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The system is intended for use by any health practitioner who has the need for any of the below functions:

1. The software may be used to display medical images. The user may adjust the contrast of the images and image process the images with an edge enhancement algorithm. The user can zoom in on a region of an image, enlarging that region on the display screen. Other image processing functions may be added in the future to allow the user to enhance some aspect of an image, such as histogram processing, spatial filtering, frequency filtering.

2. Images from the same series can be stacked to form a three dimensional model. This will allow the use of the system to reformat images in other planes, such as coronal and sagittal planes.

3. Outlining tools are provided to use the system to outline regions of interest. These outlines may be combined to define three dimensional shapes which can be viewed in three dimensional perspective views.

4. The region of interest outlines may be written back to DICOM formatted image files for export to other systems.

5. The system can be used to determine the stereotactic coordinates of a point located on an image when a stereotactic system is employed.

6. The system may be used to provide support for any stereotactic system that consists of fixed rods which can be uniquely located on CT and MRI images.

7. The system may be used to solve for the transformation between two images sets, referred to as image fusion.

8. A region of interested outlined on one image set may be transferred to a fused image set.

9. The system may be used as a front end to other systems that do not provide image fusion. An example would be outlining a region of interest on MRI scans, transferring the outlines to CT scans, and writing the outlines back into DICOM image files. Those files can be available to other systems such as a radiation therapy treatment planning system.

10. The system may be used to print hardcopy images of selected images, reformatted images, and three dimensional perspective views.

11. Image segmentation tools are provided to create three dimensional structures for viewing in three dimensional perspective views.

The intention is also to provide these basic functions as a C++ object library to any party that may wish to use the library to build their own applications. Those customers will be completely responsible for the integration, testing, use of the end product that they produce, and compliance with federal and state regulations.

System 2100 is a software program intended as a medical image display system that performs the following functions:

1. Displays medical images.

2. Can provide image processing and enhancements, such as contrast control, edge enhancement.

3. Can stack images from a series to form a three dimensional model.

4. Provides outlining and segmentation tools.

5. Can display outlined and segmented structures in three dimensional perspective views.

6. Provides generic support for stereotactic frames with the determination of the stereotactic coordinates of a point.

7. Provides three methods for solving for the transformation of coordinates between two image series, referred to as image fusion. The three methods are using stereotactic frames, using common points, and using common surfaces.

8. Can serve as a front end to other systems that do not have image fusion or segmentation methods.

9. Can be used as a means for printing hardcopy of images, reformatted images, and 3d perspective views.

10. Can serve as an object library for university research centers and other vendors (who are then responsible for the use and complying with federal and state regulations).

The provided text is a 510(k) Summary for a General Purpose Radiological Image Display System (System 2100). This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, not for proving individual performance against specific acceptance criteria through a clinical study. As such, the document does not contain the acceptance criteria or a study demonstrating the device meets such criteria.

Therefore, I cannot populate the requested table and sections. The document focuses on listing the functionalities of System 2100 and comparing them to existing medical devices to establish substantial equivalence with predicate devices like Precision View (Elekta Oncology), Xknife (Radionics), and Gamma Plan (Elekta Instruments) for device clearance by the FDA.

The document does not detail:

• Specific acceptance criteria for performance metrics (e.g., accuracy of image fusion, outlining precision, display quality).
• Any clinical or technical study that measures the device's performance against such criteria.
• Sample sizes for test or training sets.
• Data provenance, expert qualifications, or adjudication methods for ground truth.
• Results from multi-reader multi-case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance.
• How ground truth was established for any hypothetical test or training sets.

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used to help prevent deep vein thrombosis and pulmonary embolism in recumbent patients by increasing deep venous blood flow return from the lower extremittles. This is accomplished by intermittent compression of the muscles in the calf and thigh.

upgrade of the Jobst Athrombic Pump System 2000 to the System 2100. It also covers the use of thigh length sleeves with the System 2100. This device is classified as a compressible limb sleeve under 21 CFR 870.5800.

This document is a 510(k) summary for a medical device called the "Jobst Athrombic Pump System 2100." It primarily focuses on demonstrating substantial equivalence to a previously cleared device (System 2000) and another marketed device (Flowtron DVT/thigh sleeve system).

Unfortunately, the provided text does not contain the detailed information necessary to answer most of your questions regarding acceptance criteria and a study proving device performance as you've outlined. This type of 510(k) summary typically focuses on substantial equivalence arguments rather than detailed performance studies with acceptance criteria, sample sizes, ground truth establishment, or expert involvement for AI-driven devices.

Here's a breakdown of what can and cannot be extracted from the provided text based on your request:

1. A table of acceptance criteria and the reported device performance

• Cannot be provided. The document states that the System 2100 "is substantially equivalent" to existing devices and "has proven effective for several years." It does not provide specific acceptance criteria (e.g., minimum effectiveness rates, sensitivity/specificity targets) or report quantified device performance metrics against such criteria.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Cannot be provided. The document does not describe a new performance study with a test set. It relies on the established effectiveness of predicate devices.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Cannot be provided. No new test set or ground truth establishment is described.

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

• Cannot be provided. Not applicable as no new test set is described.

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

• Cannot be provided. This device is a mechanical pump system, not an AI-driven diagnostic or assistive tool. MRMC studies are not relevant here.

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

• Cannot be provided. Not applicable; this is a mechanical device, not an algorithm.

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

• Cannot be provided directly. The document implies that the ground truth for the predicate devices' effectiveness for "preventing deep vein thrombosis and pulmonary embolism" would be clinical outcomes data (i.e., whether DVT/PE actually occurred). However, it doesn't specify how this was measured or established in detail for those predicate devices.

8. The sample size for the training set

• Cannot be provided. This is not an AI/machine learning device, so there is no "training set."

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

• Cannot be provided. Not applicable.

Summary of what the document does provide:

• Device Name: Jobst Athrombic Pump System 2100
• Device Classification: Compressible limb sleeve (21 CFR 870.5800)
• Indications for Use: To help prevent deep vein thrombosis and pulmonary embolism in recumbent patients by increasing deep venous blood flow return from the lower extremities.
• Mode of Operation: Intermittent compression of the muscles in the calf and thigh.
• Predicate Devices:
  • Jobst Athrombic Pump System 2000 (for pump console)
  • Flowtron DVT/thigh sleeve system (for use with thigh length sleeves and overall system comparison)
• Argument for Equivalence: Minor modifications from System 2000, and similar operation/indications to Flowtron DVT/thigh sleeve system, both of which have "proven effective for several years."

For detailed performance data, acceptance criteria, and specific study designs, one would typically need to consult the full 510(k) submission, clinical study reports (if any were required beyond reliance on predicate device performance), or peer-reviewed publications associated with the device or its predicates. A 510(k) summary is designed to be a high-level overview.

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