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Journal articles on the topic 'Pulmonary nodules'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Heuvelmans, Marjolein A., Joan E. Walter, Rozemarijn Vliegenthart, et al. "Disagreement of diameter and volume measurements for pulmonary nodule size estimation in CT lung cancer screening." Thorax 73, no. 8 (2017): 779–81. http://dx.doi.org/10.1136/thoraxjnl-2017-210770.

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We studied 2240 indeterminate solid nodules (volume 50–500mm3) to determine the correlation of diameter and semi-automated volume measurements for pulmonary nodule size estimation. Intra-nodular diameter variation, defined as maximum minus minimum diameter through the nodule’s center, varied by 2.8 mm (median, IQR:2.2–3.7 mm), so above the 1.5 mm cutoff for nodule growth used in Lung CT Screening Reporting and Data System (Lung-RADS). Using mean or maximum axial diameter to assess nodule volume led to a substantial mean overestimation of nodule volume of 47.2% and 85.1%, respectively, compared

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Al-Umairi, Rashid S., Fatma Al-Lawati, and Fadhila M. Al-Busaidi. "Nodular Pulmonary Amyloidosis Mimicking Metastatic Pulmonary Nodules: A case report and review of the literature." Sultan Qaboos University Medical Journal [SQUMJ] 18, no. 3 (2018): 393. http://dx.doi.org/10.18295/squmj.2018.18.03.023.

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Amyloidosis is a disorder characterised by the extracellular deposition of amyloid, a fibrillary protein, in various organs such as the lungs. Pulmonary nodular amyloidosis can mimic other lung conditions that present with pulmonary nodules, such as metastasis, sarcoidosis and hyalinising granuloma. We report a 60-year-old man who presented to the Royal Hospital, Muscat, Oman, in 2017 with a history of shortness of breath upon exertion, orthopnoea and bilateral lower limb swelling. A chest X-ray showed bilateral nodular opacities. Enhanced chest computed tomography revealed bilateral pulmonary

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Zhang, Chan, Jing Li, Jian Huang, and Shangjie Wu. "Computed Tomography Image under Convolutional Neural Network Deep Learning Algorithm in Pulmonary Nodule Detection and Lung Function Examination." Journal of Healthcare Engineering 2021 (October 22, 2021): 1–9. http://dx.doi.org/10.1155/2021/3417285.

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The objective of this study was to perform segmentation and extraction of CT images of pulmonary nodules based on convolutional neural networks (CNNs). The Mask-RCNN algorithm model is a typical end-to-end image segmentation model, which uses the R-FCN structure for nodule detection. The effect of applying the two algorithm models to the computed tomography (CT) diagnosis of pulmonary nodules was analyzed, and different indexes of pulmonary nodule CT images in lung function examination after algorithm optimization were compared. A total of 56 patients diagnosed with pulmonary nodules by surger

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Hülya, Dirol, Ayse Keven, and Ege Alkan. "Patients risk factors and pulmonary nodule characteristics in the differentiation of malignant pulmonary nodules." Medical Science Pulse 16, no. 4 (2023): 1–5. http://dx.doi.org/10.5604/01.3001.0016.3153.

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Background: We have been encountering pulmonary nodules more frequently due to increased lung cancer screening programs and lung tomography imaging for other reasons. Although various guidelines have been developed regarding pulmonary nodules, uncertainty continues on the follow-up and management of nodules. Aim of the study: To define the patients risk factors and pulmonary nodule characteristics that differentiate malignant nodules from benign nodules.Material and Methods: Patients with pulmonary nodules, detected between August 2014 and January 2019 in a university hospital were analyzed re

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Haryati, Haryati, and Dimas Satrio Baringgo. "Solitary Pulmonary Nodule: Is It Benign or Malignant?" Respiratory Science 4, no. 1 (2023): 65–79. http://dx.doi.org/10.36497/respirsci.v4i1.101.

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Solitary pulmonary nodules (SPN) are round-shaped opacities with or without firm borders and ≤3 cm in diameter. 40% of solitary pulmonary nodules in high-risk populations are malignant and >10 mm in diameter. With the high incidence of pulmonary cancer, diagnosing pulmonary nodules is essential for clinicians. This review aims to discuss more solitary pulmonary nodules based on multiple recommendations for diagnosis and management. Malignancy probability assessment is the first step in evaluating each patient with new pulmonary nodules, as it significantly affects the prognosis of the disea

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Zhang, Jing, Shi Qiu, Xiaohai Cui, and Ting Liang. "A Pulmonary Nodule Spiculation Recognition Algorithm Based on Generative Adversarial Networks." BioMed Research International 2022 (June 24, 2022): 1–10. http://dx.doi.org/10.1155/2022/3341924.

