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The Infant Whole Body software option for QDR X-Ray Bone Densitometers is an optional data acquisition and analysis method that provides estimates of bone mineral content (BMC, in grams), bone mineral density (BMD, in grams/cm²), and body composition (lean body mass and fat mass of non-osseous tissues) in human infants from birth to one year of age. These data may be used at the discretion of a physician where medically necessary.

The Infant Whole Body software option for QDR X-Ray Bone Densitometers is an optional data acquisition and analysis method that provides estimates of bone mineral content (BMC. in grams), bone mineral density (BMD, in grams/cm²), and body composition (lean body mass and fat mass of non-osseous tissues) in human infants from birth to one year of age. These data may be used at the discretion of a physician where medically necessary. The Infant Whole Body software option adds an optional scan type to the QDR XP Scan Module, and an optional analysis type to the QDR XP Analysis Module of the QDR for Windows software operating system. The only differences between the Infant Whole Body software option and the adult Whole Body Software Option are: A modification to the Scan Module (data acquisition module) to enable a smaller region of interest (due to smaller subject size), thinner x-ray beam and slower scan speed to improve spatial resolution and bone edge detection, and A modification to the Analysis Module (data analysis module) include an algorithm that employs lower bone and soft tissue detection thresholds suitable for detecting and evaluating low bone densities and low soft tissue masses found in human infants.

The provided document is a 510(k) Summary of Safety and Effectiveness for the Hologic Infant Whole Body Software Option for QDR Densitometers, dated October 29, 2004. It describes the device and claims substantial equivalence to predicate devices. However, it does not contain detailed information about specific acceptance criteria or a study proving the device meets those criteria, as typically found in clinical validation studies.

The document focuses on comparing the new device's features and intended use to existing, legally marketed predicate devices (K023398 Discovery Package and K961787 Body Composition Analysis Software). The primary argument for substantial equivalence is that the Infant Whole Body software performs the same functions with minor modifications to optimize for infants (smaller region of interest, thinner x-ray beam, slower scan speed, and lower bone/soft tissue detection thresholds). This is a regulatory filing for premarket notification, not a clinical trial report.

Therefore, many of the requested details are not present in this document.

Here's a breakdown of the information that can be extracted or inferred, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state specific acceptance criteria (e.g., specific accuracy thresholds for BMC, BMD, or body composition measurements) or numerical device performance results from a validation study. The comparison table (F.8) lists attributes of the devices but does not quantify performance.

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

This information is not provided in the document. No specific test set or clinical study data is reported.

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

This information is not provided in the document, as no specific test set requiring expert ground truth is described.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

A MRMC comparative effectiveness study is not mentioned or described in the document. This type of study would compare human reader performance with and without AI assistance, which is not the focus of this 510(k) filing.

6. Standalone (Algorithm Only) Performance Study

A standalone performance study for the algorithm itself (demonstrating its accuracy in measuring BMC, BMD, and body composition in infants) is not explicitly detailed or referenced in terms of specific metrics or a study. The document states that the software provides "estimates" and relies on its similarity to predicate devices, which are already cleared for measuring these parameters. The modifications are described as improving spatial resolution and bone edge detection and employing suitable detection thresholds for infants, but no quantitative performance improvement or validation is provided.

7. Type of Ground Truth Used

The document does not specify the type of ground truth used for any performance evaluation, as no such evaluation is detailed. For bone densitometry, "ground truth" would typically involve precise physical measurements, possibly validated by phantoms or alternative highly accurate methods, but no such details are furnished.

8. Sample Size for the Training Set

This information is not provided in the document. The filing describes the product as a "software option," implying algorithmic changes rather than a deep learning model that would typically require a training set in the modern sense. Given the 2004 date, it's more likely referring to adjustments in established algorithms rather than training a machine learning model on a dataset.

9. How Ground Truth for the Training Set Was Established

This information is not provided in the document.

Summary of Document's Content Regarding Performance/Validation:

The document asserts that the Infant Whole Body Software Option is substantially equivalent to predicate devices. It achieves this by:

• Modifying the Scan Module: To enable a smaller region of interest, thinner x-ray beam, and slower scan speed to improve spatial resolution and bone edge detection for smaller subjects.
• Modifying the Analysis Module: To include an algorithm that employs lower bone and soft tissue detection thresholds suitable for infants.

The basis for regulatory clearance (510(k)) is this claim of substantial equivalence, meaning it performs the same essential functions as previously cleared devices, with modifications appropriate for its specific user population (infants), and without raising new issues of safety or effectiveness. The filing does not include a new clinical study to establish specific performance metrics or acceptance criteria for the new software option. It relies on the established safety and effectiveness of the predicate devices and the design modifications tailored for infants.

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The Hologic QDR Explorer is a fan beam X-Ray Bone Densitometer indicated for (1) the measurement of bone mineral content (BMC) and the estimation of bone mineral density (BMD), (2) comparison of measurements to reference databases, (3) the estimation of fracture risk, (4) body composition analysis, and (5) measurement of periprosthetic BMD

The Hologic QDR Explorer is a fan beam X-Ray Bone Densitometer indicated for (1) the measurement of bone mineral content (BMC) and the estimation of bone mineral density (BMD), (2) comparison of measurements to reference databases, (3) the estimation of fracture risk, (4) body composition analysis, and (5) measurement of periproshtetic BMD.

