Variability Between Radiation-Induced Cancer Risk Models in Estimating Oncogenic Risk in Intensive Care Unit Patients.

IF 2.2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Tomography Pub Date : 2025-04-03 DOI:10.3390/tomography11040042

Emilio Quaia, Chiara Zanon, Riccardo Torchio, Fabrizio Dughiero, Francesca De Monte, Marta Paiusco

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引用次数: 0

Abstract

Purpose: To evaluate the variability of oncogenic risk related to radiation exposure in patients frequently exposed to ionizing radiation for diagnostic purposes, specifically ICU patients, according to different risk models, including the BEIR VII, ICRP 103, and US EPA models.

Methods: This was an IRB-approved observational retrospective study. A total of 71 patients (58 male, 13 female; median age, 66 years; interquartile range [IQR], 65-71 years) admitted to the ICU who underwent X-ray examinations between 1 October 2021 and 28 February 2023 were included. For each patient, the cumulative effective dose during a single hospital admission was calculated. Lifetime attributable risk (LAR) was estimated based on the BEIR VII, ICRP 103, and US EPA risk models to calculate additional oncogenic risk related to radiation exposure. The Friedman test for repeated-measures analysis of variance was used to compare risk values between different models. The intraclass correlation coefficient (ICC) was used to assess the consistency of risk values between different models.

Results: Different organ, leukemia, and all-cancer risk values estimated according to different oncogenic risk models were significantly different, but the intraclass correlation coefficient revealed a good (>0.75) or even excellent (>0.9) agreement between different risk models. The ICRP 103 model estimated a lower all-cancer (median 69.05 [IQR 30.35-195.37]) and leukemia risk (8.22 [3.02-27.93]) compared to the US EPA (all-cancer: 139.68 [50.51-416.16]; leukemia: 23.34 [3.47-64.37]) and BEIR VII (all-cancer: 162.08 [70.6-371.40]; leukemia: 24.66 [12.9-58.8]) models.

Conclusions: Cancer risk values were significantly different between risk models, though inter-model agreement in the consistency of risk values was found to be good, or even excellent.

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辐射诱发癌症风险模型在估计重症监护病房患者致癌风险方面的可变性。

目的：根据不同的风险模型，包括BEIR VII、ICRP 103和US EPA模型，评估为诊断目的经常暴露于电离辐射的患者（特别是ICU患者）与辐射暴露相关的致癌风险的变异性。方法：这是一项经irb批准的观察性回顾性研究。共71例患者，其中男58例，女13例；中位年龄66岁；纳入在2021年10月1日至2023年2月28日期间接受x线检查的ICU住院患者。对于每个病人，计算一次住院期间的累积有效剂量。根据BEIR VII、ICRP 103和US EPA风险模型估计终生归因风险（LAR），以计算与辐射暴露相关的额外致癌风险。使用重复测量方差分析的Friedman检验来比较不同模型之间的风险值。采用类内相关系数（intraclass correlation coefficient， ICC）评价不同模型间风险值的一致性。结果：不同的致癌风险模型估算出的不同器官、白血病和全癌的风险值存在显著差异，但不同风险模型间的类内相关系数显示出良好（>0.75）甚至极好的一致性（>0.9）。与美国EPA （all-cancer: 139.68[50.51-416.16]）相比，ICRP 103模型估计的全癌风险（中位数69.05 [IQR 30.35-195.37]）和白血病风险（中位数8.22[3.02-27.93]）较低；白血病：23.34[3.47-64.37])和BEIR VII(所有癌症：162.08 [70.6-371.40]；白血病：24.66[12.9-58.8])例。结论：不同风险模型之间的癌症风险值存在显著差异，但模型间在风险值一致性方面的一致性是良好的，甚至是极好的。

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

Tomography Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

2.70

自引率

10.50%

发文量

222

期刊介绍： TomographyTM publishes basic (technical and pre-clinical) and clinical scientific articles which involve the advancement of imaging technologies. Tomography encompasses studies that use single or multiple imaging modalities including for example CT, US, PET, SPECT, MR and hyperpolarization technologies, as well as optical modalities (i.e. bioluminescence, photoacoustic, endomicroscopy, fiber optic imaging and optical computed tomography) in basic sciences, engineering, preclinical and clinical medicine. Tomography also welcomes studies involving exploration and refinement of contrast mechanisms and image-derived metrics within and across modalities toward the development of novel imaging probes for image-based feedback and intervention. The use of imaging in biology and medicine provides unparalleled opportunities to noninvasively interrogate tissues to obtain real-time dynamic and quantitative information required for diagnosis and response to interventions and to follow evolving pathological conditions. As multi-modal studies and the complexities of imaging technologies themselves are ever increasing to provide advanced information to scientists and clinicians. Tomography provides a unique publication venue allowing investigators the opportunity to more precisely communicate integrated findings related to the diverse and heterogeneous features associated with underlying anatomical, physiological, functional, metabolic and molecular genetic activities of normal and diseased tissue. Thus Tomography publishes peer-reviewed articles which involve the broad use of imaging of any tissue and disease type including both preclinical and clinical investigations. In addition, hardware/software along with chemical and molecular probe advances are welcome as they are deemed to significantly contribute towards the long-term goal of improving the overall impact of imaging on scientific and clinical discovery.