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Detection of Malignant Tumors in the Breast Using Strain-Encoding (SENC)…

Award Information

Agency:
Department of Health and Human Services
Branch:
N/A
Award ID:
Program Year/Program:
2013 / SBIR
Agency Tracking Number:
R44CA162870
Solicitation Year:
2013
Solicitation Topic Code:
NCI
Solicitation Number:
PA11-096
Small Business Information
DIAGNOSOFT, INC.
5001 S. Miami Blvd, Suite 340 Durham, NC 27703-
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 2013
Title: Detection of Malignant Tumors in the Breast Using Strain-Encoding (SENC) Magnetic
Agency: HHS
Contract: 4R44CA162870-02
Award Amount: $1,017,906.00
 

Abstract:

DESCRIPTION (provided by applicant): According to the American Cancer Societylts 2009 report, one in eight women will develop breast cancer in her lifetime. Early detection of breast cancer through periodic screening using x-ray mammography has been highlyeffective in lowering mortality-rates. However, some breast lesions are not visible on mammography and the use of magnetic resonance imaging (MRI) is increasingly recommended, especially for younger women with high inherited risk of breast cancer. To improve the clinical utility of MRI in breast cancer diagnosis, it is critically important to increase its specificity and to therefore reduce the emotional burden, time, and costs associated with the clinical follow-up required by these false positive diagnoses. The proposed research and collaboration between Diagnosoft, Inc. and Johns Hopkins University will develop a commercial system for improving the specificity of MRI in the detection of malignant breast tumors by imaging and quantifying their mechanicalstiffness. About 90% of breast lesions are found by palpation, either through self- inspection or by a primary physician or gynecologist. Thus, the mechanical stiffness of lesions is already important property distinguishing lesions from normal tissues. Recent evidence also suggests that mechanical stiffness may play a further role in distinguishing benign from malignant masses, and new technology has recently emerged to image stiffness using MRI and mild compression. The proposed research and development will exploit the combined imaging of conventional MRI with MRI-based stiffness imaging to increase the specificity of breast cancer diagnoses. This fast-track SBIR will be carried out in the following two phases. Phase I includes the redesign and construction of the compression device and developing a pneumatic system to use lower air pressure for operating the device; perform ergonomics and safety analysis of the device operation; and acquiring pilot data on volunteers. Phase II includes the modifying the prototype of the compression device to meet the ergonomics and safety recommendations of Phase I, developing the integrated system including the imaging sequences on the MRI scanner, image reconstruction, and image processing; and testing the system in a pilot study of healthy volunteers and patients to demonstrate feasibility and the ability to detect stiff masses that corresponds to lesions in the breast of patients. This collaboration between Johns Hopkins University for innovative research and Diagnosoftfor development will realize a new market in womenlts health care and continue thriving as a small US owned business. PUBLIC HEALTH RELEVANCE Early detection of breast cancer is highly effective in lowering mortality-rates. MRI, which is safe in terms of no ionizing radiation, can be used at younger ages for early detection of cancer; however, the existing MR imaging methods are not highly specific in detecting malignant breast tumors. We propose developing a commercial system for imaging and quantifying tissuelts mechanical stiffness to improve MRIlts specificity.

Principal Investigator:

Nael Osman
919-459-9105
nael@diagnosoft.com

Business Contact:

Nael Osman
919-459-9105
nael@diagnosoft.com
Small Business Information at Submission:

DIAGNOSOFT, INC.
5001 S. Miami Blvd, Suite 340 Durham, NC 27703-

EIN/Tax ID: 104368594
DUNS: N/A
Number of Employees: N/A
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No