This submission (K033224) is a Special 510(k) for the Hologic QDR Explorer X-Ray Bone Densitometer. Special 510(k)s are used for modifications to a device already cleared by the FDA, where the modification does not affect the intended use or fundamental scientific technology of the device. Therefore, a comprehensive de-novo study proving the device meets acceptance criteria is typically not performed, as the substantial equivalence is largely based on the predicate device's performance.

Instead, the submission focuses on demonstrating that the modified device (QDR Explorer) is substantially equivalent to its predicate (QDR-3000 K943505 and Hologic Discovery Package for QDR X-Ray Bone Densitometers K023398) and continues to meet the safety and effectiveness standards established for bone densitometers. The information provided outlines changes in specifications rather than reporting specific performance metrics against acceptance criteria from a new clinical study.

Here's an analysis of the provided information in the context of your request:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not include a table of acceptance criteria and reported device performance against those criteria as would be found in a primary clinical study for a new device. Instead, it presents a comparison table between the predicate device (QDR-3000) and the proposed device (QDR Explorer) to demonstrate substantial equivalence.

The "acceptance criteria" for a Special 510(k) often revolve around demonstrating that the modified device performs comparably to the predicate device and that the changes do not introduce new safety or effectiveness concerns. For this specific device, the "performance" aspects highlighted are primarily changes in hardware specifications.

Here's a reinterpretation of the provided table, focusing on the differences and implied acceptance of parity:

2. Sample Size for the Test Set and Data Provenance

This Special 510(k) primarily relies on the established performance of the predicate device (QDR-3000) and previous clearances for its software and additional functionalities (e.g., K023398 for Discovery software, K983028 for fracture risk, K963363 for reference databases, K961787 for body composition, K002711 for periprosthetic BMD).

There is no dedicated sample size for a "test set" reported for the QDR Explorer in this submission that would involve new clinical data collection. The submission emphasizes substantial equivalence documentation of specification changes, largely in hardware and software versions. If any testing was done to confirm the functionality of the new detector, source-to-detector distance, or new software running on new hardware, it would likely be in the form of engineering verification and validation tests, not a clinical trial with a "test set" in the traditional sense of evaluating diagnostic accuracy.

The data provenance for the predicate device's original clearance would have been specific to that submission (K943505). Similarly, the data for the cleared software (K023398) and other functionalities (K983028, K963363, K961787, K002711) would be tied to their respective 510(k) submissions. This document itself doesn't provide new clinical data.

3. Number of Experts and Qualifications for Ground Truth

Given that this is a Special 510(k) based on substantial equivalence to an already cleared predicate and the focus is on hardware/software updates, there is no mention of experts establishing a new ground truth for a test set. The fundamental "ground truth" for bone densitometry is typically established through clinical correlation studies comparing BMD measurements to, for example, fracture rates, or to other validated methods like quantitative computed tomography (QCT) or direct bone biopsy (though less common for routine densitometry validation). These would have been part of the predicate device's original clearance.

4. Adjudication Method for the Test Set

As there is no new clinical "test set" described in this submission, there is no adjudication method mentioned.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Bone densitometers are typically quantitative measurement devices. Their performance is evaluated based on precision (reproducibility of measurements) and accuracy (how well measurements correlate with actual bone mineral content/density). They are not usually evaluated through MRMC studies that assess human reader interpretation of images, as is common for diagnostic imaging AI. Therefore, no MRMC study was performed or reported here, and thus no effect size of AI assistance on human readers.

6. Standalone Algorithm Performance Study

The Hologic QDR Explorer is a physical medical device (an X-ray bone densitometer), not an AI algorithm. Its performance is the direct output of the system (BMC, BMD values). Therefore, the concept of a "standalone algorithm only without human-in-the-loop performance" doesn't directly apply. The device is the "algorithm" in a sense, as it processes the X-ray data to produce the measurements. The "performance" is the accuracy and precision of those measurements, which would have been established for the predicate device.

7. Type of Ground Truth Used

The "ground truth" for bone densitometry, in general, relies on:

• Clinical Outcomes Data: Correlation of BMD measurements with actual fracture incidence or risk.
• Pathology/Histology: In some research contexts, direct measurement of bone mineral content from biopsy.
• Expert Consensus/Reference Standards: Usage of anthropomorphic phantoms with known bone mineral densities, and comparisons to established reference populations for Z-scores and T-scores.

For this Special 510(k), the ground truth essentially lies in the established clinical utility and accuracy of the predicate device (QDR-3000) and the prior clearances for its functionalities and software. The QDR Explorer, through its substantial equivalence claim, implicitly leverages this existing ground truth rather than generating new primary ground truth data.

8. Sample Size for the Training Set

There is no "training set" mentioned in the context of this device. Bone densitometers are primarily physics-based measurement systems, not machine learning algorithms that require a training set in the typical sense. Data used for developing or validating reference databases (e.g., K963363) would involve large epidemiological studies, but this submission doesn't detail those.

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

As there is no "training set" for an AI algorithm, this question is not applicable to the information provided for this device. The development of reference databases, if considered a form of "training data," would involve large-scale population studies where age, sex, ethnicity, and direct BMD measurements are collected to establish statistical norms. These methods would have been detailed in the original 510(k)s for those specific functionalities (e.g., K963363).

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