1
|
Mahmoudi G, Toolee H, Maskani R, Jokar F, Mokfi M, Hosseinzadeh A. COVID-19 and cancer risk arising from ionizing radiation exposure through CT scans: a cross-sectional study. BMC Cancer 2024; 24:298. [PMID: 38443829 PMCID: PMC10916077 DOI: 10.1186/s12885-024-12050-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 02/23/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND The surge in the utilization of CT scans for COVID-19 diagnosis and monitoring during the pandemic is undeniable. This increase has brought to the forefront concerns about the potential long-term health consequences, especially radiation-induced cancer risk. This study aimed to quantify the potential cancer risk associated with CT scans performed for COVID-19 detection. METHODS In this cross-sectional study data from a total of 561 patients, who were referred to the radiology center at Imam Hossein Hospital in Shahroud, was collected. CT scan reports were categorized into three groups based on the radiologist's interpretation. The BEIR VII model was employed to estimate the risk of radiation-induced cancer. RESULTS Among the 561 patients, 299 (53.3%) were males and the average age of the patients was 49.61 ± 18.73 years. Of the CT scans, 408 (72.7%) were reported as normal. The average age of patients with normal, abnormal, and potentially abnormal CT scans was 47.57 ± 19.06, 54.80 ± 16.70, and 58.14 ± 16.60 years, respectively (p-value < 0.001). The average effective dose was 1.89 ± 0.21 mSv, with 1.76 ± 0.11 mSv for males and 2.05 ± 0.29 mSv for females (p-value < 0.001). The average risk of lung cancer was 3.84 ± 1.19 and 9.73 ± 3.27 cases per 100,000 patients for males and females, respectively. The average LAR for all cancer types was 10.30 ± 6.03 cases per 100,000 patients. CONCLUSIONS This study highlights the critical issue of increased CT scan usage for COVID-19 diagnosis and the potential long-term consequences, especially the risk of cancer incidence. Healthcare policies should be prepared to address this potential rise in cancer incidence and the utilization of CT scans should be restricted to cases where laboratory tests are not readily available or when clinical symptoms are severe.
Collapse
Affiliation(s)
- Golshan Mahmoudi
- School of Allied Medical Sciences, Shahroud University of Medical Sciences, Shahroud, Iran
| | - Heidar Toolee
- School of Allied Medical Sciences, Shahroud University of Medical Sciences, Shahroud, Iran
| | - Reza Maskani
- School of Allied Medical Sciences, Shahroud University of Medical Sciences, Shahroud, Iran
| | - Farzaneh Jokar
- School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran
| | - Milad Mokfi
- School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran
| | - Ali Hosseinzadeh
- Center for Health Related Social and Behavioral Sciences Research, Shahroud University of Medical Sciences, Shahroud, Iran.
- Department of Epidemiology, School of Public Health, Shahroud University of Medical Sciences, Shahroud, Iran.
| |
Collapse
|
2
|
Zeinali-Rafsanjani B, Alavi A, Lotfi M, Haseli S, Saeedi-Moghadam M, Moradpour M. Is it necessary to define new diagnostic reference levels during pandemics like the Covid19-? Radiat Phys Chem Oxf Engl 1993 2023; 205:110739. [PMID: 36567703 PMCID: PMC9764089 DOI: 10.1016/j.radphyschem.2022.110739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 10/25/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022]
Abstract
Introduction This study intended to assess the dose length product (DLP), effective cumulative radiation dose (E.D.), and additional cancer risk (ACR) due to a chest CT scan to detect or follow up the Covid-19 disease in four university-affiliated hospitals that used different imaging protocols. Indeed, this study aimed to examine the differences in decision-making between different imaging centers in choosing chest CT imaging protocols during the pandemic, and to assess whether a new diagnostic reference level (DRL) is needed in pandemic situations. Methods This retrospective study assessed the E.D. of all chest imagings for Covid-19 for six months in four different hospitals in our country. Imaging parameters and DLP (mGy.cm) were recorded. The E.D.s and ACRs from chest CT scans were calculated using an online calculator. Results Thousand-six hundred patients were included in the study. The mean cumulative dose due to chest CT was 3.97 mSv which might cause 2.59 × 10-2 ACR. The mean cumulative E.D. in different hospitals was in the range of 1.96-9.51 mSv. Conclusions The variety of mean E.D.s shows that different hospitals used different imaging protocols. Since there is no defined DRL in the pandemic, some centers use routine protocols, and others try to reduce the dose but insufficiently.In pandemics such as Covid-19, when CT scan is used for screening or follow-up, DLPs can be significantly lower than in normal situations. Therefore, international regularized organizations such as the international atomic energy agency (IAEA) or the international commission on radiological protection (IRCP) should provide new DRL ranges.
