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The intended use of the Hologic® Body Composition Software Option for QDR® X-Ray Bone Densitometers is to estimate the lean body mass and fat mass of non-osseous tissues in situations where medically necessary.

The Hologic® Body Composition Software Option for QDR® X-Ray Bone Densitometers is a software algorithm that permits an operator to display soft tissue characteristics. Soft tissue estimates are obtained using the Dual X-Ray Photon Absorptiometry (DXA) technique in which the x-ray tube emits alternating pulses of "high" and "low" energy x-rays which pass through the subject and are received by the detector array. The attenuation of the x-ray beam due to the subject is estimated by the detectors. By comparing the attenuation of the high and low energy pulses, the contributions of bone in the subject can be eliminated, leaving only the contributions due to non-osseous tissues.

Here's a breakdown of the acceptance criteria and study information for the Hologic® Body Composition Software Option for QDR® X-Ray Bone Densitometers, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly list quantitative "acceptance criteria" in the formal sense (e.g., minimum sensitivity, specificity, or specific error margins). Instead, it describes "performance data" that establishes the utility and validity and concludes substantial equivalence based on strong correlations and small differences compared to predicate devices and among its own models.

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

The document does not specify a distinct "test set" sample size. The performance data refers to:

• "Published reports using in vitro and in vivo models": No specific sample sizes for these are given.
• "Normative data generated among healthy individuals spanning the adult age-range (as well as in children and adolescents)": No specific sample size is given.
• "Studies included comparative experiments to evaluate DXA and other modalities": No specific sample size is given.
• "A study was also conducted to determine the strength of agreement among the QDR® models with the body composition software": No specific sample size is given.

Data Provenance: The document does not specify the country of origin of the data. The studies appear to be retrospective or a combination of retrospective analyses of published data and prospective internal studies ("A study was also conducted...").

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

The document does not mention the use of experts to establish ground truth for a test set in the traditional sense of human readers for image interpretation. The ground truth appears to be established through:

• Comparative experiments with "other modalities commonly used for estimating body composition": These other modalities would serve as the reference standard (ground truth). The nature and expertise involved in validating these other modalities are not detailed.
• Agreement among QDR® models: This suggests a self-validation approach within the Hologic ecosystem, implying the existing QDR® technology acted as a form of ground truth or reference.

4. Adjudication Method for the Test Set

No adjudication method is mentioned or implied, as the ground truth was established through comparison to other measurement modalities or internal consistency among QDR® models rather than human expert interpretation requiring adjudication.

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

No such MRMC comparative effectiveness study was mentioned. The device is a software algorithm for body composition measurement, not one requiring human interpretation of images in the context of an AI-assisted diagnostic workflow.

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

Yes, the performance data presented is for the standalone software algorithm. It performs the calculations for fat mass, lean mass, and total soft tissue mass based on the DXA data. The "operator" role is to display the characteristics, not to interpret raw data to derive the metrics themselves.

7. The Type of Ground Truth Used

The ground truth or reference standard appears to be:

• Comparative measurements from "other modalities commonly used for estimating body composition." The specific nature of these modalities (e.g., DEXA from other manufacturers, hydrostatic weighing, MRI) is not detailed.
• Internal consistency and agreement among different QDR® models themselves. This suggests that the established accuracy of existing QDR® hardware and software served as a reference.

8. The Sample Size for the Training Set

The document does not explicitly mention a "training set" or its size. The device is a software algorithm for processing DXA data. Its development likely relied on historical data and established physiological models, rather than a distinct machine learning training set as understood today. The "published reports using in vitro and in vivo models" and "normative data" likely informed the algorithm's development and parameters.

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

As no specific training set is outlined, the establishment of ground truth for training is not detailed. However, the foundational "utility and validity" of determining soft tissue components with QDR® devices was established through:

• In vitro and in vivo models.
• Comparative experiments evaluating DXA against other body composition modalities.
• Normative data from healthy individuals.
• Data from patients with syndromes affecting body composition (e.g., AIDS, cystic fibrosis).

This suggests that the algorithm's underlying principles were developed and validated against established scientific and medical understanding of body composition measurement, anchored by comparisons to other accepted methods and observations in various populations.

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