scholarly journals Maximizing Benefit and Minimizing Risk in Medical Imaging Use: An Educational Primer for Health Care Professions Students

2018 ◽  
Vol 5 ◽  
pp. 238212051879881 ◽  
Author(s):  
Diane Armao ◽  
Terry S Hartman ◽  
Christopher M Shea ◽  
Laurence Katz ◽  
Tracey Thurnes ◽  
...  
Keyword(s):  
Informed Consent ◽  
Medical Imaging ◽  
Educational Intervention ◽  
Radiation Safety ◽  
Health Professions ◽  
Educational Session ◽  
Computed Tomographic ◽  
Imaging Utilization ◽  
Imaging Appropriateness ◽  
Ionizing Radiation Exposure

“I am not young enough to know everything.” Oscar Wilde Background: There is insufficient knowledge among providers and patients/caregivers of ionizing radiation exposure from medical imaging examinations. This study used a brief, interactive educational intervention targeting the topics of best imaging practices and radiation safety early in health professions students’ training. The authors hypothesized that public health, medical, and physician assistant students who receive early education for imaging appropriateness and radiation safety will undergo a change in attitude and have increased awareness and knowledge of these topics. Materials and methods: The authors conducted a 1.5-hour interactive educational intervention focusing on medical imaging utilization and radiation safety. Students were presented with a pre/postquestionnaire and data were analyzed using t tests and multivariate analysis of variance. Results: A total of 301 students were enrolled in the study. There was 58% ( P < .01) and 85% ( P < .01) improvement in attitude and knowledge regarding appropriateness of imaging, respectively. The authors also found an 8% increase ( P < .01) in students who thought informed consent should be obtained prior to pediatric computed tomographic imaging. Physical assistant students were more likely than medical students to prefer obtaining informed consent at baseline ( P = .03). Conclusions: A brief educational session provided to health professions students early in their education showed an increased awareness and knowledge of the utility, limitations, and risks associated with medical imaging. Incorporation of a best imagining practice educational session early during medical education may promote more thoughtful imaging decisions for future medical providers.

scholarly journals Occupational Health and Radiation Safety of Radiography Workers

2021 ◽  
Author(s):  
Hasna Albander
Keyword(s):  
Health Status ◽  
Medical Imaging ◽  
Occupational Health ◽  
Radiation Safety ◽  
Body Parts ◽  
Radioactive Pollution ◽  
Imaging Procedures ◽  
Occupational Infections ◽  
Ionizing Radiation Exposure ◽  
Harmful Effects

Medical imaging is the identification or study procedure for obtaining medical images of body parts. Millions of imaging procedures take place worldwide each week. Radiation protection is intended to prevent the ionizing radiation exposure from having harmful effects. Exposure may result from a source of radiation outside the human body, or from ingestion of radioactive pollution from internal irradiation. This chapter presents Occupational Health and Radiation Safety of Radiography workers in the medical imaging field. This chapter also summarizes how current employment health status and knowledge gaps can be illustrated in some key and critical occupational issues as well as diseases such as radiation, nosocomial and occupational infections.

Informing Patients About Tardive Dyskinesia: Four-Year Follow Up of a Trial of Patient Education

2002 ◽  
Vol 36 (1) ◽  
pp. 99-103 ◽  
Author(s):  
Robert Chaplin ◽  
Clive Timehin
Keyword(s):  
Informed Consent ◽  
Tardive Dyskinesia ◽  
Educational Intervention ◽  
Control Group ◽  
Random Allocation ◽  
Consent To Treatment ◽  
Long Term Follow Up ◽  
Clinical Stability

Objective: This paper evaluates the effects of an educational intervention about tardive dyskinesia on knowledge and clinical stability at long-term follow up. Method: Fifty-six patients receiving antipsychotic maintenance completed a questionnaire assessing their knowledge about tardive dyskinesia. After random allocation to either educational intervention or control group, their knowledge, clinical stability and rates of tardive dyskinesia were reassessed after four years. Results: Seventy per cent of patients completed the study. The patients in the educational group retained significantly more knowledge at follow up than at baseline but this knowledge was not significantly greater than that of the control group. There were no significant differences in the clinical outcomes between the groups. Conclusion: Patients can retain a small but significant amount of information with a low risk of noncompliance. Discussion about tardive dyskinesia is necessary in the process of obtaining informed consent to treatment.

scholarly journals Evaluating the Checklist for Artificial Intelligence in Medical Imaging (CLAIM)-Based Quality of Reports Using Convolutional Neural Network for Odontogenic Cyst and Tumor Detection

2021 ◽  
Vol 11 (20) ◽  
pp. 9688
Author(s):  
Van Nhat Thang Le ◽  
Jae-Gon Kim ◽  
Yeon-Mi Yang ◽  
Dae-Woo Lee
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Medical Imaging ◽  
Convolutional Neural Network ◽  
Reporting Quality ◽  
Tumor Detection ◽  
Odontogenic Cyst ◽  
Computed Tomographic ◽  
Other Information ◽  
Quality Of Reports