Collapse
Affiliation(s)
| | - Azamalsadat Alavi
- Chronic Respiratory Disease Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mehrzad Lotfi
- Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Sara Haseli
- Chronic Respiratory Disease Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran,Co-corresponding author
| | - Mahdi Saeedi-Moghadam
- Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran,Corresponding author
| | - Moein Moradpour
- Radiology Department of Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| |
Collapse
|
3
|
Hou N, Wang L, Li M, Xie B, He L, Guo M, Liu S, Wang M, Zhang R, Wang K. Do COVID-19 CT features vary between patients from within and outside mainland China? Findings from a meta-analysis. Front Public Health 2022; 10:939095. [PMID: 36311632 PMCID: PMC9616120 DOI: 10.3389/fpubh.2022.939095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 07/25/2022] [Indexed: 01/25/2023] Open
Abstract
Background Chest computerized tomography (CT) plays an important role in detecting patients with suspected coronavirus disease 2019 (COVID-19), however, there are no systematic summaries on whether the chest CT findings of patients within mainland China are applicable to those found in patients outside. Methods Relevant studies were retrieved comprehensively by searching PubMed, Embase, and Cochrane Library databases before 15 April 2022. Quality assessment of diagnostic accuracy studies (QUADAS) was used to evaluate the quality of the included studies, which were divided into two groups according to whether they were in mainland China or outside. Data on diagnostic performance, unilateral or bilateral lung involvement, and typical chest CT imaging appearances were extracted, and then, meta-analyses were performed with R software to compare the CT features of COVID-19 pneumonia between patients from within and outside mainland China. Results Of the 8,258 studies screened, 19 studies with 3,400 patients in mainland China and 14 studies with 554 outside mainland China were included. Overall, the risk of quality assessment and publication bias was low. The diagnostic value of chest CT is similar between patients from within and outside mainland China (93, 91%). The pooled incidence of unilateral lung involvement (15, 7%), the crazy-paving sign (31, 21%), mixed ground-glass opacities (GGO) and consolidations (51, 35%), air bronchogram (44, 25%), vascular engorgement (59, 33%), bronchial wall thickening (19, 12%), and septal thickening (39, 26%) in patients from mainland China were significantly higher than those from outside; however, the incidence rates of bilateral lung involvement (75, 84%), GGO (78, 87%), consolidations (45, 58%), nodules (12, 17%), and pleural effusion (9, 15%) were significantly lower. Conclusion Considering that the chest CT features of patients in mainland China may not reflect those of the patients abroad, radiologists and clinicians should be familiar with various CT presentations suggestive of COVID-19 in different regions.
Collapse
Affiliation(s)
- Nianzong Hou
- Center of Gallbladder Disease, Shanghai East Hospital, Institute of Gallstone Disease, School of Medicine, Tongji University, Shanghai, China,Department of Hand and Foot Surgery, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Lin Wang
- Department of Critical Care Medicine, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Mingzhe Li
- School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom
| | - Bing Xie
- Department of Hand and Foot Surgery, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Lu He
- Department of Urology, Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Mingyu Guo
- Department of Hand and Foot Surgery, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Shuo Liu
- Department of Hand and Foot Surgery, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Meiyu Wang
- Department of Cardiology, The People's Hospital of Zhangdian District, Zibo, China
| | - Rumin Zhang
- Department of Critical Care Medicine, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Kai Wang
- Department of Critical Care Medicine, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China,*Correspondence: Kai Wang
| |
Collapse
|
4
|
Jordan E, Shin DE, Leekha S, Azarm S. Optimization in the Context of COVID-19 Prediction and Control: A Literature Review. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2021; 9:130072-130093. [PMID: 35781925 PMCID: PMC8768956 DOI: 10.1109/access.2021.3113812] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Accepted: 09/10/2021] [Indexed: 05/08/2023]
Abstract
This paper presents an overview of some key results from a body of optimization studies that are specifically related to COVID-19, as reported in the literature during 2020-2021. As shown in this paper, optimization studies in the context of COVID-19 have been used for many aspects of the pandemic. From these studies, it is observed that since COVID-19 is a multifaceted problem, it cannot be studied from a single perspective or framework, and neither can the related optimization models. Four new and different frameworks are proposed that capture the essence of analyzing COVID-19 (or any pandemic for that matter) and the relevant optimization models. These are: (i) microscale vs. macroscale perspective; (ii) early stages vs. later stages perspective; (iii) aspects with direct vs. indirect relationship to COVID-19; and (iv) compartmentalized perspective. To limit the scope of the review, only optimization studies related to the prediction and control of COVID-19 are considered (public health focused), and which utilize formal optimization techniques or machine learning approaches. In this context and to the best of our knowledge, this survey paper is the first in the literature with a focus on the prediction and control related optimization studies. These studies include optimization of screening testing strategies, prediction, prevention and control, resource management, vaccination prioritization, and decision support tools. Upon reviewing the literature, this paper identifies current gaps and major challenges that hinder the closure of these gaps and provides some insights into future research directions.
Collapse
Affiliation(s)
- Elizabeth Jordan
- Department of Mechanical EngineeringUniversity of MarylandCollege ParkMD20742USA
| | - Delia E. Shin
- Department of Mechanical EngineeringUniversity of MarylandCollege ParkMD20742USA
| | - Surbhi Leekha
- Department of Epidemiology and Public HealthUniversity of Maryland School of MedicineBaltimoreMD21201USA
| | - Shapour Azarm
- Department of Mechanical EngineeringUniversity of MarylandCollege ParkMD20742USA
| |
Collapse
|