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Diagnostics
Volume 15
Issue 3
10.3390/diagnostics15030278
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Review

Integrating Radiomics Signature into Clinical Pathway for Patients with Progressive Pulmonary Fibrosis

by
Giacomo Sica
1,*,†,
Vito D'Agnano
2,3,*,†,
Simon Townend Bate
3,
Federica Romano
1,
Vittorio Viglione
4,
Linda Franzese
2,5,
Mariano Scaglione
6,
Stefania Tamburrini
7,
Alfonso Reginelli
4 and
Fabio Perrotta
2,5
1
Radiology Unit, Monaldi Hospital, A.O. dei Colli, 80131 Naples, Italy
2
Department of Translational Medical Sciences, University of Campania L. Vanvitelli, 80131 Naples, Italy
3
Lungs for Living Research Centre, UCL Respiratory, University College London, London WC1E 6BT, UK
4
Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy
5
U.O.C. Clinica Pneumologica L. Vanvitelli, Monaldi Hospital, A.O. dei Colli, 80131 Naples, Italy
6
Radiology Department of Surgery, Medicine and Pharmacy, University of Sassari, 07100 Sassari, Italy
7
Department of Radiology, Ospedale del Mare, ASL NA1 Centro, 80147 Naples, Italy
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Diagnostics 2025, 15(3), 278; https://doi.org/10.3390/diagnostics15030278
Submission received: 8 December 2024 / Revised: 19 January 2025 / Accepted: 21 January 2025 / Published: 24 January 2025
(This article belongs to the Special Issue Cardiothoracic Imaging: Recent Techniques and Applications in Diagnostics, Third Edition)
Versions Notes

Abstract

Interstitial lung diseases (ILDs) are a heterogeneous group of pulmonary disorders characterised by variable degrees of inflammation, interstitial thickening, and fibrosis leading to distortion of the pulmonary architecture and gas exchange impairment. There are approximately 200 different entities in this category. ILDs are commonly classified based on several criteria, including causes, clinical features, and radiological patterns. Chest HRCT is the gold standard for the recognition of lung alteration patterns underlying interstitial lung diseases (ILDs), diagnosing specific patterns, and evaluating radiologic progression. Methods based on artificial intelligence (AI) may be used in computational medicine, especially in image-based specialties such as radiology. The evolving field of radiomics offers a unique and non-invasive approach to extracting quantitative information from medical images, particularly high-resolution computed tomography (HRCT) scans. This comprehensive review explores the burgeoning role of radiomics in unravelling the intricacies of interstitial lung disease. It focuses on its potential applications in diagnosis, prognostication, and treatment response evaluation.
Keywords: interstitial lung diseases; ILD; radiomics; artificial intelligence; deep learning; progressive pulmonary fibrosis interstitial lung diseases; ILD; radiomics; artificial intelligence; deep learning; progressive pulmonary fibrosis

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MDPI and ACS Style

Sica, G.; D'Agnano, V.; Bate, S.T.; Romano, F.; Viglione, V.; Franzese, L.; Scaglione, M.; Tamburrini, S.; Reginelli, A.; Perrotta, F. Integrating Radiomics Signature into Clinical Pathway for Patients with Progressive Pulmonary Fibrosis. Diagnostics 2025, 15, 278. https://doi.org/10.3390/diagnostics15030278

AMA Style

Sica G, D'Agnano V, Bate ST, Romano F, Viglione V, Franzese L, Scaglione M, Tamburrini S, Reginelli A, Perrotta F. Integrating Radiomics Signature into Clinical Pathway for Patients with Progressive Pulmonary Fibrosis. Diagnostics. 2025; 15(3):278. https://doi.org/10.3390/diagnostics15030278

Chicago/Turabian Style

Sica, Giacomo, Vito D'Agnano, Simon Townend Bate, Federica Romano, Vittorio Viglione, Linda Franzese, Mariano Scaglione, Stefania Tamburrini, Alfonso Reginelli, and Fabio Perrotta. 2025. "Integrating Radiomics Signature into Clinical Pathway for Patients with Progressive Pulmonary Fibrosis" Diagnostics 15, no. 3: 278. https://doi.org/10.3390/diagnostics15030278

APA Style

Sica, G., D'Agnano, V., Bate, S. T., Romano, F., Viglione, V., Franzese, L., Scaglione, M., Tamburrini, S., Reginelli, A., & Perrotta, F. (2025). Integrating Radiomics Signature into Clinical Pathway for Patients with Progressive Pulmonary Fibrosis. Diagnostics, 15(3), 278. https://doi.org/10.3390/diagnostics15030278

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