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AAPM Recommends Against Use of Bismuth Shielding for CT Scanning
In a position statement, the American Association of Physicists in Medicine advise against using bismuth shields for dose reduction in CT scanning when alternatives are available.
Regular use of bismuth shields during CT scanning to protect anterior organs is not recommended by the American Association of Physicists in Medicine (AAPM) when alternatives for shielding are available.
Bismuth shielding has been traditionally used to shield radiosensitive organs such as the breast, lens of the eye and thyroid during CT scans.
“However, bismuth shielding degrades image quality, attenuates photons exiting the patient, and causes unpredictable results when combined with automatic exposure control systems,” the group said in a position statement released this week. Click here for a pdf of the full statement.
According to the AAPM, there are several known disadvantages to bismuth shield use, such as degrading image quality and accuracy, unpredictable and potentially undesirable levels of dose and image quality, and waste of some of the patient’s radiation exposure.
To avoid the use of the shield, suggestions include reducing the dose to the specific peripheral organs by adjusting automatic exposure controls (AEC) parameters and using organ-based tube current modulation techniques.
Study Reveals Benefits of Photon-Counting CT for Assessing Acute Pulmonary Embolism
April 23rd 2024In comparison to energy-integrating detector CT for the workup of suspected acute pulmonary embolism, the use of photon-counting detector CT reduced radiation dosing by 48 percent, according to newly published research.
The Reading Room: Racial and Ethnic Minorities, Cancer Screenings, and COVID-19
November 3rd 2020In this podcast episode, Dr. Shalom Kalnicki, from Montefiore and Albert Einstein College of Medicine, discusses the disparities minority patients face with cancer screenings and what can be done to increase access during the pandemic.
AI Adjudication Bolsters Chest CT Assessment of Lung Adenocarcinoma
April 11th 2024The inclusion of simulated adjudication for resolving discordant nodule classifications in a deep learning model for assessing lung adenocarcinoma on chest CT resulted in a 12 percent increase in sensitivity rate.