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Pulmonary nodules have been found as the main pathological change in the lung. Signs of pulmonary nodule lay the major basis for the recognition of the benign and malignant of pulmonary nodules. The spiculation of pulmonary nodules is one of the main signs. Pulmonary nodules are small in volume, so they are difficult to extract accurately. Moreover, the number of spiculation samples is limited, so it is difficult to build a stable network structure. Thus, a novel pulmonary nodule spiculation recognition algorithm is proposed. MCA (morphological component analysis) model is built to segment pul

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Yin, Mingquan, Lecong Ouyang, Jianlong Tan, Wei Liu, and Weidong Zhang. "CT showed multiple pulmonary balloon lesions with intermediate balloon calcification in a case of nodular pulmonary amyloidosis: A case report." Medicine 102, no. 36 (2023): e34964. http://dx.doi.org/10.1097/md.0000000000034964.

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Rationale: Amyloidosis is a rare disease characterized by the misfolding of autologous proteins and extracellular deposition of fibrils, which can involve 1 or more vital organs in the body. Nodular pulmonary amyloidosis with extensive pulmonary cysts is even less common. This study discusses the diagnosis and treatment of a case of pulmonary nodular amyloidosis with extensive pulmonary cysts and calcification in the middle of the cysts on chest computed tomography, and reviews the related literature. We hope that this rare case will raise awareness of this disease among clinicians. Patient co

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Liu, Huitong, Xiao Yao, Bingqiang Xu, Wei Zhang, Yu Lei, and Xiaolong Chen. "Efficacy and Safety Analysis of Multislice Spiral CT-Guided Transthoracic Lung Biopsy in the Diagnosis of Pulmonary Nodules of Different Sizes." Computational and Mathematical Methods in Medicine 2022 (August 25, 2022): 1–8. http://dx.doi.org/10.1155/2022/8192832.

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Objective. This study is aimed at investigating the efficacy and safety of multislice spiral CT-guided transthoracic lung biopsy in the diagnosis of pulmonary nodules of different sizes. Methods. Data of 78 patients with pulmonary nodules who underwent CT-guided transthoracic lung biopsy in our hospital from January 2020 to December 2021 were retrospectively analyzed, and they were divided into the small nodules group ( n = 12 ), medium nodules group ( n = 35 ), and large nodules group ( n = 31 ) according to the diameter of pulmonary nodules. The results of puncture biopsy and final diagnosis

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Al-Funjan, Amera, Farid Meziane, and Rob Aspin. "Describing Pulmonary Nodules Using 3D Clustering." Advanced Engineering Research 22, no. 3 (2022): 261–71. http://dx.doi.org/10.23947/2687-1653-2022-22-3-261-271.

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Introduction. Determining the tumor (nodule) characteristics in terms of the shape, location, and type is an essential step after nodule detection in medical images for selecting the appropriate clinical intervention by radiologists. Computer-aided detection (CAD) systems efficiently succeeded in the nodule detection by 2D processing of computed tomography (CT)-scan lung images; however, the nodule (tumor) description in more detail is still a big challenge that faces these systems.Materials and Methods. In this paper, the 3D clustering is carried out on volumetric CT-scan images containing th

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Zhao, Yue, Zhongyang Wang, Xinyao Liu, et al. "Pulmonary Nodule Detection Based on Multiscale Feature Fusion." Computational and Mathematical Methods in Medicine 2022 (December 21, 2022): 1–13. http://dx.doi.org/10.1155/2022/8903037.

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As cancer with the highest morbidity and mortality in the world, lung cancer is characterized by pulmonary nodules in the early stage. The detection of pulmonary nodules is an important method for the early detection of lung cancer, which can greatly improve the survival rate of lung cancer patients. However, the accuracy of conventional detection methods for lung nodules is low. With the development of medical imaging technology, deep learning plays an increasingly important role in medical image detection, and pulmonary nodules can be accurately detected by CT images. Based on the above, a p

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Peng, Haixin, Huacong Sun, and Yanfei Guo. "3D multi-scale deep convolutional neural networks for pulmonary nodule detection." PLOS ONE 16, no. 1 (2021): e0244406. http://dx.doi.org/10.1371/journal.pone.0244406.

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With the rapid development of big data and artificial intelligence technology, computer-aided pulmonary nodule detection based on deep learning has achieved some successes. However, the sizes of pulmonary nodules vary greatly, and the pulmonary nodules have visual similarity with structures such as blood vessels and shadows around pulmonary nodules, which make the quick and accurate detection of pulmonary nodules in CT image still a challenging task. In this paper, we propose two kinds of 3D multi-scale deep convolution neural networks for nodule candidate detection and false positive reductio

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Kim, D. Y., J. H. Kim, S. M. Noh, and J. W. Park. "Pulmonary nodule detection using chest CT images." Acta Radiologica 44, no. 3 (2003): 252–57. http://dx.doi.org/10.1080/j.1600-0455.2003.00061.x.

