Preview Shoulder

by Genesis Software Innovations  · Based in United States → — Revolutionizing orthopedic surgical planning with AI-powered 3D visualization.
Orthopedics

Contact for pricing
Regulatory Status Disclosed

Overview

The Preview Shoulder software, now often referred to as ProVoyance® Shoulder, is an advanced AI-powered 3D surgical planning tool developed by Genesis Software Innovations (GSI) for orthopedic surgeons. It is specifically designed to assist in developing comprehensive pre-operative shoulder plans based on patient CT imaging studies. The software transforms CT imaging into detailed 3D bone reconstructions, providing an unparalleled understanding of the patient’s anatomy. Surgeons can digitally perform surgical planning by visualizing the patient’s shoulder anatomy as a 3D model, allowing for precise placement and optimization of implant size, location, and orientation for both anatomic and reverse shoulder arthroplasty. The platform performs automated computerized segmentation and reconstruction of imaging data, streamlining preparation cycles and improving communication across surgical teams through comprehensive planning documentation. It is intended for adult patients only and should not be used for diagnostic purposes.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Pre-operative shoulder planning based on CT imaging
  • 3D digital representations of patient's shoulder anatomy
  • Digital implant placement (optimize size, location, orientation)
  • Automated computerized segmentation of CT scans
  • Generation of surgical reports and planning documentation
  • Assists in planning reverse and anatomic shoulder arthroplasty
  • Utilizes AI/Machine Learning algorithms
  • Intuitive 3D planning features
  • Functional visualization of surgical cases
  • Enhanced visualization of complex anatomical structures

Use Cases

  • Pre-operative planning for shoulder arthroplasty
  • Optimizing implant selection and placement
  • Reducing OR time and surgical risks
  • Improving patient outcomes and satisfaction
  • Streamlining surgical preparation cycles
  • Enhancing communication across surgical teams

What Physicians Need to Know

DICOM Support & Standards
Supports standard DICOM input from CT (and potentially MRI) systems. The software receives and processes DICOM CT images, allowing users to select scan series from any accessible file source. [3, 4, 15]
PACS Integration Method
Functions as a standalone software application that imports DICOM CT scans. It performs automated computerized segmentation of CT scans, eliminating the need for external intervention to prepare images. [2, 3, 4, 6, 8]
Reading Room Workflow Impact
Designed for pre-operative shoulder arthroplasty planning, enabling surgeons to visualize patient anatomy in 3D, digitally place implants, and optimize size, location, and orientation. This functional visualization aims to enhance surgical clarity, reduce OR time, and improve patient outcomes. The intuitive 3D planning features facilitate quick learning and utilization. [2, 3, 6, 7, 8]
AI Model Architecture (deep learning approach)
Utilizes AI/Machine Learning (ML) algorithms and cutting-edge gaming engine technology for automated segmentation and reconstruction of CT imaging data, transforming it into detailed 3D bone reconstructions for surgical planning. [2, 5, 6, 8, 10]
Processing Speed (per study)
Specific processing speed per study is not explicitly stated. However, the automated segmentation and planning features are designed to improve efficiencies and reduce planning time compared to manual methods. [2, 6, 11, 13]
FDA Clearance Pathway (510k/De Novo)
Received FDA 510(k) clearance (K210556) as the first orthopedic solution under the FDA's new QIH classification for AI-based software solutions. [2, 3, 4, 5, 6, 7, 8, 15]
Supported Modalities (CT/MRI/X-ray/US)
Primarily based on CT imaging studies for pre-operative shoulder planning. The rebranded ProVoyance Shoulder also mentions standard DICOM input from CT or MRI systems and automated anatomical segmentation for CT, MRI, and X-ray. [2, 3, 4, 6, 7, 15]
Sensitivity & Specificity Data
Specific sensitivity and specificity data for Preview Shoulder are not explicitly provided. However, related AI algorithms for shoulder imaging have demonstrated high accuracy (e.g., F1 scores of 95-100%) in classifying imaging features and implant types. [12, 14, 21]
RSNA/ACR Validation
No explicit RSNA/ACR validation for Preview Shoulder was found in the provided information.
Physician Tip

Leverage Preview Shoulder's 3D visualization and automated segmentation to streamline pre-operative planning for shoulder arthroplasty, optimizing implant selection and placement. The intuitive interface and AI-driven insights can enhance surgical confidence and potentially reduce OR time. While the software provides robust planning, always integrate its output with your clinical judgment and patient-specific considerations. The ability to plan without external image preparation can significantly improve workflow efficiency.

Preview Shoulder functions as a standalone application that imports DICOM CT data. For seamless integration into a broader radiology ecosystem, consider how the generated surgical reports and 3D models can be exported and accessed within existing PACS, RIS, or EHR systems. While direct PACS integration methods are not detailed, the DICOM compatibility allows for data exchange. Future enhancements might include more direct worklist integration or automated result pushing to further optimize the reading room workflow.

Details

Category Radiology & Imaging AI, Surgical AI
Pricing Contact for pricing
DeploymentCloud-based, with initial versions available as a standalone application.
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

The Preview Shoulder software (K240172) is a 3D total shoulder arthroplasty (TSA) surgical planning software intended for orthopedic surgeons to develop pre-operative shoulder plans based on patient CT imaging studies. It assists in planning reverse and anatomic shoulder arthroplasty by allowing digital placement of implants and generating surgical reports. This was the first orthopedic solution cleared under the FDA's new QIH classification for AI-based software.

Integrations
EHR Not specified
Specialties Orthopedics

What the Web Says

Preview Shoulder, developed by Genesis Software Innovations, is a 3D pre-operative planning software designed for orthopedic surgeons to plan shoulder arthroplasty procedures using CT imaging data. It allows surgeons to visualize patient anatomy in 3D and digitally place implants to optimize size, location, and orientation. The software received FDA 510(k) clearance in May 2021, making it the first orthopedic solution under the FDA's new QIH classification for AI-based software solutions. It aims to improve surgical efficiency, reduce operating room time, and enhance patient outcomes.

Overall: Positive

Strengths

  • Enables 3D visualization of shoulder anatomy for precise planning.
  • Facilitates digital placement of implants to optimize size, location, and orientation.
  • Aims to improve surgical efficiency and reduce operating room time.
  • Designed to enhance patient outcomes.
  • FDA 510(k) cleared, including under the new QIH classification for AI-based software.
  • Developed by an international team of shoulder reconstruction specialists, AI engineers, and visual gaming programmers.

Limitations

  • No publicly disclosed pricing details; interested parties must contact the vendor.
  • Requires experience in usage and clinical assessment for proper use.
  • Does not provide a diagnosis or surgical recommendation; the surgeon is responsible for implant selection and placement.
  • Limited external validation reported in systematic reviews of AI applications in shoulder surgery.
  • General concern in the field about data bias in AI algorithms leading to potential ethical dilemmas.
  • Clinical testing was not necessary to demonstrate substantial equivalence to predicate devices.

Based on reviews from: HealthAidb, accessdata.fda.gov, Becker's Spine Review, PMC (PubMed Central), ResearchGate

Last updated: 2026-07-20

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Suggest an Edit → | Last Verified: 2026-04-20 | First Added: 2026-04-20
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