, France
| | - Jean-Philippe Domenger
- Univ. Bordeaux, LaBRI, UMR 5800, F-33400 Talence, France; CNRS, LaBRI, UMR 5800, F-33400 Talence, France
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18
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Kim SS, Jin GY, Li YZ, Lee JE, Shin HS. CT Quantification of Lungs and Airways in Normal Korean Subjects. Korean J Radiol 2017; 18:739-748. [PMID: 28670169 PMCID: PMC5447650 DOI: 10.3348/kjr.2017.18.4.739] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Accepted: 01/05/2017] [Indexed: 11/19/2022] Open
Abstract
Objective To measure and compare the quantitative parameters of the lungs and airways in Korean never-smokers and current or former smokers (“ever-smokers”). Materials and Methods Never-smokers (n = 119) and ever-smokers (n = 45) who had normal spirometry and visually normal chest computed tomography (CT) results were retrospectively enrolled in this study. For quantitative CT analyses, the low attenuation area (LAA) of LAAI-950, LAAE-856, CT attenuation value at the 15th percentile, mean lung attenuation (MLA), bronchial wall thickness of inner perimeter of a 10 mm diameter airway (Pi10), total lung capacity (TLCCT), and functional residual capacity (FRCCT) were calculated based on inspiratory and expiratory CT images. To compare the results between groups according to age, sex, and smoking history, independent t test, one way ANOVA, correlation test, and simple and multiple regression analyses were performed. Results The values of attenuation parameters and volume on inspiratory and expiratory quantitative computed tomography (QCT) were significantly different between males and females (p < 0.001). The MLA and the 15th percentile value on inspiratory QCT were significantly lower in the ever-smoker group than in the never-smoker group (p < 0.05). On expiratory QCT, all lung attenuation parameters were significantly different according to the age range (p < 0.05). Pi10 in ever-smokers was significantly correlated with forced expiratory volume in 1 second/forced vital capacity (r = −0.455, p = 0.003). In simple and multivariate regression analyses, TLCCT, FRCCT, and age showed significant associations with lung attenuation (p < 0.05), and only TLCCT was significantly associated with inspiratory Pi10. Conclusion In Korean subjects with normal spirometry and visually normal chest CT, there may be significant differences in QCT parameters according to sex, age, and smoking history.
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Affiliation(s)
- Song Soo Kim
- Department of Radiology, Chungnam National University Hospital, Chungnam National University School of Medicine, Daejeon 35015, Korea
| | - Gong Yong Jin
- Department of Radiology, Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Chonbuk National University Medical School, Institute of Medical Science, Jeonju 54907, Korea
| | - Yuan Zhe Li
- Department of Radiology, Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Jeonju 54907, Korea
| | - Jeong Eun Lee
- Department of Radiology, Chungnam National University Hospital, Chungnam National University School of Medicine, Daejeon 35015, Korea
| | - Hye Soo Shin
- Department of Radiology, Chungnam National University Hospital, Chungnam National University School of Medicine, Daejeon 35015, Korea
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Chen K, Hoffman EA, Seetharaman I, Jiao F, Lin CL, Chan KS. LINKING LUNG AIRWAY STRUCTURE TO PULMONARY FUNCTION VIA COMPOSITE BRIDGE REGRESSION. Ann Appl Stat 2016; 10:1880-1906. [PMID: 28280520 PMCID: PMC5340208 DOI: 10.1214/16-aoas947] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The human lung airway is a complex inverted tree-like structure. Detailed airway measurements can be extracted from MDCT-scanned lung images, such as segmental wall thickness, airway diameter, parent-child branch angles, etc. The wealth of lung airway data provides a unique opportunity for advancing our understanding of the fundamental structure-function relationships within the lung. An important problem is to construct and identify important lung airway features in normal subjects and connect these to standardized pulmonary function test results such as FEV1%. Among other things, the problem is complicated by the fact that a particular airway feature may be an important (relevant) predictor only when it pertains to segments of certain generations. Thus, the key is an efficient, consistent method for simultaneously conducting group selection (lung airway feature types) and within-group variable selection (airway generations), i.e., bi-level selection. Here we streamline a comprehensive procedure to process the lung airway data via imputation, normalization, transformation and groupwise principal component analysis, and then adopt a new composite penalized regression approach for conducting bi-level feature selection. As a prototype of composite penalization, the proposed composite bridge regression method is shown to admit an efficient algorithm, enjoy bi-level oracle properties, and outperform several existing methods. We analyze the MDCT lung image data from a cohort of 132 subjects with normal lung function. Our results show that, lung function in terms of FEV1% is promoted by having a less dense and more homogeneous lung comprising an airway whose segments enjoy more heterogeneity in wall thicknesses, larger mean diameters, lumen areas and branch angles. These data hold the potential of defining more accurately the "normal" subject population with borderline atypical lung functions that are clearly influenced by many genetic and environmental factors.
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20
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Miyawaki S, Tawhai MH, Hoffman EA, Wenzel SE, Lin CL. Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface. Biomech Model Mechanobiol 2016; 16:583-596. [PMID: 27704229 DOI: 10.1007/s10237-016-0838-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Accepted: 09/21/2016] [Indexed: 11/27/2022]
Abstract
We propose a method to construct three-dimensional airway geometric models based on airway skeletons, or centerlines (CLs). Given a CT-segmented airway skeleton and surface, the proposed CL-based method automatically constructs subject-specific models that contain anatomical information regarding branches, include bifurcations and trifurcations, and extend from the trachea to terminal bronchioles. The resulting model can be anatomically realistic with the assistance of an image-based surface; alternatively a model with an idealized skeleton and/or branch diameters is also possible. This method systematically identifies and classifies trifurcations to successfully construct the models, which also provides the number and type of trifurcations for the analysis of the airways from an anatomical point of view. We applied this method to 16 normal and 16 severe asthmatic subjects using their computed tomography images. The average distance between the surface of the model and the image-based surface was 11 % of the average voxel size of the image. The four most frequent locations of trifurcations were the left upper division bronchus, left lower lobar bronchus, right upper lobar bronchus, and right intermediate bronchus. The proposed method automatically constructed accurate subject-specific three-dimensional airway geometric models that contain anatomical information regarding branches using airway skeleton, diameters, and image-based surface geometry. The proposed method can construct (i) geometry automatically for population-based studies, (ii) trifurcations to retain the original airway topology, (iii) geometry that can be used for automatic generation of computational fluid dynamics meshes, and (iv) geometry based only on a skeleton and diameters for idealized branches.