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Purpose: Automated methods for the detection of pulmonary nodules and nodule volume calculation on CT are described. Material and Methods: Gray-level threshold methods were used to segment the thorax from the background and then the lung parenchyma from the thoracic wall and mediastinum. A deformable model was applied to segment the lung boundaries, and the segmentation results were compared with the thresholding method. The lesions that had high gray values were extracted from the segmented lung parenchyma. The selected lesions included nodules, blood vessels and partial volume effects. The d

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Jokerst, Clinton, Henry Tazelaar, Carlos Rojas, et al. "March 2022 Medical Image of the Month: Pulmonary Nodules in the Setting of Diffuse Idiopathic Pulmonary Neuroendocrine Cell Hyperplasia (DIPNECH)." Southwest Journal of Pulmonary, Critical Care & Sleep 24, no. 3 (2022): 40–42. http://dx.doi.org/10.13175/swjpccs010-22.

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No abstract available. Article truncated after 150 words. A 62-year-old woman presented to an outside hospital with chronic cough, prompting a CXR. Findings further prompted unenhanced chest CT to evaluate possible pulmonary nodules. The CT demonstrated multiple scattered, solid and centrilobular pulmonary nodules, most of which were small but there were two >1 cm nodules, one in the right upper lobe (RUL) and a second in the lingula (Figure 1A,B). A subsequent FDG PET-CT was performed demonstrating increased metabolic activity in the RUL nodule with no activity in the lingular nodule (Figu

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Sarikaya, Y., G. Sandal Uzun, E. B. Ata, et al. "POS0602 PULMONARY RHEUMATOID NODULES: DOES SEROLOGIC STATUS MATTER?" Annals of the Rheumatic Diseases 81, Suppl 1 (2022): 568.2–569. http://dx.doi.org/10.1136/annrheumdis-2022-eular.2526.

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BackgroundThe frequency of pulmonary rheumatoid nodules closely relates to the diagnostic modality and changes from <0.4% to 32%. Also, it is known that seropositive RA patients tend to have more extra-articular disease.ObjectivesWe aimed to compare the disease and pulmonary rheumatoid nodule characteristics of seropositive and seronegative RA patients.MethodsIn this study, all RA patients - according to ICD-10 code - and had at least one chest computerized tomography (CT) were examined and revealed 4117 individual patients. First, RA diagnosis was confirmed according the patients’ history,

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Liu, Liwei, Xin Wang, Yang Li, Liping Wang, and Jianghui Dong. "Adhesion Pulmonary Nodules Detection Based on Dot-Filter and Extracting Centerline Algorithm." Computational and Mathematical Methods in Medicine 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/597313.

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A suspected pulmonary nodule detection method was proposed based on dot-filter and extracting centerline algorithm. In this paper, we focus on the distinguishing adhesion pulmonary nodules attached to vessels in two-dimensional (2D) lung computed tomography (CT) images. Firstly, the dot-filter based on Hessian matrix was constructed to enhance the circular area of the pulmonary CT images, which enhanced the circular suspected pulmonary nodule and suppresses the line-like areas. Secondly, to detect the nondistinguishable attached pulmonary nodules by the dot-filter, an algorithm based on extrac

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Öztürk Aktaş, Özge, Ahmet Uğur Demir, and Ziya Toros Selçuk. "Outcomes of multidisciplinary management of pulmonary nodules in a tertiary center." Acta Medica 55, no. 3 (2024): 178–83. http://dx.doi.org/10.32552/2024.actamedica.1027.

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Objective: A multidisciplinary approach is recommended for managing pulmonary nodules. This study aimed to examine the malignancy rates, malignancy determinants, and follow-up results of patients with pulmonary nodules whom the multidisciplinary team evaluates. Methods: Clinical characteristics of the patients, radiological and histological characteristics of the nodules, and the follow-up outcomes were documented retrospectively. A total of 94 patients with solitary pulmonary nodules (SPNs) (n=58) and multiple pulmonary nodules (MPNs) (n=36) were included in the study. Results: Our study show

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Peng, Muyun, Guanlan Xing, Bingyu Zhang, Yaping Xu, and Fenglei Yu. "Genomic characterization of sub-centimeter pulmonary nodules." Journal of Clinical Oncology 38, no. 15_suppl (2020): e13530-e13530. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e13530.

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e13530 Background: There has been a dramatic increase in the detection of indeterminate pulmonary nodules (IPNs), many of which are 10 mm or less in diameter. The management of subcentimeter pulmonary nodules remains controversial. Deciphering the genomic landscape of subcentimeter pulmonary nodules will provide critical insights to the mechanisms of carcinogenesis and pave the way for the early prevention and interception of lung cancer. Methods: We subjected 439 IPN samples including 249 subcentimeter pulmonary nodules (≤10 mm in diameter) and 190 larger pulmonary nodules (>10 and ≤30mm i

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Taurchini, Marco, Carla Maria Irene Quarato, Elisabetta Maria Frongillo, et al. "Intraoperative Lung Ultrasound (ILU) for the Assessment of Pulmonary Nodules." Diagnostics 11, no. 9 (2021): 1691. http://dx.doi.org/10.3390/diagnostics11091691.

