胸部疾病放射诊断的新趋势和创新。

IF 7 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Jiyoung Song, Eui Jin Hwang, Soon Ho Yoon, Chang Min Park, Jin Mo Goo
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引用次数: 0

摘要

摘要:在过去的十年中,《调查放射学》发表了大量的研究成果,从根本上推动了胸部成像领域的发展。本文综述了成像方式、计算工具和临床应用方面的关键进展,重点介绍了胸部疾病(肺癌、肺结节、间质性肺疾病(ILD)、慢性阻塞性肺疾病(COPD)、COVID-19肺炎和肺栓塞)的重大突破,并概述了未来的发展方向。人工智能(AI)驱动的计算机辅助检测系统和放射学分析显著改善了肺结节的检测和分类,而光子计数检测器CT (PCD-CT)和低场MRI提供了更高的分辨率或无辐射策略。对于肺癌,CT结构分析和灌注成像可以改善预后和治疗计划。ILD评估受益于自动化诊断工具和创新成像技术,如PCD-CT和功能性MRI,它们减少了对侵入性诊断程序的需求,同时提高了准确性。在COPD中,基于双能ct的通气/灌注评估和暗场x线摄影可以更早地发现和分期肺气肿,并辅以深度学习方法来改进量化。COVID-19研究强调了胸部CT、x线片和基于人工智能的算法在快速分诊、疾病严重程度评估和随访方面的临床应用。此外,结核病仍然是一个重大的全球健康问题,这突出了人工智能辅助胸部x线摄影对早期发现和管理的重要性。同时,CT肺血管造影技术的进步,包括双能重建,使得肺栓塞的检测更加灵敏。总的来说,这些创新展示了融合新型成像技术、定量功能分析和人工智能驱动工具的力量,以改变胸部疾病管理。目前的进展有望为各种胸部疾病提供更精确和个性化的诊断和治疗策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emerging Trends and Innovations in Radiologic Diagnosis of Thoracic Diseases.

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.

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来源期刊
Investigative Radiology
Investigative Radiology 医学-核医学
CiteScore
15.10
自引率
16.40%
发文量
188
审稿时长
4-8 weeks
期刊介绍: Investigative Radiology publishes original, peer-reviewed reports on clinical and laboratory investigations in diagnostic imaging, the diagnostic use of radioactive isotopes, computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, digital subtraction angiography, and related modalities. Emphasis is on early and timely publication. Primarily research-oriented, the journal also includes a wide variety of features of interest to clinical radiologists.
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