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3D diffusion-weighted whole-body MR shows metastatic disease
Developed by radiologist Dr. Taro Takahara and colleagues at Tokai University School of Medicine in Japan, diffusion-weighted whole-body MR imaging with background body signal suppression (DWIBS) paves the way for practical whole-body 3D MR diffusion imaging. A new STIR-EPI sequence, performed with SENSE parallel processing, permits long acquisition times during free breathing to boost contrast resolution and overcome fat saturation problems.
Developed by radiologist Dr. Taro Takahara and colleagues at Tokai University School of Medicine in Japan, diffusion-weighted whole-body MR imaging with background body signal suppression (DWIBS) paves the way for practical whole-body 3D MR diffusion imaging. A new STIR-EPI sequence, performed with SENSE parallel processing, permits long acquisition times during free breathing to boost contrast resolution and overcome fat saturation problems.
Gray scale was reversed, black for white, producing a rotating 3D maximum intensity projection that resembled volumetric displays now generated with FDG-PET. The mechanism for producing DWI contrast in metastatic disease is not clearly understood but is thought to be associated with large cell sizes and high cellular densities that are common in cancerous tissue. Takahara described the approach at the International Society for Magnetic Resonance in Medicine meeting.
Study Reaffirms Low Risk for csPCa with Biopsy Omission After Negative Prostate MRI
December 19th 2024In a new study involving nearly 600 biopsy-naïve men, researchers found that only 4 percent of those with negative prostate MRI had clinically significant prostate cancer after three years of active monitoring.
Study Examines Impact of Deep Learning on Fast MRI Protocols for Knee Pain
December 17th 2024Ten-minute and five-minute knee MRI exams with compressed sequences facilitated by deep learning offered nearly equivalent sensitivity and specificity as an 18-minute conventional MRI knee exam, according to research presented recently at the RSNA conference.
Can Radiomics Bolster Low-Dose CT Prognostic Assessment for High-Risk Lung Adenocarcinoma?
December 16th 2024A CT-based radiomic model offered over 10 percent higher specificity and positive predictive value for high-risk lung adenocarcinoma in comparison to a radiographic model, according to external validation testing in a recent study.
