Various processes, including benign or malignant (mostly metastasis) processes, contribute to the occurrence of multiple pulmonary nodules. For differential diagnosis, metastasis must be excluded as an etiological factor in patients who have multiple pulmonary nodules with a known primary malignancy. However, differential diagnosis of multiple pulmonary nodules caused by benign diseases and malignant processes is challenging. Multiple pulmonary nodules resulting from metastasis may mimic those resulting from infections, inflammatory processes, and rare benign diseases. Some rare diseases, such as pulmonary sclerosing pneumocytoma and pulmonary epithelioid hemangioendothelioma, or common diseases with a rare presentation of multiple nodules must be considered in the differential diagnosis of metastasis. In addition to the clinical and laboratory findings, radiological features are crucial for differential diagnosis. The size, density, location, and border characteristics (well-defined or poorly defined) of pulmonary nodules, as well as their internal structure (solid, subsolid, or ground glass nodule), growth rate during follow-up, and associated pulmonary and extrapulmonary findings are important for differential diagnosis along with clinical and laboratory data. This article summarizes the general features and imaging findings of these diseases, which less frequently present with multiple pulmonary nodules, and the clues that can be used to distinguish these diseases from metastasis. CRITICAL RELEVANCE STATEMENT: The radiological features, clinical findings, and temporal changes during follow-up are important in distinguishing non-metastatic causes of multiple pulmonary nodules from metastatic causes and guiding diagnosis and early treatment, especially in patients with primary malignancy. KEY POINTS: Multiple pulmonary nodules have a wide range of etiologies, including metastatic disease. Metastasis as an etiology must be excluded in patients with multiple pulmonary nodules. Correlation of radiological findings (nodule size, position, and associated findings) with clinical history is crucial for differential diagnosis.
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http://dx.doi.org/10.1186/s13244-024-01856-9 | DOI Listing |
J Am Coll Surg
January 2025
Department of Thoracic Surgery. Vanderbilt University Medical Center, 1313 21st Avenue South, Nashville, TN 37232.
Background: Artificial intelligence (AI)-powered platforms may be used to ensure that clinically significant lung nodules receive appropriate management. We studied the impact of a commercially available AI natural language processing tool on detection of clinically significant indeterminate pulmonary nodules (IPNs) based on radiology reports and provision of guideline-consistent care.
Study Design: All computed tomography (CT) scans performed at a single tertiary care center in the outpatient or emergency room setting between 20-Feb-2024 and 20-March-2024 were processed by the AI natural language processing algorithm.
Inorg Chem
January 2025
Jiangsu Key Laboratory for Biomaterials and Devices, State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, PR China.
Organic-inorganic hybrid perovskites (OIHPs) have attracted enormous attention owing to their intriguing structural tunability and diverse functional properties. Reconstructive phase transitions, involving the breaking and reconstruction of chemical bonds, have rarely been found in such materials; however, these features may induce many intriguing physical properties in optics, ferroelectrics, ferromagnetics, and so forth. Here, we utilized the weak and switchable coordination bonds of HETMA-MnCl (HETMA = (2-hydroxyethyl) trimethylammonium) to construct a 1D hybrid perovskite employing a neutral framework.
View Article and Find Full Text PDFCureus
December 2024
Hematology Oncology, Miami Cancer Institute, Miami, USA.
Patients with multiple myeloma (MM) often experience infections due to aberrant immunoglobulin production by malignant plasma cells and immunosuppressive therapeutic interventions that are used to treat the condition. A rare but serious infection that may occur in these patients is Cryptococcus, an encapsulated fungus that typically infects immunocompromised individuals. Cryptococcus infections often present as pneumonia but can disseminate to the central nervous system, potentially causing meningitis.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Internal Medicine, Division of Rheumatology, Mayo Clinic, Jacksonville, FL 32224, USA.
Pulmonary involvement is commonly observed in anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), presenting with manifestations such as diffuse alveolar hemorrhage, inflammatory infiltrates, pulmonary nodules, and tracheobronchial disease. We aimed to identify distinct subgroups of tracheobronchial disease patterns in patients with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) using latent class analysis (LCA), and to evaluate their clinical characteristics and outcomes. We conducted a retrospective cohort study using electronic medical records of patients aged >18 years diagnosed with AAV and tracheobronchial disease between 1 January 2002 and 6 September 2022.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
College of Computer Science and Engineering, Taibah University, Medina 41477, Saudi Arabia.
Computer-aided diagnostic systems have achieved remarkable success in the medical field, particularly in diagnosing malignant tumors, and have done so at a rapid pace. However, the generalizability of the results remains a challenge for researchers and decreases the credibility of these models, which represents a point of criticism by physicians and specialists, especially given the sensitivity of the field. This study proposes a novel model based on deep learning to enhance lung cancer diagnosis quality, understandability, and generalizability.
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