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https://www.readbyqxmd.com/read/28697731/texture-analysis-of-pulmonary-parenchymateous-changes-related-to-pulmonary-thromboembolism-in-dogs-a-novel-approach-using-quantitative-methods
#1
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
#2
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
#3
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
#4
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
#5
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
#6
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
https://www.readbyqxmd.com/read/28523350/comparison-of-a-radiomic-biomarker-with-volumetric-analysis-for-decoding-tumour-phenotypes-of-lung-adenocarcinoma-with-different-disease-specific-survival
#7
Mei Yuan, Yu-Dong Zhang, Xue-Hui Pu, Yan Zhong, Hai Li, Jiang-Fen Wu, Tong-Fu Yu
OBJECTIVES: To compare a multi-feature-based radiomic biomarker with volumetric analysis in discriminating lung adenocarcinomas with different disease-specific survival on computed tomography (CT) scans. METHODS: This retrospective study obtained institutional review board approval and was Health Insurance Portability and Accountability Act (HIPAA) compliant. Pathologically confirmed lung adenocarcinoma (n = 431) manifested as subsolid nodules on CT were identified...
May 18, 2017: European Radiology
https://www.readbyqxmd.com/read/28522257/can-ct-measures-of-tumour-heterogeneity-stratify-risk-for-nodal-metastasis-in-patients-with-non-small-cell-lung-cancer
#8
M Craigie, J Squires, K Miles
AIM: To undertake a preliminary assessment of the potential for computed tomography (CT) measurement of tumour heterogeneity to stratify risk of nodal metastasis in patients with non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: Tumour heterogeneity in CT images from combined positron-emission tomography (PET)/CT examinations in 150 consecutive patients with NSCLC was assessed using CT texture analysis (CTTA). The short axis diameter of the largest mediastinal node was also measured...
May 15, 2017: Clinical Radiology
https://www.readbyqxmd.com/read/28520778/texture-analysis-using-proton-density-and-t2-relaxation-in-patients-with-histological-usual-interstitial-pneumonia-uip-or-nonspecific-interstitial-pneumonia-nsip
#9
Maria T A Buzan, Andreas Wetscherek, Claus Peter Heussel, Michael Kreuter, Felix J Herth, Arne Warth, Hans-Ulrich Kauczor, Carmen Monica Pop, Julien Dinkel
OBJECTIVES: The purpose of our study was to assess proton density (PD) and T2 relaxation time of usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP) and to evaluate their utility in differentiating the two patterns. Furthermore, we aim to investigate whether these two parameters could help differentiate active-inflammatory and stable-fibrotic lesions in NSIP. METHODS: 32 patients (mean age: 69 years; M:F, 1:1) with pathologically proven disease (UIP:NSIP, 1:1), underwent thoracic thin-section multislice CT scan and 1...
2017: PloS One
https://www.readbyqxmd.com/read/28493789/idiopathic-pulmonary-fibrosis-data-driven-textural-analysis-of-extent-of-fibrosis-at-baseline-and-15-month-follow-up
#10
Stephen M Humphries, Kunihiro Yagihashi, Jason Huckleberry, Byung-Hak Rho, Joyce D Schroeder, Matthew Strand, Marvin I Schwarz, Kevin R Flaherty, Ella A Kazerooni, Edwin J R van Beek, David A Lynch
Purpose To evaluate associations between pulmonary function and both quantitative analysis and visual assessment of thin-section computed tomography (CT) images at baseline and at 15-month follow-up in subjects with idiopathic pulmonary fibrosis (IPF). Materials and Methods This retrospective analysis of preexisting anonymized data, collected prospectively between 2007 and 2013 in a HIPAA-compliant study, was exempt from additional institutional review board approval. The extent of lung fibrosis at baseline inspiratory chest CT in 280 subjects enrolled in the IPF Network was evaluated...
May 10, 2017: Radiology
https://www.readbyqxmd.com/read/28473055/automatic-feature-learning-using-multichannel-roi-based-on-deep-structured-algorithms-for-computerized-lung-cancer-diagnosis
#11
Wenqing Sun, Bin Zheng, Wei Qian
This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand-crafted features. All of the 1018 cases were acquired from Lung Image Database Consortium (LIDC) public lung cancer database. The nodules were segmented according to four radiologists' markings, and 13,668 samples were generated by rotating every slice of nodule images...
April 13, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28430603/tumor-heterogeneity-assessed-by-texture-analysis-on-contrast-enhanced-ct-in-lung-adenocarcinoma-association-with-pathologic-grade
#12
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...
February 16, 2017: Oncotarget
https://www.readbyqxmd.com/read/28422299/incorporation-of-pre-therapy-18-f-fdg-uptake-data-with-ct-texture-features-into-a-radiomics-model-for-radiation-pneumonitis-diagnosis
#13
Gregory J Anthony, Alexandra Cunliffe, Richard Castillo, Ngoc Pham, Thomas Guerrero, Samuel G Armato, Hania A Al-Hallaq
PURPOSE: To determine whether the addition of standardized uptake value (SUV) from PET scans to CT lung texture features could improve a radiomics-based model of radiation pneumonitis (RP) diagnosis in patients undergoing radiotherapy. METHODS AND MATERIALS: Anonymized data from 96 esophageal cancer patients (18 RP-positive cases of Grade ≥ 2) were collected including pre-therapy PET/CT scans, pre-/post-therapy diagnostic CT scans and RP status. Twenty texture features (first-order, fractal, Laws' filter and gray-level co-occurrence matrix) were calculated from diagnostic CT scans and compared in anatomically matched regions of the lung...