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Affiliation(s)
- Shinjiro Miyawaki
- IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, IA, 52242, USA
- CH2M, 1100 NE Circle Blvd., Suite 300, Corvallis, OR, 97330, USA
| | - Merryn H Tawhai
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Eric A Hoffman
- The Department of Biomedical Engineering, Medicine, and Radiology, University of Iowa, Iowa City, IA, 52242, USA
| | - Sally E Wenzel
- The Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Ching-Long Lin
- IIHR-Hydroscience and Engineering and the Department of Mechanical and Industrial Engineering, University of Iowa, 3131 Seamans Center, Iowa City, IA, 52242, USA.
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22
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Zheng B, Leader JK, McMurray JM, Park SC, Fuhrman CR, Gur D, Sciurba FC. Automated detection and quantitative assessment of pulmonary airways depicted on CT images. Med Phys 2016; 34:2844-52. [PMID: 17821992 DOI: 10.1118/1.2742777] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
We developed and tested a fully automated computerized scheme that identifies pulmonary airway sections depicted on computed tomography (CT) images and computes their sizes including the lumen and airway wall areas. The scheme includes four processing modules that (1) segment left and right lung areas, (2) identify airway locations, (3) segment airway walls from neighboring pixels, and (4) compute airway sizes. The scheme uses both a raster scanning and a labeling algorithm complemented by simple classification rules for region size and circularity to automatically search for and identify airway sections of interest. A profile tracking method is used to segment airway walls from neighboring pixels including those associated with dense tissue (i.e., pulmonary arteries) along scanning radial rays. A partial pixel membership method is used to compute airway size. The scheme was tested on ten randomly selected CT studies that included 26 sets of CT images acquired using both low and conventional dose CT examinations with one of four reconstruction algorithms (namely, "bone," "lung," "soft," and "standard" convolution kernels). Three image section thicknesses (1.25, 2.5, and 5 mm) were evaluated. The scheme detected a large number of quantifiable airway sections when the CT images were reconstructed using high spatial frequency convolution kernels. The detection results demonstrated a consistent trend for all test image sets in that as airway lumen size increases, on average the airway wall area increases as well and the wall area percentage decreases. The study suggested that CT images reconstructed using high spatial frequency convolution kernels and thin-section thickness were most amenable to automated detection, reasonable segmentation, and quantified assessment when the airways are close to being perpendicular to the CT image plane.
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Affiliation(s)
- Bin Zheng
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA.
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23
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Bradley RS, Withers PJ. Post-processing techniques for making reliable measurements from curve-skeletons. Comput Biol Med 2016; 72:120-31. [PMID: 27035863 DOI: 10.1016/j.compbiomed.2016.03.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Revised: 03/16/2016] [Accepted: 03/16/2016] [Indexed: 10/22/2022]
Abstract
Interconnected 3-D networks occur widely in biology and the geometry of such branched networks can be described by curve-skeletons, allowing parameters such as path lengths, path tortuosities and cross-sectional thicknesses to be quantified. However, curve-skeletons are typically sensitive to small scale surface features which may arise from noise in the imaging data. In this paper, new post-processing techniques for curve-skeletons are presented which ensure that measurements of lengths and thicknesses are less sensitive to these small scale surface features. The techniques achieve sub-voxel accuracy and are based on a minimal sphere-network representation in which the object is modelled as a string of minimally overlapping spheres, and as such samples the object on a scale related to the local thickness. A new measure of cross-sectional dimension termed the modal radius is defined and shown to be more robust in comparison with the standard measure (the internal radius), while retaining the desirable feature of capturing the size of structures in terms of a single measure. The techniques are demonstrated by application to trabecular bone and tumour vascular network case studies where the volumetric data was obtained by high resolution computed tomography.
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Affiliation(s)
- Robert S Bradley
- Henry Moseley X-ray Imaging Facility, School of Materials, The University of Manchester, Oxford Road, Manchester M13 9PL, UK.
| | - Philip J Withers
- Henry Moseley X-ray Imaging Facility, School of Materials, The University of Manchester, Oxford Road, Manchester M13 9PL, UK.
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Kizhakke Puliyakote AS, Vasilescu DM, Sen Sharma K, Wang G, Hoffman EA. A skeleton-tree-based approach to acinar morphometric analysis using microcomputed tomography with comparison of acini in young and old C57BL/6 mice. J Appl Physiol (1985) 2016; 120:1402-9. [PMID: 26940656 DOI: 10.1152/japplphysiol.00923.2015] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Accepted: 02/29/2016] [Indexed: 11/22/2022] Open
Abstract
We seek to establish a method using interior tomographic techniques (Xradia MicroXCT-400) for acinar morphometric analysis using the pathway center lines from micro X-ray computed tomographic (Micro-CT) images as the road map. Through the application of these techniques, we present a method to extend the atlas of murine lungs to acinar levels and present a comparison between two age groups of the C57BL/6 strain. Lungs fixed via vascular perfusion were scanned using high-resolution Micro-CT protocols. Individual acini were segmented, and skeletonized paths to alveolar sacs from the entrance to the acinus were formed. Morphometric parameters, including branch lengths, diameters, and branching angles, were generated. Six mice each, at two age groups (∼20 and ∼90 wk of age), were studied. Additive Gaussian noise (0 mean and SD 1, 2, 5, and 10) was used to test the robustness of the analytical method. Noise-based variations were within ±6 μm for branch lengths and ±5 μm for diameters. At a noise level of 10, errors increased. Branch diameters were less susceptible to noise than lengths. There was >95% center line overlap across all noise levels. The measurements obtained using the center lines as a road map were not affected by added noise. Acini from younger mice had smaller branch diameters and lengths at all generations without significant differences in branching angles. The relative distribution of volume in the alveolar ducts was similar across both age groups. The method has been demonstrated to be repeatable and robust to image noise and provides a new, nondestructive technique to assess and compare acinar morphometry quantitatively.
