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https://www.readbyqxmd.com/read/29685079/method-to-characterize-inorganic-particulates-in-lung-tissue-biopsies-using-field-emission-scanning-electron-microscopy
#1
Heather A Lowers, G N Breit, M Strand, R M Pillers, G P Meeker, T I Todorov, G S Plumlee, R E Wolf, M Robinson, J Parr, R Miller, S Groshong, F Green, C Rose
Humans accumulate large numbers of inorganic particles in their lungs over a lifetime. Whether this causes or contributes to debilitating disease over a normal lifespan depends on the type and concentration of the particles. We developed and tested a protocol for in situ characterization of the types and distribution of inorganic particles in biopsied lung tissue from three human groups using field emission scanning electron microscopy (FE-SEM) combined with energy dispersive spectroscopy (EDS). Many distinct particle types were recognized among the 13 000 particles analyzed...
April 23, 2018: Toxicology Mechanisms and Methods
https://www.readbyqxmd.com/read/29667885/radiomics-approach-to-prediction-of-occult-mediastinal-lymph-node-metastasis-of-lung-adenocarcinoma
#2
Yan Zhong, Mei Yuan, Teng Zhang, Yu-Dong Zhang, Hai Li, Tong-Fu Yu
OBJECTIVE: The purpose of this study was to evaluate the prognostic impact of radiomic features from CT scans in predicting occult mediastinal lymph node (LN) metastasis of lung adenocarcinoma. MATERIALS AND METHODS: A total of 492 patients with lung adenocarcinoma who underwent preoperative unenhanced chest CT were enrolled in the study. A total of 300 radiomics features quantifying tumor intensity, texture, and wavelet were extracted from the segmented entire-tumor volume of interest of the primary tumor...
April 18, 2018: AJR. American Journal of Roentgenology
https://www.readbyqxmd.com/read/29662920/assessing-ct-acquisition-parameters-with-visual-search-model-observers
#3
Zohreh Karbaschi, Howard C Gifford
A principal difference between the channelized Hotelling (CH) and visual-search (VS) model observers is how they respond to noise texture in images. We compared the two observers in lesion-detection studies to evaluate linear and angular sampling parameters for CT. Simulated lung images were generated from a single two-dimensional mathematical torso phantom containing circular lesions of fixed radius and relative contrast. Projection datasets were produced for two detector pixel sizes and from 15 to 128 projections at 15 and 65 M counts per set...
April 2018: Journal of Medical Imaging
https://www.readbyqxmd.com/read/29650315/radiomics-based-features-for-pattern-recognition-of-lung-cancer-histopathology-and-metastases
#4
José Raniery Ferreira Junior, Marcel Koenigkam-Santos, Federico Enrique Garcia Cipriano, Alexandre Todorovic Fabro, Paulo Mazzoncini de Azevedo-Marques
BACKGROUND AND OBJECTIVES: lung cancer is the leading cause of cancer-related deaths in the world, and its poor prognosis varies markedly according to tumor staging. Computed tomography (CT) is the imaging modality of choice for lung cancer evaluation, being used for diagnosis and clinical staging. Besides tumor stage, other features, like histopathological subtype, can also add prognostic information. In this work, radiomics-based CT features were used to predict lung cancer histopathology and metastases using machine learning models...
June 2018: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/29623375/ability-of-fdg-pet-and-ct-radiomics-features-to-differentiate-between-primary-and-metastatic-lung-lesions
#5
Margarita Kirienko, Luca Cozzi, Alexia Rossi, Emanuele Voulaz, Lidija Antunovic, Antonella Fogliata, Arturo Chiti, Martina Sollini
PURPOSE: To evaluate the ability of CT and PET radiomics features to classify lung lesions as primary or metastatic, and secondly to differentiate histological subtypes of primary lung cancers. METHODS: A cohort of 534 patients with lung lesions were retrospectively studied. Radiomics texture features were extracted using the LIFEx package from semiautomatically segmented PET and CT images. Histology data were recorded in all patients. The patient cohort was divided into a training and a validation group and linear discriminant analysis (LDA) was performed to classify the lesions using both direct and backward stepwise methods...
April 6, 2018: European Journal of Nuclear Medicine and Molecular Imaging
https://www.readbyqxmd.com/read/29616661/shell-feature-a-new-radiomics-descriptor-for-predicting-distant-failure-after-radiotherapy-in-non-small-cell-lung-cancer-and-cervix-cancer
#6
Hongxia Hao, Zhiguo Zhou, Shulong Li, Genevieve Maquilan, Michael R Folkert, Puneeth Iyengar, Kenneth D Westover, Kevin Albuquerque, Fang Liu, Hak Choy, Robert D Timmerman, Lin Yang, Jing Wang
Distant failure is the main cause for human cancer-related mortalities. To develop a model for predicting distant failure in non-small cell lung cancer (NSCLC) and cervix caner (CC) patients, a shell feature, consisting of outer voxels around the tumor boundary, was constructed using pre-treatment positron emission tomography (PET) images from 48 NSCLC patients received stereotactic body radiation therapy (SBRT) and 52 CC patients underwent external beam radiation therapy and concurrent chemotherapy followed with high-dose-rate intracavitary brachytherapy...
