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Characterization of Biological Effects of Computed Tomography by Assessing the DNA Damage Response

Abstract

The purpose of this work is to characterize the biological response of clinically relevant low doses of ionizing radiation (IR) to inform risk assessment for diagnostic radiographic procedures. Computed tomography (CT) exams provide a non-invasive, fast and extremely detailed diagnostic tool for physicians. Despite the immense impact diagnostic radiology has had on the advancement of healthcare, recent incidents and retrospective studies have focused attention on radiation dose and potential risks from diagnostic exams, especially CT. Because CT exams are often necessary and very commonly employed to provide standard and life-saving medical care, it is crucial to understand the potential risks and avoid adverse health effects. As current risk estimate are based on population statistics and the "average patient" is rarely average, determining the risk for an individual scenario based on specific patient parameters could revolutionize diagnostic medicine. The lack of scientific evidence for specific biological mechanisms in response to low doses of IR makes even defining risk particularly imprecise. Furthermore, the relationship between physical and biological dose following IR is especially unclear for low dose modalities such as CT. Due to the dynamic nature of cellular damage repair, it is clear that accurate and reproducible kinetic analysis is essential to properly assess the gammaH2AX response. For this reason, this work focuses on 1) developing and evaluating a technique to be applied to kinetic analysis of DNA damage in patient blood samples for clinical application, 2) investigating the differences in DNA damage repair kinetics between dose levels and the effects of short-interval fractionated low-dose irradiation schemes on phosphorylation of H2AX, and 3) applying the previously developed technique to characterize the response to CT examinations in patients.

It is important to control variables which may have unrelated and unintended effects on biological endpoints. Standard procedures of blood sample collection followed by ill-defined storage at room temperature or on ice before laboratory analysis is suboptimal when analyzing highly dynamic systems such as the DNA damage response. The developed rapid fixation protocol that uses immediate exposure to formaldehyde after treatment was superior to the standard practice for isolation and fixation of whole blood as well as cell culture samples. Comparison of different sample handling protocols indicates that whole blood samples are especially sensitive to changes in their environment.

Dose-response kinetics to IR were established in both cultured and whole blood human lymphocytes. The biological response to IR was measured by immunofluorescent analysis of gammaH2AX by flow cytometry at different time points To understand the response to doses from CT exams fractionated exposures were employed. Both the kinetics and extent of H2AX phosphorylation appear to be dose-dependent. For the first time, differences in DNA repair kinetics of both cultured and whole blood lymphocytes are characterized. Moreover, using a modified split-dose in vitro experiment, it is shown that phosphorylation of H2AX is significantly reduced following exposure to CT doses fractionated over a few minutes compared to the same total dose delivered as a single exposure. The possibility of an altered H2AX phosphorylation response to split-dose irradiations could have marked implications for current diagnostic procedures and thus underscores the importance of understanding how imaging protocols may affect the biological response in order to accurately assess risk estimates and biological dose. Though the consequences on late effects and other related risks are unclear, these findings suggest that risk may be a function of not only total dose delivered, but also other contributing factors such as scan and patient parameters.

Here, the complexity of the biological response to a variety of CT protocols and the relation to patient and CT exam parameters is described. Blood from 21 adult patients undergoing clinically-indicated CT exams was analyzed to assess the effects of CTs in vivo. Varying biological responses are observed after irradiation. While no clear dose response is evident, three distinct biological responses to CT examinations: fast, slow and none are suggested. Additionally, age and average dose-rate are significant factors in the biological response. Interestingly, ex vivo and in vivo samples differ in biological response to CT exams. These effects suggests distinct DNA damage responses depending on exam conditions that may not necessarily be reflected solely by dose metrics like dose length product (DLP) or CT dose index (CTDI) which only quantify scanner output. Even though this study only had a small population size, two patients were identified who exhibited aberrant responses compared to the rest of the population indicating that this application could provide a useful tool to identify putative radiation sensitive individuals who may require further testing to ensure the least risk to the patient.

This work provides compelling evidence supporting differential biological responses not only between high and low doses, but also between single and multiple exposures of low doses of ionizing radiation. Moreover, individual patient factors may further modulate the response to radiographic procedures. Although the radio-protector experiments provide some interesting insight into the possible mechanisms by which these responses are controlled, it is clear that this work has instigated more questions than it has answered. Future work needs to further probe the responsible mechanisms involved in the damage response at different dose levels and schemes as well as those involved in carcinogenesis and other late effects. In addition to understanding the response at a cellular level, it is imperative to also examine the systemic response as well as how repeated exposures over an individual's lifetime may affect lifetime risk. Once it is possible to integrate both cellular and systemic knowledge then it may be possible to accurately forecast individual risk.

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