Evaluating the Knowledge of Computed Tomography and Magnetic Resonance Imaging Parameters Between Undergraduate Students and Radiographers in Jeddah, Saudi Arabia: A Cross-Sectional Study.
Lamees A Aljuaid, Mathayel A Alblowi, Sarah Yahya Almary, Khalid M Alshamrani, Ahmad M Subahi
{"title":"Evaluating the Knowledge of Computed Tomography and Magnetic Resonance Imaging Parameters Between Undergraduate Students and Radiographers in Jeddah, Saudi Arabia: A Cross-Sectional Study.","authors":"Lamees A Aljuaid, Mathayel A Alblowi, Sarah Yahya Almary, Khalid M Alshamrani, Ahmad M Subahi","doi":"10.2147/AMEP.S530231","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Cross-sectional imaging modalities, such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), are essential for accurate diagnoses in medical care. Therefore, a solid understanding of CT and MRI parameters is necessary to obtain good image quality with minimal risk to patients. Previous studies have showed a significant knowledge gap regarding CT and MRI parameters; thus, this study aimed to evaluate the effectiveness of university curricula and clinical practice in hospitals among undergraduate students and technologists in Jeddah.</p><p><strong>Methods: </strong>Quantitative data were collected through a validated structured cross-sectional survey administered to a cluster sample of undergraduate students and radiographers in Jeddah. The survey consisted of 36 closed-ended multiple-choice questions. Eleven questions were related to CT parameters and 25 were associated with MRI parameters.</p><p><strong>Results: </strong>Normality tests revealed that both the CT and MRI scores were non-normally distributed (p = 0.0001). The Kruskal-Wallis test for the CT section yielded a p-value of 0.292, while all MRI sections also yielded p > 0.05 among the groups. Despite slight differences in knowledge scores across groups (3rd-year students, 4th-year students, internship students, radiographers, and others), internship students showed the highest mean CT knowledge scores. In terms of MRI scores, while the mean averages were similar across the groups, the technologists showed the lowest average standard deviation. These results could be attributed to the fact that the CT and MRI parameters were automated.</p><p><strong>Conclusion: </strong>These findings indicate a variation in the knowledge levels of CT and MRI parameters within this sample. We recommend the implementation of an annual refresher course to enhance the quality of healthcare practices and radiology education programs.</p>","PeriodicalId":47404,"journal":{"name":"Advances in Medical Education and Practice","volume":"16 ","pages":"1351-1358"},"PeriodicalIF":1.7000,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12336375/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Medical Education and Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/AMEP.S530231","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Cross-sectional imaging modalities, such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), are essential for accurate diagnoses in medical care. Therefore, a solid understanding of CT and MRI parameters is necessary to obtain good image quality with minimal risk to patients. Previous studies have showed a significant knowledge gap regarding CT and MRI parameters; thus, this study aimed to evaluate the effectiveness of university curricula and clinical practice in hospitals among undergraduate students and technologists in Jeddah.
Methods: Quantitative data were collected through a validated structured cross-sectional survey administered to a cluster sample of undergraduate students and radiographers in Jeddah. The survey consisted of 36 closed-ended multiple-choice questions. Eleven questions were related to CT parameters and 25 were associated with MRI parameters.
Results: Normality tests revealed that both the CT and MRI scores were non-normally distributed (p = 0.0001). The Kruskal-Wallis test for the CT section yielded a p-value of 0.292, while all MRI sections also yielded p > 0.05 among the groups. Despite slight differences in knowledge scores across groups (3rd-year students, 4th-year students, internship students, radiographers, and others), internship students showed the highest mean CT knowledge scores. In terms of MRI scores, while the mean averages were similar across the groups, the technologists showed the lowest average standard deviation. These results could be attributed to the fact that the CT and MRI parameters were automated.
Conclusion: These findings indicate a variation in the knowledge levels of CT and MRI parameters within this sample. We recommend the implementation of an annual refresher course to enhance the quality of healthcare practices and radiology education programs.