BoneXpert

Visiana
BoneXpert analyses an X-ray of a child's hand automatically, without any interference from a human. The main result is the Greulich Pyle bone age - TW2/3 bone ages can also be given. BoneXpert also reports the bone age standard deviation score. The X-ray can be of a left or a right hand and the hand can assume any rotation in the image plane. The analysis is automatically rejected, if it cannot be done reliably, e.g. if there is too much image postprocessing. Finally, the Bone Heath Index is determined from the cortical thicknesses in the metacarpals.
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Information source: Vendor
Last updated: October 7, 2024

General Information

General
Product name BoneXpert
Company Visiana
Subspeciality MSK
Modality X-ray
Disease targeted Short stature, tall stature, early or late puberty, Congenital Adrenal Hyperplasia (CAH), orthopedic treatment planning, orthodontics, sports medicine, legal medicine, clinical trials
Key-features Bone age, Bone Health Index, Percent Adult Height
Suggested use Without interference of a radiologist: AI-only diagnosis

Technical Specifications

Data characteristics
Population Children from age 0 (zero) years, all ethnicities
Input Posterior anterior (PA) hand radiograph
Input format DICOM
Output Annotated DICOM image, DICOM-encapsulated pdf report, Structured Report
Output format DICOM
Technology
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Stand-alone third party application, Support for RIS integration with DICOM Structured Reports
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker)
Trigger for analysis Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time 3 - 10 seconds

Regulatory

Certification
CE
Certified, Class I , MDD
FDA No or not yet
Intended Use Statements
Intended use (according to CE) The intended use of BoneXpert is to perform an automatic determination of bone age and bone health index (BHI). The bone age determination can replace the conventional manual rating and the operation needs no supervision by an expert.

Market

Market presence
On market since 03-2009
Distribution channels
Countries present (clinical, non-research use) >40
Paying clinical customers (institutes) >200
Research/test users (institutes) 13
Pricing
Pricing model Subscription
Based on Number of analyses

Evidence

Evidence
Peer reviewed papers on performance
  • A comparison of two artificial intelligence-based methods for assessing bone age in Turkish children: BoneXpert and VUNO Med-Bone Age (read)

  • Performance of two different artificial intelligence (AI) methods for assessing carpal bone age compared to the standard Greulich and Pyle method (read)

  • Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction (read)

  • BoneXpert V1: Clinical review: An automated method for determination of bone age (read)

  • BoneXpert V1,2,3: A paediatric bone index derived by automated radiogrammetry (read)

  • BoneXpert V2: Automated determination of bone age from hand X-rays at the end of puberty and its applicability for age estimation (read)

  • BoneXpert V2: Clinical application of automatic Greulich-Pyle bone age in children with short stature (read)

  • BoneXpert V2: Prediction of Adult Height Based on Automated Determination of Bone Age (read)

  • BoneXpert V2: Validation and Reference Values of Automated Bone Age Determination for Four Ethnicities (read)

  • BoneXpert V2: Validation of automatic bone age rating in children with precocious and early puberty (read)

  • BoneXpert V2: Validation of automatic bone age determination in children with congenital adrenal hyperplasia (read)

  • BoneXpert V3: Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment (read)

  • BoneXpert V3: Accuracy and self‑validation of automated bone age determination (read)
Non-peer reviewed papers on performance

  • The RSNA Pediatric Bone Age Machine Learning Challenge, Radiology 2018 (read)
Other relevant papers

  • BoneXpert V2: Bone age assessment: automated techniques coming of age? (read)

  • Explainer video on the product (watch)

  • Explainer video on the architecture of the integration (watch)