Background: The diagnostic accuracy of computed tomography (CT)-guided percutaneous core needle biopsy (CNB) for small (≤ 20 mm) ground-glass opacity (GGO) lesions has not been reported in detail.

Objectives: To evaluate factors that affect the diagnostic accuracy of CT-guided percutaneous CNB for small (≤ 20 mm) GGO pulmonary lesions.

Methods: From January 2014 to February 2018, 156 patients with a small (≤ 20 mm) GGO pulmonary lesion who underwent CT-guided CNB were enrolled in this study. Factors affecting diagnostic accuracy were evaluated by analyzing patient and lesion characteristics and technical factors. Significant factors were identified by multivariate logistic regression.

Results: The diagnostic accuracy of CT-guided percutaneous CNB was 90.4% for small (≤ 20 mm) GGO pulmonary lesions. The diagnostic accuracy was higher for larger lesions (72.5% for lesions ≤ 10 mm, 96.6% for lesions between 11 and 20 mm [P < 0.001]). The diagnostic accuracy of CT-guided percutaneous CNB was 74.5% for lesions with > 90% GGO components and 97.2% for lesions with 50-90% GGO components (P < 0.001). In multivariate analysis, the significant factors influencing diagnostic accuracy were lesion size (P = 0.022; odds ratio [OR] for a lesion between 11 and 20 mm in size was approximately 5 times higher than that for a lesion ≤ 10 mm; 95% confidence interval [CI], 1.3 to 18.5), and GGO component (P = 0.015; OR for a lesion with 50-90% GGO components was approximately 6 times higher than that for a lesion with > 90% GGO components; 95% CI: 1.4 to 25.7).

Conclusions: Lesion size and GGO component are factors affecting diagnostic accuracy. The diagnostic accuracy was higher for larger lesions and lesions with 50-90% GGO components.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9264544PMC
http://dx.doi.org/10.1186/s12890-022-02058-zDOI Listing

Publication Analysis

Top Keywords

diagnostic accuracy
32
small ≤ 20 mm
20
ct-guided percutaneous
16
ggo components
16
accuracy ct-guided
12
≤ 20 mm ggo
12
ggo pulmonary
12
ggo
9
≤ 20 mm ground-glass
8
ground-glass opacity
8

Similar Publications

Background: Current diagnostic imaging modalities have limited ability to differentiate between malignant and benign pancreaticobiliary disease, and lack accuracy in detecting lymph node metastases. F-Prostate-Specific Membrane Antigen (PSMA) PET/CT is an imaging modality used for staging of prostate cancer, but has incidentally also identified PSMA-avid pancreatic lesions, histologically characterized as pancreatic ductal adenocarcinoma (PDAC). This phase I/II study aimed to assess the feasibility of F-PSMA PET/CT to detect PDAC.

View Article and Find Full Text PDF

Diagnosis of Parkinson's disease by eliciting trait-specific eye movements in multi-visual tasks.

J Transl Med

January 2025

School of Information and Communication Engineering, Dalian University of Technology, No. 2 Linggong Road, 116024, Dalian, China.

Background: Parkinson's Disease (PD) is a neurodegenerative disorder, and eye movement abnormalities are a significant symptom of its diagnosis. In this paper, we developed a multi-task driven by eye movement in a virtual reality (VR) environment to elicit PD-specific eye movement abnormalities. The abnormal features were subsequently modeled by using the proposed deep learning algorithm to achieve an auxiliary diagnosis of PD.

View Article and Find Full Text PDF

Introduction: Stroke-associated pneumonia (SAP) is a major cause of mortality during the acute phase of stroke. The ADS score is widely used to predict SAP risk but does not include 24-h non-contrast computed tomography-Alberta Stroke Program Early CT Score (NCCT-ASPECTS) or red cell distribution width (RDW). We aim to evaluate the added prognostic value of incorporating 24-h NCCT-ASPECTS and RDW into the ADS score and to develop a novel prediction model for SAP following thrombolysis.

View Article and Find Full Text PDF

Background: Alopecia areata (AA) is a common non-scarring hair loss disorder associated with autoimmune conditions. However, the pathobiology of AA is not well understood, and there is no targeted therapy available for AA.  METHODS: In this study, differential gene expression analysis, immune status assessment, weighted correlation network analysis (WGCNA), and functional enrichment analysis were performed to identify shared genes associated with both immunological response and AA.

View Article and Find Full Text PDF

Assessment of using transfer learning with different classifiers in hypodontia diagnosis.

BMC Oral Health

January 2025

Pediatric Dentistry Department, Faculty of Dentistry, Başkent University, 06490, Ankara, Turkey.

Background: Hypodontia is the absence of one or more teeth in the primary or permanent dentition during development, and radiographic imaging is the most common method of diagnosis. However, in recent years, artificial intelligence-based decision support systems have been employed to make highly accurate diagnoses. The aim of this study was to classify single premolar agenesis, multiple premolar agenesis, and without tooth agenesis using various artificial intelligence approaches.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!