D2P vs OrthoNext Platform System

Similar category, different focus. These tools serve overlapping but distinct needs. Comparability 65/100 Comparability is an AI-graded 0–100 score of how directly these two tools compete — higher means a more apples-to-apples comparison.

D2P

by 3D Systems

OrthoNext Platform System

by Orthofix Srl

AI Verdict

D2P is a versatile tool for creating patient-specific 3D anatomical models from 2D imaging for advanced visualization, surgical planning, and 3D printing across multiple specialties. In contrast, the OrthoNext Platform System is a specialized cloud-based application focused on preoperative and postoperative orthopedic surgical planning, specifically utilizing Orthofix product templates and AI for marker identification. While both contribute to surgical planning in orthopedics, D2P emphasizes 3D model generation and physical model creation, whereas OrthoNext focuses on template-based planning with specific implant systems.

Choose D2P if…

Choose D2P if your workflow demands the creation of highly detailed, patient-specific 3D anatomical models from 2D medical images for advanced visualization, complex surgical planning, or direct 3D printing. This tool is ideal when extensive 3D model editing, deep learning-driven segmentation, and integration with a comprehensive 3D printing ecosystem are critical for your clinical applications.

View D2P →

Choose OrthoNext Platform System if…

Choose OrthoNext Platform System if your focus is on precise preoperative and postoperative planning for orthopedic surgeries, particularly when utilizing Orthofix product templates. This web-based, AI-powered solution is best suited for orthopedic surgeons requiring accurate implant templating, measurements, and osteotomy simulations directly on radiological images.

View OrthoNext Platform System →

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Quick Comparison

Feature	D2P	OrthoNext Platform System
Pricing	Contact for pricing	Contact for pricing
Deployment	Stand-alone modular software package (workstation-based)	Cloud
FDA Status	Yes AI-estimated	Yes AI-estimated

Head-to-Head

AI-generated assessment across six dimensions based on each tool's documented features and compliance posture. Grounded in public data — not a substitute for hands-on evaluation.

Usability

OrthoNext Platform System

Tool B (OrthoNext) is a web-based application with a guided planning process and simple user interface, offering easier access and a lower barrier to entry for general users. While Tool A (D2P) is described as very easy to use for its complex 3D modeling and VR features, its workstation-based deployment may imply more setup and specialized hardware requirements for some users.

Clinical Value

D2P

Tool A (D2P) provides advanced visualization, deep learning-driven segmentation, and the ability to create patient-specific 3D printed anatomical models for diagnostic and pre-surgical planning across multiple specialties. This offers a more comprehensive and tangible output for complex cases, enhancing precision and understanding.

Pricing & Value

Tie

Both Tool A (D2P) and Tool B (OrthoNext) state that pricing is not publicly available and requires direct contact with their respective sales teams. Without transparent pricing information for either product, a direct comparison of their value propositions is not possible.

Enterprise Readiness

OrthoNext Platform System

Tool B (OrthoNext) is a cloud-based web application, which inherently offers advantages for enterprise scalability, remote accessibility, and potentially reduced IT overhead for deployment and maintenance across multiple users and locations. Tool A (D2P) is a workstation-based software, which might require more individual setup and management within a large enterprise environment.

Innovation

D2P

Tool A (D2P) leverages deep learning for automatic segmentation and offers immersive Virtual Reality (VR) visualization for non-diagnostic use, providing advanced methods for understanding complex anatomy and surgical planning. While Tool B (OrthoNext) uses AI for automatic marker identification, Tool A's combination of deep learning and VR for 3D model creation and interaction represents a broader innovative approach.

Support & Docs

OrthoNext Platform System

Tool B (OrthoNext) explicitly mentions and provides a 'Software User's Guide' and 'Support and Contact Information' within its documentation, indicating a structured approach to user assistance. Information regarding specific support and documentation for Tool A (D2P) was not readily available in the provided facts or search results.

Feature-by-Feature

Detail beyond the Quick Comparison summary. For pricing, deployment, BAA, FDA, and HIPAA see the Overview tab.