April 4, 2018: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/29608508/tumor-heterogeneity-hypoxia-and-immune-markers-in-surgically-resected-non-small-cell-lung-cancer
#7
Angelo Castello, Fabio Grizzi, Luca Toschi, Sabrina Rossi, Daoud Rahal, Federica Marchesi, Carlo Russo, Giovanna Finocchiaro, Egesta Lopci
OBJECTIVES: This study aimed to determine the prognostic role of textural features and their association with metabolic parameters, hypoxia, and cancer-related immune markers in non-small-cell lung cancer (NSCLC) patients. PATIENTS AND METHODS: The trial was registered at http://www.clinicaltrials.gov (NCT02519062). From January 2010 to May 2014, 44 patients (male : female=33 : 11; median age: 69.5 years), referred to our Institution for NSCLC resection, were enrolled...
March 30, 2018: Nuclear Medicine Communications
https://www.readbyqxmd.com/read/29599334/evaluation-of-shape-and-textural-features-from-ct-as-prognostic-biomarkers-in-non-small-cell-lung-cancer
#8
Francesco Bianconi, Mario Luca Fravolini, Raquel Bello-Cerezo, Matteo Minestrini, Michele Scialpi, Barbara Palumbo
BACKGROUND/AIM: We retrospectively investigated the prognostic potential (correlation with overall survival) of 9 shape and 21 textural features from non-contrast-enhanced computed tomography (CT) in patients with non-small-cell lung cancer. MATERIALS AND METHODS: We considered a public dataset of 203 individuals with inoperable, histologically- or cytologically-confirmed NSCLC. Three-dimensional shape and textural features from CT were computed using proprietary code and their prognostic potential evaluated through four different statistical protocols...
April 2018: Anticancer Research
https://www.readbyqxmd.com/read/29571806/pulmonary-nodules-assessing-the-imaging-biomarkers-of-malignancy-in-a-coffee-break
#9
A Talwar, J M Y Willaime, L C Pickup, M Enescu, D Boukerroui, W Hickes, N M Rahman, M J Gooding, T Kadir, F V Gleeson
INTRODUCTION: Although nodule volumetry is a recognized biomarker of malignancy in pulmonary nodules (PNs), caution is needed in its interpretation because of variables such as respiratory volume variation and inter-scan variability of up to 25%. CT Texture Analysis (CTTA) is a potential independent biomarker of malignancy but inter-scan variability and respiratory volume variation has not been assessed. METHODS: In this prospective cohort study, 40 patients (20 with an indeterminate PN and 20 with pulmonary metastases) underwent two LDCTs within a 60-min period (the "Coffee-break") with the aim of assessing the repeatability of CTTA and semi-automated volume measurements...
April 2018: European Journal of Radiology
https://www.readbyqxmd.com/read/29571801/chest-ct-texture-analysis-for-response-assessment-in-systemic-sclerosis
#10
C Kloth, J Henes, T Xenitidis, W M Thaiss, A C Blum, J Fritz, K Nikolaou, M Horger, Sorin Dumitru Ioanoviciu
PURPOSE: To evaluate the role of CT-textural features for monitoring lung involvement in subjects with systemic sclerosis(SSc) undergoing autologous stem cell transplantation(SCT) by comparison with semi-quantitative chest-CT, pulmonary function tests(PFT) and clinical parameters (modified Rodnan skin score[mRSS]). METHODS: In a retrospective single centre analysis, we identified 23 consecutive subjects(11male) with SSc between 07/2005 and 11/2016 that underwent chest CTs before, 6 and 12 months post-SCT...
April 2018: European Journal of Radiology
https://www.readbyqxmd.com/read/29563137/a-new-approach-to-predict-progression-free-survival-in-stage-iv-egfr-mutant-nsclc-patients-with-egfr-tki-therapy
#11
Jiangdian Song, Jingyun Shi, Di Dong, Mengjie Fang, Wenzhao Zhong, Kun Wang, Ning Wu, Yanqi Huang, Zhenyu Liu, Yue Cheng, Yuncui Gan, Yongzhao Zhou, Ping Zhou, Bojiang Chen, Changhong Liang, Zaiyi Liu, Weimin Li, Jie Tian
PURPOSE: We established a computed tomography (CT)-derived approach to achieve accurate progression-free survival (PFS) prediction to EGFR tyrosine kinase inhibitors (TKIs) therapy in multicenter, stage IV EGFR-mutated non-small-cell lung cancer (NSCLC) patients. EXPERIMENTAL DESIGN: 1032 CT-based phenotypic characteristics were extracted according to the intensity, shape and texture of NSCLC pre-therapy images. Based on these CT features extracted from 117 stage IV EGFR-mutant NSCLC patients, a CT-based phenotypic signature was proposed using a Cox regression model with LASSO penalty for the survival risk stratification of EGFR-TKI therapy...
