3,836 results match your criteria Solitary Pulmonary Nodule Imaging


Diagnostic Performance of Machine Learning Models Based on F-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules.

Mol Imaging Radionucl Ther 2022 Jun;31(2):82-88

University of Sharjah, College of Health Sciences, Department of Medical Diagnostic Imaging, Sharjah, United Arab Emirates.

Objectives: This study aimed to evaluate the ability of fluorine-fluorodeoxyglucose (F-FDG) positron emission tomography/computed tomography (PET/CT) radiomic features combined with machine learning methods to distinguish between benign and malignant solitary pulmonary nodules (SPN).

Methods: Data of 48 patients with SPN detected on F-FDG PET/CT scan were evaluated retrospectively. The texture feature extraction from PET/CT images was performed using an open-source application (LIFEx). Read More

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Overlapping Reconstructions in Thin-section Computed Tomography: Benefits for Lung Nodule Volume Measurements.

J Thorac Imaging 2022 Jul 16;37(4):W56-W57. Epub 2021 Dec 16.

Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.

The aim of our study was to assess the influence of overlapping image reconstruction on thin-section chest computed tomography (CT) in patients with small lung nodules. In all, 40 patients with 128 pulmonary nodules underwent chest CT on a third-generation dual-source CT. All images were reconstructed with a section thickness of 1 mm and an increment of 0. Read More

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Implementation of sodium alginate-FeO to localize undiagnosed small pulmonary nodules for surgical management in a preclinical rabbit model.

Sci Rep 2022 Jun 15;12(1):9979. Epub 2022 Jun 15.

Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.

Many methods are used to locate preoperative small pulmonary nodules. However, deficiencies of complications and success rates exist. We introduce a novel magnetic gel for small pulmonary nodules localization in rabbit model, and furtherly evaluate its safety and feasibility. Read More

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Lung nodule diagnosis and cancer histology classification from computed tomography data by convolutional neural networks: A survey.

Comput Biol Med 2022 Jul 6;146:105691. Epub 2022 Jun 6.

Department of Information Engineering, Engineering Faculty, Università Politecnica delle Marche, Ancona, Italy. Electronic address:

Lung cancer is among the deadliest cancers. Besides lung nodule classification and diagnosis, developing non-invasive systems to classify lung cancer histological types/subtypes may help clinicians to make targeted treatment decisions timely, having a positive impact on patients' comfort and survival rate. As convolutional neural networks have proven to be responsible for the significant improvement of the accuracy in lung cancer diagnosis, with this survey we intend to: show the contribution of convolutional neural networks not only in identifying malignant lung nodules but also in classifying lung cancer histological types/subtypes directly from computed tomography data; point out the strengths and weaknesses of slice-based and scan-based approaches employing convolutional neural networks; and highlight the challenges and prospective solutions to successfully apply convolutional neural networks for such classification tasks. Read More

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Deep Learning-Based Digitally Reconstructed Tomography of the Chest in the Evaluation of Solitary Pulmonary Nodules: A Feasibility Study.

Acad Radiol 2022 Jun 9. Epub 2022 Jun 9.

Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, Illinois.

Rationale And Objectives: Computed tomography (CT) is preferred for evaluating solitary pulmonary nodules (SPNs) but access or availability may be lacking, in addition, overlapping anatomy can hinder detection of SPNs on chest radiographs. We developed and evaluated the clinical feasibility of a deep learning algorithm to generate digitally reconstructed tomography (DRT) images of the chest from digitally reconstructed frontal and lateral radiographs (DRRs) and use them to detect SPNs.

Methods: This single-institution retrospective study included 637 patients with noncontrast helical CT of the chest (mean age 68 years, median age 69 years, standard deviation 11. Read More

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Solitary Pulmonary Nodule Evaluation: Pearls and Pitfalls.

Semin Ultrasound CT MR 2022 Jun 5;43(3):230-245. Epub 2022 Feb 5.

Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY.

Lung nodules are frequently encountered while interpreting chest CTs and are challenging to detect, characterize, and manage given they can represent both benign or malignant etiologies. An understanding of features associated with malignancy and causes of interpretive pitfalls is helpful to avoid misdiagnoses. This review addresses pertinent topics related to the etiologies for missed lung nodules on radiography and CT. Read More

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Pulmonary Nodule Clinical Trial Data Collection and Intelligent Differential Diagnosis for Medical Internet of Things.

Contrast Media Mol Imaging 2022 26;2022:2058284. Epub 2022 May 26.