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Background: The primary aim of this study was to confirm the validity of intraoperative lung ultrasound (ILU) as a safe and effective method of localization for difficult to visualize pulmonary nodules during Video-Assisted Thoracoscopic Surgery (VATS) and open thoracotomy. The secondary aim was to enhance knowledge on the morphological patterns of presentation of pulmonary nodules on direct ultrasound examination. Materials and methods: 131 patients with lung nodule and indication for surgery were enrolled. All patients underwent pre-operative imaging of the chest, including Chest Computed To

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Qiao, Rong, Siyao Sang, Jiajun Teng, Hua Zhong, Hui Li, and Baohui Han. "Genetic Polymorphisms of ACE1 Rs4646994 Associated with Lung Cancer in Patients with Pulmonary Nodules: A Case–Control Study." Biomedicines 11, no. 6 (2023): 1549. http://dx.doi.org/10.3390/biomedicines11061549.

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Background: Currently, many detection methods have high sensitivity to the diagnosis of lung cancer. However, some postoperative patients with pulmonary nodules are eventually diagnosed as having benign nodules. The ideal evaluation of an individual with a pulmonary nodule would expedite therapy for a malignant nodule and minimize testing for those with a benign nodule. Methods: This case–control study is designed to explore the relationship between ACE1 rs4646994 polymorphism and the risk of lung cancer in patients with pulmonary nodules, for which 400 individuals with lung cancer and benign

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Bilgin, E., M. Ekici, Y. Baytar, et al. "THU0131 LOCALISATION OF RHEUMATOID LUNG NODULES IN PATIENTS WITH RHEUMATOID ARTHRITIS-RELATED INTERSTITIAL LUNG DISEASE: RIGHT OR LEFT?" Annals of the Rheumatic Diseases 79, Suppl 1 (2020): 281.1–281. http://dx.doi.org/10.1136/annrheumdis-2020-eular.627.

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Background:The frequency of pulmonary rheumatoid nodules closely relates to the diagnostic modality and changes from <0.4% to 32% [1]. However, data regarding pulmonary rheumatoid nodules in RA-related interstitial lung disease (RA-ILD) is scarce.Objectives:The aim of this study was to describe the general features and localisation of pulmonary rheumatoid nodules in RA-ILD patients followed up in a single tertiary center.Methods:During January 2010 and March 2019, 826 RA patients had lung computerized tomography (CT) in Hacettepe University. Three radiologists re-evaluated lung CTs and 156/

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Peng, Muyun, Fenglei Yu, Xiaofeng Chen, Jing Bai, Xuefeng Xia, and Guanlan Xing. "Comprehensive characterization of genomic and radiologic features reveals distinct driver patterns of RTK/RAS pathway in pulmonary nodules presenting as ground-glass opacity." Journal of Clinical Oncology 39, no. 15_suppl (2021): e20516-e20516. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.e20516.

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e20516 Background: GGO-associated pulmonary nodule has been known as radiological appearances of early stage and exhibit more indolent biological behavior. The correlation of different driver gene and radiological features remain poorly understood. Methods: We performed high-depth sequencing of 334 resected pulmonary nodules presenting as GGO from 262 Chinese patients with a custom 1021-gene panel. 130 were multiple pulmonary nodules from 58 patients (2-4 samples per patient). Clinical-pathologic and radiologic parameters of these pulmonary nodules were collected. Immunohistochemistry and mult

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Li, Jie, Wei Wang, Shizhi Long, Xin Liu, Long Huang, and Yuanxun Li. "Chest Computerized Tomography Images under Iterative Model Reconstruction Algorithm in Patients with Lung Cancer." Scientific Programming 2021 (October 7, 2021): 1–8. http://dx.doi.org/10.1155/2021/7897784.

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To explore the effect of the full iterative model reconstruction algorithm (IMR) on chest CT image processing and its adoption value in the clinical diagnosis of lung cancer patients, multislice spiral CT (MSCT) scans were performed on 96 patients with pulmonary nodules. Reconstruction was performed by hybrid iterative reconstruction (iDose4) and IMR2 algorithms. Then, the image contrast, spatial resolution, density resolution, image uniformity, and noise of the CT reconstructed image were recorded. The benign and malignant pulmonary nodules of patients were collected and classified into malig

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Li, Jonathan C., Sameh Tadros, Franziska Rosser, and Kathryn S. Torok. "Pulmonary Nodules in Juvenile Systemic Sclerosis: A Case-Series from the National Registry for Childhood Onset Scleroderma (NRCOS)." Diagnostics 13, no. 12 (2023): 2103. http://dx.doi.org/10.3390/diagnostics13122103.

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Background: Juvenile systemic sclerosis (jSSc) is a systemic inflammatory and fibrotic autoimmune disease. Adult guidelines recommend obtaining a screening high-resolution computed tomography scan (CT) at diagnosis. As these recommendations are adopted as standard of care for jSSc, increased screening with CT may lead to increased detection of nodules. The implications of nodules identified in jSSc are unclear and unreported. Methods: A retrospective chart review was performed on the prospectively enrolled National Registry for Childhood-Onset Scleroderma (NRCOS) cohort over an enrollment peri

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Lu, Zhiqian, Feixiang Long, and Xiaodong He. "Classification and Segmentation Algorithm in Benign and Malignant Pulmonary Nodules under Different CT Reconstruction." Computational and Mathematical Methods in Medicine 2022 (April 21, 2022): 1–6. http://dx.doi.org/10.1155/2022/3490463.

