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The bone density estimates from the pDEXATN and Discovery™ Bone Densitometers can be compared to gender and ethnic matched reference populations as an aid in determining the presence of bone disease other than agerelated bone loss. T-Score, % Young Reference, Z-Score, % Age Matched, and long and short term change values are provided. These reference populations include Caucasian, Afro-American, Hispanic, and Asian men and women.

The bone density estimates from the pDEXA™ and Discovery™ bone densitometers can be used as an aid to physicians in determining fracture risk.

In general, the Multi-Racial Reference Population capability for the pDEXA and Discovery bone densitometers compares the pDEXA and Discovery scan results to average values for people without bone related disease, who have the same gender and ethnic background as the patient. Its purpose is to aid the physician in determining the presence of bone disease other than age related bone loss. Both age matched and young reference comparisons are made. T-Score, Z-Score, % Young Reference, % Age Matched, and a graphical representation are presented.

The Norland pDEXA and Discovery bone densitometers scan the forearm using the industry standard DXA pencil beam technology to assess bone density of the distal and proximal radius plus ulna sites. The Discovery is a newer, smaller version of the pDEXA with faster scan speeds and lower dose. The Discovery dose is

The provided text describes the 510(k) summary for the "Multi-Racial Reference Population for pDEXA™ and Discovery™ Bone Densitometers." The device is not an AI/ML algorithm in the modern sense but rather a reference population used for interpreting bone density measurements. Therefore, many of the typical acceptance criteria and study design elements for AI/ML devices, such as performance metrics, ground truth establishment, training sets, and expert adjudication, are not directly applicable.

Instead, the "acceptance criteria" here relate to the validation of the multi-racial reference population's comparability and appropriateness for use with the pDEXA and Discovery bone densitometers. The study demonstrates that this new reference population is comparable to existing ones and does not raise new safety or effectiveness concerns.

Here's an attempt to structure the information as requested, adapting for the nature of this device:

Acceptance Criteria and Study to Prove Device Meets Criteria

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and the Data Provenance

The provided 510(k) summary does not detail the specific sample size used to construct or validate the multi-racial reference population, nor does it specify the data provenance (e.g., country of origin, retrospective/prospective). This type of information is typically found in the full 510(k) submission, not the summary document. However, given the nature of a reference population, it would typically be derived from a large, representative, and prospectively collected cohort study or a collection of such studies.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

Not applicable in the typical sense for this device. A "ground truth" for a reference population is established through epidemiological studies defining normal bone mineral density across different demographics. This involves large-scale data collection, statistical analysis, and potentially clinical consensus on thresholds (e.g., WHO criteria for fracture risk) rather than individual expert review of cases for algorithm performance.

4. Adjudication Method for the Test Set

Not applicable. This is not a device that processes individual cases requiring human adjudication for performance evaluation. The "adjudication" for a reference population would be the scientific and statistical rigor applied to its construction and validation against established medical standards.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was Done, If So, what was the effect size of how much human readers improve with AI vs without AI assistance

Not applicable. This device is a reference dataset, not an AI/ML diagnostic tool that assists human readers in interpreting images.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done

The device is a "standalone" reference population. It processes bone density measurements from the hardware (pDEXA/Discovery) and provides comparative metrics (T-Score, Z-Score, etc.) without a human-in-the-loop interpretation being part of the function of the reference population itself. Physicians then use these metrics to aid their diagnosis.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The "ground truth" for a bone mineral density reference population is based on:

• Epidemiological data: Large-scale population studies that define normal bone mineral density across various age, gender, and ethnic groups.
• Clinical outcomes data: Particularly for fracture risk assessment, the "truth" is often derived from longitudinal studies correlating bone mineral density values with actual fracture incidence (e.g., the basis for WHO criteria).
• Expert consensus: Derived from scientific bodies (like the WHO) establishing diagnostic thresholds (e.g., T-scores for osteoporosis).

8. The Sample Size for the Training Set

Not explicitly stated in the 510(k) summary but would typically be large, encompassing thousands or tens of thousands of individuals to create a robust and representative reference population. For AI/ML, this would be the "training set." For a reference population, it's the "derivation cohort."

9. How the Ground Truth for the Training Set Was Established

For a reference population, the "ground truth" (or normative data) is established through rigorous epidemiological studies:

• Participant Selection: Healthy individuals, representative of the target demographics (age, gender, ethnicity), are recruited, often excluding those with conditions or medications known to affect bone metabolism.
• Data Collection: Bone mineral density measurements are performed using standardized DXA techniques.
• Statistical Analysis: The collected data is statistically analyzed to determine mean BMD and standard deviations for each demographic subgroup (age, gender, ethnicity).
• Clinical Validation: The derived reference values are often cross-referenced with established clinical guidelines and, for fracture risk, validated against observed clinical outcomes.

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