- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
Emerging Prostate and Brain MRI AI Platform Gets FDA Nod
In addition to a previously FDA-cleared brain magnetic resonance imaging (MRI) module, the Advantis Platform features an artificial intelligence-powered prostate MRI module that offers simultaneous viewing of conventional and advanced sequences, and reportedly generates automated PI-RADS assessments.
The Food and Drug Administration (FDA) has reportedly granted 510(k) clearance to the Advantis Platform (Advantis Medical Imaging), which offers artificial intelligence-enabled modules for multiparametric prostate MRI as well as brain MRI analysis.
The Advantis Prostate module streamlines radiology workflows with automated diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI maps, and simultaneous viewing of advanced and conventional sequences in one viewer, according to Advantis Medical Imaging. The company adds that the Advantis Prostate module provides automated PI-RADS reporting with one click.
Images courtesy of Advantis Medical Imaging.
Advantis Medical Imaging said the Advantis Brain module (which previously garnered FDA 510(k) clearance under the name Brainance MD) offers a variety of features including automated processing of dynamic susceptibility contrast (DSC) MRI perfusion scans with expedient exporting of maps and key findings to the existing PACS system. Another benefit of Advantis Brain is fully automated tractography with single-click fiber tracking on diffusion tensor imaging (DTI), according to the company.
“This latest FDA clearance is a testament to our commitment to delivering innovative solutions that streamline workflows and provide clinicians with reliable, accessible and efficient software tools,” noted Zoi Giavri, the chief product office for Advantis Medical Imaging. “Our recent integration of the multiparametric prostate MRI module in our software suite, Advantis Platform, complements the existing brain MRI module while both of them enable healthcare professions to more easily extract meaningful information from MRIs.”
(Editor’s note: For related content, see “Can Explainable AI Enhance Diagnosis and PI-RADS Classification of Prostate Cancer on MRI?” and “FDA Clears New AI Software for MRI Detection of Prostate 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.
Study Emphasizes PSMA PET Staging of High-Risk, Hormone Sensitive Prostate Cancer
January 4th 2025In patients with high-risk, hormone sensitive prostate cancer who had no evidence of metastasis on conventional imaging, PSMA PET revealed polymetastatic disease in 24 percent of patients and M1 disease staging in 46 percent of patients.
Can MRI and Micro-Ultrasound Guidance Bolster Focal Laser Ablation Outcomes for Prostate Cancer?
January 3rd 2025For patients with localized prostate cancer and PI-RADS 3 or higher lesions, MRI-guided micro-ultrasound multifiber focal laser ablation had an 18 percent recurrence rate at one year, according to newly published research.
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.
Can AI Enhance PET/MRI Assessment for Extraprostatic Tumor Extension in Patients with PCa?
December 17th 2024The use of an adjunctive machine learning model led to 17 and 21 percent improvements in the AUC and sensitivity rate, respectively, for PET/MRI in diagnosing extraprostatic tumor extension in patients with primary prostate cancer.