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Background and Objective. Effective segmentation of pulmonary nodules can effectively assist in the diagnosis of benign and malignant pulmonary nodules. We aim to explore the effectiveness of classification and segmentation algorithms in diagnosing benign and malignant pulmonary nodules under different CT reconstructions. 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 netw

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Yu, Tong, Xiaoyan Zhao, Joseph K. Leader, et al. "Vascular Biomarkers for Pulmonary Nodule Malignancy: Arteries vs. Veins." Cancers 16, no. 19 (2024): 3274. http://dx.doi.org/10.3390/cancers16193274.

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Objective: This study aims to investigate the association between the arteries and veins surrounding a pulmonary nodule and its malignancy. Methods: A dataset of 146 subjects from a LDCT lung cancer screening program was used in this study. AI algorithms were used to automatically segment and quantify nodules and their surrounding macro-vasculature. The macro-vasculature was differentiated into arteries and veins. Vessel branch count, volume, and tortuosity were quantified for arteries and veins at different distances from the nodule surface. Univariate and multivariate logistic regression (LR

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Sweidan, Alexander J., Navneet K. Singh, Alexander Stein, and Maged Tanios. "Nodular Sarcoidosis Masquerading as Cancer." Clinical Medicine Insights: Circulatory, Respiratory and Pulmonary Medicine 11 (January 1, 2017): 117954841770312. http://dx.doi.org/10.1177/1179548417703123.

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Nodular lung disease is a rare pulmonary manifestation of sarcoidosis and resembles metastatic neoplasm disease. Nodular sarcoidosis is rare, varying from 1.6% to 4% of patients with sarcoidosis. Radiographic nodules measure from 1 to 5 cm in diameter that typically consist of coalescent granulomas. There is limited data on this form of sarcoidosis and its presentation can mimic primary or metastatic pulmonary neoplasms. Nodular sarcoidosis has a favorable prognosis, and resolution can be seen with oral corticosteroids. Herein, we present such a case of nodular pulmonary sarcoidosis with a lun

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Larici, Anna Rita, Alessandra Farchione, Paola Franchi, et al. "Lung nodules: size still matters." European Respiratory Review 26, no. 146 (2017): 170025. http://dx.doi.org/10.1183/16000617.0025-2017.

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The incidence of indeterminate pulmonary nodules has risen constantly over the past few years. Determination of lung nodule malignancy is pivotal, because the early diagnosis of lung cancer could lead to a definitive intervention. According to the current international guidelines, size and growth rate represent the main indicators to determine the nature of a pulmonary nodule. However, there are some limitations in evaluating and characterising nodules when only their dimensions are taken into account. There is no single method for measuring nodules, and intrinsic errors, which can determine v

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Roshankhah, Roshan, John Blackwell, Thomas M. Egan, and Marie Muller. "Localizing pulmonary nodules for surgical resection using ultrasound multiple scattering." Journal of the Acoustical Society of America 151, no. 4 (2022): A77. http://dx.doi.org/10.1121/10.0010710.

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Using conventional ultrasound to image pulmonary nodules is elusive due to multiple scattering in highly heterogeneous lung tissue. It is possible to leverage multiple scattering as a source of contrast between nodules and healthy lung parenchyma, because lung nodules do not contain air-filled alveoli. We developed a method based on the separation of multiple and single scattering using singular value decomposition. When combined with a depression detection algorithm, this allows us to render a map of the regions exhibiting less multiple scattering, associated with the presence of nodules. The

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Jung, Young Ju, Hwajung Kim, Youngmee Kim, and Won-Kyung Cho. "Clinical Correlates of Incidental Probable Benign Pulmonary Nodules with Diameters Less than 8 mm in a Healthy Korean Cohort: A Retrospective Study." Journal of Clinical Medicine 12, no. 23 (2023): 7501. http://dx.doi.org/10.3390/jcm12237501.

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Incidental pulmonary nodules detected via computed tomography (CT) are usually small, solid nodules (diameters less than 8 mm) that are likely benign and are difficult to biopsy. Additional features of the benignity of these small nodules may help determine the need and periodicity of further follow-up and should be identified. This study was conducted to examine the clinical factors associated with benign solid pulmonary nodules measuring less than 8 mm in diameter. This retrospective study enrolled participants who underwent low-dose chest CT scans for 3 consecutive years during routine heal

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Judge, Eoin P., Jessica Abrahams, Danielle Costigan, et al. "Pulmonary Nodular Lymphoid Hyperplasia presenting cavitating pulmonary nodules." Pathology - Research and Practice 211, no. 12 (2015): 1006–9. http://dx.doi.org/10.1016/j.prp.2015.09.002.

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Koroscil, Matthew T., Mitchell H. Bowman, Michael J. Morris, Andrew J. Skabelund, and Andrew M. Hersh. "Effect of a pulmonary nodule fact sheet on patient anxiety and knowledge: a quality improvement initiative." BMJ Open Quality 7, no. 3 (2018): e000437. http://dx.doi.org/10.1136/bmjoq-2018-000437.

