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AutoDensity is a post-processing software intended to estimate spine Bone Mineral Density (BMD) from EOSedge dual energy images for orthopedic pre-surgical assessment applications. It is an opportunistic tool that enables immediate assessment of bone density from EOSedge images acquired for other purposes.

AutoDensity is not intended to replace DXA screening. Suspected low BMD should be confirmed by a DXA exam.

Clinical judgment and experience are required to properly use the software.

Based on EOSedge™ system's images acquired with the dual energy protocols cleared in K233920, AutoDensity software provides an estimate of the Bone Mineral Density (BMD) for L1-L4 in EOSedge AP radiographs of the spine. These values are used to aid in BMD estimation in orthopedic surgical planning workflows to help inform patient assessment and surgical decisions. AutoDensity is opportunistic in nature and provides BMD information with equivalent radiation dose compared to the EOSedge images concurrently acquired and used for general radiographic exams. AutoDensity is not intended to replace DXA screening.

Here's a breakdown of the acceptance criteria and the study details for the AutoDensity device, based on the provided FDA 510(k) clearance letter:

1. Acceptance Criteria and Reported Device Performance

Device Name: AutoDensity
Intended Use: Post-processing software to estimate spine Bone Mineral Density (BMD) from EOSedge dual energy images for orthopedic pre-surgical assessment applications.

2. Sample Sizes and Data Provenance

Test Set (for ROI Performance Evaluation):

• Sample Size: 129 patients.
• Data Provenance: All cases obtained from EOSedge systems (K233920). The document does not specify the country of origin but mentions a clinical study with 65% US subjects and 35% French subjects for clinical performance testing, which might suggest a similar distribution for the test set, though it's not explicitly stated for the ROI test set. The data was retrospective as it was "obtained from EOSedge systems."

3. Number of Experts and Qualifications for Ground Truth

For ROI Performance Evaluation Test Set:

• Number of Experts: At least 3 (implied by "3 truther majority voting principle") plus one senior US board certified expert radiologist who acted as the gold standard adjudicator.
• Qualifications:
  • Two trained technologists (for initial ROI and level identification).
  • One senior US board-certified expert radiologist (for supervision, review, selection of most accurate set, and final adjustments).

4. Adjudication Method for the Test Set

For ROI Performance Evaluation Test Set:

• Adjudication Method: A "3 truther majority voting principle" was used, with input from a senior US board-certified expert radiologist (acting as the "gold standard"). The radiologist reviewed results, selected the more accurate set, and made necessary adjustments. This combines elements of majority voting with expert adjudication.

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

• Was an MRMC study done? No, the provided document does not mention an MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The performance data presented focuses on the standalone performance of the AI algorithm and its agreement/precision with a reference device or clinical measurements.

6. Standalone Performance Study (Algorithm Only)

• Was a standalone study done? Yes. The "Region of Interest (ROI) Performance Evaluation" section explicitly states: "To assess the standalone performance of the AI algorithm of AutoDensity, the test was performed with..." This section details the evaluation of the algorithm's predictions against ground truth for vertebral level identification and spine ROI accuracy.

7. Type of Ground Truth Used

For ROI Performance Evaluation Test Set:

• Type of Ground Truth: Expert consensus with adjudication. Ground truths for ROIs and level identification were established by two trained technologists under the supervision of a senior US board-certified radiologist. The radiologist made the final informed decision, often described as a "gold standard."

8. Sample Size for the Training Set

• Training Set Sample Size: The AI algorithm was trained using 4,679 3D reconstructions and 9,358 corresponding EOS (K152788) or EOSedge (K233920) biplanar 2D X-ray images.

9. How Ground Truth for the Training Set was Established

• The document implies that the training data was "selected to only keep relevant images with the fields of view of interest." However, it does not explicitly detail how the ground truth for the training set was established (e.g., whether it used expert annotations, a similar adjudication process, or other methods). It primarily focuses on the test set ground truth establishment.

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