Computer-Aided Diagnostic for Use in Multiparametric MRI for Prostate Cancer


Multiparametric MRI improves image detail and prostate cancer detection rates compared to standard MRI. Computer aided diagnostics (CAD) used in combination with multiparametric MRI images may further improve prostate cancer detection and visualization. The technology, developed by researchers at the National Institutes of Health Clinical Center (NIHCC), is an automated CAD system for use in processing and visualizing prostate lesions on multiparametric MRI images. The system uses specialized algorithms (an ensemble of multiple random decision tress, Random Forest) that is trained against: 1) hand drawn contours, 2) recorded biopsy results, and 3) normal cases from randomly sampled patient images weighted for lesion size. This CAD system produces a more accurate probability map of potential cancerous lesions in multiparametric MRI images.

In addition, the CAD system may be used in several applications and settings including, but not limited to: 1) cloud-based prostate cancer screening, 2) use in under-resourced clinical settings with few or underexperienced radiologists, 3) integration into a work station or a picture archiving and communication system (PACS), 4) or serve as standalone software to be used on existing systems. This technology is currently available for licensing and co-development partnerships.

Potential Commercial Applications: Competitive Advantages:
  • Computer Assisted Diagnostics
 
  • Faster image analysis, improved workflow
  • More accurate diagnosis and treatment guidance
  • Potential for cloud-based prostate cancer screening
  • Use in under-resourced clinical settings
  • Standalone software in existing systems
  • Can be integrated into a work station or PACS


Inventors:

Nathan Lay (CC)  ➽ more inventions...

Yohannes Tsehay (CC)  ➽ more inventions...

Ronald Summers (CC)  ➽ more inventions...

Ismail Turkbey (NCI)  ➽ more inventions...


Intellectual Property:
US Application No. 62/462,256
PCT Application No. PCT/US2018/019249

Publications:
Lay N, et al. PMID 28630883

Collaboration Opportunity:

Researchers at the NIHCC seek licensing and/or co-development research collaborations for this technology.


Licensing Contact:
Edward (Tedd) Fenn, J.D.
Email: tedd.fenn@nih.gov
Phone: 240-276-6833

OTT Reference No: E-183-2016-0
Updated: Jun 23, 2017