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IntroductionThe utilisation of chest CT for the evaluation of pulmonary disorders, including low-dose CT for lung cancer screening, is increasing in the USA. As a result, the discovery of both screening-detected and incidental pulmonary nodules has become more frequent. Despite an overall low risk of malignancy, pulmonary nodules are a common cause of emotional distress among adult patients.MethodsWe conducted a multi-institutional quality improvement (QI) initiative involving 101 participants to determine the effect of a pulmonary nodule fact sheet on patient knowledge and anxiety. Males and

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Liu, Y., Y. J. Hou, C. X. Qin, et al. "A Data Augmentation Method and the Embedding Mechanism for Detection of Pulmonary Nodules on Small Samples." Journal of Physics: Conference Series 2890, no. 1 (2024): 012029. http://dx.doi.org/10.1088/1742-6596/2890/1/012029.

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Abstract Lung Computed Tomography (CT) screening for pulmonary nodules provides an effective method for early diagnosis. The deep-learning-based computer-aided detection (CAD) system effectively identifies and precisely localizes suspicious pulmonary nodules in CT images, thereby significantly enhancing the accuracy and efficiency of CT diagnosis. In the medical field, the availability of medical data is limited, and research using small samples is of practical significance. By studying the data augmentation technology based on the generative model under the condition of small samples, and ref

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Lin, Cheng-Hsun, Tsai-Wang Huang, Hsian-He Hsu, Wen-Chiuan Tsai, and Kai-Hsiung Ko. "Efficacy and Safety of CT-Guided Patent Blue Injection to Localize Deep Pulmonary Nodules of the Thorax." Medicina 61, no. 6 (2025): 1027. https://doi.org/10.3390/medicina61061027.

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Background and Objectives: The needle path is crucial for preoperative localization of deep thoracic pulmonary nodules using CT-guided patent blue dye (PBD) injection. This study aimed to evaluate the efficacy and safety of four categorized needle approach paths tailored to the anatomical location of the nodules. Materials and Methods: We retrospectively evaluated data from 50 consecutive patients (50 deep pulmonary nodules), who underwent CT-guided localization with PBD injection, between November 2015 and May 2023 at our hospital. The nodules could be divided into four categories: (1) perifi

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Xu, Hai, Xue-Hui Pu, Tong-Fu Yu, et al. "Incidence and natural course of CT-detected pulmonary ground-glass nodules in Chinese women with breast cancer: a retrospective, single-center, long-term follow-up study in 4682 consecutive patients." Acta Radiologica 61, no. 2 (2019): 175–83. http://dx.doi.org/10.1177/0284185119856259.

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Background Increased use of thin-section computed tomography (CT) scans has revealed that small lung nodules, termed ground-glass nodules, are frequent in primary breast cancer patients and are associated with pre-invasive or invasive pulmonary adenocarcinomas. However, little is known of the incidence and fate of ground-glass nodules. Purpose To elucidate the incidence and natural course of CT-detected pulmonary ground-glass nodules in Chinese women with breast cancer. Material and Methods We retrospectively reviewed data from female breast cancer patients who underwent lung CT scans and who

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Coleman, Christopher, Aziza Nassar, and Barbara McComb. "Pulmonary Hyalinizing Granuloma Associated with Idiopathic Thrombocytopenic Purpura." Journal of Clinical Imaging Science 4 (February 25, 2014): 8. http://dx.doi.org/10.4103/2156-7514.127835.

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Pulmonary hyalinizing granuloma (PHG) is a rare, benign lung disease of unknown etiology. It manifests as discrete, rounded nodules within the lung parenchyma. A 39-year-old woman presented for investigation after pulmonary nodules were found incidentally. Chest computed tomography showed multiple, discrete, non-enhancing pulmonary nodules bilaterally. Positron emission tomography (PET) was negative. Biopsy demonstrated a non-specific lymphoplasmacytic infiltrate. Open resection yielded two nodules consistent with hyalinizing granulomas. The differential for multiple pulmonary nodules is broad

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Feng, Shan-Li, Jun-Yao Li, and Chun-Ling Dong. "Primary biliary cholangitis presenting with granulomatous lung disease misdiagnosed as lung cancer: A case report." World Journal of Clinical Cases 12, no. 2 (2024): 354–60. http://dx.doi.org/10.12998/wjcc.v12.i2.354.

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BACKGROUND There are few cases of pulmonary granulomatous changes secondary to primary biliary cirrhosis (PBC). No case of granulomatous lung disease secondary to PBC misdiagnosed as lung cancer had been reported. CASE SUMMARY A middle-aged woman presented with lung nodules and was misdiagnosed with lung cancer by positron emission tomography/computed tomography. She underwent left lobectomy, and the pathology of the nodules showed granulomatous inflammation, which was then treated with antibiotics. However, a new nodule appeared. Further investigation with lung biopsy and liver serology led t

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Catelli, Chiara, Susanna Guerrini, Miriana D’Alessandro, et al. "Sarcoid Nodule or Lung Cancer? A High-Resolution Computed Tomography-Based Retrospective Study of Pulmonary Nodules in Patients with Sarcoidosis." Diagnostics 14, no. 21 (2024): 2389. http://dx.doi.org/10.3390/diagnostics14212389.

