头颅CT成像解剖和指征诊断参考水平(DRLs)的比较:对辐射剂量管理的意义。

IF 3.3 Q2 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Imaging Pub Date : 2025-03-19 eCollection Date: 2025-01-01 DOI:10.1155/ijbi/6464273
Benard Ohene-Botwe, Samuel Anim-Sampong, Robert Saizi
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引用次数: 0

摘要

计算机断层扫描(CT)成像中的许多诊断参考水平(drl)主要基于解剖位置,往往忽略了由于不同临床适应症而导致的辐射暴露变化。虽然基于适应症的DRL(来自容积加权CT剂量指数(CTDIvol)和剂量长度积(DLP)等剂量描述符)被推荐用于优化患者的辐射暴露,但许多研究仍然使用基于解剖的DRL值。本研究旨在量化头部CT成像中解剖和指征DRL值之间的差异,并评估其对辐射剂量管理的影响。这将支持在解释患者剂量管理中基于适应症的drl和解剖性drl的区别时的叙述。方法:采用回顾性定量研究设计,我们使用具有相似特征的头部CT扫描数据集开发并比较了解剖学和常见适应症的DRL值。研究的适应症包括脑肿瘤/颅内占位性病变(ISOL)、头部损伤/创伤、脑卒中和解剖检查。使用SPSS Version 29进行数据分析。结果:研究结果表明,使用基于解剖的DLP DRL值进行CT头部检查导致在单相CT头部检查中,头部损伤/创伤的中位数、第25百分位和第75百分位值被低估20.2%、30.0%和14.5%。相反,在整个检查中,使用基于解剖的DLP DRL作为CT脑卒中DRL的基准,对中位数、第25百分位和第75百分位值的高估分别为18.3%、23.9%和13.5%。脑肿瘤/ISOL的DLP值分别被低估62.6%、60.4%和71.8%。结论:该研究强调,在头部CT扫描中,将解剖DLP DRL值用于特定适应症可能会导致DLP值被低估或高估,与基于适应症的DRL相比,它们在放射管理中的可靠性更低。因此,促进基于适应症的drl的建立和应用,实现CT成像中更准确的剂量管理势在必行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Anatomical and Indication-Based Diagnostic Reference Levels (DRLs) in Head CT Imaging: Implications for Radiation Dose Management.

Introduction: Many diagnostic reference levels (DRLs) in computed tomography (CT) imaging are based mainly on anatomical locations and often overlook variations in radiation exposure due to different clinical indications. While indication-based DRLs, derived from dose descriptors like volume-weighted CT dose index (CTDIvol) and dose length product (DLP), are recommended for optimising patient radiation exposure, many studies still use anatomical-based DRL values. This study is aimed at quantifying the differences between anatomical and indication-based DRL values in head CT imaging and assessing its implications for radiation dose management. This will support the narrative when explaining the distinction between indication-based DRLs and anatomical DRLs for patients' dose management. Methods: Employing a retrospective quantitative study design, we developed and compared anatomical and common indication-based DRL values using a dataset of head CT scans with similar characteristics. The indications included in the study were brain tumor/intracranial space-occupying lesion (ISOL), head injury/trauma, stroke, and anatomical examinations. Data analysis was conducted using SPSS Version 29. Results: The findings suggest that using anatomical-based DLP DRL values for CT head examinations leads to underestimations in the median, 25th percentile, and 75th percentile values of head injury/trauma by 20.2%, 30.0%, and 14.5% in single-phase CT head procedures. Conversely, for the entire examination, using anatomical-based DLP DRL as a benchmark for CT stroke DRL overestimates median, 25th percentile, and 75th percentile values by 18.3%, 23.9%, and 13.5%. Brain tumor/ISOL DLP values are underestimated by 62.6%, 60.4%, and 71.8%, respectively. Conclusion:The study highlights that using anatomical DLP DRL values for specific indications in head CT scans can lead to underestimated or overestimated DLP values, making them less reliable for radiation management compared to indication-based DRLs. Therefore, it is imperative to promote the establishment and use of indication-based DRLs for more accurate dose management in CT imaging.

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来源期刊
CiteScore
12.00
自引率
0.00%
发文量
11
审稿时长
20 weeks
期刊介绍: The International Journal of Biomedical Imaging is managed by a board of editors comprising internationally renowned active researchers. The journal is freely accessible online and also offered for purchase in print format. It employs a web-based review system to ensure swift turnaround times while maintaining high standards. In addition to regular issues, special issues are organized by guest editors. The subject areas covered include (but are not limited to): Digital radiography and tomosynthesis X-ray computed tomography (CT) Magnetic resonance imaging (MRI) Single photon emission computed tomography (SPECT) Positron emission tomography (PET) Ultrasound imaging Diffuse optical tomography, coherence, fluorescence, bioluminescence tomography, impedance tomography Neutron imaging for biomedical applications Magnetic and optical spectroscopy, and optical biopsy Optical, electron, scanning tunneling/atomic force microscopy Small animal imaging Functional, cellular, and molecular imaging Imaging assays for screening and molecular analysis Microarray image analysis and bioinformatics Emerging biomedical imaging techniques Imaging modality fusion Biomedical imaging instrumentation Biomedical image processing, pattern recognition, and analysis Biomedical image visualization, compression, transmission, and storage Imaging and modeling related to systems biology and systems biomedicine Applied mathematics, applied physics, and chemistry related to biomedical imaging Grid-enabling technology for biomedical imaging and informatics
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