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Affiliation(s)
- Abhilash S Kizhakke Puliyakote
- Department of Radiology, University of Iowa, Iowa City, Iowa; Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
| | | | - Kriti Sen Sharma
- Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia; and
| | - Ge Wang
- Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia; and Department of Biomedical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, Iowa; Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa; Department of Medicine, University of Iowa, Iowa City, Iowa;
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Childhood-onset asthma in smokers. association between CT measures of airway size, lung function, and chronic airflow obstruction. Ann Am Thorac Soc 2015; 11:1371-8. [PMID: 25296268 DOI: 10.1513/annalsats.201403-095oc] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
RATIONALE AND OBJECTIVES Asthma is associated with chronic airflow obstruction. Our goal was to assess the association of computed tomographic measures of airway wall volume and lumen volume with the FEV1 and chronic airflow obstruction in smokers with childhood-onset asthma. METHODS We analyzed clinical, lung function, and volumetric computed tomographic airway volume data from 7,266 smokers, including 590 with childhood-onset asthma. Small wall volume and small lumen volume of segmental airways were defined as measures 1 SD below the mean. We assessed the association between small wall volume, small lumen volume, FEV1, and chronic airflow obstruction (post-bronchodilator FEV1/FVC ratio < 0.7) using linear and logistic models. MEASUREMENTS AND MAIN RESULTS Compared with subjects without childhood-onset asthma, those with childhood-onset asthma had smaller wall volume and lumen volume (P < 0.0001) of segmental airways. Among subjects with childhood-onset asthma, those with the smallest wall volume and lumen volume had the lowest FEV1 and greatest odds of chronic airflow obstruction. A similar tendency was seen in those without childhood-onset asthma. When comparing these two groups, both small wall volume and small lumen volume were more strongly associated with FEV1 and chronic airflow obstruction among subjects with childhood-asthma in multivariate models. CONCLUSION In smokers with childhood-onset asthma, smaller airways are associated with reduced lung function and chronic airflow obstruction. Clinical trial registered with www.clinicaltrials.gov (NCT00608764).
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Jin D, Iyer KS, Chen C, Hoffman EA, Saha PK. A Robust and Efficient Curve Skeletonization Algorithm for Tree-Like Objects Using Minimum Cost Paths. Pattern Recognit Lett 2015; 76:32-40. [PMID: 27175043 DOI: 10.1016/j.patrec.2015.04.002] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Conventional curve skeletonization algorithms using the principle of Blum's transform, often, produce unwanted spurious branches due to boundary irregularities, digital effects, and other artifacts. This paper presents a new robust and efficient curve skeletonization algorithm for three-dimensional (3-D) elongated fuzzy objects using a minimum cost path approach, which avoids spurious branches without requiring post-pruning. Starting from a root voxel, the method iteratively expands the skeleton by adding new branches in each iteration that connects the farthest quench voxel to the current skeleton using a minimum cost path. The path-cost function is formulated using a novel measure of local significance factor defined by the fuzzy distance transform field, which forces the path to stick to the centerline of an object. The algorithm terminates when dilated skeletal branches fill the entire object volume or the current farthest quench voxel fails to generate a meaningful skeletal branch. Accuracy of the algorithm has been evaluated using computer-generated phantoms with known skeletons. Performance of the method in terms of false and missing skeletal branches, as defined by human experts, has been examined using in vivo CT imaging of human intrathoracic airways. Results from both experiments have established the superiority of the new method as compared to the existing methods in terms of accuracy as well as robustness in detecting true and false skeletal branches. The new algorithm makes a significant reduction in computation complexity by enabling detection of multiple new skeletal branches in one iteration. Specifically, this algorithm reduces the number of iterations from the number of terminal tree branches to the worst case performance of tree depth. In fact, experimental results suggest that, on an average, the order of computation complexity is reduced to the logarithm of the number of terminal branches of a tree-like object.
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Affiliation(s)
- Dakai Jin
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA
| | - Krishna S Iyer
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | - Cheng Chen
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | - Punam K Saha
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA; Department of Radiology, University of Iowa, Iowa City, Iowa, USA
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Diaz AA, Rahaghi FN, Ross JC, Harmouche R, Tschirren J, San José Estépar R, Washko GR. Understanding the contribution of native tracheobronchial structure to lung function: CT assessment of airway morphology in never smokers. Respir Res 2015; 16:23. [PMID: 25848985 PMCID: PMC4335784 DOI: 10.1186/s12931-015-0181-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2014] [Accepted: 01/26/2015] [Indexed: 11/10/2022] Open
Abstract
Background Computed tomographic (CT) airway lumen narrowing is associated with lower lung function. Although volumetric CT measures of airways (wall volume [WV] and lumen volume [LV]) compared to cross sectional measures can more accurately reflect bronchial morphology, data of their use in never smokers is scarce. We hypothesize that native tracheobronchial tree morphology as assessed by volumetric CT metrics play a significant role in determining lung function in normal subjects. We aimed to assess the relationships between airway size, the projected branching generation number (BGN) to reach airways of <2mm lumen diameter –the site for airflow obstruction in smokers- and measures of lung function including forced expiratory volume in 1 second (FEV1) and forced expiratory flow between 25% and 75% of vital capacity (FEF 25–75). Methods We assessed WV and LV of segmental and subsegmental airways from six bronchial paths as well as lung volume on CT scans from 106 never smokers. We calculated the lumen area ratio of the subsegmental to segmental airways and estimated the projected BGN to reach a <2mm-lumen-diameter airway assuming a dichotomized tracheobronchial tree model. Regression analysis was used to assess the relationships between airway size, BGN, FEF 25–75, and FEV1. Results We found that in models adjusted for demographics, LV and WV of segmental and subsegmental airways were directly related to FEV1 (P <0.05 for all the models). In adjusted models for age, sex, race, LV and lung volume or height, the projected BGN was directly associated with FEF 25–75 and FEV1 (P = 0.001) where subjects with lower FEV1 had fewer calculated branch generations between the subsegmental bronchus and small airways. There was no association between airway lumen area ratio and lung volume. Conclusion We conclude that in never smokers, those with smaller central airways had lower airflow and those with lower airflow had less parallel airway pathways independent of lung size. These findings suggest that variability in the structure of the tracheobronchial tree may influence the risk of developing clinically relevant smoking related airway obstruction. Electronic supplementary material The online version of this article (doi:10.1186/s12931-015-0181-y) contains supplementary material, which is available to authorized users.
