STTR Phase II: Automated system for creating custom three-dimensional radiofrequency ablation lesion geometries in post-lumpectomy margin ablation breast cancer treatment

Information

  • NSF Award
  • 1738541
Owner
  • Award Id
    1738541
  • Award Effective Date
    9/15/2017 - 6 years ago
  • Award Expiration Date
    8/31/2019 - 4 years ago
  • Award Amount
    $ 486,217.00
  • Award Instrument
    Standard Grant

STTR Phase II: Automated system for creating custom three-dimensional radiofrequency ablation lesion geometries in post-lumpectomy margin ablation breast cancer treatment

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project will focus on the design of the first completely automated radio frequency ablation (RFA) system for breast tissue. Of the approximately 200,000 breast cancer patients in the US who elect lumpectomy annually, over 20% must undergo re-operation due to lack of clear margins. Furthermore, many breast cancer patients who are treated with lumpectomy require expensive adjuvant radiation therapy that can last up to 7 weeks causing time away from work and family. Fortunately, performing intraoperative RFA of the lumpectomy cavity has been shown to decrease the need for re-operations and radiation therapy by sterilizing tumor margins. However, no RFA devices are designed for post-lumpectomy breast cavities or breast tissue. The RFA system being developed in this project will automate post-lumpectomy RFA, accurately and precisely delivering energy based on local tissue properties and desired ablation depth in three dimensions thus customizing treatment for each patient. Eventual commercialization of this system could provide early stage breast cancer patients new treatment options that improve quality of life, reduce burdens of care, and costs while providing breast cancer recurrence control. <br/><br/>The proposed project aims to develop a system (control unit and device) for optimal post-lumpectomy RFA. The proposed device is designed to mechanically fit the post-lumpectomy cavity for near-perfect tissue contact. The control unit includes advanced algorithms that utilize machine learning to create a three-dimensional ablation status map of each margin (ablation vs in-ablated) for controlling ablation. The combined system allows the surgeon to customize and monitor the three-dimensional ablation profile and automates therapy delivery to ensure accurate, precise ablation results. The objectives propose gathering device requirements, identifying critical tasks of an automated RFA procedure, and improving the system algorithm by collecting training data in cadaveric and prophylactic mastectomy specimens. The intellectual merits proposed are: (1) an automated ablation system implemented on an embedded microprocessor and co?]processor FPGA capable of ablation shape estimation and control; (2) a system that demonstrates clinical relevance through successful ablation in human tissue and surgeon usability.

  • Program Officer
    Jesus Soriano Molla
  • Min Amd Letter Date
    9/22/2017 - 6 years ago
  • Max Amd Letter Date
    9/22/2017 - 6 years ago
  • ARRA Amount

Institutions

  • Name
    Innoblative Designs
  • City
    Chicago
  • State
    IL
  • Country
    United States
  • Address
    4660 N Ravenswood Avenue
  • Postal Code
    606404510
  • Phone Number
    3129655472

Investigators

  • First Name
    Alan
  • Last Name
    Sahakian
  • Email Address
    sahakian@ece.nwu.edu
  • Start Date
    9/22/2017 12:00:00 AM
  • First Name
    Robert
  • Last Name
    Rioux
  • Email Address
    bob@innoblative.com
  • Start Date
    9/22/2017 12:00:00 AM

Program Element

  • Text
    STTR PHASE II
  • Code
    1591

Program Reference

  • Text
    STTR PHASE II
  • Code
    1591
  • Text
    BIOMEDICAL ENGINEERING
  • Code
    5345
  • Text
    Health and Safety
  • Code
    8042