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CT lung texture

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https://www.readbyqxmd.com/read/29060752/content-based-retrieval-for-lung-nodule-diagnosis-using-learned-distance-metric
#1
Guohui Wei, He Ma, Wei Qian, Hongyang Jiang, Xinzhuo Zhao
Similarity metric of the lung nodules can be useful in differentiating between benign and malignant lung nodule lesions on computed tomography (CT). Unlike previous computerized schemes, which focus on the features extracting, we concentrate on similarity metric of the lung nodules. In this study, we first assemble a lung nodule dataset which is from LIDC-IDRI lung CT images. This dataset includes 746 lung nodules in which 375 domain radiologists identified malignant nodules and 371 domain radiologists-identified benign nodules...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29036692/clinical-utility-of-texture-analysis-of-18f-fdg-pet-ct-in-patients-with-stage-i-lung-cancer-treated-with-stereotactic-body-radiotherapy
#2
Kazuya Takeda, Kentaro Takanami, Yuko Shirata, Takaya Yamamoto, Noriyoshi Takahashi, Kengo Ito, Kei Takase, Keiichi Jingu
We evaluated the reproducibility and predictive value of texture parameters and existing parameters of 18F-FDG PET/CT images in Stage I non-small-cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT). Twenty-six patients with Stage I NSCLC (T1-2N0M0) were retrospectively analyzed. All of the patients underwent an 18F-FDG PET/CT scan before treatment and were treated with SBRT. Each tumor was delineated using PET Edge (MIM Software Inc., Cleveland, OH), and texture parameters were calculated using open-source code CGITA...
September 21, 2017: Journal of Radiation Research
https://www.readbyqxmd.com/read/28961108/low-dose-lung-ct-image-restoration-using-adaptive-prior-features-from-full-dose-training-database
#3
Yuanke Zhang, Junyan Rong, Hongbing Lu, Yuxiang Xing, Jing Meng
The valuable structure features in full-dose CT (FdCT) scans can be exploited as prior knowledge for low-dose CT (LdCT) imaging. However, lacking the capability to represent local characteristics of interested structures of the LdCT image adaptively may result in poor preservation of details/textures in LdCT image. This study aims to explore a novel prior knowledge retrieval and representation paradigm, called adaptive prior features assisted restoration algorithm (APFA), for the purpose of better restoration of the low-dose lung CT images by capturing local features from FdCT scans adaptively...
September 27, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28944403/prediction-of-disease-free-survival-by-the-pet-ct-radiomic-signature-in-non-small-cell-lung-cancer-patients-undergoing-surgery
#4
Margarita Kirienko, Luca Cozzi, Lidija Antunovic, Lisa Lozza, Antonella Fogliata, Emanuele Voulaz, Alexia Rossi, Arturo Chiti, Martina Sollini
PURPOSE: Radiomic features derived from the texture analysis of different imaging modalities e show promise in lesion characterisation, response prediction, and prognostication in lung cancer patients. The present study aimed to identify an images-based radiomic signature capable of predicting disease-free survival (DFS) in non-small cell lung cancer (NSCLC) patients undergoing surgery. METHODS: A cohort of 295 patients was selected. Clinical parameters (age, sex, histological type, tumour grade, and stage) were recorded for all patients...
September 24, 2017: European Journal of Nuclear Medicine and Molecular Imaging
https://www.readbyqxmd.com/read/28934225/harmonizing-the-pixel-size-in-retrospective-computed-tomography-radiomics-studies
#5
Dennis Mackin, Xenia Fave, Lifei Zhang, Jinzhong Yang, A Kyle Jones, Chaan S Ng, Laurence Court
Consistent pixel sizes are of fundamental importance for assessing texture features that relate intensity and spatial information in radiomics studies. To correct for the effects of variable pixel sizes, we combined image resampling with Butterworth filtering in the frequency domain and tested the correction on computed tomography (CT) scans of lung cancer patients reconstructed 5 times with pixel sizes varying from 0.59 to 0.98 mm. One hundred fifty radiomics features were calculated for each preprocessing and field-of-view combination...