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Computer assisted detection of abnormal airway variation in CT scans related to paediatric tuberculosis. Med Image Anal 2014; 18:963-76. [DOI: 10.1016/j.media.2014.05.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2013] [Revised: 04/13/2014] [Accepted: 05/23/2014] [Indexed: 11/20/2022]
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Jin D, Iyer KS, Hoffman EA, Saha PK. A New Approach of Arc Skeletonization for Tree-Like Objects Using Minimum Cost Path. PROCEEDINGS OF THE ... IAPR INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION. INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION 2014; 2014:942-947. [PMID: 25621320 DOI: 10.1109/icpr.2014.172] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Traditional arc skeletonization algorithms using the principle of Blum's transform, often, produce unwanted spurious branches due to boundary irregularities and digital effects on objects and other artifacts. This paper presents a new robust approach of extracting arc skeletons for three-dimensional (3-D) elongated fuzzy objects, which avoids spurious branches without requiring post-pruning. Starting from a root voxel, the method iteratively expands the skeleton by adding a new branch in each iteration that connects the farthest voxel to the current skeleton using a minimum-cost geodesic path. The path-cost function is formulated using a novel measure of local significance factor defined by fuzzy distance transform field, which forces the path to stick to the centerline of the object. The algorithm terminates when dilated skeletal branches fill the entire object volume or the current farthest voxel fails to generate a meaningful branch. Accuracy of the algorithm has been evaluated using computer-generated blurred and noisy phantoms with known skeletons. Performance of the method in terms of false and missing skeletal branches, as defined by human expert, has been examined using in vivo CT imaging of human intrathoracic airways. Experimental results from both experiments have established the superiority of the new method as compared to a widely used conventional method in terms of accuracy of medialness as well as robustness of true and false skeletal branches.
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Affiliation(s)
- Dakai Jin
- Department of Electrical and Computer Engineering , University of Iowa, Iowa City, USA
| | - Krishna S Iyer
- Department of Radiology , University of Iowa Iowa City, USA
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van Rikxoort EM, van Ginneken B. Automated segmentation of pulmonary structures in thoracic computed tomography scans: a review. Phys Med Biol 2014; 58:R187-220. [PMID: 23956328 DOI: 10.1088/0031-9155/58/17/r187] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Computed tomography (CT) is the modality of choice for imaging the lungs in vivo. Sub-millimeter isotropic images of the lungs can be obtained within seconds, allowing the detection of small lesions and detailed analysis of disease processes. The high resolution of thoracic CT and the high prevalence of lung diseases require a high degree of automation in the analysis pipeline. The automated segmentation of pulmonary structures in thoracic CT has been an important research topic for over a decade now. This systematic review provides an overview of current literature. We discuss segmentation methods for the lungs, the pulmonary vasculature, the airways, including airway tree construction and airway wall segmentation, the fissures, the lobes and the pulmonary segments. For each topic, the current state of the art is summarized, and topics for future research are identified.
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Affiliation(s)
- Eva M van Rikxoort
- Diagnostic Image Analysis Group, Department of Radiology, Radboud University Nijmegen Medical Centre, The Netherlands.
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Kim SS, Yagihashi K, Stinson DS, Zach JA, McKenzie AS, Curran-Everett D, Wan ES, Silverman EK, Crapo JD, Lynch DA. Visual Assessment of CT Findings in Smokers With Nonobstructed Spirometric Abnormalities in The COPDGene ® Study. CHRONIC OBSTRUCTIVE PULMONARY DISEASES-JOURNAL OF THE COPD FOUNDATION 2014; 1:88-96. [PMID: 25197723 DOI: 10.15326/jcopdf.1.1.2013.0001#sthash.l0atdpjm.dpuf] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Within the COPD Genetic Epidemiology (COPDGene®) study population of cigarette smokers, 9% were found to be unclassifiable by the Global Initiative for chronic Obstructive Lung Disease (GOLD) criteria. This study was to identify the differences in computed tomography (CT) findings between this nonobstructed (GOLDU) group and a control group of smokers with normal lung function. This research was approved by the institutional review board of each institution. CT images of 400 participants in the COPDGene® study (200 GOLDU, 200 smokers with normal lung function) were retrospectively evaluated in a blinded fashion. Visual CT assessment included lobar analysis of emphysema (type, extent), presence of paraseptal emphysema, airway wall thickening, expiratory air trapping, centrilobular nodules, atelectasis, non-fibrotic and fibrotic interstitial lung disease (ILD), pleural thickening, diaphragmatic eventration, vertebral body changes and internal thoracic diameters (in mm). Univariate comparisons of groups for each CT parameter and multiple logistic regression were performed to determine the imaging features associated with GOLDU. When compared with the control group, GOLDU participants had a significantly higher prevalence of unilateral diaphragm eventration (30% vs. 16%), airway wall thickening, centrilobular nodules, reticular abnormality, paraseptal emphysema (33% vs. 17%), linear atelectasis (60% vs. 35.6%), kyphosis (12% vs. 4%), and a smaller internal transverse thoracic diameter (255 ± 22.5 [standard deviation] vs. 264.8 ± 22.4, mm) (all p<0.05). With multiple logistic regression, all of these CT parameters, except non-fibrotic ILD and kyphosis, remained significantly associated with GOLDU status (p<0.05). In cigarette smokers, chest wall abnormalities and parenchymal lung disease, which contribute to restrictive physiologic impairment, are associated with GOLD-nonobstructed status.
