New perspectives on advances in diagnosis through imaging in chronic respiratory diseases: a systematic literature review

Authors

DOI:

https://doi.org/10.51798/sijis.v5i1.717

Keywords:

Chronic respiratory diseases, Imaging technologies, Artificial intelligence, Diagnosis, Treatment

Abstract

Background: Chronic respiratory diseases, such as asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease, and cystic fibrosis, present substantial global health challenges. This systematic review explores recent advances in imaging-based diagnostic methods for these conditions, emphasizing high-resolution computed tomography (HRCT), magnetic resonance imaging (MRI), positron emission tomography (PET), and artificial intelligence (AI). Methodology: A systematic search of databases identified studies published in the last five years, focusing on innovative imaging techniques for chronic respiratory diseases. Inclusion criteria emphasized diagnostic accuracy and advancements in imaging modalities. Results: Seven studies were included, covering interventions in intensive care, mesenchymal stem cell therapy for COVID-19-induced acute respiratory distress syndrome (ARDS), endovascular treatment for aortic arch aneurysms, and lung cancer screening. MSC therapy demonstrated positive outcomes in ARDS patients, while endovascular repair showed technical success. LungSEARCH highlighted the effectiveness of lung cancer screening in high-risk populations. Discussion: Recent imaging technologies, including HRCT, MRI, PET, and AI, have revolutionized chronic respiratory disease diagnosis. The review emphasizes their clinical applications, impact on patient outcomes, and potential for personalized medicine. AI enhances image analysis accuracy, yet challenges like cost and interpretation discrepancies persist. Conclusion: Imaging technologies, particularly HRCT, MRI, PET, and AI, show promise in improving diagnostic accuracy and personalized treatment for chronic respiratory diseases. Collaboration among healthcare professionals, researchers, and industry stakeholders is crucial for addressing challenges and ensuring widespread access to advanced diagnostic tools. Future directions involve refining imaging methods for routine clinical integration, advancing patient care, and reducing the burden of respiratory diseases.

Author Biographies

Annabel Fernández Alfonso, Universidad de Ciencias Médicas de la Habana, Cuba

Intensive Care and Emergencies Specialist, Universidad de Ciencias Médicas de la Habana, Cuba. 

Katherine María Guevara Suárez, Universidad de las Américas, Ecuador

General Physician and Graduate Researcher, Universidad de las Américas, Ecuador

Cristian Xavier Proaño Bautista, Universidad Nacional de Chimborazo, Ecuador

General Physician and Researcher, Universidad Nacional de Chimborazo, Ecuador

Rosa Mercerdes Cantos Cantos, Universidad Católica de Cuenca, Ecuador

General Physician and Researcher, Universidad Católica de Cuenca, Ecuador

Gissela Nicool Calvache Cañar, Hospital Yarovi Makuar, Ecuador

General Physician and Researcher, Hospital Yarovi Makuar, Ecuador

References

Almalki, W. H. (2022). Introduction to Lung Disease. In Microbiome in Inflammatory Lung Diseases (pp. 1-12): Springer.

Bartholmai, B. J., Raghunath, S., Karwoski, R. A., Moua, T., Rajagopalan, S., Maldonado, F., . . . Robb, R. A. J. J. o. t. i. (2013). Quantitative CT imaging of interstitial lung diseases. 28(5).

Cohade, C., & Wahl, R. L. (2003). Applications of positron emission tomography/computed tomography image fusion in clinical positron emission tomography—clinical use, interpretation methods, diagnostic improvements. Paper presented at the Seminars in nuclear medicine.

Dupuis, J., Harel, F., Nguyen, Q. T. J. C., & Imaging, T. (2014). Molecular imaging of the pulmonary circulation in health and disease. 2, 415-426.

Fekete, M., Fazekas-Pongor, V., Balazs, P., Tarantini, S., Nemeth, A. N., & Varga, J. T. J. W. K. W. (2021). Role of new digital technologies and telemedicine in pulmonary rehabilitation: Smart devices in the treatment of chronic respiratory diseases. 133(21-22), 1201-1207.

Fernández-Francos, S., Eiro, N., González-Galiano, N., & Vizoso, F. J. J. I. j. o. m. s. (2021). Mesenchymal stem cell-based therapy as an alternative to the treatment of acute respiratory distress syndrome: current evidence and future perspectives. 22(15), 7850.

