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Automatic, Opportunistic Surveillance of Hip Bone Fragility in X-ray Images

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R44AG081031-01A1
Agency Tracking Number: R44AG081031
Amount: $915,851.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: NIA
Solicitation Number: PA22-176
Solicitation Year: 2022
Award Year: 2023
Award Start Date (Proposal Award Date): 2023-06-01
Award End Date (Contract End Date): 2025-02-28
Small Business Information
57 Chapel St, Suite 200
Newton, MA 02458-1080
United States
DUNS: 802270988
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (888) 589-6213
Business Contact
Phone: (888) 589-6213
Research Institution

PROJECT SUMMARY / ABSTRACTApproximately 1 in 3 women and 1 in 5 men over the age of 50 will suffer from a fragility fracture in their
remaining lifetime. Fragility hip fracture is one of the most serious and debilitating outcomes of osteoporosis with
a 20–40% mortality rate during the first year after the fracture. Hip fracture incidence rates are known to increase
exponentially with age in both women and men; and with the rising life expectancy throughout the globe, the
number of men and women who will be above the threshold of fragility fracture is expected to almost double,
with a prediction of 319 million cases by 2040. Thus, the number of fractures is predicted to double as well.In this Direct Phase II SBIR, BioSensics, in collaboration with orthopaedic, radiology, endocrinology and
biomechanics experts at Harvard Medical School, proposes to develop a cloud-based software solution for
automatic, opportunistic screening for hip fracture risk using plain X-ray images, called XFx. X-ray studies are
ubiquitous in all corners of the world, are inexpensive and provide high resolution studies that offer insight into
bone geometry, microstructure and density, at a low ionizing radiation dose. The proposed software solution will
include 1) a desktop application for uploading X-ray images and displaying and visualizing XFx results, and 2) a
secure cloud-based backend for receiving the uploaded X-ray images and performing the analysis. The software
architecture will support on-premise integration with a hospital cloud services (e.g., PACS systems) to enable
automatic, opportunistic screening for hip fracture risk using plain X-ray images. The solution will stand by in the
central imaging data server of hospitals or clinics, investigate each non-investigated X-ray image, and if
recognized to include a proximal femur, automatically execute the AI/ML-based classification scheme to identify
patients with osteoporosis or at high risk of hip fracture. If a patient is identified to have osteoporosis or a high
risk of fracture, the software will flag the patient. The clinician providing care for the patient will then be prompted
to consider ordering an evaluation of fragility fracture risk and receive a full report.This process is reimbursable under the Current Procedural Terminology (CPT) code 76499 “Unlisted
Diagnostic Radiographic Procedure.” This code is used when no other specific procedure code exists. The
existence of this CPT will support the initial marketing of the proposed solution. In Phase III, we will prepare an
application for a new Category III CPT code and submit if for consideration by the American Medical Association
(AMA) CPT Editorial Panel. Given the clinical need of the proposed solution, and recent approval of a CPT code
for radiology artificial intelligence (code 0691T) for automated analysis of existing imaging studies for vertebral
fracture and bone density assessment, our application for a new CPT code should not face any difficulties. In
the longer term, the proposed imaging analysis technology can be used for automatic analysis of thousands of
medical images that are taken every day in hospitals and clinics. This will enable detection of diseases and
conditions at early stages (e.g., bone metastasis and different tumors), thus facilitating preventive measures and
better care for those individuals at risk.

* Information listed above is at the time of submission. *

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