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Affiliation(s)
- Song Soo Kim
- Department of Radiology, National Jewish Health, Denver, CO ; Department of Radiology, Chungnam National University Hospital, Chungnam National University School of Medicine, Daejeon, Republic of Korea
| | | | | | - Jordan A Zach
- Department of Radiology, National Jewish Health, Denver, CO
| | | | - Douglas Curran-Everett
- Division of Biostatistics and Bioinformatics, National Jewish Health, and Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado, Denver, CO
| | - Emily S Wan
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - James D Crapo
- Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, CO
| | - David A Lynch
- Department of Radiology, National Jewish Health, Denver, CO
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Relationships between airflow obstruction and quantitative CT measurements of emphysema, air trapping, and airways in subjects with and without chronic obstructive pulmonary disease. AJR Am J Roentgenol 2013; 201:W460-70. [PMID: 23971478 DOI: 10.2214/ajr.12.10102] [Citation(s) in RCA: 232] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE This study evaluates the relationships between quantitative CT (QCT) and spirometric measurements of disease severity in cigarette smokers with and without chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS Inspiratory and expiratory CT scans of 4062 subjects in the Genetic Epidemiology of COPD (COPDGene) Study were evaluated. Measures examined included emphysema, defined as the percentage of low-attenuation areas≤-950 HU on inspiratory CT, which we refer to as "LAA-950I"; air trapping, defined as the percentage of low-attenuation areas≤-856 HU on expiratory CT, which we refer to as "LAA-856E"; and the inner diameter, inner and outer areas, wall area, airway wall thickness, and square root of the wall area of a hypothetical airway of 10-mm internal perimeter of segmental and subsegmental airways. Correlations were determined between spirometry and several QCT measures using statistics software (SAS, version 9.2). RESULTS QCT measurements of low-attenuation areas correlate strongly and significantly (p<0.0001) with spirometry. The correlation between LAA-856E and forced expiratory volume in 1 second (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) (r=-0.77 and -0.84, respectively) is stronger than the correlation between LAA-950I and FEV1 and FEV1/FVC (r=-0.67 and r=-0.76). Inspiratory and expiratory volume changes decreased with increasing disease severity, as measured by the Global Initiative for Chronic Obstructive Pulmonary Disease (GOLD) staging system (p<0.0001). When airway variables were included with low-attenuation area measures in a multiple regression model, the model accounted for a statistically greater proportion of variation in FEV1 and FEV1/FVC (R2=0.72 and 0.77, respectively). Airway measurements alone are less correlated with spirometric measures of FEV1 (r=0.15 to -0.44) and FEV1/FVC (r=0.19 to -0.34). CONCLUSION QCT measurements are strongly associated with spirometric results showing impairment in smokers. LAA-856E strongly correlates with physiologic measurements of airway obstruction. Airway measurements can be used concurrently with QCT measures of low-attenuation areas to accurately predict lung function.
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Maklad AS, Matsuhiro M, Suzuki H, Kawata Y, Niki N, Satake M, Moriyama N, Utsunomiya T, Shimada M. Blood vessel-based liver segmentation using the portal phase of an abdominal CT dataset. Med Phys 2013; 40:113501. [DOI: 10.1118/1.4823765] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
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Counter WB, Wang IQ, Farncombe TH, Labiris NR. Airway and pulmonary vascular measurements using contrast-enhanced micro-CT in rodents. Am J Physiol Lung Cell Mol Physiol 2013; 304:L831-43. [DOI: 10.1152/ajplung.00281.2012] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Preclinical imaging allows pulmonary researchers to study lung disease and pulmonary drug delivery noninvasively and longitudinally in small animals. However, anatomically localizing a pathology or drug deposition to a particular lung region is not easily done. Thus, a detailed knowledge of the anatomical structure of small animal lungs is necessary for understanding disease progression and in addition would facilitate the analysis of the imaging data, mapping drug deposition and relating function to structure. In this study, contrast-enhanced micro-computed tomography (CT) of the lung produced high-resolution images that allowed for the characterization of the rodent airway and pulmonary vasculature. Contrast-enhanced micro-CT was used to visualize the airways and pulmonary vasculature in Sprague-Dawley rats (200–225 g) and BALB/c mice (20–25 g) postmortem. Segmented volumes from these images were processed to yield automated measurements of the airways and pulmonary vasculature. The diameters, lengths, and branching angles of the airway, arterial, and venous trees were measured and analyzed as a function of generation number and vessel diameter to establish rules that could be applied at all levels of tree hierarchy. In the rat, airway, arterial, and venous tress were measured down to the 20th, 16th, and 14th generation, respectively. In the mouse, airway, arterial, and venous trees were measured down to the 16th, 8th, and 7th generation, respectively. This structural information, catalogued in a rodent database, will increase our understanding of lung structure and will aid in future studies of the relationship between structure and function in animal models of disease.
