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超低剂量胸部 CT 结合降噪技术在肺结节检测中的应用。

Ultra-Low Dose Chest CT with Denoising for Lung Nodule Detection.

机构信息

Department of Diagnostic Radiology, Sheba Medical Center, Tel Hashomer, Israel.

Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

出版信息

Isr Med Assoc J. 2021 Sep;23(9):550-555.

PMID:34472229
Abstract

BACKGROUND

Medical imaging and the resultant ionizing radiation exposure is a public concern due to the possible risk of cancer induction.

OBJECTIVES

To assess the accuracy of ultra-low-dose (ULD) chest computed tomography (CT) with denoising versus normal dose (ND) chest CT using the Lung CT Screening Reporting and Data System (Lung-RADS).

METHODS

This prospective single-arm study comprised 52 patients who underwent both ND and ULD scans. Subsequently AI-based denoising methods were applied to produce a denoised ULD scan. Two chest radiologists independently and blindly assessed all scans. Each scan was assigned a Lung-RADS score and grouped as 1 + 2 and 3 + 4.

RESULTS

The study included 30 men (58%) and 22 women (42%); mean age 69.9 ± 9 years (range 54-88). ULD scan radiation exposure was comparable on average to 3.6-4.8% of the radiation depending on patient BMI. Denoising increased signal-to-noise ratio by 27.7%. We found substantial inter-observer agreement in all scans for Lung-RADS grouping. Denoised scans performed better than ULD scans when negative likelihood ratio (LR-) was calculated (0.04--0.08 vs. 0.08-0.12). Other than radiation changes, diameter measurement differences and part-solid nodules misclassification as a ground-glass nodule caused most Lung-RADS miscategorization.

CONCLUSIONS

When assessing asymptomatic patients for pulmonary nodules, finding a negative screen using ULD CT with denoising makes it highly unlikely for a patient to have a pulmonary nodule that requires aggressive investigation. Future studies of this technique should include larger cohorts and be considered for lung cancer screening as radiation exposure is radically reduced.

摘要

背景

由于电离辐射致癌的可能性,医学影像学及其带来的辐射暴露是公众关注的焦点。

目的

使用 Lung CT Screening Reporting and Data System(Lung-RADS)评估超低剂量(ULD)胸部 CT 与常规剂量(ND)胸部 CT 的去噪降噪的准确性。

方法

这项前瞻性单臂研究纳入了 52 名同时接受 ND 和 ULD 扫描的患者。随后,应用基于人工智能的去噪方法生成去噪 ULD 扫描。两名胸部放射科医生独立且盲法评估所有扫描。为每个扫描分配一个 Lung-RADS 评分,并将其分为 1+2 组和 3+4 组。

结果

研究纳入 30 名男性(58%)和 22 名女性(42%);平均年龄 69.9±9 岁(54-88 岁)。根据患者 BMI,ULD 扫描的辐射暴露平均相当于 ND 扫描的 3.6%-4.8%。去噪可将信噪比提高 27.7%。我们发现,在所有扫描中,观察者间对 Lung-RADS 分组的一致性都很高。当计算负似然比(LR-)时,去噪扫描比 ULD 扫描表现更好(0.04-0.08 比 0.08-0.12)。除了辐射变化,直径测量差异和部分实性结节误诊为磨玻璃结节是造成 Lung-RADS 误分类的主要原因。

结论

在对无症状患者进行肺结节评估时,使用 ULD CT 进行去噪降噪后,如果结果为阴性,那么患者患有需要进行积极检查的肺结节的可能性极低。应在未来的此类技术研究中纳入更大的队列,并将其考虑用于肺癌筛查,因为辐射暴露会大幅降低。

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