This review aimed to explore whether studies employing a convolutional neural network (CNN) for odontogenic cyst and tumor detection follow the methodological reporting recommendations, the checklist for artificial intelligence in medical imaging (CLAIM). We retrieved the CNN studies using panoramic and cone-beam-computed tomographic images from inception to April 2021 in PubMed, EMBASE, Scopus, and Web of Science. The included studies were assessed according to the CLAIM. Among the 55 studies yielded, 6 CNN studies for odontogenic cyst and tumor detection were included. Following the CLAIM items, abstract, methods, results, discussion across the included studies were insufficiently described. The problem areas included item 2 in the abstract; items 6–9, 11–18, 20, 21, 23, 24, 26–31 in the methods; items 33, 34, 36, 37 in the results; item 38 in the discussion; and items 40–41 in “other information.” The CNN reports for odontogenic cyst and tumor detection were evaluated as low quality. Inadequate reporting reduces the robustness, comparability, and generalizability of a CNN study for dental radiograph diagnostics. The CLAIM is accepted as a good guideline in the study design to improve the reporting quality on artificial intelligence studies in the dental field.

scholarly journals Immunomodulatory drugs in multiple myeloma: Impact of the SCARMET (Self CARe and MEdication Toxicity) educational intervention on outpatients’ knowledge to manage adverse effects

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243309
Author(s):  
Juliette Périchou ◽  
Florence Ranchon ◽  
Chloé Herledan ◽  
Laure Huot ◽  
Virginie Larbre ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Adverse Effects ◽  
Educational Intervention ◽  
Self Care ◽  
Medication Possession Ratio ◽  
Immunomodulatory Drugs ◽  
Self Assessment ◽  
Educational Session ◽  
Number Of Patients ◽  
The Impact

Long-term multiple myeloma therapy by immunomodulatory drugs (IMiDs) raises the question of management of adverse effects. The aim of this study is to assess the impact of an educational session for patients on the acquisition of knowledge to manage hematologic and thromboembolic adverse effects of IMiDs. In this prospective single-center study, patients attended an educational session with a hospital clinical pharmacist and a nurse. The primary endpoint was the patient’s level of knowledge for the management of IMiDs adverse effects, assess with a dedicated questionnaire administered before the session then 1 and 6 months after. Assessment of knowledge was combined with self-assessment of certainty. The secondary endpoints were adherence and IMiD treatment satisfaction. 50 patients were included. Patient knowledge increased at 1 month (p<0.001) despite a loss of knowledge at 6 months (p<0.05). Six months after the educational intervention, the number of patients with skills considered satisfactory by the pharmacist and nurse increased (p<0.01). Most patients showed satisfactory adherence, with medication possession ratio ≥ 80%. The Self CARe and MEdication Toxicity (SCARMET) study highlighted the impact of multidisciplinary follow-up in multiple myeloma patients to improve knowledge of toxicity self-management.

scholarly journals Leveraging the Score Curriculum for a Longitudinal Educational Intervention for Teaching Surgical Informed Consent

2021 ◽  
Vol 233 (5) ◽  
pp. e166
Author(s):  
Brian R. Quaranto ◽  
MIchael D. Lamb ◽  
James K. Lukan ◽  
Bobbie Ann A. White ◽  
Linda M. Harris ◽  
...  
Keyword(s):  
Informed Consent ◽  
Educational Intervention

A Brief Educational Intervention Does Not Change Patient Attitudes Towards Research Involving an Emergency Exception from Informed Consent.

2007 ◽  
Vol 14 (5 Supplement 1) ◽  
pp. S150-S151 ◽  
Author(s):  
J. Goldstein ◽  
K. Delaney ◽  
A. Pelletier ◽  
J. Fisher ◽  
P. Blanc ◽  
...  
Keyword(s):  
Informed Consent ◽  
Educational Intervention ◽  
Patient Attitudes

Artificial intelligence in medical imaging: implications for patient radiation safety

2021 ◽  
pp. 20210406
Author(s):  
Jarrel Seah ◽  
Zoe Brady ◽  
Kyle Ewert ◽  
Meng Law
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Medical Imaging ◽  
Radiation Safety ◽  
Tomographic Reconstruction ◽  
Positron Emission ◽  
Learning Techniques ◽  
Current Reconstruction ◽  
Patient Radiation Dose ◽  
Dose Reductions

Artificial Intelligence (AI), including deep learning, is currently revolutionising the field of medical imaging, with far reaching implications for almost every facet of diagnostic imaging, including patient radiation safety. This paper introduces basic concepts in deep learning and provides an overview of its recent history and its application in tomographic reconstruction as well as other applications in medical imaging to reduce patient radiation dose, as well as a brief description of previous tomographic reconstruction techniques. This review also describes the commonly used deep learning techniques as applied to tomographic reconstruction and draws parallels to current reconstruction techniques. Finally, this paper reviews some of the estimated dose reductions in computed tomography (CT) and positron emission tomography (PET) in the recent literature enabled by deep learning, as well as some of the potential problems that may be encountered such as the obscuration of pathology, and highlights the need for additional clinical reader studies from the imaging community.

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