2017: PloS One
https://www.readbyqxmd.com/read/28929225/prediction-of-survival-by-texture-based-automated-quantitative-assessment-of-regional-disease-patterns-on-ct-in-idiopathic-pulmonary-fibrosis
#6
Sang Min Lee, Joon Beom Seo, Sang Young Oh, Tae Hoon Kim, Jin Woo Song, Sang Min Lee, Namkug Kim
OBJECTIVES: To retrospectively investigate whether the baseline extent and 1-year change in regional disease patterns on CT can predict survival of patients with idiopathic pulmonary fibrosis (IPF). METHODS: A total of 144 IPF patients with CT scans at the time of diagnosis and 1 year later were included. The extents of five regional disease patterns were quantified using an in-house texture-based automated system. The fibrosis score was defined as the sum of the extent of honeycombing and reticular opacity...
September 19, 2017: European Radiology
https://www.readbyqxmd.com/read/28898189/ct-texture-analysis-definitions-applications-biologic-correlates-and-challenges
#7
Meghan G Lubner, Andrew D Smith, Kumar Sandrasegaran, Dushyant V Sahani, Perry J Pickhardt
This review discusses potential oncologic and nononcologic applications of CT texture analysis ( CTTA CT texture analysis ), an emerging area of "radiomics" that extracts, analyzes, and interprets quantitative imaging features. CTTA CT texture analysis allows objective assessment of lesion and organ heterogeneity beyond what is possible with subjective visual interpretation and may reflect information about the tissue microenvironment. CTTA CT texture analysis has shown promise in lesion characterization, such as differentiating benign from malignant or more biologically aggressive lesions...
September 2017: Radiographics: a Review Publication of the Radiological Society of North America, Inc
https://www.readbyqxmd.com/read/28881840/tumor-heterogeneity-assessed-by-texture-analysis-on-contrast-enhanced-ct-in-lung-adenocarcinoma-association-with-pathologic-grade
#8
Ying Liu, Shichang Liu, Fangyuan Qu, Qian Li, Runfen Cheng, Zhaoxiang Ye
Objectives To investigate whether texture features on contrast-enhanced computed tomography (CECT) images of lung adenocarcinoma have association with pathologic grade. Methods A cohort of 148 patients with surgically operated adenocarcinoma was retrospectively reviewed. Fifty-four CT features of the primary lung tumor were extracted from CECT images using open-source 3D Slicer software; meanwhile, enhancement homogeneity was evaluated by two radiologists using visual assessment. Multivariate logistic regression analysis was performed to determine significant image indicator of pathologic grade...
August 8, 2017: Oncotarget
https://www.readbyqxmd.com/read/28856247/quantitative-image-quality-comparison-of-reduced-and-standard-dose-dual-energy-multiphase-chest-abdomen-and-pelvis-ct
#9
Mario Buty, Ziyue Xu, Aaron Wu, Mingchen Gao, Chelyse Nelson, Georgios Z Papadakis, Uygar Teomete, Haydar Celik, Baris Turkbey, Peter Choyke, Daniel J Mollura, Ulas Bagci, Les R Folio
We present a new image quality assessment method for determining whether reducing radiation dose impairs the image quality of computed tomography (CT) in qualitative and quantitative clinical analyses tasks. In this Institutional Review Board-exempt study, we conducted a review of 50 patients (male, 22; female, 28) who underwent reduced-dose CT scanning on the first follow-up after standard-dose multiphase CT scanning. Scans were for surveillance of von Hippel-Lindau disease (N = 26) and renal cell carcinoma (N = 10)...
June 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28844845/lepidic-predominant-pulmonary-lesions-lpl-ct-based-distinction-from-more-invasive-adenocarcinomas-using-3d-volumetric-density-and-first-order-ct-texture-analysis
#10
Jeffrey B Alpert, Henry Rusinek, Jane P Ko, Bari Dane, Harvey I Pass, Bernard K Crawford, Amy Rapkiewicz, David P Naidich
RATIONALE AND OBJECTIVES: This study aimed to differentiate pathologically defined lepidic predominant lesions (LPL) from more invasive adenocarcinomas (INV) using three-dimensional (3D) volumetric density and first-order texture histogram analysis of surgically excised stage 1 lung adenocarcinomas. MATERIALS AND METHODS: This retrospective study was institutional review board approved and Health Insurance Portability and Accountability Act compliant. Sixty-four cases of pathologically proven stage 1 lung adenocarcinoma surgically resected between September 2006 and October 2015, including LPL (n = 43) and INV (n = 21), were evaluated using high-resolution computed tomography...