Department of Cardiothoracic Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325000, China.

In this paper, the medical Internet of things (IoT) is used to pool data from clinical trials of pulmonary nodules, and on this basis, intelligent differential diagnosis techniques are investigated. A filtered orthogonal frequency division multiplexing model based on polarisation coding is proposed, where the input data are fed to a modulator after polarisation cascade coding, and the system performance is analysed under a medical Internet of things modulated additive Gaussian white noise channel. The above polarisation-coded filtered orthogonal frequency division multiplexing system components are applied to electroencephalogram (EEG) signal transmission, to which a threshold compression module and a vector reconstruction module are added to address the system power burden associated with the acquisition and transmission of large amounts of real-time EEG data in the medical IoT. Read More

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Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery.

J Vis Exp 2022 05 4(183). Epub 2022 May 4.

Section of Interventional Pulmonology, Division of Pulmonary and Critical Care Medicine, University of North Carolina at Chapel Hill;

The increased use of chest computed tomography (CT) has led to an increased detection of pulmonary nodules requiring diagnostic evaluation and/or excision. Many of these nodules are identified and excised via minimally invasive thoracic surgery; however, subcentimeter and subsolid nodules are frequently difficult to identify intra-operatively. This can be mitigated by the use of electromagnetic transthoracic needle localization. Read More

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The value of radiomics based on dual-energy CT for differentiating benign from malignant solitary pulmonary nodules.

BMC Med Imaging 2022 May 21;22(1):95. Epub 2022 May 21.

Toxicology Department, WestChina-Frontier PharmaTech Co., Ltd. (WCFP), Chengdu, 610075, China.

Objective: To investigate the value of monochromatic dual-energy CT (DECT) images based on radiomics in differentiating benign from malignant solitary pulmonary nodules.

Materials And Methods: This retrospective study was approved by the institutional review board, and informed consent was waived. Pathologically confirmed lung nodules smaller than 3 cm with integrated arterial phase and venous phase (AP and VP) gemstone spectral imaging were retrospectively identified. Read More

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Efficient multiscale fully convolutional UNet model for segmentation of 3D lung nodule from CT image.

J Med Imaging (Bellingham) 2022 Sep 11;9(5):052402. Epub 2022 May 11.

Karunya Institute of Technology and Sciences, Department of Computer Science and Engineering, Coimbatore, Tamil Nadu, India.

Segmentation of lung nodules in chest CT images is essential for image-driven lung cancer diagnosis and follow-up treatment planning. Manual segmentation of lung nodules is subjective because the approach depends on the knowledge and experience of the specialist. We proposed a multiscale fully convolutional three-dimensional UNet (MF-3D UNet) model for automatic segmentation of lung nodules in CT images. Read More

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September 2022

Refining the Diagnosis, Minimizing the Approach: Advances in Pulmonary Nodule Marking Strategies.

Arch Bronconeumol 2022 May 1;58(5):392-394. Epub 2022 May 1.

Servicio de Medicina Nuclear, Hospital Universitario Vall d'Hebron, Barcelona, España.

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The risk factors for the failure of hook wire localization of ground glass nodules prior to thoracoscopic surgery.

J Cardiothorac Surg 2022 May 11;17(1):114. Epub 2022 May 11.

Graduate School, Tianjin Medical University, Tianjin, 300070, People's Republic of China.

Objectives: To retrospectively analyse the potential influencing factors of CT-guided hook wire localization failure prior to thoracoscopic resection surgery of ground glass nodules (GGNs), and determine the main risk elements for localization failure.

Methods: In all, 372 patients were included in this study, with 21 patients showing localization failure. The related parameters of patients, GGNs, and localization were analysed through univariate and multiple logistic regression analysis to determine the risk factors of localization failure. Read More

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Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population.

PLoS One 2022 5;17(5):e0266799. Epub 2022 May 5.

Department of Radiology, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom.

Objective: In this study, we evaluated a commercially available computer assisted diagnosis system (CAD). The deep learning algorithm of the CAD was trained with a lung cancer screening cohort and developed for detection, classification, quantification, and growth of actionable pulmonary nodules on chest CT scans. Here, we evaluated the CAD in a retrospective cohort of a routine clinical population. Read More

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Predictive model for the probability of malignancy in solitary pulmonary nodules: a meta-analysis.

J Cardiothorac Surg 2022 May 3;17(1):102. Epub 2022 May 3.

Department of Radiology, Xuzhou Central Hospital, Xuzhou, China.

