Radiation doses and potential cancer risks during mammography procedures at southern Saudi Arabia

Saeed, M.K.

doi:10.52547/ijrr.19.4.20

Cited by 3 publications

(3 citation statements)

References 24 publications

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“…Velocity of light(c) (10) Where: E is in unit (eV) (assuming unit volume); I in (Watt/sr) and c is (3 x10 8 m/s 2 ) Therefore, merging Equations 5, 9 and 10; (11) Where: E i and E z are the total circuit /incident and output photon Energy measures of and from the circuit respectively. E F is the photon Energy of Intensity I F at the metal filter.…”

Section: Energy Of Radiation Per Volume (E) = Intensity Of Radiation(i)/mentioning

confidence: 99%

“…Therefore, optimizing X-ray Mammography procedures, to deliver even better-quality screening, and still operate at a safe level of radiation and radiation intensity is a continual urgent need towards the effective and efficient diagnosis, prevention, treatments and management of breast cancer. Additionally, a modern reasonable assessment of the quality of the mammogram, should be in its ability to compulsorily strike a balance between benefits and risks of patient's exposure [11]. For a data-driven world of ours, and the huge opportunities presented by Data, AI, digital healthcare and associated technologies; innovative measures to analyse, manage and optimize X-ray Mammography procedures have great potentials to improve screening procedures, reduce mortality rates and provide continuous improvements to systems for the diagnosis, treatment and management of breast cancer, in safer, more precise and less risky approaches.…”

Section: Introductionmentioning

confidence: 99%

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Analytical Optimization of X-ray Mammography for Increased Benefits and Safety; using: Data Analytics, Electronics Engineering and Artificial Intelligence

Kalu¹

2023

J Health Statist Rep

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Objective: To analyse, understand and investigate common X-ray Mammography techniques, terminologies and properties; and how the X-ray Mammography systems can be optimized for a safer, more effective, more efficient, more energy efficient procedure for breast cancer diagnosis; using Deep Learning (DL)/ Artificial Intelligence (AI), Analytical, Electronic Engineering, tools and Methodologies. Methods: Using data and breast cancer image datasets from validated open source data stores; investigative and comparative analyses were carried out on common X-ray Mammography techniques in relation to breast cancer diagnosis and treatments for Women; as well as optimization analyses using Electronic engineering principles and Artificial Intelligence principles on the quality, intensity, radiation photon energy, HVL(Half Value Layer), Tube current-time product, Metal filters properties (e.g. K-edge energy cut off), and classification validation accuracy of the X-ray Mammography properties, procedure, processes and systems. The methodical and data-driven analyses were carried out using the following Data, Artificial Intelligence (AI) and Electronic Engineering, methodologies and algorithms: Data Analytics, Convolutional Neural Networks (CNN) in Machine Learning (ML) Engineering, and X-ray-Impedance Circuit Composite System Analysis

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Section: Energy Of Radiation Per Volume (E) = Intensity Of Radiation(i)/mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analytical Optimization of X-ray Mammography for Increased Benefits and Safety; using: Data Analytics, Electronics Engineering and Artificial Intelligence

Kalu¹

2023

J Health Statist Rep

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“…15 A recent study conducted in the southern region of Saudi Arabia provided some input on the local mean glandular dose (MGD) parameter and revealed that MGD for mammography procedures were measured between 1.01±0.3 and 1.09 ±0.2 for cranial caudal (CC) and mediolateral oblique (MLO) projections, respectively. 16 As mentioned previously, physicians and studies alike have raised concerns about radiation exposure during imaging. This has necessitated the implementation of dose-monitoring algorithms that analyze data from radiological examinations and support the benefits of medical imaging while minimizing patient exposure to unnecessary ionizing radiation.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Data Management on the Achievable Dose and Efficiency of Mammography and Radiography During the COVID-19 Era: A Facility-Based Cohort Study

Hegazi¹,

Al-Sharydah²,

AlFawaz³

et al. 2023

RMHP

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To evaluate the impact of using computational data management resources and analytical software on radiation doses in mammography and radiography during the COVID-19 pandemic, develop departmental diagnostic reference levels (DRLs), and describe achievable doses (ADs) for mammography and radiography based on measured dose parameters. Patients and Methods: This ambispective cohort study enrolled 795 and 12,115 patients who underwent mammography and radiography, respectively, at the King Fahd Hospital of the University, Al-Khobar City, Saudi Arabia between May 25 and November 4, 2021. Demographic data were acquired from patients' electronic medical charts. Data on mammographic and radiographic dose determinants were acquired from the data management software. Based on the time when the data management software was operational in the institute, the study was divided into the pre-implementation and post-implementation phases. Continuous and categorical variables were compared between the two phases using an unpaired t-test and the chi-square test. Results: The median accumulated average glandular dose (AGD; a mammographic dose determinant) in the post-implementation phase was three-fold higher than that in the pre-implementation phase. The average mammographic exposure time in the postimplementation phase was 16.3 ms shorter than that in the pre-implementation phase. Furthermore, the median values of the dose area product ([DAP], a radiographic dose determinant) were 9.72 and 19.4 cGycm 2 in the pre-implementation and post-implementation phases, respectively. Conclusion: Although the data management software used in this study helped reduce the radiation exposure time by 16.3 ms in mammography, its impact on the mean accumulated AGD was unfavorable. Similarly, radiographic exposure indices, including DAP, tube voltage, tube current, and exposure time, were not significantly different after the data management software was implemented. Close monitoring of patient radiation doses in mammography and radiography, and dose reduction will become possible if imaging facilities use DRLs and ADs via automated systems.

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Evaluation of mean glandular dose from mammography screening: A single-center study

Alahmad,

AlEnazi,

Alshahrani

et al. 2023

Journal of Radiation Research and Applied Sciences

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Radiation doses and potential cancer risks during mammography procedures at southern Saudi Arabia

Cited by 3 publications

References 24 publications

Analytical Optimization of X-ray Mammography for Increased Benefits and Safety; using: Data Analytics, Electronics Engineering and Artificial Intelligence

Analytical Optimization of X-ray Mammography for Increased Benefits and Safety; using: Data Analytics, Electronics Engineering and Artificial Intelligence

The Impact of Data Management on the Achievable Dose and Efficiency of Mammography and Radiography During the COVID-19 Era: A Facility-Based Cohort Study

Evaluation of mean glandular dose from mammography screening: A single-center study

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