New Study Questions Benefits of Patient Shielding during Imaging
|
By MedImaging International staff writers Posted on 16 Apr 2019 |
A new study claims that patient shielding in diagnostic imaging provides negligible benefits and actually increases risks.
A study written by researchers at the University of Colorado School of Medicine (Aurora, CO, USA) reviews the historical rationale for patient shielding, explains why the risks that come with patient shielding now outweigh what little benefit still exists, and makes the case for why it is time to abandon the legacy practice of patient shielding in radiology. First introduced as a regulation in 1976 in order to protect patients from the hereditary risks of radiation exposure, the wording has not changed since the initial version was released, despite the fact no hereditary effects have been observed in humans since the regulation was introduced.
In addition, as the authors point out, radiation doses during the four decades since the regulation was released have decreased significantly, thanks to advances in imaging technology. For instance, radiation doses to patients undergoing anteroposterior examinations of the pelvis have decreased more than 96% over the last 60 years. They also suggest that as more imaging technologies currently rely on automatic exposure control, patient shields could lead to an increase in radiation doses due to attenuation, and to a decrease in image quality. The study was published in the April 2019 issue of the American Journal of Roentgenology.
“It is important to think about how much protection is really being provided to the patient. For anatomy outside the imaging field of view [FOV], radiation exposure results almost entirely from internal scatter generated within a patient,” wrote study authors Rebecca Milman Marsh, PhD, and Michael Silosky, MSc. “As contact shielding cannot protect against internal scatter, shielding anatomy outside the imaging FOV provides negligible protection to the patient. This holds true for all examinations, including those of pediatric and pregnant patients.”
“The assumption is that shielding improves patient safety. This belief is often regarded as fact, with little consideration given to its veracity,” concluded the authors. “Although change is difficult, it is incumbent on radiologic technologists, medical physicists, and radiologists to abandon the practice of patient shielding in radiology. This is especially important regarding issues of radiation risk, for which misinformation is rampant. Consequently, how to address patient concerns as facilities stop providing patient shielding should be considered.”
Related Links:
University of Colorado School of Medicine
A study written by researchers at the University of Colorado School of Medicine (Aurora, CO, USA) reviews the historical rationale for patient shielding, explains why the risks that come with patient shielding now outweigh what little benefit still exists, and makes the case for why it is time to abandon the legacy practice of patient shielding in radiology. First introduced as a regulation in 1976 in order to protect patients from the hereditary risks of radiation exposure, the wording has not changed since the initial version was released, despite the fact no hereditary effects have been observed in humans since the regulation was introduced.
In addition, as the authors point out, radiation doses during the four decades since the regulation was released have decreased significantly, thanks to advances in imaging technology. For instance, radiation doses to patients undergoing anteroposterior examinations of the pelvis have decreased more than 96% over the last 60 years. They also suggest that as more imaging technologies currently rely on automatic exposure control, patient shields could lead to an increase in radiation doses due to attenuation, and to a decrease in image quality. The study was published in the April 2019 issue of the American Journal of Roentgenology.
“It is important to think about how much protection is really being provided to the patient. For anatomy outside the imaging field of view [FOV], radiation exposure results almost entirely from internal scatter generated within a patient,” wrote study authors Rebecca Milman Marsh, PhD, and Michael Silosky, MSc. “As contact shielding cannot protect against internal scatter, shielding anatomy outside the imaging FOV provides negligible protection to the patient. This holds true for all examinations, including those of pediatric and pregnant patients.”
“The assumption is that shielding improves patient safety. This belief is often regarded as fact, with little consideration given to its veracity,” concluded the authors. “Although change is difficult, it is incumbent on radiologic technologists, medical physicists, and radiologists to abandon the practice of patient shielding in radiology. This is especially important regarding issues of radiation risk, for which misinformation is rampant. Consequently, how to address patient concerns as facilities stop providing patient shielding should be considered.”
