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QP-Prostate®
Discover QP-Prostate®
Prostate cancer is the second most common cancer in men, representing a significant public health concern. While MRI scans are essential for early detection, the growing demand has surpassed the availability of radiology experts, with diagnostic delays and inconsistencies in interpretation as direct consequences. Only a minority of the medical community consistently follows PI-RADS v2.1 guidelines.
QP-Prostate introduces enhanced diagnostic capabilities, streamlining radiologists’ workflows by automatically ensuring compliance with PI-RADS v2.1 guidelines, accurately segmenting the prostate gland, and efficiently identifying suspicious lesions*. These advancements enable radiologists to provide faster and more accurate assessments, directly improving patient care.
Prostate segmentation & lesion detection
QP-Prostate’s AI algorithm achieves 88% accuracy in segmenting the prostate gland and seminal vesicles, highlighting High (orange) and Moderate (yellow) risk areas for clinically significant prostate cancer (csPCa). This precision supports PSA density calculations and fusion biopsy planning. Our advanced AI-driven lesion detection, utilizing biparametric input (T2W and DWI), efficiently identifies prostate cancer lesions, setting a new standard for accuracy, speed, and diagnostic precision.
Your AI solution for advanced prostate cancer detection
QP-Prostate: a set of enhanced diagnostic capabilities
AI-based automatic lesion detection*
Our AI algorithm, trained with pathology outcomes as ground truth, is designed to efficiently detect clinically significant prostate cancer lesions using biparametric inputs (T2w, DWI and ADC), outperforming competitors in detection rate and speed. These AI algorithms are intended to elevate radiologists’ diagnostic accuracy with automated detection of biopsy-proven, clinically significant prostate cancer lesions.
Precision in segmentation
QP-Prostate’s AI algorithm automatically identifies the prostate anatomy and segments the full prostate gland with market-leading performance (88% DSC1), as well as the seminal vesicles, to assist in PSA density calculations. The results can be directly exported for fusion biopsy procedures.
Quantitative analysis
QP-Prostate automatically verifies MRI acquisition protocol according to PI-RADSv2.1 guidelines, ensuring that radiologists work with high-quality MRI examinations from the start.
The platform provides spatially registered, motion corrected, synthesized b-1400s/mm2 DWI and ADC map series, offering rich quantitative diffusion information. This dataset empowers radiologists to analyze potentially cancerous lesions with confidence. For mpMRI studies, perfusion analysis (Ktrans, Kep, Ve maps) are automatically generated.
Cloud to PACS integration
All analysis outputs are directly sent back to the hospital PACS for their visualization without disrupting radiology workflows.
How does it work?
Changing the narrative in prostate diagnosis thanks to maximum accuracy in prostate MRI interpretation
In short, QP-Prostate leverages advanced artificial intelligence image processing techniques to offer a state-of-the-art approach to prostate MRI interpretation. This image processing software is compatible with standard workstations and allows for the visualization and analysis of DICOM data by qualified professionals.
Developed by Quibim, QP-Prostate excels in automating the segmentation of critical prostate regions, including the transition zone, peripheral zone and seminal vesicles. By streamlining these complex processes, the software not only aids in the interpretation of prostate MRI images, but also enables more accurate diagnoses. This combination of sophisticated AI-based analysis and user-friendly implementation makes QP-Prostate an invaluable tool in the hands of healthcare professionals, ensuring better patient outcomes through more reliable and detailed assessments.
References
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Jimenez-Pastor A, et al. Eur Radiol. 2023;33(7):5087-5096.
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Sánchez Iglesias Á, et al. Cancers (Basel). 2023;15(16):4163.
*In the US: Lesion detection functionality pending 510(k), not available for sale within the United States
**Pilot study conducted in 2023 at Massachussets General Hospital.