1
|
Thorne MC. Special issues and computational techniques: the Bernard Wheatley Award for 2021. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2022; 42:030201. [PMID: 35815731 DOI: 10.1088/1361-6498/ac7e03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 07/04/2022] [Indexed: 06/15/2023]
Affiliation(s)
- M C Thorne
- Quarry Cottage, Hamsterley, Bishop Auckland, County Durham, DL13 3NJ, United Kingdom
| |
Collapse
|
2
|
Talaat K, Anderoglu O. Lagrangian Investigation of Convective Mass Transfer of Dissolved Elements at Specimen Boundaries in a Flowing Molten Lead Loop. NUCL SCI ENG 2022. [DOI: 10.1080/00295639.2022.2062107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Khaled Talaat
- University of New Mexico, Nuclear Engineering Department, Albuquerque, New Mexico 87106
| | - Osman Anderoglu
- University of New Mexico, Nuclear Engineering Department, Albuquerque, New Mexico 87106
| |
Collapse
|
3
|
Deciphering Exhaled Aerosol Fingerprints for Early Diagnosis and Personalized Therapeutics of Obstructive Respiratory Diseases in Small Airways. JOURNAL OF NANOTHERANOSTICS 2021. [DOI: 10.3390/jnt2030007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challenging to detect using current techniques due to the diseases’ location (inaccessibility to biopsy) and size (below normal CT/MRI resolution). In this review, we present a new method for lung disease detection and treatment in small airways based on exhaled aerosols, whose patterns are uniquely related to the health of the lungs. Proof-of-concept studies are first presented in idealized lung geometries. We subsequently describe the recent developments in feature extraction and classification of the exhaled aerosol images to establish the relationship between the images and the underlying airway remodeling. Different feature extraction algorithms (aerosol density, fractal dimension, principal mode analysis, and dynamic mode decomposition) and machine learning approaches (support vector machine, random forest, and convolutional neural network) are elaborated upon. Finally, future studies and frequent questions related to clinical applications of the proposed aerosol breath testing are discussed from the authors’ perspective. The proposed breath testing has clinical advantages over conventional approaches, such as easy-to-perform, non-invasive, providing real-time feedback, and is promising in detecting symptomless lung diseases at early stages.
Collapse
|