MS-Net: Learning to assess the malignant status of a lung nodule by a radiologist and her peers.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of applied clinical medical physics"
DOI: 10.1002/acm2.13964
Abstract: BACKGROUND Automatically assessing the malignant status of lung nodules based on CTscan images can help reduce the workload of radiologists while improving their diagnostic accuracy. PURPOSE Despite remarkable progress in the automatic diagnosis of pulmonary… read more here.
Keywords: diagnosis; status lung; lung; malignant status ... See more keywords
Digital Decoding of Single Extracellular Vesicle Phenotype Differentiates Early Malignant and Benign Lung Lesions
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DOI: 10.1002/advs.202204207
Abstract: Accurate identification of malignant lung lesions is a prerequisite for rational clinical management to reduce morbidity and mortality of lung cancer. However, classification of lung nodules into malignant and benign cases is difficult as they… read more here.
Keywords: lung lesions; lung; malignant benign; benign lung ... See more keywords
Derivation and validation of a prediction model for patients with lung nodules malignancy regardless of mediastinal/hilar lymphadenopathy
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Surgical Oncology"
DOI: 10.1002/jso.27072
Abstract: Clinical prediction models to classify lung nodules often exclude patients with mediastinal/hilar lymphadenopathy, although the presence of mediastinal/hilar lymphadenopathy does not always indicate malignancy. Herein, we developed and validated a multimodal prediction model for lung… read more here.
Keywords: hilar lymphadenopathy; prediction model; lung nodules; mediastinal hilar ... See more keywords
Hybrid U‐Net‐based deep learning model for volume segmentation of lung nodules in CT images
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DOI: 10.1002/mp.15810
Abstract: Abstract Objective Accurate segmentation of the lung nodule in computed tomography images is a critical component of a computer‐assisted lung cancer detection/diagnosis system. However, lung nodule segmentation is a challenging task due to the heterogeneity… read more here.
Keywords: dice; segmentation; model; lung nodules ... See more keywords
PET/MRI assessment of lung nodules in primary abdominal malignancies: sensitivity and outcome analysis
Sign Up to like & getrecommendations! Published in 2021 at "European Journal of Nuclear Medicine and Molecular Imaging"
DOI: 10.1007/s00259-020-05113-1
Abstract: To evaluate PET/MR lung nodule detection compared to PET/CT or CT, to determine growth of nodules missed by PET/MR, and to investigate the impact of missed nodules on clinical management in primary abdominal malignancies. This… read more here.
Keywords: primary abdominal; pet; abdominal malignancies; lung nodules ... See more keywords
Rheumatoid pulmonary nodules: clinical and imaging features compared with malignancy
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DOI: 10.1007/s00330-018-5755-x
Abstract: ObjectivesThe objective of this study was to identify clinical and imaging features that distinguish rheumatoid lung nodules from malignancy.MethodsWe conducted a retrospective review of 73 rheumatoid patients with histologically-proven rheumatoid and malignant lung nodules encountered… read more here.
Keywords: rheumatoid; rheumatoid lung; lung nodules; compared malignancy ... See more keywords
Comparison of image quality between spectral photon-counting CT and dual-layer CT for the evaluation of lung nodules: a phantom study
Sign Up to like & getrecommendations! Published in 2021 at "European Radiology"
DOI: 10.1007/s00330-021-08103-5
Abstract: To evaluate the image quality (IQ) of a spectral photon-counting CT (SPCCT) using filtered back projection (FBP) and hybrid iterative reconstruction (IR) algorithms (iDose4), in comparison with a dual-layer CT (DLCT) system, and to choose… read more here.
Keywords: image; lung nodules; lung; photon counting ... See more keywords
Diagnostic Performance of the Herder Model in Veterans Undergoing PET Scans for Pulmonary Nodule Evaluation
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DOI: 10.1007/s00408-021-00495-x
Abstract: British Thoracic Society (BTS) guidelines recommend using the Herder model to risk-stratify lung nodules after positron emission tomography (PET). However, this approach has not been adequately evaluated, particularly among Veterans. A single-center retrospective cohort study… read more here.
Keywords: diagnostic performance; lung nodules; bts guidelines; model ... See more keywords
A bilinear convolutional neural network for lung nodules classification on CT images
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-020-02283-z
Abstract: Purpose Lung cancer is the most frequent cancer worldwide and is the leading cause of cancer-related deaths. Its early detection and treatment at the stage of a lung nodule improve the prognosis. In this study… read more here.
Keywords: classification; lung nodules; convolutional neural; neural network ... See more keywords
Strategies to optimize management of incidental radiographic findings in the primary care setting: A mixed methods study.
Sign Up to like & getrecommendations! Published in 2021 at "American journal of surgery"
DOI: 10.1016/j.amjsurg.2021.03.038
Abstract: BACKGROUND Incidental adrenal masses (IAMs) are common. Primary care providers (PCPs) are frequently responsible for incidentaloma evaluations. We evaluated whether PCPs view this paradigm effective, barriers faced, and strategies to optimize care delivery. METHODS This… read more here.
Keywords: primary care; lung nodules; management; strategies optimize ... See more keywords
Assessment of Plasma Proteomics Biomarker’s Ability to Distinguish Benign From Malignant Lung Nodules
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DOI: 10.1016/j.chest.2018.02.012
Abstract: BACKGROUND: Lung nodules are a diagnostic challenge, with an estimated yearly incidence of 1.6 million in the United States. This study evaluated the accuracy of an integrated proteomic classifier in identifying benign nodules in patients… read more here.
Keywords: lung; lung nodules; integrated classifier; benign nodules ... See more keywords