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The Pediatric Reference Database is a software option used with Hologic QDR Series X-Ray Bone Densitometers. The software expands the range of bone densitometry reference data to include ages 3-20 years of age. The software provides a comparison of measured Bone Mineral Density (BMD) measurements obtained by dual energy x-ray absorptiometry to a database of BMD reference values in children. These data may be used for comparative purposes at the discretion of the physician.

The Pediatric Reference Database is a software option which simply extends the existing, commercially available reference databases' ability to generate a Z-score for younger subjects. The Pediatric Reference Database for the Hologic QDR Series X-Ray Bone Densitometers provides AP Spine, Hip and "Total" body bone densitometry reference data for male, white American children. This software is used in conjunction with previously existing software in the QDR Series Densitometers which calculates and reports results relative to sex, ethnicity and age-matched values. The reference database is used to expand the range of bone densitometry reference values to include age 3-20 years of age. The software provides a comparison of Bone Mineral Density (BMD) measurements obtained by dual energy x-ray absorptiometry to a database of BMD reference values. Patient results for each analysis region can be compared to reference values both graphically and numerically to each category of the age dependent reference Bone Mineral Density (BMD) values. The sex and ethnicity of the patient are generated with a marker placed at the position corresponding to the estimated patient BMD and age. Deviation "scores," are computed, quantifying (in standard deviation units) the difference between the patient's estimated BMD and the mean population standard (Z-score) reference data. In addition, the patient BMD is expressed in percent of the age matched mean in percent of the pediatric mean.

The provided text describes a Pediatric Reference Database for Hologic QDR Series X-Ray Bone Densitometers, a software option that extends the existing reference databases to include ages 3-20 years.

Here's an analysis of the acceptance criteria and the study as per your request:

Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria in the typical sense of a target performance metric (e.g., sensitivity, specificity, accuracy) with thresholds. Instead, the "acceptance criteria" appear to be met by demonstrating substantial equivalence to predicate devices. The study's reported "performance" is implicitly that the device functions as intended by providing a Z-score and comparison to age-matched values for pediatric populations, which is consistent with the function of the predicate devices.

Note: The document focuses on demonstrating substantial equivalence, which is a regulatory pathway. It does not provide a traditional performance study with explicit numerical metrics (e.g., accuracy, precision of the Z-score calculation itself, or clinical outcomes). The "study" here is the collection and presentation of reference data.

Detailed Study Information:

The provided text does not describe a traditional study in the sense of an experiment to test the performance of the device against a cohort. Instead, it describes a reference database that enhances an existing device's functionality. Therefore, many of the requested details about a "study" (like test sets, ground truth establishment for test sets, expert adjudication methods, MRMC studies, standalone performance, and training sets) are not directly applicable or are not explicitly stated in the provided text.

Based on the information given, here's what can be inferred or explicitly stated:

1. Sample size used for the test set and the data provenance:

   • Test Set Sample Size: Not applicable in the context of a "test set" for performance evaluation, as this document is about establishing a reference database. The database itself comprises the reference data. The size of the population from which the reference data was collected is not stated.
   • Data Provenance: The reference data is for "male, white American children." This indicates the data origin is from the United States and is retrospective in the sense that it represents a collected population. It's not a prospective study to test a hypothesis about the device's performance.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not explicitly stated/Not applicable. The "ground truth" here is the reference data itself, representing a healthy pediatric population's BMD values. The process of collecting and validating this reference data (e.g., how the healthy population was defined, how measurements were ensured to be accurate) is not detailed. There's no mention of experts establishing a "ground truth" for individual cases in a test set.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • Not applicable. There is no "test set" in the context of diagnostic performance requiring adjudication of results.

4. 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, an MRMC study was not done. This device is a reference database, not an AI-assisted diagnostic tool.

