Canon Medical Systems announced that the U.S. Food & Drug Administration (FDA) has cleared its Compressed SPEEDER technology for use in the company’s Vantage Orian 1.5T MRI system.
Canon Medical Systems announced that the U.S. Food & Drug Administration (FDA) has cleared its Compressed SPEEDER technology for use in the company’s Vantage Orian 1.5T MRI system.
The technology, which is also available on the Vantage Galan 3T MRI system, can help reduce overall MRI scan times by reconstructing full resolution images from under-sampled data and avoiding unfolding error artifacts. In addition, it can help capture higher resolution images in 2D Fast Spin Echo acquisitions.
Reduced scan time not only presents an advantage for patients who find it difficult to remain still during long scans, but it also allows for additional time for disinfection of MRI systems and imaging suites between patients as practices begin to return to more normal patient volumes.
Faced with new, stringent cleaning protocols, more complex patient appointment management and other changes to workflow, the Compressed SPEEDER technology may help ease some post-pandemic growing pains for radiology departments and practices as many work to adjust to the “new normal.”
Canon’s new technology is included in an updated version of the M-Power software available for the Vantage Orian 1.5T. The software comes standard with Windows 10 and cybersecurity functionality, including continuous updates from Microsoft and whitelisting functions which allow for access only to authorized applications and processes.
“In MR imaging, shortening scan times is vastly important for both the patient and physician,” said Jonathan Furuyama, managing director, MR Business Unit, Canon Medical Systems USA, Inc., in a statement. “With the help of Compressed SPEEDER along with Windows 10 on the Vantage Orian 1.5T MR system, healthcare providers can offer a quick, comfortable and safe experience for their patients.”
Can Deep Learning Radiomics with bpMRI Bolster Accuracy for Prostate Cancer Prognosis?
January 22nd 2025An emerging deep learning radiomics model based on biparametric MRI (bpMRI) offered a 14 to 17 percent higher AUC range than PI-RADS scoring for predicting the aggressiveness of prostate cancer, according to new research findings.
Seven Takeaways from New CT and MRI Guidelines for Ovarian Cancer Staging
January 20th 2025In an update of previous guidelines from the European Society of Urogenital Radiology published in 2010, a 21-expert panel offered consensus recommendations on the utility of CT, MRI and PET-CT in the staging and follow-up imaging for patients with ovarian cancer.
Can Generative AI Facilitate Simulated Contrast Enhancement for Prostate MRI?
January 14th 2025Deep learning synthesis of contrast-enhanced MRI from non-contrast prostate MRI sequences provided an average multiscale structural similarity index of 70 percent with actual contrast-enhanced prostate MRI in external validation testing from newly published research.
Can MRI-Based AI Enhance Risk Stratification in Prostate Cancer?
January 13th 2025Employing baseline MRI and clinical data, an emerging deep learning model was 32 percent more likely to predict the progression of low-risk prostate cancer (PCa) to clinically significant prostate cancer (csPCa), according to new research.