August 24, 2017: Academic Radiology
https://www.readbyqxmd.com/read/28839156/diagnostic-classification-of-solitary-pulmonary-nodules-using-dual-time-18-f-fdg-pet-ct-image-texture-features-in-granuloma-endemic-regions
#11
Song Chen, Stephanie Harmon, Timothy Perk, Xuena Li, Meijie Chen, Yaming Li, Robert Jeraj
Lung cancer, the most commonly diagnosed cancer worldwide, usually presents as solid pulmonary nodules (SPNs) on early diagnostic images. Classification of malignant disease at this early timepoint is critical for improving the success of surgical resection and increasing 5-year survival rates. (18)F-fluorodeoxyglucose ((18)F-FDG) PET/CT has demonstrated value for SPNs diagnosis with high sensitivity to detect malignant SPNs, but lower specificity in diagnosing malignant SPNs in populations with endemic infectious lung disease...
August 24, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28807589/differences-in-texture-analysis-parameters-between-active-alveolitis-and-lung-fibrosis-in-chest-ct-of-patients-with-systemic-sclerosis-a-feasibility-study
#12
Christopher Kloth, Anya C Blum, Wolfgang M Thaiss, Heike Preibsch, Hendrik Ditt, Rainer Grimmer, Jan Fritz, Konstantin Nikolaou, Hans Bösmüller, Marius Horger
RATIONALE AND OBJECTIVES: This study aimed to determine the diagnostic aid of computed tomography (CT) features for the differentiation of active alveolitis and fibrosis using a CT texture analysis (CTTA) prototype and CT densitometry in patients with systemic sclerosis (SSc) using ancillary high-resolution computed tomography (HRCT) features and their longitudinal course as standard of reference. MATERIALS AND METHODS: We retrospectively analyzed thin-slice noncontrast chest CT image data of 43 patients with SSc (18 men, mean age 51...
August 11, 2017: Academic Radiology
https://www.readbyqxmd.com/read/28748524/the-effects-of-segmentation-algorithms-on-the-measurement-of-18-f-fdg-pet-texture-parameters-in-non-small-cell-lung-cancer
#13
Usman Bashir, Gurdip Azad, Muhammad Musib Siddique, Saana Dhillon, Nikheel Patel, Paul Bassett, David Landau, Vicky Goh, Gary Cook
BACKGROUND: Measures of tumour heterogeneity derived from 18-fluoro-2-deoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) scans are increasingly reported as potential biomarkers of non-small cell lung cancer (NSCLC) for classification and prognostication. Several segmentation algorithms have been used to delineate tumours, but their effects on the reproducibility and predictive and prognostic capability of derived parameters have not been evaluated. The purpose of our study was to retrospectively compare various segmentation algorithms in terms of inter-observer reproducibility and prognostic capability of texture parameters derived from non-small cell lung cancer (NSCLC) (18)F-FDG PET/CT images...
December 2017: EJNMMI Research
https://www.readbyqxmd.com/read/28727543/non-small-cell-lung-cancer-radiogenomics-map-identifies-relationships-between-molecular-and-imaging-phenotypes-with-prognostic-implications
#14
Mu Zhou, Ann Leung, Sebastian Echegaray, Andrew Gentles, Joseph B Shrager, Kristin C Jensen, Gerald J Berry, Sylvia K Plevritis, Daniel L Rubin, Sandy Napel, Olivier Gevaert
Purpose To create a radiogenomic map linking computed tomographic (CT) image features and gene expression profiles generated by RNA sequencing for patients with non-small cell lung cancer (NSCLC). Materials and Methods A cohort of 113 patients with NSCLC diagnosed between April 2008 and September 2014 who had preoperative CT data and tumor tissue available was studied. For each tumor, a thoracic radiologist recorded 87 semantic image features, selected to reflect radiologic characteristics of nodule shape, margin, texture, tumor environment, and overall lung characteristics...
July 20, 2017: Radiology
https://www.readbyqxmd.com/read/28697731/texture-analysis-of-pulmonary-parenchymateous-changes-related-to-pulmonary-thromboembolism-in-dogs-a-novel-approach-using-quantitative-methods
#15
C B Marschner, M Kokla, J M Amigo, E A Rozanski, B Wiinberg, F J McEvoy
BACKGROUND: Diagnosis of pulmonary thromboembolism (PTE) in dogs relies on computed tomography pulmonary angiography (CTPA), but detailed interpretation of CTPA images is demanding for the radiologist and only large vessels may be evaluated. New approaches for better detection of smaller thrombi include dual energy computed tomography (DECT) as well as computer assisted diagnosis (CAD) techniques. The purpose of this study was to investigate the performance of quantitative texture analysis for detecting dogs with PTE using grey-level co-occurrence matrices (GLCM) and multivariate statistical classification analyses...
