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Volume Interactions Pte Ltd's Image Processing System is a medical device for the display and visualization of 3D medical image data derived from tomographic radiology images, excluding mammography images. It is intended to be used by qualified and trained medical professionals, after proper installation.

Volume Interactions Image Processing System reads DICOM 3.0 format medical image data sets (and other formats) and displays 3D image reconstructions of these data sets through various user selectable industry standard rendering methods and algorithms. The clinical users can spatially manipulate, process to highlight structures and volumes of interest, and measure distances and volumes in the 3D image reconstructions. The processed data can be stored either as 3D image data in a proprietary format, or as 2D picture projections of the 3D image data in TIFF image format. The system runs on commercially available PC compatible computers and hardware components with the Microsoft Windows NT and 2000 operating systems.

The system consists of three product modules namely, RadioDexter™, Dextroscope™ and Dextrobeam™. The modules are described as follows:

RadioDexter™ is software that processes tomographic (e.g.: Computer Tomography, Magnetic Resonance Imaging) data and produces stereoscopic 3D renderings for surgery planning and visualization purposes. The software uses various user selectable industry standard rendering methods and algorithms.

DTI (Diffusion Tensor Imaging) is an add-on module to RadioDexter™. This module allows the user to visualize white matter anatomy in the form of fiber tracks. The intended use of this module is to generate and provide a visual reference of white matter fiber tracks in a 3D virtual reality environment during the process of neurosurgery planning using the Dextroscope™ or during a discussion/collaboration using the Dextrobeam™. It is not intended to be used otherwise.

Dextroscope™ is an interactive console and display system that allows the user to interact with two hands with the 3D images generated by the RadioDexter™ software. The Dextroscope™ user works seated, with both forearms positioned on armrests. Wearing stereoscopic glasses, the user looks into a mirror and perceives the virtual image within comfortable reach of both hands for precise hand-eye coordinated manipulation. The hardware uses various industry standard components.

Dextrobeam™ is an interactive console intended for group collaborative discussions with 3D images using a stereoscopic projection system. The Dextrobeam™ system uses the base of the Dextroscope™ as the 3D interaction interface with the virtual objects. The monitor of the Dextroscope™ is replaced by a screen projection system, so instead of looking into the mirror of the Dextroscope™, the user looks at large stereoscopic screen projections while working with the virtual data in reach of his hands. This enables the discussion of 3D data sets with other specialists in stereoscopic 3D. The hardware uses various industry standard components.

The provided submission describes an "Image Processing System" (RadioDexter™, Dextroscope™, and Dextrobeam™) by Volume Interactions Pte Ltd. This device is for the display and visualization of 3D medical image data from tomographic radiology images. The submission pertains to a 510(k) premarket notification, which focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than on presenting results from specific clinical trials or studies designed to meet detailed acceptance criteria.

Therefore, the document does not contain information typically found in a study demonstrating how a device meets acceptance criteria, such as:

• A table of acceptance criteria and reported device performance.
• Sample sizes for test sets, data provenance, number/qualifications of experts, or adjudication methods for test sets.
• Multi-reader multi-case (MRMC) comparative effectiveness study results.
• Standalone (algorithm-only) performance results.
• Details on the type of ground truth used or the sample size and establishment of ground truth for a training set in a way that would be typical for an AI/ML medical device submission proving performance against acceptance criteria.

The submission is for a device categorized as an "Image Processing System" and "Picture Archiving and Communications System (PACS)." The focus here is on ensuring the device's functionality and safety and technological equivalence to a predicate device, as opposed to demonstrating specific diagnostic performance metrics (e.g., sensitivity, specificity, AUC) that are common for AI/ML-driven diagnostic aids.

