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SMART PCFD software includes AI-powered algorithms and is intended to be used to support orthopedic healthcare professionals in the diagnosis and surgical planning of Progressive Collapsing Foot Deformity (PCFD) in a hospital or clinic environment. The medical image modality intended to be used in the software is weight-bearing CT (WBCT).

SMART PCFD software provides for the user:

• Visualization report of the three-dimensional (3D) mathematical models and measurements of the anatomical structures of foot and ankle and three-dimensional models of orthopedic fixation devices,
• Measurement templates containing radiographic measures of foot and ankle, and
• Surgical planning application for visualization of foot and ankle anatomical three-dimensional structures, radiographic measures, and surgical instrument parameters supporting the following common flatfoot procedures: Medial Displacement Calcaneal Osteotomy (MDCO), Lateral Column Lengthening (LCL), and Cotton Osteotomy (CO).

The visualization report containing the measurements is intended to be used to support orthopedic healthcare professionals in the diagnosis of PCFD. The surgical planning application contains the visualizations of the three-dimensional structural models, orthopedic fixation device models and surgical instrument parameters combined with the measurements is intended to be used to support orthopedic healthcare professionals in surgical planning of PCFD.

The SMART PCFD software is intended to be used in reviewing and digitally processing computed tomography images for the purposes of interpretation by a specialized medical practitioner. The device segments the medical images and creates a 3D model of the bones of the foot and ankle. Measurements, including anatomical axes, are provided to the user and the device allows for presurgical planning.

The device includes the same machine learning derived outputs as the primary predicate SMART Bun-Yo-Matic CT (K240642) device and no new validations were conducted.

Details on the previously performed validation are summarized below. The testing for 82 CT image series presented 100% correctly identified bones of foot and ankle. The existence of metal was identified correctly for 98.8% of the images (specificity 98%, sensitivity 100%).

Here's a breakdown of the acceptance criteria and study information for the SMART PCFD device, as extracted from the provided FDA 510(k) clearance letter:

1. Table of Acceptance Criteria and Reported Device Performance

The clearance letter does not explicitly state acceptance criteria in a formal table format with specific thresholds for each metric. Instead, it describes performance results. Based on the provided text, the acceptance criteria can be inferred from the reported performance, implying that these levels of performance were deemed acceptable.

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

• Test Set Sample Size: 82 CT image studies.
• Data Provenance:
  • Country of Origin: Various sites across USA and Europe, with a minimum of 50% of the images originating from the USA.
  • Retrospective/Prospective: Not explicitly stated, but the description of collected studies from "patients with different ages and racial groups" and "clinical subgroups ranging from control/normal feet to pre-/post-operative clinical conditions" suggests retrospective data collection.
  • Patient Demographics: Different ages and racial groups, minimum of 35% male/female within each dataset, mean age approximately 47 years (SD 15 years), and representatives from White, (Non-)Hispanic, African American, and Native racial groups.
  • Clinical Conditions: Balanced in terms of subjects with different foot alignment, and subjects from clinical subgroups ranging from control/normal feet (44% with test data) to pre-/post-operative clinical conditions such as Hallux Valgus, Progressive Collapsing Foot Deformity, fractures, or with metal implants (40% of the test data).

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

• Number of Experts: Three (3).
• Qualifications of Experts: U.S. Orthopedic surgeons. Specific years of experience are not mentioned.

4. Adjudication Method for the Test Set

• Adjudication Method: Majority vote. "Based on the majority vote of three, two same responses were required to establish a ground truth on each of the DICOM series." This indicates a "2-out-of-3" or "2+1" adjudication where two experts must agree to establish ground truth.

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

• Was an MRMC study done? No. The document describes standalone algorithm performance, and comparison to human readers with or without AI assistance is not mentioned.

6. Standalone Performance Study

• Was a standalone study done? Yes. The "Details on the previously performed validation are summarized below" section describes testing conducted on the algorithm itself, independently of human interaction. The reported device performance for bone and metal identification comes directly from this standalone evaluation.

7. Type of Ground Truth Used

• Type of Ground Truth: Expert consensus. The ground truths for bone and metal identification were "independently established by three (3) U.S. Orthopedic surgeons" who "reviewed each of the DICOM series through axial/sagittal/coronal views and/or 3D reconstruction and marked on a spreadsheet the presence of a bone and metal."

8. Sample Size for the Training Set

• AI algorithm for bone identification: 145 CT image studies.
• Metal identification: 130 CT image studies.

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

The document states that the "AI algorithm for bone identification was developed using 145 CT image studies and metal identification was developed using 130 CT image studies." It then goes on to describe how ground truths for the test set were established by three U.S. Orthopedic surgeons. However, the document does not explicitly describe how the ground truth for the training set was established. It's common practice for training data to also be annotated by experts, but the details of that process are not provided in this specific excerpt.

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