Understanding the harm of low‑dose computed tomography radiation to the body (Review)

Shi, Hai-Min; Sun, Zhichao; Ju, Fang-He

doi:10.3892/etm.2022.11461

Cited by 14 publications

(7 citation statements)

References 57 publications

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“…CT scans involve ionizing radiation, which can pose risks, especially with repeated scans. 29 Second, technical factors such as scan parameters, respiratory control, and image postprocessing can influence image quality and usability. For example, poor beam collimation can lead to image artifacts and diagnostic inaccuracy.…”

Section: Data Quality and Availabilitymentioning

confidence: 99%

Computed tomography‐based artificial intelligence in lung disease—Chronic obstructive pulmonary disease

Wang,

Li,

Gao

et al. 2024

MedComm – Future Medicine

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Chronic obstructive pulmonary disease (COPD) stands as a global health crisis, responsible for substantial morbidity and mortality on a worldwide scale. Its insidious nature underscores the importance of early detection and accurate diagnosis. While spirometry has been the cornerstone for COPD diagnosis, the role of computed tomography (CT) imaging has evolved, offering a valuable avenue for early detection and subtype classification. Recently, the advent of artificial intelligence (AI) has brought forth the potential to revolutionize the accuracy and efficiency of COPD diagnosis, with a specific focus on CT images. This intersection of healthcare and technology signifies a paradigm shift in the way we approach COPD management. The transformative capacity of AI positions it as a vital instrument for early detection and precise subtype classification of COPD. Moreover, the synergistic relationship between medical imaging and AI paves the way for more precise and efficient disease management. Therefore, in this perspective, we tend to offer a comprehensive exploration of the latest breakthroughs in the field of CT‐based AI in COPD diagnosis, aiming to demonstrate the promise and potential of AI in refining the accuracy of COPD classification and to illuminate the evolving landscape of AI's impact on COPD management.

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Section: Data Quality and Availabilitymentioning

confidence: 99%

Computed tomography‐based artificial intelligence in lung disease—Chronic obstructive pulmonary disease

Wang,

Li,

Gao

et al. 2024

MedComm – Future Medicine

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“…Several studies have followed people who had CT scans or other imaging procedures. For recent reviews see [ 135 , 152 ]. These studies suggest cancer risks increase with increasing doses over about 100 mGy with increasing evidence for risks below 100 mGy.…”

Section: Relevance and Impacts In Radiation Protection And Medicinementioning

confidence: 99%

Low Dose and Non-Targeted Radiation Effects in Environmental Protection and Medicine—A New Model Focusing on Electromagnetic Signaling

Mothersill

Cocchetto

Seymour

2022

IJMS

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The role of signalling in initiating and perpetuating effects triggered by deposition of ionising radiation energy in parts of a system is very clear. Less clear are the very early steps involved in converting energy to chemical and biological effects in non-targeted parts of the system. The paper aims to present a new model, which could aid our understanding of the role of low dose effects in determining ultimate disease outcomes. We propose a key role for electromagnetic signals resulting from physico-chemical processes such as excitation decay, and acoustic waves. These lead to the initiation of damage response pathways such as elevation of reactive oxygen species and membrane associated changes in key ion channels. Critically, these signalling pathways allow coordination of responses across system levels. For example, depending on how these perturbations are transduced, adverse or beneficial outcomes may predominate. We suggest that by appreciating the importance of signalling and communication between multiple levels of organisation, a unified theory could emerge. This would allow the development of models incorporating time, space and system level to position data in appropriate areas of a multidimensional domain. We propose the use of the term “infosome” to capture the nature of radiation-induced communication systems which include physical as well as chemical signals. We have named our model “the variable response model” or “VRM” which allows for multiple outcomes following exposure to low doses or to signals from low dose irradiated cells, tissues or organisms. We suggest that the use of both dose and infosome in radiation protection might open up new conceptual avenues that could allow intrinsic uncertainty to be embraced within a holistic protection framework.

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“…Doses discussed in this paper are doses mostly delivered by radiation coming from the CT device to which patients were exposed. Delivered doses during a single conventional CT scan can be comparable to or in some cases higher than an annual effective dose from natural background radiation of about 3 mSv [ 24 , 25 ]. To analyse possible harmful influence of radiation on biological tissue in detail, various factors must be taken into account, including the age of the study population, type of rays, exposure characteristics and body parts exposed to radiation [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

“…Delivered doses during a single conventional CT scan can be comparable to or in some cases higher than an annual effective dose from natural background radiation of about 3 mSv [ 24 , 25 ]. To analyse possible harmful influence of radiation on biological tissue in detail, various factors must be taken into account, including the age of the study population, type of rays, exposure characteristics and body parts exposed to radiation [ 25 ]. The previously introduced effective dose is only valid for comparing doses from different hospitals or countries, and it cannot be used for the detailed assessment of individual risk.…”

Section: Introductionmentioning

confidence: 99%

Dose Descriptors and Assessment of Risk of Exposure-Induced Death in Patients Undergoing COVID-19 Related Chest Computed Tomography

et al. 2022

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For more than two years, coronavirus disease 19 (COVID-19) has represented a threat to global health and lifestyles. Computed tomography (CT) imaging provides useful information in patients with COVID-19 pneumonia. However, this diagnostic modality is based on exposure to ionizing radiation, which is associated with an increased risk of radiation-induced cancer. In this study, we evaluated the common dose descriptors, CTDIvol and DLP, for 1180 adult patients. This data was used to estimate the effective dose, and risk of exposure-induced death (REID). Awareness of the extensive use of CT as a diagnostic tool in the management of COVID-19 during the pandemic is vital for the evaluation of radiation exposure parameters, dose reduction methods development and radiation protection.

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Understanding the harm of low‑dose computed tomography radiation to the body (Review)

Cited by 14 publications

References 57 publications

Computed tomography‐based artificial intelligence in lung disease—Chronic obstructive pulmonary disease

Computed tomography‐based artificial intelligence in lung disease—Chronic obstructive pulmonary disease

Low Dose and Non-Targeted Radiation Effects in Environmental Protection and Medicine—A New Model Focusing on Electromagnetic Signaling

Dose Descriptors and Assessment of Risk of Exposure-Induced Death in Patients Undergoing COVID-19 Related Chest Computed Tomography

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