Feasibility of Sub-milliSievert Low-dose Computed Tomography with Deep Learning Image Reconstruction in Evaluating Pulmonary Subsolid Nodules: A Prospective Intra-individual Comparison Study.

IF 3.8 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Huiyuan Zhu, Zike Huang, Qunhui Chen, Weiling Ma, Jiahui Yu, Shiqing Wang, Guangyu Tao, Jun Xing, Haixin Jiang, Xiwen Sun, Jing Liu, Hong Yu, Lin Zhu
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引用次数: 0

Abstract

Rationale and objectives: To comprehensively assess the feasibility of low-dose computed tomography (LDCT) using deep learning image reconstruction (DLIR) for evaluating pulmonary subsolid nodules, which are challenging due to their susceptibility to noise.

Materials and methods: Patients undergoing both standard-dose CT (SDCT) and LDCT between March and June 2023 were prospectively enrolled. LDCT images were reconstructed with high-strength DLIR (DLIR-H), medium-strength DLIR (DLIR-M), adaptive statistical iterative reconstruction-V level 50% (ASIR-V-50%), and filtered back projection (FBP); SDCT with FBP as the reference standard. Objective assessment, including image noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR), and subjective assessment using five-point scales by five radiologists were performed. Detection and false-positive rate of subsolid nodules, and morphologic features of nodules were recorded.

Results: 102 patients (mean age, 57.0 ± 12.3 years) with 358 subsolid nodules in SDCT were enrolled. The mean effective dose of SDCT and LDCT were 5.37 ± 0.80mSv and 0.86 ± 0.14mSv, respectively (P < 0.001). DLIR-H showed the lowest noise, highest CNRs, SNRs, and subjective scores among LDCT groups (all P < 0.001), almost approaching comparability with SDCT. The detection rates for DLIR-H, DLIR-M, ASIR-V-50%, and FBP were 76.5%, 76.3%, 83.8%, and 72.1%, respectively (P < 0.001), with false-positive rate of 2.5%, 2.2%, 8.3%, and 1.1%, respectively (P < 0.001). DLIR-H showed the highest detection rates for morphologic features (79.4%-95.2%) compared to DLIR-M (74.6%-88.9%), ASIR-V-50% (72.0%-88.4%), and FBP (66.1%-84.1%) (all P ≤ 0.001).

Conclusion: Sub-milliSievert LDCT with DLIR-H offers substantial dose reduction without compromising image quality. It is promising for evaluating subsolid nodules with a high detection rate and better identification of morphologic features.

亚毫西弗低剂量计算机断层扫描与深度学习图像重建在评估肺部实性下结节中的可行性:一项前瞻性个体内比较研究。
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
Academic Radiology
Academic Radiology 医学-核医学
CiteScore
7.60
自引率
10.40%
发文量
432
审稿时长
18 days
期刊介绍: Academic Radiology publishes original reports of 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, image-guided interventions and related techniques. It also includes brief technical reports describing original observations, techniques, and instrumental developments; state-of-the-art reports on clinical issues, new technology and other topics of current medical importance; meta-analyses; scientific studies and opinions on radiologic education; and letters to the Editor.
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