5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

   • Not applicable, but the device inherently functions "standalone" as a reference. The software provides Z-scores based on the input BMD measurement and patient demographics. It's a computational tool, not an AI algorithm that makes diagnostic interpretations. Its "performance" is its ability to correctly reference the input BMD against its stored database.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

   • Reference Database Values derived from a healthy population. The "ground truth" is the established set of age-, sex-, and ethnicity-matched Bone Mineral Density values for healthy children. The methodology for establishing this healthy population baseline is not detailed in the provided text, but it would typically involve anthropometric measurements, medical history, and DEXA scans from a large, representative cohort of healthy children.

7. The sample size for the training set:

   • Not explicitly stated. The term "training set" is not used, as this is a reference database, not a machine learning model. The size of the population from which the "Pediatric Reference Database" data was derived is not provided.

8. How the ground truth for the training set was established:

   • Not explicitly stated, but implied as a collected reference population. The "ground truth" for this reference database would have been established through a systematic collection of Bone Mineral Density (BMD) measurements from a cohort of healthy male, white American children across the age range of 3-20 years, using validated DEXA scanning protocols. The process would involve defining inclusion/exclusion criteria for "healthy," performing scans, and statistically characterizing the BMD distribution to create age-specific means and standard deviations.

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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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The Discovery Package for QDR X-Ray Bone Densitometers is indicated for the estimation of bone mineral density (BMD), comparison of measured variables obtained from a given QDR scan to a database of reference values, the estimation of fracture risk, vertebral deformity assessment, body composition analysis, and discrimination of bone from prosthetics using the Hologic QDR® X-Ray Bone Densitometers.

The Discovery Package for QDR Bone Densitometers is a software system that integrates all of the previously cleared features of prior versions of the QDR Densitometers in a Microsoft Windows XP operating environment.

The provided text is a 510(k) summary for the "Discovery Package for Hologic QDR X-Ray Bone Densitometers." This document is a regulatory submission for a software system that integrates previously cleared features of bone densitometers into a new operating environment. As such, the study described focuses on software validation rather than a clinical performance study with acceptance criteria in the typical sense of measuring diagnostic accuracy.

Therefore, the information requested in your prompt regarding acceptance criteria, device performance, sample sizes for test and training sets, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth types is not available within this 510(k) summary.

Here's why and what information is available:

• Software System: The device is described as "a software system that integrates all of the previously cleared features of prior versions of the QDR Densitometers in a Microsoft Windows XP operating environment." This suggests that the primary validation would involve ensuring the software correctly performs the functions it's designed for, consistent with its predicate devices.
• Predicate Devices: The submission heavily relies on predicate devices (K992677, K992775, K983028, K963363, K941362, K943505, K913321, K894795, K883280, K001812). This typically means the new device is being shown to be "substantially equivalent" to these existing, legally marketed devices. Demonstrating substantial equivalence for a software update often involves comparing the new software's output to the predicate's output without necessarily needing extensive new clinical trials or diagnostic accuracy studies.
• Lack of Clinical Study Details: The summary does not contain any sections detailing a clinical study, performance metrics like sensitivity/specificity, or a comparison against a human expert baseline. The focus is on the integration of existing functionalities into a new operating system.

Therefore, I cannot populate the table or answer most of the questions as the information is not provided in the given text.

Information that can be extracted or inferred:

• Device Trade Name: Discovery Package for Hologic QDR X-Ray Bone Densitometers
• Intended Use: Estimation of bone mineral density (BMD), comparison of measured variables to a reference database, estimation of fracture risk, vertebral deformity assessment, body composition analysis, and discrimination of bone from prosthetics using Hologic QDR X-Ray Bone Densitometers.
• Device Description: A software system integrating previously cleared features of prior QDR Densitometer versions into a Microsoft Windows XP operating environment.

Without a detailed study report within this 510(k) summary focusing on specific performance metrics, it's impossible to describe acceptance criteria or the study proving the device meets them in the context of diagnostic accuracy.

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