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Affiliation(s)
- W. B. Counter
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Medical Physics, McMaster University, Hamilton, Ontario, Canada
| | - I. Q. Wang
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - T. H. Farncombe
- Department of Radiology, McMaster University, Hamilton, Ontario, Canada; and
- Department of Nuclear Medicine, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - N. R. Labiris
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Nuclear Medicine, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
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Mesanovic N, Huseinagic H, Mujagic S. 3D TRACHEOBRONCHIAL AIRWAY TREE SEGMENTATION FROM THORAX CT IMAGES. BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS 2013. [DOI: 10.4015/s1016237213500154] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Segmentation of the lung structures is an important operation in the medical analysis. This paper is proposing a region growing algorithm for airway segmentation. The proposed method for the airway tree segmentation works fully in 3D and performs the measurements in the original gray-scale volume for increased accuracy and efficiency. This algorithm uses region growing and morphological operators. The airway segmentation algorithm is intended to serve qualitative and quantitative purposes, and additional three descriptors are being used for evaluation of the airway segmentation. The proposed method was evaluated using the database of 15 patients who underwent lung CT scans, with varying image quality and anatomical changes. Overlap measure is used to show the difference between measured volumes from the established gold standard and the proposed method. The student t-test and Pearson test showed high correlation of the results with the gold standard. Overall, the test results were satisfactory since accurate segmentation was achieved in 95% of the patients.
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Affiliation(s)
- Nihad Mesanovic
- IT Sector, University Clinical Centre, Trnovac bb, 75000 Tuzla, Bosnia and Herzegovina
| | - Haris Huseinagic
- Department of Radiology and Nuclear Medicine, University Clinical Centre, Trnovac bb, 75000 Tuzla, Bosnia and Herzegovina
| | - Svjetlana Mujagic
- Department of Radiology and Nuclear Medicine, University Clinical Centre, Trnovac bb, 75000 Tuzla, Bosnia and Herzegovina
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Andronikou S, Irving B, Hlabangana LT, Pillay T, Taylor P, Goussard P, Gie R. Technical developments in postprocessing of paediatric airway imaging. Pediatr Radiol 2013; 43:269-84. [PMID: 23417253 DOI: 10.1007/s00247-012-2468-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2012] [Accepted: 07/09/2012] [Indexed: 11/30/2022]
Abstract
CT postprocessing allows more scan information to be viewed at one time allowing an accurate diagnosis to be made more efficiently, and is particularly important in paediatric practice where invasive clinical diagnostic tools can be replaced or at least assisted by modern postprocessing techniques. Four visualization techniques in clinical use are described in this paper including the advantages and disadvantages of each: multiplanar reformation, maximum and minimum intensity projections, shaded surface display and volume rendering. Volume-rendered internal visualization in the form of virtual endoscopy is also discussed. In addition, the clinical usefulness in paediatric practice of demonstrating airway compression and its causes are discussed. Advanced postprocessing techniques that must still find their way from the biomedical research environment into clinical use are introduced with specific reference to computer-aided diagnosis.
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Affiliation(s)
- Savvas Andronikou
- Radiology Department, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
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Abstract
OBJECTIVES The purposes of this study were to evaluate the reference range of quantitative computed tomography (QCT) measures of lung attenuation and airway parameter measurements in healthy nonsmoking adults and to identify sources of variation in those measures and possible means to adjust for them. MATERIALS AND METHODS Within the COPDGene study, 92 healthy non-Hispanic white nonsmokers (29 men, 63 women; mean [SD] age, 62.7 [9.0] years; mean [SD] body mass index [BMI], 28.1 [5.1] kg/m(2)) underwent volumetric computed tomography (CT) at full inspiration and at the end of a normal expiration. On QCT analysis (Pulmonary Workstation 2, VIDA Diagnostics), inspiratory low-attenuation areas were defined as lung tissue with attenuation values -950 Hounsfield units or less on inspiratory CT (LAA(I-950)). Expiratory low-attenuation areas were defined as lung tissue -856 Hounsfield units or less on expiratory CT (LAA(E-856)). We used simple linear regression to determine the impact of age and sex on QCT parameters and multiple regression to assess the additional impact of total lung capacity and functional residual capacity measured by CT (TLC(CT) and FRC(CT)), scanner type, and mean tracheal air attenuation. Airways were evaluated using measures of airway wall thickness, inner luminal area, wall area percentage (WA%), and standardized thickness of an airway with inner perimeter of 10 mm (Pi10). RESULTS Mean (SD) %LAA(I-950) was 2.0% (2.7%), and mean (SD) %LAA(E-856) was 9.2% (6.8%). Mean (SD) %LAA(I-950) was 3.6% (3.2%) in men, compared with 1.3% (2.0%) in women (P < 0.001). The %LAA(I-950) did not change significantly with age (P = 0.08) or BMI (P = 0.52). %LAA(E-856) did not show any independent relationship with age (P = 0.33), sex (P = 0.70), or BMI (P = 0.32). On multivariate analysis, %LAA(I-950) showed a direct relationship to TLC(CT) (P = 0.002) and an inverse relationship to mean tracheal air attenuation (P = 0.003), and %LAA(E-856) was related to age (P = 0.001), FRC(CT) (P = 0.007), and scanner type (P < 0.001). Multivariate analysis of segmental airways showed that inner luminal area and WA% were significantly related to TLC(CT) (P < 0.001) and age (0.006). Moreover, WA% was associated with sex (P = 0.05), axial pixel size (P = 0.03), and slice interval (P = 0.04). Lastly, airway wall thickness was strongly influenced by axial pixel size (P < 0.001). CONCLUSIONS Although the attenuation characteristics of normal lung differ by age and sex, these differences do not persist on multivariate analysis. Potential sources of variation in measurement of attenuation-based QCT parameters include depth of inspiration/expiration and scanner type. Tracheal air attenuation may partially correct variation because of scanner type. Sources of variation in QCT airway measurements may include age, sex, BMI, depth of inspiration, and spatial resolution.