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Background: The objective of this retrospective study was to compare the characteristics of sarcoid nodules and neoplastic nodules using high-resolution computed tomography (HRCT) in sarcoidosis patients. Methods: This is a single-center retrospective study. From 2010 to 2023, among 685 patients affected by pulmonary sarcoidosis, 23 patients developed pulmonary nodules of a suspicious malignant nature. The HRCT characteristics of biopsy-proven malignant (Group A) vs. inflammatory (Group B) nodules were analyzed and compared. Results: A significant difference was observed between the groups in

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Chun-Man Yan, Chun-Man Yan, and Cheng Wang Chun-Man Yan. "Automatic Detection and Localization of Pulmonary Nodules in CT Images Based on YOLOv5." 電腦學刊 33, no. 3 (2022): 113–23. http://dx.doi.org/10.53106/199115992022063303009.

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<p>Lung cancer has always threatening human health and life. As small pulmonary nodules are main early features of lung cancer, early screening for small pulmonary nodules through computed tomography (CT) imaging is essential for the treatment of lung cancer. In this paper, the YOLOv5 model is improved to improve the ability of detection and recognition of small pulmonary nodules in complex CT lung images. Firstly, the preprocessing step is put into effect to obtain the lung parenchyma in CT images. Then, the backbone structure of YOLOv5 is improved by iResNet to improve the ability of f

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Omar, Raad Kadhim, Jassim Motlak Hassan, and Karam Abdall Kasim. "Computer-aided diagnostic system kinds and pulmonary nodule detection efficacy." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 5 (2022): 4734–45. https://doi.org/10.11591/ijece.v12i5.pp4734-4745.

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This paper summarizes the literature on computer-aided detection (CAD) systems used to identify and diagnose lung nodules in images obtained with computed tomography (CT) scanners. The importance of developing such systems lies in the fact that the process of manually detecting lung nodules is painstaking and sequential work for radiologists, as it takes a long time. Moreover, the pulmonary nodules have multiple appearances and shapes, and the large number of slices generated by the scanner creates great difficulty in accurately locating the lung nodules. The handcraft nodules detection proces

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Kasikovic-Lecic, Svetlana, Milan Popovic, Bosiljka Krajnovic, Milorad Bijelovic, and Dragana Tegeltija. "Nodular amyloidosis of the lung presenting as lung malignancy." Srpski arhiv za celokupno lekarstvo, no. 00 (2022): 112. http://dx.doi.org/10.2298/sarh220915112k.

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Introduction. Amyloidosis is a disease associated with the extracellular deposition of insoluble protein material called amyloid. It can be acquired or hereditary, systemic or organ-limited. Nodular pulmonary amyloidosis is defined as one or more tumefactive amyloid deposits in the lungs. Case outlines. This study presents two cases that were hospitalized at the Institute for Pulmonary Diseases to clarify the origin of lesions detected on CT scans of lung parenchyma. In the first case, in a 78-year-old woman, numerous non-calcified nodules were described on the chest CT. The patient died durin

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Wayne, Max T., Hallie C. Prescott, and Douglas A. Arenberg. "Prevalence and consequences of non-adherence to an evidence-based approach for incidental pulmonary nodules." PLOS ONE 17, no. 9 (2022): e0274107. http://dx.doi.org/10.1371/journal.pone.0274107.

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Importance Distinguishing benign from malignant pulmonary nodules is challenging. Evidence-based guidelines exist, but their impact on patient-centered outcomes is unknown. Objective To understand if the evaluation of incidental pulmonary nodules that follows an evidence-based management strategy is associated with fewer invasive procedures for benign lesions and/or fewer delays in cancer diagnosis. Design Retrospective cohort study. Setting Large academic medical center. Participants Adults (≥18 years age) with an incidental pulmonary nodule discovered between January 2012 and December 2014.

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Vaarwerk, Bas, Gianni Bisogno, Kieran McHugh, et al. "Indeterminate Pulmonary Nodules at Diagnosis in Rhabdomyosarcoma: Are They Clinically Significant? A Report From the European Paediatric Soft Tissue Sarcoma Study Group." Journal of Clinical Oncology 37, no. 9 (2019): 723–30. http://dx.doi.org/10.1200/jco.18.01535.

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Purpose To evaluate the clinical significance of indeterminate pulmonary nodules at diagnosis (defined as ≤ 4 pulmonary nodules < 5 mm or 1 nodule measuring ≥ 5 and < 10 mm) in patients with pediatric rhabdomyosarcoma (RMS). Patients and Methods We selected patients with supposed nonmetastatic RMS treated in large pediatric oncology centers in the United Kingdom, France, Italy, and the Netherlands, who were enrolled in the European Soft Tissue Sarcoma Study Group (E pSSG) RMS 2005 study. Patients included in the current study received a diagnosis between September 2005 and December 2013,

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Walter, Kristin. "Pulmonary Nodules." JAMA 326, no. 15 (2021): 1544. http://dx.doi.org/10.1001/jama.2021.12319.

