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Preview Shoulder

Genesis Software Innovations • Radiology • 04/04/2024

510(k)IEC 62304 Class B
FDA Summary PDF

Device Purpose

Preview Shoulder is a pre-operative planning software that assists orthopedic surgeons in developing shoulder arthroplasty strategies by utilizing patient CT scans to create interactive 3D anatomical models for virtual implant placement. Its methodology involves DICOM image importation, sophisticated 3D reconstruction with mesh refinement, calculation of humeral features, and digital templating of scapula and humerus implants, with its accuracy and functionality confirmed through non-clinical validation.

Summary

Preview Shoulder is a standalone software application designed as a tool for orthopedic surgeons to develop pre-operative plans for total shoulder arthroplasty, encompassing both reverse and anatomic procedures, based on patient CT imaging studies. The software processes DICOM CT scans to create 3D digital representations of the patient's shoulder anatomy, allowing surgeons to virtually place 3D models of various implants, including both scapula and humerus components. It facilitates digital surgical planning by showing this representation and enabling implant placement within the patient's anatomy. The system is intended for adult patients only and requires experience and clinical assessment for proper use; it explicitly does not provide diagnostic information or surgical recommendations, with the surgeon retaining full responsibility for all clinical decisions and implant selection. The software operates on a user's personal computer (Windows or MacOS) and imports CT scans from local file sources, without direct communication to PACS systems. Key technological advancements include post-processing algorithms to refine 3D mesh quality and algorithms to calculate humerus-side features, aiding in implant selection and placement. Preview Shoulder allows the user to generate a report detailing the output of the planning activity. Non-clinical software verification and validation testing demonstrated the device's safety and effectiveness, ensuring the accurate and repeatable production of 3D reconstructed bones and surgical coordinates. The measurement capabilities of the software were validated against the Osirix MD benchmark tool using anonymized patient shoulder CT images, and all user features were validated by surgeons.

AI Regulatory Concerns

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Keywords

Preview ShoulderPre-operative planningShoulder arthroplastyCT imagingDICOM3D modelingImplant placementOrthopedic surgerySurgical simulationSoftware validation

Device Metadata

Submission Number
K240172
Company
Genesis Software Innovations
Panel
Radiology
Product Code
N/A
Data Type
Images
Clinical Function
Intervention
AI Function
Analysis
AI Subclass
quantification/feature localization

Relevant Clinical Questions

  • Q1. What specific algorithms are employed for the 3D mesh refinement and humerus-side feature calculation, and how has their accuracy been validated across diverse patient anatomies and varying CT image qualities?; Does the Preview Shoulder software offer any quantitative outputs or simulations, such as predicted range of motion or potential impingement analysis, based on the planned implant positioning?; How does the software handle complex anatomical variations or severe pathological conditions that might affect the accuracy of 3D reconstruction and subsequent implant planning?; What is the typical time investment required for a surgeon to complete a pre-operative plan using Preview Shoulder, from CT import to final report generation?; Are there plans to integrate the output of Preview Shoulder with intra-operative navigation systems or to facilitate the creation of patient-specific surgical guides?

Risk Classification

ESL Analysis
FDA Device ClassII

FDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Post-§524B but no clear network capability detected

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Cybersecurity Evidence

Powered by SBOMator™

Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.

Cyber Score25/100
SBOM Evidence⚠ Not in summary - likely in full submission per §524B
Cyber Risk Assessment✓ Detected in Summary
Postmarket Plan⚠ Not in summary - likely in full submission per §524B
§524B ApplicableYes

Supply Chain BOM Evidence

Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.

SBOMSoftware Bill of Materials
- Not detected
ML-BOMMachine Learning Bill of Materials(algorithm)
✓ Detected
SaaSBOMSoftware-as-a-Service Bill of Materials
- Not detected
HBOMHardware Bill of Materials
- Not detected
CBOMCryptography Bill of Materials
- Not detected
VDR/VEXVulnerability Disclosure Report / Vulnerability Exploitability eXchange
- Not detected
OBOMOperations Bill of Materials
- Not detected

Analysis:

• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.

• Evidence of ML-BOM detected in AI-generated device summary.

• SBOM not mentioned in AI-generated device summary. Under §524B (effective Oct 2023), cyber devices must provide a SBOM.

• Postmarket cybersecurity monitoring plan not clearly documented in AI-generated device summary.

• Not detected in AI-generated device summary: SBOM, SaaSBOM, HBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.

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Preview Shoulder - Genesis Software Innovations | ESL FDA AI Device Intelligence