Feature	D2P	OrthoNext Platform System
Name	D2P	OrthoNext Platform System
Company	3D Systems	Orthofix Srl
Primary Purpose	Converts 2D medical imaging data (DICOM) into accurate 3D digital anatomical models for advanced visualization, surgical planning, and 3D printing of patient-specific models.	AI-powered web application for precise preoperative and postoperative orthopedic surgical planning, utilizing radiological images and Orthofix product templates.
Specialties	Neurosurgery, Orthopedics, Radiology	Orthopedics
Key AI/Automation Feature	Automatic and manual segmentation tools (deep learning driven)	AI-Powered Automatic Marker Identification on X-rays (version 2.1)
Input Data Type	2D medical imaging data (DICOM), Supports various imaging modalities (CT, MR, CBCT)	Radiological images
Output/Planning Capabilities	3D digital anatomical models, surgical planning, 3D printing of patient-specific models, Export of 3D digital models in various file formats.	Preoperative and postoperative orthopedic surgery planning, Simulation of osteotomy plan positioning.
Visualization/Templating	Virtual Reality (VR) visualization for non-diagnostic use, High-quality volume rendering and mesh coloring.	Overlaying Orthofix product templates on radiological images, Precise template positioning, Accurate calibration and templating.

Videos

Demos, reviews, and walkthroughs featuring D2P and OrthoNext Platform System.

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Frequently Asked Questions

How do these tools integrate with existing PACS and EHR systems to streamline surgical planning workflows, and what data exchange capabilities do they offer?

D2P is a standalone modular software package that converts DICOM data into 3D models and is intended for use as a software interface for transferring imaging information from a medical scanner to an output file, and for pre-operative surgical planning. OrthoNext is a web-based application for preoperative orthopedic surgical planning that utilizes radiological images and Orthofix product templates, and while it uses radiological images, its integration depth with broader PACS/EHR systems for seamless data flow beyond image import and template overlay is not explicitly detailed.

What is the reported accuracy and precision of the anatomical models or templating provided by each tool, especially considering their use of AI and deep learning?

D2P utilizes deep learning for automatic segmentation tools to create accurate 3D digital anatomical models, which are validated for diagnostic use when printed with compatible 3D Systems printers and materials. OrthoNext emphasizes accurate calibration, measurements, and templating, and its version 2.1 includes AI-Powered Automatic Marker Identification on X-rays to enhance precision in orthopedic surgical planning.

Beyond the listed specialties, what specific clinical scenarios or surgical complexities does each tool excel at addressing, particularly regarding patient-specific anatomy versus implant templating?

D2P excels in advanced visualization and 3D model creation for complex anatomies, supporting surgical planning in neurosurgery, orthopedics, and radiology, and enabling the creation of patient-specific models for difficult-to-visualize anatomy. OrthoNext is specifically designed for preoperative and postoperative orthopedic surgical planning, particularly for overlaying Orthofix product templates and simulating osteotomy plan positioning, making it highly specialized for implant-focused orthopedic procedures.

What is the typical learning curve for a new physician user to become proficient with each tool, considering D2P's VR capabilities and OrthoNext's web-based interface?

D2P offers advanced features like 3D model editing and VR visualization, which, while powerful for enhancing 3D understanding, may involve a learning curve for mastering segmentation and editing tools. OrthoNext, as a web-based application with a guided planning process and simple user interface, aims for ease of use, potentially suggesting a quicker adoption for orthopedic templating tasks.

What audit-trail capabilities does each system offer to track changes and user interactions with patient data and surgical plans, and what additional security measures are in place beyond standard data encryption?

Neither D2P nor OrthoNext explicitly detail specific audit-trail features or advanced security measures beyond general statements about handling protected health information within a regulated medical device context. For D2P, its standalone nature and integration with 3D Systems printers imply a controlled environment for data processing and model creation. OrthoNext, being a web-based application, would typically rely on robust cloud security practices, but specific audit logs for user actions are not mentioned in the provided facts.

For a multi-site healthcare system, what are the key considerations for deploying and managing each tool across different locations, particularly regarding data access and user consistency?

D2P, as a workstation-based modular software, would require individual installations and management at each site, with considerations for DICOM data transfer and local processing power. OrthoNext, being a cloud-based web application, inherently supports multi-site access and user consistency through a centralized platform, simplifying deployment and management across geographically dispersed locations.

Can we access customer references or case studies demonstrating successful implementations in similar clinical environments, and what level of technical and clinical support is provided post-implementation?

3D Systems, the company behind D2P, provides customer stories and resources on its website, including those related to healthcare applications, which may offer insights into successful implementations. For OrthoNext, while the provided information doesn't explicitly mention customer references or detailed support structures, Orthofix Srl offers a user guide and demo, suggesting basic support materials are available.