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Dose can drop in large patients
The trade-off between image noise and radiation exposure in low-dose multislice CT for kidney stone detection has not been kind to overweight patients. They are often excluded from low-dose studies, scanned at higher doses, or scanned repeatedly with normal doses.
The trade-off between image noise and radiation exposure in low-dose multislice CT for kidney stone detection has not been kind to overweight patients. They are often excluded from low-dose studies, scanned at higher doses, or scanned repeatedly with normal doses. A 4D tube current modulation-adapted to the x-, y-, and z-planes continuously during scanning-was found to reduce dose by more than 60% without affecting accuracy in overweight patients (AJR 2007;188:553-562).
Dr. Tom H. Mulkens, a radiologist at Heilig Hart Hospital in Lier, Belgium, and colleagues concluded that this technique could become standard in overweight and obese patients with suspected acute renal colic.
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
Current Perspectives on Radiology Workforce Issues and Potential Solutions
March 14th 2024Emphasizing the gravity of the ongoing workforce shortage in radiology, these authors recommend a change agenda focusing on expanded numbers of residency positions, reassessment of educational pathways, maintaining a strong presence in hospital settings and practice level initiatives to reduce administrative burden and achieve appropriate reimbursement beyond RVU measurements.
Could Cloud-Based 'Progressive Loading' be a Boon for Radiology Workflows?
March 13th 2024The newly launched Progressive Loading feature, available through RamSoft’s OmegaAI software, reportedly offers radiologist rapid uploading of images that is faster than on-site networks and other cloud-based systems regardless of the network radiologists are using.