Related Links:
University of Colorado School of Medicine
Latest Radiography News
- X-Ray Breakthrough Captures Three Image-Contrast Types in Single Shot
- AI Generates Future Knee X-Rays to Predict Osteoarthritis Progression Risk
- AI Algorithm Uses Mammograms to Accurately Predict Cardiovascular Risk in Women
- AI Hybrid Strategy Improves Mammogram Interpretation
- AI Technology Predicts Personalized Five-Year Risk of Developing Breast Cancer
- RSNA AI Challenge Models Can Independently Interpret Mammograms
- New Technique Combines X-Ray Imaging and Radar for Safer Cancer Diagnosis
- New AI Tool Helps Doctors Read Chest X‑Rays Better
- Wearable X-Ray Imaging Detecting Fabric to Provide On-The-Go Diagnostic Scanning
- AI Helps Radiologists Spot More Lesions in Mammograms
- AI Detects Fatty Liver Disease from Chest X-Rays
- AI Detects Hidden Heart Disease in Existing CT Chest Scans
- Ultra-Lightweight AI Model Runs Without GPU to Break Barriers in Lung Cancer Diagnosis
- AI Radiology Tool Identifies Life-Threatening Conditions in Milliseconds

- Machine Learning Algorithm Identifies Cardiovascular Risk from Routine Bone Density Scans
- AI Improves Early Detection of Interval Breast Cancers
Channels
MRI
view channel
Novel Imaging Approach to Improve Treatment for Spinal Cord Injuries
Vascular dysfunction in the spinal cord contributes to multiple neurological conditions, including traumatic injuries and degenerative cervical myelopathy, where reduced blood flow can lead to progressive... Read more
AI-Assisted Model Enhances MRI Heart Scans
A cardiac MRI can reveal critical information about the heart’s function and any abnormalities, but traditional scans take 30 to 90 minutes and often suffer from poor image quality due to patient movement.... Read more
AI Model Outperforms Doctors at Identifying Patients Most At-Risk of Cardiac Arrest
Hypertrophic cardiomyopathy is one of the most common inherited heart conditions and a leading cause of sudden cardiac death in young individuals and athletes. While many patients live normal lives, some... Read moreUltrasound
view channel
Wearable Ultrasound Imaging System to Enable Real-Time Disease Monitoring
Chronic conditions such as hypertension and heart failure require close monitoring, yet today’s ultrasound imaging is largely confined to hospitals and short, episodic scans. This reactive model limits... Read more
Ultrasound Technique Visualizes Deep Blood Vessels in 3D Without Contrast Agents
Producing clear 3D images of deep blood vessels has long been difficult without relying on contrast agents, CT scans, or MRI. Standard ultrasound typically provides only 2D cross-sections, limiting clinicians’... Read moreNuclear Medicine
view channel
PET Imaging of Inflammation Predicts Recovery and Guides Therapy After Heart Attack
Acute myocardial infarction can trigger lasting heart damage, yet clinicians still lack reliable tools to identify which patients will regain function and which may develop heart failure.... Read more
Radiotheranostic Approach Detects, Kills and Reprograms Aggressive Cancers
Aggressive cancers such as osteosarcoma and glioblastoma often resist standard therapies, thrive in hostile tumor environments, and recur despite surgery, radiation, or chemotherapy. These tumors also... Read more
New Imaging Solution Improves Survival for Patients with Recurring Prostate Cancer
Detecting recurrent prostate cancer remains one of the most difficult challenges in oncology, as standard imaging methods such as bone scans and CT scans often fail to accurately locate small or early-stage tumors.... Read moreGeneral/Advanced Imaging
view channel
3D Scanning Approach Enables Ultra-Precise Brain Surgery
Precise navigation is critical in neurosurgery, yet even small alignment errors can affect outcomes when operating deep within the brain. A new 3D surface-scanning approach now provides a radiation-free... Read more
AI Tool Improves Medical Imaging Process by 90%
Accurately labeling different regions within medical scans, a process known as medical image segmentation, is critical for diagnosis, surgery planning, and research. Traditionally, this has been a manual... Read more
New Ultrasmall, Light-Sensitive Nanoparticles Could Serve as Contrast Agents
Medical imaging technologies face ongoing challenges in capturing accurate, detailed views of internal processes, especially in conditions like cancer, where tracking disease development and treatment... Read more
AI Algorithm Accurately Predicts Pancreatic Cancer Metastasis Using Routine CT Images
In pancreatic cancer, detecting whether the disease has spread to other organs is critical for determining whether surgery is appropriate. If metastasis is present, surgery is not recommended, yet current... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read morePatient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more