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Kim SS, Seo JB, Lee HY, Nevrekar DV, Forssen AV, Crapo JD, Schroeder JD, Lynch DA. Chronic obstructive pulmonary disease: lobe-based visual assessment of volumetric CT by Using standard images--comparison with quantitative CT and pulmonary function test in the COPDGene study. Radiology 2012; 266:626-35. [PMID: 23220894 DOI: 10.1148/radiol.12120385] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To provide a new detailed visual assessment scheme of computed tomography (CT) for chronic obstructive pulmonary disease (COPD) by using standard reference images and to compare this visual assessment method with quantitative CT and several physiologic parameters. MATERIALS AND METHODS This research was approved by the institutional review board of each institution. CT images of 200 participants in the COPDGene study were evaluated. Four thoracic radiologists performed independent, lobar analysis of volumetric CT images for type (centrilobular, panlobular, and mixed) and extent (on a six-point scale) of emphysema, the presence of bronchiectasis, airway wall thickening, and tracheal abnormalities. Standard images for each finding, generated by two radiologists, were used for reference. The extent of emphysema, airway wall thickening, and luminal area were quantified at the lobar level by using commercial software. Spearman rank test and simple and multiple regression analyses were performed to compare the results of visual assessment with physiologic and quantitative parameters. RESULTS The type of emphysema, determined by four readers, showed good agreement (κ = 0.63). The extent of the emphysema in each lobe showed good agreement (mean weighted κ = 0.70) and correlated with findings at quantitative CT (r = 0.75), forced expiratory volume in 1 second (FEV(1)) (r = -0.68), FEV(1)/forced vital capacity (FVC) ratio (r = -0.74) (P < .001). Agreement for airway wall thickening was fair (mean κ = 0.41), and the number of lobes with thickened bronchial walls correlated with FEV(1) (r = -0.60) and FEV(1)/FVC ratio (r = -0.60) (P < .001). CONCLUSION Visual assessment of emphysema and airways disease in individuals with COPD can provide reproducible, physiologically substantial information that may complement that provided by quantitative CT assessment.
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Affiliation(s)
- Song Soo Kim
- Department of Radiology, Division of Biostatistics and Bioinformatics, and Department of Internal Medicine, National Jewish Health, University of Colorado Denver School of Medicine, Denver, Colorado, USA
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Van Tho N, Wada H, Ogawa E, Nakano Y. Recent findings in chronic obstructive pulmonary disease by using quantitative computed tomography. Respir Investig 2012; 50:78-87. [PMID: 23021766 DOI: 10.1016/j.resinv.2012.08.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2012] [Revised: 07/27/2012] [Accepted: 08/08/2012] [Indexed: 11/17/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is characterized by an incompletely reversible airflow limitation that results from a combination of airway wall remodeling and emphysematous lung destruction. Forced expiratory volume in 1s (FEV(1)) has been considered the gold standard for diagnosis, classification, and follow-up in patients with COPD, but it has certain limitations and it is still necessary to find other noninvasive modalities to complement FEV(1) to evaluate the effect of therapeutic interventions and the pathogenesis of COPD. Quantitative computed tomography (CT) has partly met this demand. The extent of emphysema and airway dimensions measured using quantitative CT are associated with morphological and functional changes and clinical symptoms in patients with COPD. Phenotyping COPD based on quantitative CT has facilitated interventional and genotypic studies. Recent advances in COPD findings with quantitative CT are discussed in this review.
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Affiliation(s)
- Nguyen Van Tho
- Division of Respiratory Medicine, Department of Medicine, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
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Paré PD, Nagano T, Coxson HO. Airway imaging in disease: gimmick or useful tool? J Appl Physiol (1985) 2012; 113:636-46. [PMID: 22604891 PMCID: PMC3424064 DOI: 10.1152/japplphysiol.00372.2012] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2012] [Accepted: 05/15/2012] [Indexed: 01/06/2023] Open
Abstract
Airway remodeling is an important pathophysiological mechanism in a variety of chronic airway diseases. Historically investigators have had to use invasive techniques such as histological examination of excised tissue to study airway wall structure. The last several years has seen a proliferation of relatively noninvasive techniques to assess the airway branching pattern, wall thickness, and more recently, airway wall tissue components. These methods include computed tomography, magnetic resonance imaging, and optical coherence tomography. These new imaging technologies have become popular because to understand the physiology of lung disease it is important we understand the underlying anatomy. However, these new approaches are not standardized or available in all centers so a review of their validity and clinical utility is appropriate. This review documents how investigators are working hard to correct for inconsistencies between techniques so that they become more accepted and utilized in clinical settings. These new imaging techniques are very likely to play a frontline role in the study of lung disease and will, hopefully, allow clinicians and investigators to better understand disease pathogenesis and to design and assess new therapeutic interventions.
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Affiliation(s)
- Peter D Paré
- University of British Columbia James Hogg Research Centre and Institute for Heart + Lung Health, Vancouver, British Columbia, Canada
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Three-dimensional skeletonization and symbolic description in vascular imaging: preliminary results. Int J Comput Assist Radiol Surg 2012; 8:233-46. [DOI: 10.1007/s11548-012-0784-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2012] [Accepted: 07/11/2012] [Indexed: 10/28/2022]
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Abstract
Clinical signs of paediatric pulmonary tuberculosis (TB) include stenosis and deformation of the airways. This paper presents two methods to analyse airway shape and detect airway pathology from CT images. Features were extracted using (1) the principal components of the airway surface mesh and (2) branch radius and orientation features. These methods were applied to a dataset of 61 TB and non-TB paediatric patients. Nested cross-validation of the support vector classifier found the sensitivity of detecting TB to be 86% and a specificity of 91% for the first 10 PCA modes while radius based features had a sensitivity of 86% and a specificity of 94%. These methods show the potential of computer assisted detection of TB and other airway pathology from airway shape deformation.
