利用未增强胸部计算机断层扫描图像对肺部病变进行定量分析。

IF 1.9 4区 医学 Q3 RESPIRATORY SYSTEM
Fariba Zarei, Payam Jannatdoust, Siamak Malekpour, Mahshad Razaghi, Sabyasachi Chatterjee, Vani Varadhan Chatterjee, Amirbahador Abbasi, Rezvan Ravanfar Haghighi
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引用次数: 0

摘要

简介胸片和计算机断层扫描(CT)可能会意外发现肺部结节。如果没有特定的成像特征,如钙化、坏死和对比度增强,很难区分恶性和良性肺结节。然而,这些病变可能表现出不同的图像纹理特征,无法通过肉眼进行评估。因此,Hounsfield 单位(HU)值的直方图分析(HA)等计算机辅助定量方法可以提高诊断准确性,减少侵入性活检的需要:在这项探索性对照研究中,我们回顾性地选择了 20 名良性病变(10 人)和癌症(10 人)患者的非增强胸部 CT 图像。良性病变和恶性病变在胸部 CT 图像中的表现非常相似,因此只能通过病理报告来鉴别。每个病灶的所有切片都在病灶内部插入了自由手感兴趣区(ROI)。记录 HU 值的平均值、最小值、最大值和标准偏差,并利用这些值制作 HA:HA显示,大多数恶性病变的平均HU值介于30和50之间,最大HU值小于150,最小HU值介于-30和20之间。结论:结论:定量 CT 分析可在未增强胸部 CT 图像上区分恶性和良性病变,但没有特定的恶性模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Quantitative analysis of lung lesions using unenhanced chest computed tomography images

Quantitative analysis of lung lesions using unenhanced chest computed tomography images

Introduction

Chest radiograph and computed tomography (CT) scans can accidentally reveal pulmonary nodules. Malignant and benign pulmonary nodules can be difficult to distinguish without specific imaging features, such as calcification, necrosis, and contrast enhancement. However, these lesions may exhibit different image texture characteristics which cannot be assessed visually. Thus, a computer-assisted quantitative method like histogram analysis (HA) of Hounsfield unit (HU) values can improve diagnostic accuracy, reducing the need for invasive biopsy.

Methods

In this exploratory control study, nonenhanced chest CT images of 20 patients with benign (10) and cancerous (10) lesion were selected retrospectively. The appearances of benign and malignant lesions were very similar in chest CT images, and only pathology report was used to discriminate them. Free hand region of interest (ROI) was inserted inside the lesion for all slices of each lesion. Mean, minimum, maximum, and standard deviations of HU values were recorded and used to make HA.

Results

HA showed that the most malignant lesions have a mean HU value between 30 and 50, a maximum HU less than 150, and a minimum HU between −30 and 20. Lesions outside these ranges were mostly benign.

Conclusion

Quantitative CT analysis may differentiate malignant from benign lesions without specific malignancy patterns on unenhanced chest CT image.

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来源期刊
Clinical Respiratory Journal
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)
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