March 21, 2018: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
https://www.readbyqxmd.com/read/29550204/a-texture-analysis-based-prediction-model-for-lymph-node-metastasis-in-stage-ia-lung-adenocarcinoma
#12
Yawei Gu, Yunlang She, Chenyang Dai, Yijiu Ren, Ziwen Fan, Huiyuan Zhu, Xiwen Sun, Huikang Xie, Gening Jiang, Dong Xie, Chang Chen
BACKGROUND: Some clinical N0 lung adenocarcinoma have been pathologically diagnosed as N1 or N2. To improve the preoperative diagnostic accuracy of lymph node (LN) disease, we developed a prediction model for LN metastasis in cT1N0M0 lung adenocarcinoma based on computed tomography (CT) texture analysis and clinical characteristics to estimate the probability of LN metastasis. METHODS: The records of 501 consecutive patients with cT1N0M0 lung adenocarcinoma who underwent CT scan and pulmonary resection with systematic lymph nodes dissection or lymph nodes sampling were reviewed...
March 14, 2018: Annals of Thoracic Surgery
https://www.readbyqxmd.com/read/29519407/exploration-of-temporal-stability-and-prognostic-power-of-radiomic-features-based-on-electronic-portal-imaging-device-images
#13
Mazen Soufi, Hidetaka Arimura, Takahiro Nakamoto, Taka-Aki Hirose, Saiji Ohga, Yoshiyuki Umezu, Hiroshi Honda, Tomonari Sasaki
PURPOSE: We aimed to explore the temporal stability of radiomic features in the presence of tumor motion and the prognostic powers of temporally stable features. METHODS: We selected single fraction dynamic electronic portal imaging device (EPID) (n = 275 frames) and static digitally reconstructed radiographs (DRRs) of 11 lung cancer patients, who received stereotactic body radiation therapy (SBRT) under free breathing. Forty-seven statistical radiomic features, which consisted of 14 histogram-based features and 33 texture features derived from the graylevel co-occurrence and graylevel run-length matrices, were computed...
February 2018: Physica Medica: PM
https://www.readbyqxmd.com/read/29513054/influence-of-inter-observer-delineation-variability-on-radiomics-stability-in-different-tumor-sites
#14
Matea Pavic, Marta Bogowicz, Xaver Würms, Stefan Glatz, Tobias Finazzi, Oliver Riesterer, Johannes Roesch, Leonie Rudofsky, Martina Friess, Patrick Veit-Haibach, Martin Huellner, Isabelle Opitz, Walter Weder, Thomas Frauenfelder, Matthias Guckenberger, Stephanie Tanadini-Lang
BACKGROUND: Radiomics is a promising methodology for quantitative analysis and description of radiological images using advanced mathematics and statistics. Tumor delineation, which is still often done manually, is an essential step in radiomics, however, inter-observer variability is a well-known uncertainty in radiation oncology. This study investigated the impact of inter-observer variability (IOV) in manual tumor delineation on the reliability of radiomic features (RF). METHODS: Three different tumor types (head and neck squamous cell carcinoma (HNSCC), malignant pleural mesothelioma (MPM) and non-small cell lung cancer (NSCLC)) were included...
March 7, 2018: Acta Oncologica
https://www.readbyqxmd.com/read/29494598/18f-fluorodeoxyglucose-positron-emission-tomography-fdg-pet-radiomics-of-metastatic-lymph-nodes-and-primary-tumor-in-non-small-cell-lung-cancer-nsclc-a-prospective-externally-validated-study
#15
Sara Carvalho, Ralph T H Leijenaar, Esther G C Troost, Janna E van Timmeren, Cary Oberije, Wouter van Elmpt, Lioe-Fee de Geus-Oei, Johan Bussink, Philippe Lambin
BACKGROUND: Lymph node stage prior to treatment is strongly related to disease progression and poor prognosis in non-small cell lung cancer (NSCLC). However, few studies have investigated metabolic imaging features derived from pre-radiotherapy 18F-fluorodeoxyglucose (FDG) positron-emission tomography (PET) of metastatic hilar/mediastinal lymph nodes (LNs). We hypothesized that these would provide complementary prognostic information to FDG-PET descriptors to only the primary tumor (tumor)...
