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The Automated Bone Mineral Density Software Module (ABMD) is a post-processing AI-powered software intended to measure bone mineral density (BMD) from existing CT scans by averaging Hounsfield units in the trabecular region of vertebral bones. ABMD is not intended to replace DXA or any other tests dedicated to BMD measurement. It is solely designed for measuring BMD in existing CT scans ordered for reasons other than BMD measurement. In summary, ABMD is an opportunistic AI-powered tool that enables: (1) retrospective assessment of bone density from CT scans acquired for other purposes, (2) assessment of bone density in conjunction with another medically appropriate procedure involving CT scans, and (3) assessment of bone density without a phantom as an independent measurement procedure.

The Automated Bone Mineral Density (ABMD) Software is a software module that estimates bone mineral density in the vertebral bones by averaging Hounsfield Units (HU) in the trabecular area. ABMD Software is a post-processing software that works on existing CT scans. ABMD Software measurements are to be reviewed by radiologists and should be used by healthcare providers in conjunction with clinical evaluation.

Here's a breakdown of the acceptance criteria and study information for the ABMD Software based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Study 1 (Reference Dataset):
  • Sample Size: 993 cases.
  • Data Provenance: Not explicitly stated, but indicated as a "cohort of asymptomatic cases who underwent CT scans." The geographical origin (country) is not specified. It is retrospective as it uses "existing CT scans."
• Study 2:
  • Sample Size: 172 asymptomatic cases.
  • Data Provenance: Not explicitly stated, but indicated as cases who underwent "whole-body DXA scans as well as CT scans." The geographical origin (country) is not specified. It is retrospective as it uses "existing CT scans."

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

• Number of Experts: Not explicitly stated in terms of a specific count. However, the ground truth was established by "trained operators."
• Qualifications of Experts: Described as "trained operators" for both manual QCT measurements and DXA scan derivations. Specific qualifications like "radiologist with 10 years of experience" are not provided.

4. Adjudication Method for the Test Set

• The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for the test set's ground truth. It states that "QCT BMD, T-score, and Z-score values derived from manual measurement by trained operators" were used for ground truthing. This implies a single measurement by a "trained operator" formed the ground truth for QCT, and DXA values were also used, presumably from standard reports.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly described in the provided text. The studies focused on comparing the ABMD software to manual QCT measurements and DXA measurements, not on how human readers perform with or without AI assistance.

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

• Yes, standalone performance was assessed. The studies directly compare the ABMD Software's measurements (which are algorithm-driven) to established ground truth methods (manual QCT and DXA). The text states, "The ABMD Software strongly correlated with manual QCT-based BMD measurement" and "The ABMD Software also correlated with DXA BMD measurement." This indicates the algorithm's performance independent of human-in-the-loop interaction for the measurement itself, though the results are intended for review by radiologists.

7. The Type of Ground Truth Used

• Study 1:
  • Type: Expert consensus (implicitly, from "trained operators") for QCT BMD, T-score, and Z-score values derived from manual measurements.
• Study 2:
  • Type: Combined expert consensus (implicitly, from "trained operators") for QCT BMD, T-score, and Z-score values derived from manual measurements, and clinical outcomes/measurements from DXA scans (DXA T-score and Z-score values).

8. The Sample Size for the Training Set

• The document does not explicitly state the sample size for the training set. It mentions the ABMD Software uses "an AI trained model," but the details of the training data are not provided in this summary.

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

• The document does not explicitly state how the ground truth for the training set was established. It only mentions the ground truthing process for the test/reference datasets.

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