Based on the provided text, the following can be extracted and inferred:

1. Acceptance Criteria and Reported Device Performance:

   • The submission does not explicitly define acceptance criteria as performance metrics (e.g., sensitivity, specificity, accuracy) would be for an AI/ML diagnostic device.
   • The "acceptance criteria" in this context are implicitly understood as demonstrating substantial equivalence to the predicate device (K063730).
   • The device's reported "performance" is that it "reads DICOM 3.0 format medical image data sets (and other formats) and displays 3D image reconstructions of these data sets through various user selectable industry standard rendering methods and algorithms." It also allows users to "spatially manipulate, process to highlight structures and volumes of interest, and measure distances and volumes."
   • The DTI add-on module's performance is to "visualize white matter anatomy in the form of fiber tracks" and "generate and provide a visual reference of white matter fiber tracks."

   Table of Acceptance Criteria and Reported Device Performance (Inferred from Substantial Equivalence):

   Acceptance Criterion (Inferred from Substantial Equivalence)	Reported Device Performance
   Use same operating principle as predicate device.	Device reads and displays 3D medical image data.
   Have same technological characteristics as predicate device.	Device uses various user-selectable industry standard rendering methods and algorithms; runs on commercially available PC compatible computers with Microsoft Windows NT and 2000.
   Incorporate similar basic software and hardware design.	System comprises RadioDexter™, Dextroscope™, and Dextrobeam™. Hardware uses industry standard components.
   Have same fundamental scientific technology.	(Identical to predicate)
   DTI module safety and effectiveness.	DTI module "has been verified and validated according to Volume Interactions' procedures for product design and development. The validation proves the safety and effectiveness of the module." (No specific performance metrics are given for "safety and effectiveness" in the document).

2. Sample size used for the test set and the data provenance:

   • The document does not detail specific "test sets" or their sample sizes as would be typical for performance evaluation of a new algorithm. The validation mentioned for the DTI module likely involved internal testing procedures rather than a large clinical test set.
   • Data provenance (country of origin, retrospective/prospective) is not mentioned. The device reads DICOM 3.0 format medical image data, implying it processes medical images from various sources, but the origin of data used for any internal verification/validation is not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • This information is not provided. The nature of the device (image processing and visualization) means "ground truth" might refer to the accuracy of 3D reconstructions or measurements, rather than diagnostic labels.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • This information is not provided.

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:

   • This type of study was not mentioned. The device is an image processing and visualization system, not an AI-driven diagnostic aid that would typically undergo such a comparative effectiveness study to measure reader improvement. The DTI module "provides a visual reference" for planning, implying it's a tool for visualization, not a standalone diagnostic interpretation by AI.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • The document implies that the DTI module provides "visual reference" for human professionals ("intended to be used by qualified and trained medical professionals"). It describes functionality ("generate and provide a visual reference") rather than a standalone diagnostic performance metric. Thus, no standalone performance evaluation in the typical sense of a diagnostic algorithm is mentioned.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • This information is not provided in detail. For an image processing system, ground truth might relate to the accuracy of the 3D reconstructions against the original slice data, or the accuracy of measurements compared to known physical dimensions, or the anatomical correctness of fiber tracks as verified by neuroanatomists. The document only states the DTI validation "proves the safety and effectiveness of the module."

8. The sample size for the training set:

   • This information is not provided. The document predates the widespread regulatory focus on AI/ML training data sets. The DTI module would likely have been developed and "trained" or optimized with a set of DTI images, but no details are given.

9. How the ground truth for the training set was established:

   • This information is not provided.

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Volume Interactions Pte Ltd's Image Processing System is a medical device for the display and visualization of 3D medical image data derived from tomographic radiology images, excluding mammography images. It is intended to be used by qualified and trained medical professionals, after proper installation.

Volume Interactions Pte Ltd's Image Processing System is not intended to be used in direct contact with the patient nor is it intended to be connected to equipment that is used in direct contact with the patient.