2018: PloS One
https://www.readbyqxmd.com/read/29492880/multistage-segmentation-model-and-svm-ensemble-for-precise-lung-nodule-detection
#16
Syed Muhammad Naqi, Muhammad Sharif, Mussarat Yasmin
PURPOSE: Lung cancer detection at its initial stages increases the survival chances of patients. Automatic detection of lung nodules facilitates radiologists during the diagnosis. However, there is a challenge of false positives in automated systems which may lead to wrong findings. Precise segmentation facilitates to accurately extract nodules from lung CT images in order to improve performance of the diagnostic method. METHODS: A multistage segmentation model is presented in this study...
February 28, 2018: International Journal of Computer Assisted Radiology and Surgery
https://www.readbyqxmd.com/read/29477490/ct-texture-analysis-of-subsolid-nodules-for-differentiating-invasive-from-in-situ-and-minimally-invasive-lung-adenocarcinoma-subtypes
#17
J G Cohen, E Reymond, M Medici, M Lederlin, S Lantuejoul, F Laurent, A C Toffart, A Moreau-Gaudry, A Jankowski, G R Ferretti
PURPOSE: The purpose of this study was to evaluate the usefulness of computed tomography-texture analysis (CTTA) in differentiating between in-situ and minimally-invasive from invasive adenocarcinomas in subsolid lung nodules (SSLNs). MATERIAL AND METHODS: Two radiologists retrospectively reviewed 49 SSLNs in 44 patients. There were 27 men and 17 women with a mean age of 63±7 (SD) years (range: 47-78years). For each SSLN, type (pure ground-glass or part-solid) was assessed by consensus and CTTA was conducted independently by each observer using a filtration-histogram technique...
February 21, 2018: Diagnostic and Interventional Imaging
https://www.readbyqxmd.com/read/29469054/significance-of-the-impact-of-motion-compensation-on-the-variability-of-pet-image-features
#18
Montserrat Carles, Thomas Bach, Irene Torres-Espallardo, Dimos Baltas, Ursula Nestle, Luis Martí-Bonmatí
In lung cancer, quantification by Positron-Emission-Tomography/Computed-Tomography (PET/CT) imaging presents challenges due to respiratory movement. Our primary aim was to study the impact of the compensation of motion implied by retrospectively gated (4D)-PET/CT on the variability of PET quantitative parameters. Its significance was evaluated by comparison with respect to the variability due to (i) the voxel size comprised by image reconstruction and (ii) the voxel size in image post-resampling. The method employed for features extraction was chosen based on the analysis of: (i) the effect of the standardized-uptake-value (SUV) discretization on the complementarity between texture features (TF) and the conventional indexes; (ii) the impact of the segmentation method on image features variability and (iii) the variability of image features across the time frames of 4D-PET...
February 22, 2018: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/29457229/radiomics-analysis-of-pulmonary-nodules-in-low-dose-ct-for-early-detection-of-lung-cancer
#19
Wookjin Choi, Jung Hun Oh, Sadegh Riyahi, Chia-Ju Liu, Feng Jiang, Wengen Chen, Charles White, Andreas Rimner, James G Mechalakos, Joseph O Deasy, Wei Lu
PURPOSE: To develop a radiomics prediction model to improve pulmonary nodule (PN) classification in low-dose CT. To compare the model with the American College of Radiology (ACR) Lung CT Screening Reporting and Data System (Lung-RADS) for early detection of lung cancer. METHODS: We examined a set of 72 PNs (31 benign and 41 malignant) from the Lung Image Database Consortium image collection (LIDC-IDRI). 103 CT radiomic features were extracted from each PN. Before the model building process, distinctive features were identified using a hierarchical clustering method...
February 19, 2018: Medical Physics
https://www.readbyqxmd.com/read/29416740/prognostic-value-of-histogram-analysis-in-advanced-non-small-cell-lung-cancer-a-radiomic-study
#20
Bluthgen Maria Virginia, Faivre Laura, Rosellini Silvia, Ferrara Roberto, Facchinetti Francesco, Haspinger Eva, Ferte Charles, Ammari Samy, Michiels Stefan, Soria Jean-Charles, Caramella Caroline, Besse Benjamin
Introduction: Quantitative assessment of heterogeneity by histogram analysis (HA) of tumor images can potentially provide a non-invasive prognostic biomarker. We assessed the prognostic value of HA and evaluated a correlation with molecular signature. Results: CT scans performed between July 2009 and January 2015 from 692 patients were reviewed. HA was performed on scans from 313 patients in the training dataset and 108 in the validation dataset. Median follow-up were 33...
January 5, 2018: Oncotarget
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