July 2017: Medical Physics
https://www.readbyqxmd.com/read/28409834/fully-automatic-detection-of-lung-nodules-in-ct-images-using-a-hybrid-feature%C3%A2-set
#14
Furqan Shaukat, Gulistan Raja, Ali Gooya, Alejandro F Frangi
PURPOSE: The aim of this study was to develop a novel technique for lung nodule detection using an optimized feature set. This feature set has been achieved after rigorous experimentation, which has helped in reducing the false positives significantly. METHOD: The proposed method starts with preprocessing, removing any present noise from input images, followed by lung segmentation using optimal thresholding. Then the image is enhanced using multiscale dot enhancement filtering prior to nodule detection and feature extraction...
April 13, 2017: Medical Physics
https://www.readbyqxmd.com/read/28392615/ultra-high-spatial-resolution-multi-energy-ct-using-photon-counting-detector-technology
#15
S Leng, R Gutjahr, A Ferrero, S Kappler, A Henning, A Halaweish, W Zhou, J Montoya, C McCollough
Two ultra-high-resolution (UHR) imaging modes, each with two energy thresholds, were implemented on a research, whole-body photon-counting-detector (PCD) CT scanner, referred to as sharp and UHR, respectively. The UHR mode has a pixel size of 0.25 mm at iso-center for both energy thresholds, with a collimation of 32 × 0.25 mm. The sharp mode has a 0.25 mm pixel for the low-energy threshold and 0.5 mm for the high-energy threshold, with a collimation of 48 × 0.25 mm. Kidney stones with mixed mineral composition and lung nodules with different shapes were scanned using both modes, and with the standard imaging mode, referred to as macro mode (0...
February 11, 2017: Proceedings of SPIE
https://www.readbyqxmd.com/read/28297322/evaluation-of-the-tool-reg-refine-for-user-guided-deformable-image-registration
#16
Perry B Johnson, Kyle R Padgett, Kuan L Chen, Nesrin Dogan
"Reg Refine" is a tool available in the MIM Maestro v6.4.5 platform (www.mimsoftware.com) that allows the user to actively participate in the deformable image registration process. The purpose of this work was to evaluate the efficacy of this tool and investigate strategies for how to apply it effectively. This was done by performing DIR on two publicly available ground-truth models, the Pixel-based Breathing Thorax Model (POPI) for lung, and the Deformable Image Registration Evaluation Project (DIREP) for head and neck...
May 2016: Journal of Applied Clinical Medical Physics
https://www.readbyqxmd.com/read/28295386/an-integrated-segmentation-and-shape-based-classification-scheme-for-distinguishing-adenocarcinomas-from-granulomas-on-lung-ct
#17
Mehdi Alilou, Niha Beig, Mahdi Orooji, Prabhakar Rajiah, Vamsidhar Velcheti, Sagar Rakshit, Niyoti Reddy, Michael Yang, Frank Jacono, Robert C Gilkeson, Philip Linden, Anant Madabhushi
PURPOSE: Distinguishing between benign granulmoas and adenocarcinomas is confounded by their similar visual appearance on routine CT scans. Unfortunately, owing to the inability to discriminate these lesions radigraphically, many patients with benign granulomas are subjected to unnecessary surgical wedge resections and biopsies for pathologic confirmation of cancer presence or absence. This suggests the need for improved computerized characterization of these nodules in order to distinguish between these two classes of lesions on CT scans...
March 14, 2017: Medical Physics
https://www.readbyqxmd.com/read/28268558/texton-and-sparse-representation-based-texture-classification-of-lung-parenchyma-in-ct-images
#18
Jie Yang, Xinyang Feng, Elsa D Angelini, Andrew F Laine
Automated texture analysis of lung computed tomography (CT) images is a critical tool in subtyping pulmonary emphysema and diagnosing chronic obstructive pulmonary disease (COPD). Texton-based methods encode lung textures with nearest-texton frequency histograms, and have achieved high performance for supervised classification of emphysema subtypes from annotated lung CT images. In this work, we first explore characterizing lung textures with sparse decomposition from texton dictionaries, using different regularization strategies, and then extend the sparsity-inducing constraint to the construction of the dictionaries...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268557/prediction-of-malignant-and-benign-of-lung-tumor-using-a-quantitative-radiomic-method
#19
Jun Wang, Xia Liu, Di Dong, Jiangdian Song, Min Xu, Yali Zang, Jie Tian
Lung cancer is the leading cause of cancer mortality around the world, the early diagnosis of lung cancer plays a very important role in therapeutic regimen selection. However, lung cancers are spatially and temporally heterogeneous; this limits the use of invasive biopsy. But radiomics which refers to the comprehensive quantification of tumour phenotypes by applying a large number of quantitative image features has the ability to capture intra-tumoural heterogeneity in a non-invasive way. Here we carry out a radiomic analysis of 150 features quantifying lung tumour image intensity, shape and texture...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268556/association-between-tumor-heterogeneity-and-progression-free-survival-in-non-small-cell-lung-cancer-patients-with-egfr-mutations-undergoing-tyrosine-kinase-inhibitors-therapy
#20
Jiangdian Song, Di Dong, Yanqi Huang, Yali Zang, Zaiyi Liu, Jie Tian
For non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations, current staging methods do not accurately predict the risk of disease recurrence after tyrosine kinase inhibitors (TKI) therapy. Developing a noninvasive method to predict whether individual could benefit from TKI therapy has great clinical significance. In this research, a radiomics approach was proposed to determine whether the tumor heterogeneity of NSCLC, which was measured by the texture on computed tomography (CT), could make an independent prediction of progression-free survival (PFS)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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