Image Processing System (Dextroscope™ MK10, Dextrobeam™ MK3 and MK4, RadioDexter™ 1.0)

The provided document is a 510(k) premarket notification letter from the FDA for an "Image Processing System (Dextroscope™ MK10, Dextrobeam™ MK3 and MK4, RadioDexter™ 1.0)". This letter confirms the substantial equivalence of the device to legally marketed predicate devices.

However, the document does not contain any information regarding acceptance criteria, device performance studies, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, or details about training sets.

The letter is primarily a regulatory communication stating that the device can be legally marketed. It describes the device's intended use as "display and visualization of 3D medical image data derived from tomographic radiology images, excluding mammography images" for use by "qualified and trained medical professionals."

Therefore, I cannot fulfill your request to describe the acceptance criteria and the study that proves the device meets them, as this information is not present in the provided text.

Ask a specific question about this device

Volume Interactions Pte Ltd's Image Processing System is a medical device for the display and visualization of 3D medical image data derived from tomographic radiology images. It is intended to be used by qualified and trained medical professionals, after proper installation.

Volume Interactions Pte Ltd's Image Processing System is not intended to be used in direct contact with the patient nor is it intended to be connected to equipment that is used in direct contact with the patient.

Image Processing System

The provided text is a determination letter from the FDA regarding a 510(k) premarket notification for an "Image Processing System." It does not contain information about acceptance criteria, device performance, validation studies, sample sizes, or expert qualifications. Therefore, I cannot provide the requested information based on the given text.

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Volume Interactions Pte Ltd's Image Processing System is a medical device for the display and visualization of 3D medical image data derived from CT and MRI scans. It is intended to be used by qualified and trained medial professionals, after proper installation.

Volume Interactions Pte Ltd's Image Processing System is not intended to be used in direct contact with the patient nor is it intended to be connected to equipment that is used in direct contact with the patient.

Image Processing System (RadioDexter™ 1.0, Dextroscope™ MK10, and Dextrobeam™ MK3)

This FDA 510(k) clearance letter for the "Image Processing System (RadioDexter™ 1.0, Dextroscope™ MK10, and Dextrobeam™ MK3)" does not contain information about acceptance criteria, device performance, or any studies proving the device meets acceptance criteria.

The letter primarily:

• Confirms the device's substantial equivalence to a legally marketed predicate device.
• States the device's classification (Class II, Product Code 90 LLZ).
• Outlines general regulatory requirements for marketing the device.
• Includes an "Indications for Use Statement" that describes the device's purpose: "a medical device for the display and visualization of 3D medical image data derived from CT and MRI scans" and that it's "intended to be used by qualified and trained medical professionals, after proper installation."

Therefore, I cannot fulfill your request for:

1. A table of acceptance criteria and reported device performance.
2. Sample sizes or data provenance for a test set.
3. Details on experts or ground truth for a test set.
4. Adjudication methods.
5. MRMC comparative effectiveness study results.
6. Standalone performance details.
7. Type of ground truth used.
8. Training set sample size.
9. How training set ground truth was established.

This document is a regulatory clearance and does not typically include the detailed technical study information you are asking for. That information would usually be found within the 510(k) submission itself, which is not provided in these pages.

Ask a specific question about this device

Volume Interactions Pte Ltd's Image Processing System is a medical device for the display and visualization of 3D medical image data derived from CT and MRI scans. It is intended to be used by qualified and trained medial professionals, after proper installation.

Volume Interactions Pte Ltd's Image Processing System is not intended to be used in direct contact with the patient nor is it intended to be connected to equipment that is used in direct contact with the patient.

Volume Interactions Image Processing System reads DICOM 3.0 format medical image data sets (and other formats) and displays 3D image reconstructions of these data sets through various user selectable industry standard rendering methods and algorithms. The clinical users can spatially manipulate, process to highlight structures and volumes of interest, and measure distances and volumes in the 3D image reconstructions. The processed data can be stored either as 3D image data in a proprietary format. or as 2D picture projections of the 3D image data in TIFF image format. The system runs on commercially available IBM PC compatible computers and hardware components with the Microsoft Windows NT and 2000 operating systems.