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Automated detection of junctions structures and tracking of their trajectories in 4D images. INFORMATION PROCESSING IN MEDICAL IMAGING : PROCEEDINGS OF THE ... CONFERENCE 2011; 22:486-97. [PMID: 21761680 DOI: 10.1007/978-3-642-22092-0_40] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Junction structures, as the natural anatomical markers, are useful to study the organ or tumor motion. However, detection and tracking of the junctions in four-dimensional (4D) images are challenging. The paper presents a novel framework to automate this task. Detection of their centers and sizes is first achieved by an analysis of local shape profiles on one segmented reference image. Junctions are then separately tracked by simultaneously using neighboring intensity features from all images. Defined by a closed B-spline space curve, the individual trajectory is assumed to be cyclic and obtained by maximizing the metric of combined correlation coefficients. Local extrema are suppressed by improving the initial conditions using random walks from pair-wise optimizations. Our approach has been applied to analyze the vessel junctions in five real 4D respiration-gated computed tomography (CT) image datasets with promising results. More than 500 junctions in the lung are detected with an average accuracy of greater than 85% and the mean error between the automated and the manual tracking is sub-voxel.
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Jovanović B, Nikezić D, Stevanović N. Applied mathematical modeling for calculating the probability of the cell killing per hit in the human lung. J Radioanal Nucl Chem 2011. [DOI: 10.1007/s10967-011-1331-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Peterson ET, Dai J, Holmes JH, Fain SB. Measurement of lung airways in three dimensions using hyperpolarized helium-3 MRI. Phys Med Biol 2011; 56:3107-22. [PMID: 21521907 DOI: 10.1088/0031-9155/56/10/014] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Large airway measurement is clinically important in cases of airway disease and trauma. The gold standard is computed tomography (CT), which allows for airway measurement. However, the ionizing radiation dose associated with CT is a major limitation in longitudinal studies and trauma. To avoid ionizing radiation from CT, we present a method for measuring the large airway diameter in humans using hyperpolarized helium-3 (HPHe) MRI in conjunction with a dynamic 3D radial acquisition. An algorithm is introduced which utilizes the significant airway contrast for semi-automated segmentation and skeletonization which is used to derive the airway lumen diameter. The HPHe MRI method was validated with quantitative CT in an excised and desiccated porcine lung (linear regression R(2) = 0.974 and slope = 0.966 over 32 airway segments). The airway lumen diameters were then compared in 24 human subjects (22 asthmatics and 2 normals; linear regression R(2) value of 0.799 and slope = 0.768 over 309 airway segments). The feasibility for airway path analysis to areas of ventilation defect is also demonstrated.
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Affiliation(s)
- Eric T Peterson
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA
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Wang X, Fang C, Xia Y, Feng D. Airway segmentation for low-contrast CT images from combined PET/CT scanners based on airway modelling and seed prediction. Biomed Signal Process Control 2011. [DOI: 10.1016/j.bspc.2010.05.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Tawhai MH, Hoffman EA, Lin CL. The lung physiome: merging imaging-based measures with predictive computational models. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2010; 1:61-72. [PMID: 20835982 DOI: 10.1002/wsbm.17] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Global measurements of the lung provided by standard pulmonary function tests do not give insight into the regional basis of lung function and lung disease. Advances in imaging methodologies, computer technologies, and subject-specific simulations are creating new opportunities to study structure-function relationships in the lung through multidisciplinary research. The digital Human Lung Atlas is an image-based resource compiled from male and female subjects spanning several decades of age. The Atlas comprises both structural and functional measures, and includes computational models derived to match individual subjects for personalized prediction of function. The computational models in the Atlas form part of the Lung Physiome project, which is an international effort to develop integrative models of lung function at all levels of biological organization. The computational models provide mechanistic interpretation of imaging measures; the Atlas provides structural data on which to base model geometry, and functional data against which to test hypotheses. The example of simulating airflow on a subject-specific basis is considered. Methods for deriving multiscale models of the airway geometry for individual subjects in the Atlas are outlined, and methods for modeling turbulent flows in the airway are reviewed.
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Affiliation(s)
- Merryn H Tawhai
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Eric A Hoffman
- Department of Radiology and Biomedical Engineering, The University of Iowa, Iowa City, IA 52242, USA
| | - Ching-Long Lin
- Department of Mechanical Engineering and IIHR, The University of Iowa, Iowa City, IA 52242, USA
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Verscheure L, Peyrodie L, Makni N, Betrouni N, Maouche S, Vermandel M. Dijkstra's algorithm applied to 3D skeletonization of the brain vascular tree: evaluation and application to symbolic. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2010; 2010:3081-4. [PMID: 21095739 DOI: 10.1109/iembs.2010.5626112] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
This paper describes the methodology and the evaluation of a 3D skeletonization algorithm applied on brain vascular structure. This method is based on the application of the minimum cost-spanning tree using Dijkstra's algorithm and seems well appropriate to tubular objects. We briefly describe the different steps, from the segmentation to the skeleton analysis. Besides, we propose an original evaluation scheme of the method based on digital phantom and clinical data. The final aim of this work is to provide a symbolic description framework applied to cerebro-vascular structures.
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Affiliation(s)
- L Verscheure
- Inserm, U703 research unit. THAIS. Institut Hippocrate, 152 rue du Docteur Yersin 59120 Loos CHRU de Lille France.
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Scarr G. Simple geometry in complex organisms. J Bodyw Mov Ther 2010; 14:424-44. [DOI: 10.1016/j.jbmt.2008.11.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2008] [Revised: 10/22/2008] [Accepted: 11/22/2008] [Indexed: 11/30/2022]
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Abstract
Computed tomography has facilitated recognition that chronic obstructive pulmonary disease is not a single disease but encompasses several overlapping entities, including emphysema, bronchitis, and small airways disease. Quantitative computed tomography can effectively characterize and quantify the extent of emphysema, airway wall thickening, and air trapping related to small airways disease.
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