July 11, 2017: BMC Veterinary Research
https://www.readbyqxmd.com/read/28615677/associations-between-radiologist-defined-semantic-and-automatically-computed-radiomic-features-in-non-small-cell-lung-cancer
#16
Stephen S F Yip, Ying Liu, Chintan Parmar, Qian Li, Shichang Liu, Fangyuan Qu, Zhaoxiang Ye, Robert J Gillies, Hugo J W L Aerts
Tumor phenotypes captured in computed tomography (CT) images can be described qualitatively and quantitatively using radiologist-defined "semantic" and computer-derived "radiomic" features, respectively. While both types of features have shown to be promising predictors of prognosis, the association between these groups of features remains unclear. We investigated the associations between semantic and radiomic features in CT images of 258 non-small cell lung adenocarcinomas. The tumor imaging phenotypes were described using 9 qualitative semantic features that were scored by radiologists, and 57 quantitative radiomic features that were automatically calculated using mathematical algorithms...
June 14, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28612050/a-rapid-segmentation-insensitive-digital-biopsy-method-for-radiomic-feature-extraction-method-and-pilot-study-using-ct-images-of-non-small-cell-lung-cancer
#17
Sebastian Echegaray, Viswam Nair, Michael Kadoch, Ann Leung, Daniel Rubin, Olivier Gevaert, Sandy Napel
Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts. We propose a new paradigm, called "digital biopsy," that allows for the collection of intensity- and texture-based features from these regions at least 1 order of magnitude faster than the current manual or semiautomated methods. A radiologist reviewed automated segmentations of lung nodules from 100 preoperative volume computed tomography scans of patients with non-small cell lung cancer, and manually adjusted the nodule boundaries in each section, to be used as a reference standard, requiring up to 45 minutes per nodule...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28604371/factors-influencing-the-robustness-of-p-value-measurements-in-ct-texture-prognosis-studies
#18
Sarah McQuaid, James Scuffham, Sheaka Alobaidli, Vineet Prakash, Veni Ezhil, Andrew Nisbet, Christopher South, Philip Evans
Several studies have recently reported on the value of CT texture analysis in predicting survival, although the topic remains controversial, with further validation needed in order to consolidate the evidence base. The aim of this study was to investigate the effect of varying the input parameters in the Kaplan-Meier analysis, to determine whether the resulting P-value can be considered to be a robust indicator of the parameter's prognostic potential. A retrospective analysis of the CT-based normalised entropy of 51 patients with lung cancer was performed and overall survival data for these patients were collected...
July 7, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28552117/feature-selection-using-ant-colony-optimization-with-tandem-run-recruitment-to-diagnose-bronchitis-from-ct-scan-images
#19
J Dhalia Sweetlin, H Khanna Nehemiah, A Kannan
BACKGROUND AND OBJECTIVES: Computer-aided diagnosis (CAD) plays a vital role in the routine clinical activity for the detection of lung disorders using computed tomography (CT) images. It serves as a source of second opinion that radiologists may consider in order to interpret CT images. In this work, the purpose of CAD is to improve the diagnostic accuracy of pulmonary bronchitis from CT images of the lung. METHODS: Left and right lung fields are segmented using optimal thresholding from the lung CT images...
July 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28545080/computerized-margin-and-texture-analyses-for-differentiating-bacterial-pneumonia-and-invasive-mucinous-adenocarcinoma-presenting-as-consolidation
#20
Hyun Jung Koo, Mi Young Kim, Ja Hwan Koo, Yu Sub Sung, Jiwon Jung, Sung-Han Kim, Chang-Min Choi, Hwa Jung Kim
Radiologists have used margin characteristics based on routine visual analysis; however, the attenuation changes at the margin of the lesion on CT images have not been quantitatively assessed. We established a CT-based margin analysis method by comparing a target lesion with normal lung attenuation, drawing a slope to represent the attenuation changes. This approach was applied to patients with invasive mucinous adenocarcinoma (n = 40) or bacterial pneumonia (n = 30). Correlations among multiple regions of interest (ROIs) were obtained using intraclass correlation coefficient (ICC) values...
2017: PloS One
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