Suppr超能文献

扩散加权成像和T2加权成像联合评估可用于肺癌与良性肺结节及肿块的鉴别诊断。

Combination Assessment of Diffusion-Weighted Imaging and T2-Weighted Imaging Is Acceptable for the Differential Diagnosis of Lung Cancer from Benign Pulmonary Nodules and Masses.

作者信息

Usuda Katsuo, Ishikawa Masahito, Iwai Shun, Iijima Yoshihito, Motono Nozomu, Matoba Munetaka, Doai Mariko, Hirata Keiya, Uramoto Hidetaka

机构信息

Department of Thoracic Surgery, Kanazawa Medical University, Ishikawa 920-0293, Japan.

Department of Radiology, Kanazawa Medical University, Ishikawa 920-0293, Japan.

出版信息

Cancers (Basel). 2021 Mar 28;13(7):1551. doi: 10.3390/cancers13071551.

Abstract

The purpose of this study is to determine whether the combination assessment of DWI and T2-weighted imaging (T2WI) improves the diagnostic ability for differential diagnosis of lung cancer from benign pulmonary nodules and masses (BPNMs). The optimal cut-off value (OCV) for differential diagnosis was set at 1.470 × 10 mm/s for apparent diffusion coefficient (ADC), and at 2.45 for T2 contrast ratio (T2 CR). The ADC (1.24 ± 0.29 × 10 mm/s) of lung cancer was significantly lower than that (1.69 ± 0.58 × 10 mm/s) of BPNM. The T2 CR (2.01 ± 0.52) of lung cancer was significantly lower than that (2.74 ± 1.02) of BPNM. As using the OCV for ADC, the sensitivity was 83.9% (220/262), the specificity 63.4% (33/52), and the accuracy 80.6% (253/314). As using the OCV for T2 CR, the sensitivity was 89.7% (235/262), the specificity 61.5% (32/52), and the accuracy 85.0% (267/314). In 212 PNMs which were judged to be malignant by both DWI and T2WI, 203 PNMs (95.8%) were lung cancers. In 33 PNMs which were judged to be benign by both DWI and T2WI, 23 PNMs (69.7%) were BPNMs. The combined assessment of DWI and T2WI could judge PNMs more precisely and would be acceptable for differential diagnosis of PNMs.

摘要

本研究的目的是确定弥散加权成像(DWI)与T2加权成像(T2WI)的联合评估是否能提高肺癌与良性肺结节及肿块(BPNM)鉴别诊断的诊断能力。鉴别诊断的最佳截断值(OCV)设定为表观扩散系数(ADC)为1.470×10⁻³mm²/s,T2对比率(T2 CR)为2.45。肺癌的ADC(1.24±0.29×10⁻³mm²/s)显著低于BPNM的ADC(1.69±0.58×10⁻³mm²/s)。肺癌的T2 CR(2.01±0.52)显著低于BPNM的T2 CR(2.74±1.02)。以ADC的OCV进行判断时,敏感性为83.9%(220/262),特异性为63.4%(33/52),准确性为80.6%(253/314)。以T2 CR的OCV进行判断时,敏感性为89.7%(235/262),特异性为61.5%(32/52),准确性为85.0%(267/314)。在DWI和T2WI均判定为恶性的212个肺结节中,203个(95.8%)为肺癌。在DWI和T2WI均判定为良性的33个肺结节中,23个(69.7%)为BPNM。DWI与T2WI的联合评估能更准确地判断肺结节,可用于肺结节的鉴别诊断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffb/8037373/72f99c595da7/cancers-13-01551-g001.jpg

相似文献

7
Differentiating benign and malignant inflammatory breast lesions: Value of T2 weighted and diffusion weighted MR images.
Magn Reson Imaging. 2018 Jul;50:38-44. doi: 10.1016/j.mri.2018.03.012. Epub 2018 Mar 12.

引用本文的文献

1
Zero-echo time magnetic resonance imaging for visualizing pulmonary neoplasms.
BMC Med Imaging. 2025 Jul 7;25(1):274. doi: 10.1186/s12880-025-01666-5.
2
Diffusion-Weighted MRI: Potential Tool for Pulmonary Nodule Characterization.
Indian J Radiol Imaging. 2023 Nov 23;34(1):1-2. doi: 10.1055/s-0043-1776884. eCollection 2024 Jan.
3
Predicting Non-Small-Cell Lung Cancer Survival after Curative Surgery via Deep Learning of Diffusion MRI.
Diagnostics (Basel). 2023 Aug 1;13(15):2555. doi: 10.3390/diagnostics13152555.
5
State of the Art: Lung Cancer Staging Using Updated Imaging Modalities.
Bioengineering (Basel). 2022 Sep 22;9(10):493. doi: 10.3390/bioengineering9100493.
8
Automatic Detection of Colorectal Polyps Using Transfer Learning.
Sensors (Basel). 2021 Aug 24;21(17):5704. doi: 10.3390/s21175704.

本文引用的文献

2
MRI in Evaluation of Solitary Pulmonary Nodules.
Turk Thorac J. 2019 Jan 31;20(2):90-96. doi: 10.5152/TurkThoracJ.2018.18049. Print 2019 Apr.
3
Conventional MRI to detect the differences between mass-like tuberculosis and lung cancer.
J Thorac Dis. 2018 Oct;10(10):5673-5684. doi: 10.21037/jtd.2018.09.125.
4
Can Solitary Pulmonary Nodules Be Accurately Characterized with Diffusion-weighted MRI?
Radiology. 2019 Feb;290(2):535-536. doi: 10.1148/radiol.2018182442. Epub 2018 Nov 27.
8
Progressive massive fibrosis in patients with pneumoconiosis: utility of MRI in differentiating from lung cancer.
Acta Radiol. 2018 Jan;59(1):72-80. doi: 10.1177/0284185117700929. Epub 2017 Mar 31.
9
ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases-a Preliminary Study.
Mol Imaging Biol. 2017 Dec;19(6):953-962. doi: 10.1007/s11307-017-1073-y.
10
Molecular magnetic resonance imaging in cancer.
J Transl Med. 2015 Sep 23;13:313. doi: 10.1186/s12967-015-0659-x.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验