Evidence map›Paper›PMID 41144121›Full record

ArticleCurrent medical science2025

Image Quality Optimization in 60 kVp Head-Neck CTA: A Comparative Study of FBP, ClearView, and ClearInfinity Reconstruction Algorithms.

Shao-Fang Wang, Zhen Li, Li-Hui Dai, Huan Liu, Yan-Qiu Zhang, Yan Huang, Xiang-Yue Zha, Jing Zhang, Qiu-Xia Wang

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Current medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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2 citing papers in PubMed.

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5 · Who and what money

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9 authors.

Shao-Fang Wang *Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Zhen Li *Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Li-Hui DaiDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Huan LiuDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Yan-Qiu ZhangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Yan HuangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Xiang-Yue ZhaDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Jing ZhangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. tjh_jingzhang@hust.edu.cn.
Qiu-Xia WangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. wangqiuxia@hust.edu.cn.

Funding

Hubei Provincial Key Research and Development Program 2024BCB008National Key Research and Development Program of China 2024YFC2419300National Natural Science Foundation of China 82471967Natural Science Foundation of Hubei Province 2025AFB733
6 · The paper itself

Abstract

objectiveTo compare the impact of different reconstruction algorithms on the image quality of 60 kVp head and neck CT angiography (CTA) using subjective and objective metrics, with a focus on vessel edge sharpness.

methodsThis prospective study enrolled 45 patients who underwent ultra-low-voltage (60 kVp) head and neck CTA. Image datasets were reconstructed with filtered back-projection (FBP), ClearView (CV) and ClearInfinity (CI) algorithms at low (30%), medium (50%), and high (70%) strengths. Image quality was assessed subjectively and objectively via the Kruskal‒Wallis test for multiple comparisons. Objective parameters, including edge rise slope (ERS) and edge rise distance (ERD), were analyzed via the Friedman test of multiple comparisons statistics.

resultsSubjective assessments favored the CI50 reconstruction algorithm, demonstrating superior or satisfactory results compared to the other algorithms, with significantly better vessel delineation, edge definition and diagnostic confidence (all P < 0.05). Objective analysis revealed that the CV50 and CV70 algorithms significantly reduced ERS and/or elevated ERD (both P < 0.05). However, the CI50 algorithm maintained comparable vessel edge sharpness (P > 0.05) across all evaluated head and neck vascular segments when compared with the FBP algorithm.

conclusionsThe CI50 reconstruction algorithm optimizes image quality in 60 kVp head and neck CTA. It provides vessel edge sharpness comparable to FBP while offering superior vessel delineation, edge definition, and diagnostic confidence compared to FBP and CV algorithm. These findings suggest that CI50 has the potential to improve diagnostic accuracy in low-dose vascular imaging.

Indexed as

AlgorithmsComputed Tomography AngiographyHeadImage Processing, Computer-AssistedNeckRadiographic Image Interpretation, Computer-AssistedAdultAgedFemaleHumansMaleMiddle AgedProspective Studies60 kVpComputed tomography angiographyDeep learning reconstructionHeal-neck imagingImage qualityLow-dose CTReconstruction algorithmVessel sharpness

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