Background: To date, multiple predictive models have been developed with the goal of reliably differentiating between solitary pulmonary nodules (SPNs) that are malignant and those that are benign. The present meta-analysis was conducted to assess the diagnostic utility of these predictive models in the context of SPN differential diagnosis.

Methods: The PubMed, Embase, Cochrane Library, CNKI, Wanfang, and VIP databases were searched for relevant studies published through August 31, 2021. Read More

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Classification and Segmentation Algorithm in Benign and Malignant Pulmonary Nodules under Different CT Reconstruction.

Comput Math Methods Med 2022 21;2022:3490463. Epub 2022 Apr 21.

Cancer Center, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou 310014, China.

Methods: The imaging data of 55 patients with chest CT plain scan in the Xuancheng People's Hospital were collected retrospectively. The data of each patient included lung window reconstruction, mediastinum reconstruction, and bone window reconstruction. The depth neural network and 3D convolution neural network were used to construct the model and train the classification and segmentation algorithm. Read More

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Predictors of malignancy in patients with solitary pulmonary nodules undergoing pulmonary resection.

Clin Respir J 2022 May 26;16(5):361-368. Epub 2022 Apr 26.

Department of Cardiovascular and Thoracic Surgery, West Virginia University Heart and Vascular Institute, Morgantown, West Virginia, USA.

Background: The management of a solitary pulmonary nodule is a challenging issue in pulmonary disease. Although many factors have been defined as predictors for malignancy in solitary pulmonary nodules, the accurate diagnosis can only be established with the permanent histological diagnosis.

Objective: We tried to clarify the possible predictors of malignancy in solitary pulmonary nodules in patients who had definitive histological diagnosis. Read More

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Imaging Characteristics and Prognostic Value of Isolated Pulmonary Metastasis from Colorectal Cancer Demonstrated withF-FDG PET/CT.

Biomed Res Int 2022 14;2022:2230079. Epub 2022 Apr 14.

Department of Nuclear Medicine, Changshu No. 2 People's Hospital, Changshu, China.

Objective: Solitary pulmonary lesions (SPNs) in patients with a history of colorectal cancer (CRC) may be attributed to metastatic lung tumors, primary lung cancer, or benign nodules. We aimed to analyze the imaging characteristics of SPNs in CRC patients to differentiate these pulmonary nodules and evaluate the prognostic value of isolated pulmonary metastasis from CRC using F-FDG PET/CT.

Methods: From January 2013 to January 2021, 62 CRC patients with SPNs demonstrated with F-FDG PET/CT were retrospectively enrolled in the present study. Read More

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Pulmonary nodule malignancy probability: a diagnostic accuracy meta-analysis of the Mayo model.

Clin Radiol 2022 06 11;77(6):443-450. Epub 2022 Apr 11.

Pulmonary and Respiratory Failure Department, First ICU, Evaggelismos Hospital, Athens, Greece; National and Kapodistrian University of Athens, Athens, Greece. Electronic address:

Aim: To quantify the overall diagnostic accuracy of the Mayo model in predicting the probability of malignancy of solitary pulmonary nodules (SPNs) by carrying out a systematic review and meta-analysis.

Materials And Methods: PubMed, Scopus, and references of relevant articles were searched systematically from inception up to 21 September 2021, to identify observational cohort studies, which reported on the diagnostic accuracy of the Mayo model in predicting the probability of malignancy in SPNs. The primary outcome was the pooled area under the receiver operating characteristic (ROC) curve (AUC). Read More

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One-stage pulmonary nodule detection using 3-D DCNN with feature fusion and attention mechanism in CT image.

Comput Methods Programs Biomed 2022 Jun 4;220:106786. Epub 2022 Apr 4.

Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan; Graduate Institute of Network and Multimedia, National Taiwan University, Taipei, Taiwan; Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan; MOST Joint Research Center for AI Technology and All Vista Healthcare, Taipei, Taiwan. Electronic address:

Background And Objective: Lung cancer is the most common cause of cancer-related death in the world. Low-dose computed tomography (LDCT) is a widely used modality in lung cancer detection. The nodule is an abnormal tissue and may evolve into lung cancer. Read More

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Diagnostic value of circulating genetically abnormal cells to support computed tomography for benign and malignant pulmonary nodules.

BMC Cancer 2022 Apr 9;22(1):382. Epub 2022 Apr 9.

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan Province, China.