Gorman, E., Millar, J., McAuley, D., & O’Kane, C. J. E. r. o. r. m. (2021). Mesenchymal stromal cells for acute respiratory distress syndrome (ARDS), sepsis, and COVID-19 infection: optimizing the therapeutic potential. 15(3), 301-324.

Hasan, D., Imam, H., Megally, H., Makhlouf, H., ElKady, R. J. E. J. o. R., & Medicine, N. (2020). The qualitative and quantitative high-resolution computed tomography in the evaluation of interstitial lung diseases. 51(1), 1-7.

Hashemian, S.-M. R., Aliannejad, R., Zarrabi, M., Soleimani, M., Vosough, M., Hosseini, S.-E., . . . therapy. (2021). Mesenchymal stem cells derived from perinatal tissues for treatment of critically ill COVID-19-induced ARDS patients: a case series. 12(1), 1-12.

Hisert, K. B., Birket, S. E., Clancy, J. P., Downey, D. G., Engelhardt, J. F., Fajac, I., . . . Thibodeau, P. J. T. l. r. m. (2023). Understanding and addressing the needs of people with cystic fibrosis in the era of CFTR modulator therapy. 11(10), 916-931.

Hsueh, P.-R., Ho, S.-J., Hsieh, P.-C., Liu, I.-M., & Jean, S.-S. J. S. C. I. (2023). Use of Multiple Doses of Intravenous Infusion of Umbilical Cord-Mesenchymal Stem Cells for the Treatment of Adult Patients with Severe COVID-19-Related Acute Respiratory Distress Syndrome: Literature Review. 2023.

Huang, C., Huang, L., Wang, Y., Li, X., Ren, L., Gu, X., . . . Zhou, X. J. T. L. (2021). 6-month consequences of COVID-19 in patients discharged from hospital: a cohort study. 397(10270), 220-232.

Jeny, F., Brillet, P.-Y., Kim, Y.-W., Freynet, O., Nunes, H., & Valeyre, D. J. E. r. o. r. m. (2019). The place of high-resolution computed tomography imaging in the investigation of interstitial lung disease. 13(1), 79-94.

Jeon, H., Da Nam, B., Yoon, C.-H., & Kim, H.-S. J. J. o. R. D. (2024). Radiologic approach and progressive exploration of connective tissue disease-related interstitial lung disease: meeting the curiosity of rheumatologists. 31(1), 3.

Klumpp, M., Hintze, M., Immonen, M., Ródenas-Rigla, F., Pilati, F., Aparicio-Martínez, F., . . . Urbann, O. (2021). Artificial intelligence for hospital health care: Application cases and answers to challenges in European hospitals. Paper presented at the Healthcare.

Kusmirek, J. E., Magnusson, J. D., & Perlman, S. B. J. C. P. R. (2020). Current applications for nuclear medicine imaging in pulmonary disease. 9, 82-95.

Ley-Zaporozhan, J., Ley, S., & Kauczor, H.-U. J. E. r. (2008). Morphological and functional imaging in COPD with CT and MRI: present and future. 18, 510-521.

Martinez, F. J., Collard, H. R., Pardo, A., Raghu, G., Richeldi, L., Selman, M., . . . Wells, A. U. J. N. r. D. p. (2017). Idiopathic pulmonary fibrosis. 3(1), 1-19.

Members, W. C., Isselbacher, E. M., Preventza, O., Hamilton Black III, J., Augoustides, J. G., Beck, A. W., . . . Brown-Zimmerman, M. M. J. J. o. t. A. C. o. C. (2022). 2022 ACC/AHA guideline for the diagnosis and management of aortic disease: a report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. 80(24), e223-e393.

Milne, S., & King, G. G. J. J. o. t. d. (2014). Advanced imaging in COPD: insights into pulmonary pathophysiology. 6(11), 1570.

Nachiappan, A. C., Rahbar, K., Shi, X., Guy, E. S., Mortani Barbosa Jr, E. J., Shroff, G. S., . . . Hammer, M. M. J. R. (2017). Pulmonary tuberculosis: role of radiology in diagnosis and management. 37(1), 52-72.