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Sone, Shusuke, Kenji Tsushima, Kazuo Yoshida, Kazutoshi Hamanaka, Takaomi Hanaoka, and Ryoichi Kondo. "Pulmonary Nodules." Academic Radiology 17, no. 7 (2010): 900–911. http://dx.doi.org/10.1016/j.acra.2010.03.003.

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Slatore, Christopher G., and Renda Soylemez Wiener. "Pulmonary Nodules." Chest 153, no. 4 (2018): 1004–15. http://dx.doi.org/10.1016/j.chest.2017.10.013.

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Liu, Dongquan, Shaojun Zhu, Bangquan Liu, Dechao Sun, and Fangqin Fei. "Improvement of CT Target Scanning Quality for Pulmonary Nodules by PDCA Management Method." Mathematical Problems in Engineering 2021 (March 18, 2021): 1–9. http://dx.doi.org/10.1155/2021/6632960.

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High CT image quality is an important guarantee for doctors to correctly diagnose pulmonary nodules. The aim of this study was to explore the application value of PDCA management method in improving the quality of CT target scanning for pulmonary nodules. We identified 480 patients’ CT image with at least one pulmonary nodule admitted in Ninghai First hospital from September 1st, 2018, to April 30th, 2019. 240 CT images are carried out by the conventional target scanning method, and we analyzed the reasons for the low quality of some CT target scanning images of pulmonary nodules in the radiol

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Qi, Hongzhuo, Qifan Xuan, Pingping Liu, et al. "Deep Learning Radiomics Features of Mediastinal Fat and Pulmonary Nodules on Lung CT Images Distinguish Benignancy and Malignancy." Biomedicines 12, no. 8 (2024): 1865. http://dx.doi.org/10.3390/biomedicines12081865.

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This study investigated the relationship between mediastinal fat and pulmonary nodule status, aiming to develop a deep learning-based radiomics model for diagnosing benign and malignant pulmonary nodules. We proposed a combined model using CT images of both pulmonary nodules and the fat around the chest (mediastinal fat). Patients from three centers were divided into training, validation, internal testing, and external testing sets. Quantitative radiomics and deep learning features from CT images served as predictive factors. A logistic regression model was used to combine data from both pulmo

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Shao, Junjie, Lingxiao Zhou, Sze Yan Fion Yeung, Ting Lei, Wanlong Zhang, and Xiaocong Yuan. "Pulmonary Nodule Detection and Classification Using All-Optical Deep Diffractive Neural Network." Life 13, no. 5 (2023): 1148. http://dx.doi.org/10.3390/life13051148.

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A deep diffractive neural network (D2NN) is a fast optical computing structure that has been widely used in image classification, logical operations, and other fields. Computed tomography (CT) imaging is a reliable method for detecting and analyzing pulmonary nodules. In this paper, we propose using an all-optical D2NN for pulmonary nodule detection and classification based on CT imaging for lung cancer. The network was trained based on the LIDC-IDRI dataset, and the performance was evaluated on a test set. For pulmonary nodule detection, the existence of nodules scanned from CT images were es

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Kadhim, Omar Raad, Hassan Jassim Motlak, and Kasim Karam Abdalla. "Computer-aided diagnostic system kinds and pulmonary nodule detection efficacy." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 5 (2022): 4734. http://dx.doi.org/10.11591/ijece.v12i5.pp4734-4745.

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Abstract:

This paper summarizes the literature on computer-aided detection (CAD) systems used to identify and diagnose lung nodules in images obtained with computed tomography (CT) scanners. The importance of developing such systems lies in the fact that the process of manually detecting lung nodules is painstaking and sequential work for radiologists, as it takes a long time. Moreover, the pulmonary nodules have multiple appearances and shapes, and the large number of slices generated by the scanner creates great difficulty in accurately locating the lung nodules. The handcraft nodules detection proces

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Onishi, Yuya, Atsushi Teramoto, Masakazu Tsujimoto, et al. "Automated Pulmonary Nodule Classification in Computed Tomography Images Using a Deep Convolutional Neural Network Trained by Generative Adversarial Networks." BioMed Research International 2019 (January 2, 2019): 1–9. http://dx.doi.org/10.1155/2019/6051939.

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Lung cancer is a leading cause of death worldwide. Although computed tomography (CT) examinations are frequently used for lung cancer diagnosis, it can be difficult to distinguish between benign and malignant pulmonary nodules on the basis of CT images alone. Therefore, a bronchoscopic biopsy may be conducted if malignancy is suspected following CT examinations. However, biopsies are highly invasive, and patients with benign nodules may undergo many unnecessary biopsies. To prevent this, an imaging diagnosis with high classification accuracy is essential. In this study, we investigate the auto

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