Background: The accuracy of CT and tumour markers in screening lung cancer needs to be improved. Computer-aided diagnosis has been reported to effectively improve the diagnostic accuracy of imaging data, and recent studies have shown that circulating genetically abnormal cell (CAC) has the potential to become a novel marker of lung cancer. The purpose of this research is explore new ways of lung cancer screening. Read More

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Thermal ablation for pulmonary subsolid nodules: Which consensus guidelines? which future perspectives?

Authors:
Roberto Iezzi

J Cancer Res Ther 2021 12;17(7):1593-1595

Fondazione Policlinico Universitario A. Gemelli IRCCS, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia - Istituto di Radiologia, l.go A gemelli 8, 00168; Università Cattolica del Sacro Cuore, ROMA, Italia.

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December 2021

Diagnostic Value of Artificial Intelligence Based on CT Image in Benign and Malignant Pulmonary Nodules.

J Oncol 2022 24;2022:5818423. Epub 2022 Mar 24.

Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Science, Beijing, China.

Objective: To evaluate the diagnostic value of artificial intelligence-assisted CT imaging in benign and malignant pulmonary nodules.

Methods: The CT scan screening of pulmonary nodules from November 2018 to November 2020 was retrospectively collected. The diagnosis of pulmonary nodules and surgical treatment were performed. Read More

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Robotic Navigational Bronchoscopy Combined with Needle-Based Confocal Laser Endomicroscopy: Case Report of a Novel Approach to Diagnose Small Lung Nodules.

Respiration 2022 29;101(5):494-499. Epub 2022 Mar 29.

Department of Respiratory Medicine, Amsterdam UMC, Amsterdam, The Netherlands.

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death. Advancements in navigational bronchoscopy have shown encouraging results but the diagnostic yield of small lung nodules by bronchoscopic techniques is still below that of transthoracic needle aspiration. The development of robotic bronchoscopy has demonstrated a significantly improved navigational success but the diagnostic yield is regularly limited by near-miss of the target nodule. Read More

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[Chinese Experts Consensus on Artificial Intelligence Assisted Management for 
Pulmonary Nodule (2022 Version)].

Authors:

Zhongguo Fei Ai Za Zhi 2022 Apr 28;25(4):219-225. Epub 2022 Mar 28.

Low-dose computed tomography (CT) for lung cancer screening has been proven to reduce lung cancer deaths in the screening group compared with the control group. The increasing number of pulmonary nodules being detected by CT scans significantly increase the workload of the radiologists for scan interpretation. Artificial intelligence (AI) has the potential to increase the efficiency of pulmonary nodule discrimination and has been tested in preliminary studies for nodule management. Read More

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Robotic Assisted Bronchoscopy: The Ultimate Solution for Peripheral Pulmonary Nodules?

Respiration 2022 23;101(5):437-440. Epub 2022 Mar 23.

Technical Physician, Pulmonary Diseases, Radboudumc, Nijmegen, The Netherlands.

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Bronchoscopic approaches to sampling lung nodules: Aiming for the bulls eye.

Respirology 2022 05 21;27(5):325-327. Epub 2022 Mar 21.

Department of Respiratory Medicine, Royal Brompton Hospital, London, UK.

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Interhospital variability in localization techniques for small pulmonary nodules in children: A pediatric surgical oncology research collaborative study.

J Pediatr Surg 2022 Jun 23;57(6):1013-1017. Epub 2022 Feb 23.

Children's Hospital Colorado, Aurora, CO, United States.

Background: Pulmonary nodules that are deep within lung parenchyma and/or small in size can be challenging to localize for biopsy. This study describes current trends in performance of image-guided localization techniques for pulmonary nodules in pediatric patients.

Methods: A retrospective review was performed on patients < 21 years of age undergoing localization of pulmonary nodules at 15 institutions. Read More

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The impact of cardiopulmonary hemodynamic factors in volumetry for pulmonary nodule management.

BMC Med Imaging 2022 03 18;22(1):49. Epub 2022 Mar 18.

Imaging Department, University of Manchester, Manchester, UK.

Background: The acceptance of coronary CT angiogram (CCTA) scans in the management of stable angina has led to an exponential increase in studies performed and reported incidental findings, including pulmonary nodules (PN). Using low-dose CT scans, volumetry tools are used in growth assessment and risk stratification of PN between 5 and 8 mm in diameter. Volumetry of PN could also benefit from the increased temporal resolution of CCTA scans, potentially expediting clinical decisions when an incidental PN is first detected on a CCTA scan, and allow for better resource management and planning in a Radiology department. Read More

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