Ohno, Y., Hanamatsu, S., Obama, Y., Ueda, T., Ikeda, H., Hattori, H., . . . Toyama, H. J. T. B. J. o. R. (2022). Overview of MRI for pulmonary functional imaging. 95(1132), 20201053.

Razzak, M. I., Naz, S., & Zaib, A. J. C. i. B. A. o. D. M. (2018). Deep learning for medical image processing: Overview, challenges and the future. 323-350.

Rush, A. J., & Ibrahim, H. M. J. F. (2018). A clinician’s perspective on biomarkers. 16(2), 124-134.

Shukla, S. D., Vanka, K. S., Chavelier, A., Shastri, M. D., Tambuwala, M. M., Bakshi, H. A., . . . O’toole, R. F. (2020). Chronic respiratory diseases: An introduction and need for novel drug delivery approaches. In Targeting chronic inflammatory lung diseases using advanced drug delivery systems (pp. 1-31): Elsevier.

Spiro, S. G., Shah, P. L., Rintoul, R. C., George, J., Janes, S., Callister, M., . . . Griffiths, C. J. E. R. J. (2019). Sequential screening for lung cancer in a high-risk group: randomised controlled trial: LungSEARCH: a randomised controlled trial of Surveillance using sputum and imaging for the EARly detection of lung Cancer in a High-risk group. 54(4).

Stewart, N. J., Smith, L. J., Chan, H.-F., Eaden, J. A., Rajaram, S., Swift, A. J., . . . Hughes, D. J. T. B. J. o. R. (2022). Lung MRI with hyperpolarised gases: current & future clinical perspectives. 95(1132), 20210207.

Turner, C. (2021). Quantification of Respiratory Motion in Positron Emission Tomography for Precise Radiation Treatment of Lung Cancer.

van der Kamp, M. R., Hengeveld, V. S., Brusse-Keizer, M. G., Thio, B. J., & Tabak, M. J. J. o. M. I. R. (2023). eHealth Technologies for Monitoring Pediatric Asthma at Home: Scoping Review. 25, e45896.

Vanfleteren, L. E., Kocks, J. W., Stone, I. S., Breyer-Kohansal, R., Greulich, T., Lacedonia, D., . . . Barnes, N. J. T. (2013). Moving from the Oslerian paradigm to the post-genomic era: are asthma and COPD outdated terms? , thoraxjnl-2013-203602.

Walsh, S. L., & Hansell, D. M. (2014). High-resolution CT of interstitial lung disease: a continuous evolution. Paper presented at the Seminars in respiratory and critical care medicine.

Washko, G. R., & Parraga, G. J. E. R. J. (2018). COPD biomarkers and phenotypes: opportunities for better outcomes with precision imaging. 52(5).

Weatherley, N. D., Eaden, J. A., Stewart, N. J., Bartholmai, B. J., Swift, A. J., Bianchi, S. M., & Wild, J. M. J. T. (2019). Experimental and quantitative imaging techniques in interstitial lung disease. thoraxjnl-2018-211779.

Wong, J., Tenorio, E. R., Lima, G., Dias-Neto, M., Baghbani-Oskouei, A., Mendes, B., . . . Radiology, I. (2023). Early Feasibility of Endovascular Repair of Distal Aortic Arch Aneurysms Using Patient-Specific Single Retrograde Left Subclavian Artery Branch Stent Graft. 46(2), 249-254.

Yu, Y., Jain, B., Anand, G., Heidarian, M., Lowe, A., Kalra, A. J. B., & X, B. (2023). Technologies for non-invasive physiological sensing: Status, challenges, and future horizons. 100420.

Zhou, S. K., Greenspan, H., Davatzikos, C., Duncan, J. S., Van Ginneken, B., Madabhushi, A., . . . Summers, R. M. J. P. o. t. I. (2021). A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises. 109(5), 820-838.

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Published

2024-02-23

How to Cite

Fernández Alfonso, A. ., Guevara Suárez, K. M., Proaño Bautista, C. X., Cantos Cantos, R. M., & Calvache Cañar, G. N. (2024). New perspectives on advances in diagnosis through imaging in chronic respiratory diseases: a systematic literature review. Sapienza: International Journal of Interdisciplinary Studies, 5(1), e24019. https://doi.org/10.51798/sijis.v5i1.717

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Health Sciences - Original Articles