Successful Application of Artificial Intelligence-Assisted Analysis of Invasive Pulmonary Adenocarcinoma Less Than 6 mm in Size: A Case Report and Literature Review

IF 1.9 4区医学 Q3 RESPIRATORY SYSTEM

Clinical Respiratory Journal Pub Date : 2025-05-28 DOI:10.1111/crj.70073

Lu Zhang, Dawei Yang, Xianwei Ye, Chunxue Bai

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引用次数: 0

Abstract

Introduction

Screening of lung nodules helps on early diagnosis of lung cancer, especially invasive pulmonary adenocarcinoma. Artificial intelligence (AI) has been applied in diagnosis of cancers. We used the AI-assisted lung nodule diagnostic system in the screening of lung nodules and lung cancer.

Case Presentation

A 66-year-old male complained of coughs and nodules in the right lung of 3-year duration. A ground-glass opacity was found in the right upper lung by routine computed tomography (CT). He had no family history of cancer, genetic diseases, or infectious diseases. AI-assisted analysis found four nodules, of which one was with the risk of malignancy of 88% (LungRads3), one was with the risk of malignancy of 15% (LungRads2), and the other two were smaller in size and considered benign. The patient underwent a thoracoscopic wedge resection of the right upper lung. The intraoperative frozen section pathology report confirmed invasive pulmonary adenocarcinoma, grade II, and primarily of alveolar and adherent types without metastasis.

Conclusion

In summary, AI-assisted lung nodule diagnostic system is effective in the screening of lung nodules and the differentiation between benign and malignant.

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人工智能辅助分析6mm以下浸润性肺腺癌的成功应用：1例报告及文献复习

肺结节筛查有助于肺癌的早期诊断，尤其是浸润性肺腺癌。人工智能（AI）已被应用于癌症诊断。我们使用人工智能辅助肺结节诊断系统筛查肺结节和肺癌。66岁男性，自诉咳嗽及右肺结节3年。常规CT示右上肺磨玻璃影。他没有癌症、遗传疾病或传染病的家族史。人工智能辅助分析发现4个结节，其中1个结节的恶性风险为88% (lungrad3)， 1个结节的恶性风险为15% (LungRads2)，另外2个较小，认为是良性的。患者接受了胸腔镜右上肺楔形切除术。术中冰冻切片病理报告证实浸润性肺腺癌，II级，主要为肺泡型和粘附型，无转移。结论综上所述，人工智能辅助肺结节诊断系统对肺结节的筛查及良恶性鉴别具有较好的应用价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical Respiratory Journal 医学-呼吸系统

CiteScore

3.70

自引率

0.00%

发文量

104

审稿时长

>12 weeks

期刊介绍： Overview Effective with the 2016 volume, this journal will be published in an online-only format. Aims and Scope The Clinical Respiratory Journal (CRJ) provides a forum for clinical research in all areas of respiratory medicine from clinical lung disease to basic research relevant to the clinic. We publish original research, review articles, case studies, editorials and book reviews in all areas of clinical lung disease including: Asthma Allergy COPD Non-invasive ventilation Sleep related breathing disorders Interstitial lung diseases Lung cancer Clinical genetics Rhinitis Airway and lung infection Epidemiology Pediatrics CRJ provides a fast-track service for selected Phase II and Phase III trial studies. Keywords Clinical Respiratory Journal, respiratory, pulmonary, medicine, clinical, lung disease, Abstracting and Indexing Information Academic Search (EBSCO Publishing) Academic Search Alumni Edition (EBSCO Publishing) Embase (Elsevier) Health & Medical Collection (ProQuest) Health Research Premium Collection (ProQuest) HEED: Health Economic Evaluations Database (Wiley-Blackwell) Hospital Premium Collection (ProQuest) Journal Citation Reports/Science Edition (Clarivate Analytics) MEDLINE/PubMed (NLM) ProQuest Central (ProQuest) Science Citation Index Expanded (Clarivate Analytics) SCOPUS (Elsevier)