Emerging Trends and Innovations in Radiologic Diagnosis of Thoracic Diseases

Over the past decade, Investigative Radiology has published numerous studies that have fundamentally advanced the field of thoracic imaging. This review summarizes key developments in imaging modalities, computational tools, and clinical applications, highlighting major breakthroughs in thoracic diseases-lung cancer, pulmonary nodules, interstitial lung disease (ILD), chronic obstructive pulmonary disease (COPD), COVID-19 pneumonia, and pulmonary embolism-and outlining future directions.Artificial intelligence (AI)-driven computer-aided detection systems and radiomic analyses have notably improved the detection and classification of pulmonary nodules, while photon-counting detector CT (PCD-CT) and low-field MRI offer enhanced resolution or radiation-free strategies. For lung cancer, CT texture analysis and perfusion imaging refine prognostication and therapy planning. ILD assessment benefits from automated diagnostic tools and innovative imaging techniques, such as PCD-CT and functional MRI, which reduce the need for invasive diagnostic procedures while improving accuracy. In COPD, dual-energy CT-based ventilation/perfusion assessment and dark-field radiography enable earlier detection and staging of emphysema, complemented by deep learning approaches for improved quantification. COVID-19 research has underscored the clinical utility of chest CT, radiographs, and AI-based algorithms for rapid triage, disease severity evaluation, and follow-up. Furthermore, tuberculosis remains a significant global health concern, highlighting the importance of AI-assisted chest radiography for early detection and management. Meanwhile, advances in CT pulmonary angiography, including dual-energy reconstructions, allow more sensitive detection of pulmonary emboli.Collectively, these innovations demonstrate the power of merging novel imaging technologies, quantitative functional analysis, and AI-driven tools to transform thoracic disease management. Ongoing progress promises more precise and personalized diagnostic and therapeutic strategies for diverse thoracic diseases.

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Publication Details

Journal
Investigative Radiology
Published
2025-03-19
DOI
https://doi.org/10.1097/rli.0000000000001179
Citations
2
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
3.04
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Emerging Trends and Innovations in Radiologic Diagnosis of Thoracic Diseases

Jiyoung Song, Jin Mo Goo, Eui Jin Hwang, Soon Ho Yoon et al.
2 citations
Investigative Radiology
Lung Cancer Diagnosis and Treatment
3.04
article

Emerging Trends and Innovations in Radiologic Diagnosis of Thoracic Diseases

Jiyoung Song, Jin Mo Goo, Eui Jin Hwang, Soon Ho Yoon, Chang Min Park
article en
2 citations

Abstract

Over the past decade, Investigative Radiology has published numerous studies that have fundamentally advanced the field of thoracic imaging. This review summarizes key developments in imaging modalities, computational tools, and clinical applications, highlighting major breakthroughs in thoracic diseases-lung cancer, pulmonary nodules, interstitial lung disease (ILD), chronic obstructive pulmonary disease (COPD), COVID-19 pneumonia, and pulmonary embolism-and outlining future directions.Artificial intelligence (AI)-driven computer-aided detection systems and radiomic analyses have notably improved the detection and classification of pulmonary nodules, while photon-counting detector CT (PCD-CT) and low-field MRI offer enhanced resolution or radiation-free strategies. For lung cancer, CT texture analysis and perfusion imaging refine prognostication and therapy planning. ILD assessment benefits from automated diagnostic tools and innovative imaging techniques, such as PCD-CT and functional MRI, which reduce the need for invasive diagnostic procedures while improving accuracy. In COPD, dual-energy CT-based ventilation/perfusion assessment and dark-field radiography enable earlier detection and staging of emphysema, complemented by deep learning approaches for improved quantification. COVID-19 research has underscored the clinical utility of chest CT, radiographs, and AI-based algorithms for rapid triage, disease severity evaluation, and follow-up. Furthermore, tuberculosis remains a significant global health concern, highlighting the importance of AI-assisted chest radiography for early detection and management. Meanwhile, advances in CT pulmonary angiography, including dual-energy reconstructions, allow more sensitive detection of pulmonary emboli.Collectively, these innovations demonstrate the power of merging novel imaging technologies, quantitative functional analysis, and AI-driven tools to transform thoracic disease management. Ongoing progress promises more precise and personalized diagnostic and therapeutic strategies for diverse thoracic diseases.

Investigative RadiologyVol. 61(3)
Seoul National University Hospital (KR)
Openalex Percentile: Top 10%
Lung Cancer Diagnosis and Treatment
3.04
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