The system consists of three product modules namely, VizDexter™ 2.0, Dextroscope™ and DextroBeam™. The modules are described as follows:

VizDexter™ 2.0 is software that processes tomographic (e.g.: Computer Tomography, Magnetic Resonance Imaging) data and produces stereoscopic 3D renderings for surgery planning and visualization purposes. The software user selectable industry standard rendering methods and algorithms.

Dextroscope™ is an interactive console and display system that allows the user to interact with two hands with the 3D images generated by the VizDexter™ software. The Dextroscope™ user works seated, with both forearms positioned on armrests. Wearing stereoscopic glasses, the user looks into a mirror and perceives the virtual image within comfortable reach of both hands for precise hand-eye coordinated manipulation. The hardware uses various industry standard components.

DextroBeam™ is an interactive console intended for group collaborative discussions with 3D images using a stereoscopic projection system. The DextroBeam™ system uses the base of the Dextroscope™ as the 3D interaction interface with the virtual objects. The monitor of the Dextroscope™ is replaced by a screen projection system, so instead of looking into the mirror of the Dextroscope™, the user looks at large stereoscopic screen projections while working with the virtual data in reach of his hands. This enables the discussion of 3D data sets with other specialists in stereoscopic 3D. The hardware uses various industry standard components.

The provided text is a 510(k) summary for the Volume Interactions Image Processing System (VizDexter™ 2.0, Dextroscope™, and DextroBeam™). This document focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria through a study.

Therefore, the document does not contain the acceptance criteria or a study that proves the device meets specific performance criteria in the way a clinical validation or standalone performance study would. It primarily compares the technological characteristics and intended use of the new device with existing, legally marketed devices.

However, based on the information provided, here's what can be inferred or explicitly stated regarding the device's nature and the lack of specific performance study details:

1. Table of Acceptance Criteria and Reported Device Performance:

The 510(k) summary does not present specific quantitative acceptance criteria or a direct study measuring device performance against such criteria. The "performance" demonstrated is substantial equivalence to predicate devices in functionality and safety. The tables compare features, not quantitative performance metrics.

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

No information is provided regarding a "test set" in the context of a performance study. The submission relies on a comparison of technological characteristics with predicate devices.

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

Not applicable, as no performance study with a test set requiring ground truth establishment is described.

4. Adjudication Method for the Test Set:

Not applicable, as no performance study with a test set requiring adjudication is described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

No MRMC study is mentioned in the document. The comparison is between the technological features of the device and its predicates, not a comparative effectiveness study involving human readers with and without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done:

No standalone performance study for the algorithm itself (VizDexter™ 2.0) is described in terms of specific performance metrics. The document focuses on the system as a whole, including the human interaction components (Dextroscope™, DextroBeam™). The functions described are image processing and visualization, which inherently involve human interpretation.

7. The Type of Ground Truth Used:

Not applicable, as no performance study is detailed that would require a ground truth for evaluation.

8. The Sample Size for the Training Set:

No information is provided regarding a "training set." The device is an "Image Processing System" that utilizes "industry standard rendering methods and algorithms," implying it's not a machine learning model that would require a dedicated training set in the modern sense.

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

Not applicable, as no training set is mentioned.

In summary:

This 510(k) submission is a "substantial equivalence" filing for an image processing and visualization system from 2002. It focuses on demonstrating that the device has similar technological characteristics and intended use as already marketed devices. It does not present clinical performance data, acceptance criteria, or studies of the kind typically expected for AI/ML-driven diagnostic devices today. The "proof" of meeting acceptance criteria is implicitly through the FDA's determination of substantial equivalence based on the comparison of features and the device's classification as a Picture Archiving and Communications System, where the clinician retains responsibility for interpretation.

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