(42 days)
InstaPACS™InstaRISPACS ™ is a software device (DICOM Gateway Application, Enterprise Server, and Workstation) used for viewing and manipulating digital medical images. Digital images (including mammography and data from various sources (including CT, MR, US, RF units, computed and direct radiographic devices, secondary capture devices, scanners, imaging gateways, or imaging sources) can be displayed, processed, stored and communicated across computer networks using this software. InstaPACS™InstaRISPACS™ can be integrated with an institution's existing Hospital Information System (HIS) or Radiology Information System (RIS) based on the study of the System, providing seamless access to reports for fully-integrated electronic patient records.
Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretation. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 Mpixel resolution and meets other technical specifications reviewed and accepted by FDA.
InstaPACS™/InstaRISPACS™ is a software application used for viewing and manipulating medical images. Digital images and data from various sources (including CT, MR, US, RF units, computed and direct radiographic devices, secondary capture devices, scanners, imaging gateways, or imaging sources) can be displayed, processed, stored and communicated across computer networks using this software. When viewing images, users can perform adjustments of window width and level, annotation, and various image manipulations. In addition, the device can be integrated with an institution's existing Hospital Information System or Radiology Information System (based on the study), providing seamless access to reports for fully-integrated electronic patient records.
InstaPACS™/InstaRISPACS™ allows multiple centers or hospitals to send their images to a central server where Radiologists can view images over Web. It consists of following components:
- . Central Server - runs the Web Server and Image Server and provide study and image data to doctors. The server includes a DICOM Gateway Application which is deployed at remote centers or hospitals. It receives images from modalities over LAN and uploads them to central server
- WorkStation User at the client side can access the study list in the . browser. They can select the patient and download the images.
The provided text is a 510(k) summary for a Picture Archiving Communications System (PACS) software, InstaPACS™/InstaRISPACS™. It focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific clinical studies with performance metrics.
Based on the provided text, here's an analysis of the acceptance criteria and study information:
Acceptance Criteria and Reported Device Performance
| Acceptance Criteria Category | Description | Reported Device Performance/Conclusion |
|---|---|---|
| Substantial Equivalence | The device must demonstrate substantial equivalence to a legally marketed predicate device in terms of intended use, technological characteristics, safety, and effectiveness. | "The new device and predicate devices are substantially equivalent in the areas of technical characteristics, general function, application, and intended use. The new device does not raise any new potential safety risks and is equivalent in performance to the existing legally marketed devices." |
"Nonclinical tests demonstrate that the device is as safe, as effective, and performs as well as the predicate device. Therefore, InstaPACS™/InstaRISPACS™ is substantially equivalent to the predicate device." |
| Functional Verification | The system must perform all intended input and output functions and actions in each operational mode. | "The complete system configuration has been assessed and tested at the factory and has passed all predetermined in-house testing criteria. The Validation Test Plan was designed to evaluate all input functions, output functions, and actions performed by the InstaPACS™InstaRISPACS™ software in each operational mode and followed the process documented in the System Validation Test Plan."
"Validation testing indicated that as required by the risk analysis, designated individuals performed all verification and validation activities and that the results demonstrated that the predetermined acceptance criteria were met." |
| Safety Risks | The device should not introduce new safety risks. | "The new device does not raise any new potential safety risks..." |
| Performance Equivalence | The device should perform equivalently to existing legally marketed devices. | "...is equivalent in performance to the existing legally marketed devices." |
| Non-Diagnostic Role | The software itself is not intended to perform diagnosis, but rather to facilitate interpretation by qualified medical professionals. | "Diagnosis is not performed by the software but by Radiologists, Clinicians and referring Physicians. A physician, providing ample opportunity for competent human intervention interprets images and information being displayed and printed." |
| Mammography Handling (Specific) | Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretation. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 MPixel resolution and meets other technical specifications reviewed and accepted by FDA. | The "Indications for Use" statement explicitly includes these conditions as part of the device's intended use and limitations. The document doesn't provide a specific "performance" against this, but rather states these as conditions of use to meet regulatory requirements, implying the device is designed to operate within these constraints. |
Study Information:
The provided document describes a Nonclinical Testing approach for the InstaPACS™/InstaRISPACS™ system. This is a foundational regulatory submission that demonstrates substantial equivalence to a predicate device, rather than providing detailed clinical study results with performance metrics (like sensitivity, specificity, etc.) in the way one might expect for a diagnostic AI algorithm.
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Sample size used for the test set and the data provenance:
- The document mentions "The complete system configuration has been assessed and tested at the factory and has passed all predetermined in-house testing criteria." It also states, "Validation testing indicated that as required by the risk analysis, designated individuals performed all verification and validation activities and that the results demonstrated that the predetermined acceptance criteria were met."
- However, no specific sample size for a "test set" of medical images or patient cases is provided. The testing appears to be centered on system functionality and software validation, not a clinical performance study with annotated data.
- Data provenance: Not explicitly stated regarding specific images used for any functional validation. The submitter is MEDDIFF Technologies Pvt. Ltd. based in Bangalore, Karnataka - India.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- This information is not provided as the study described is a nonclinical, system validation rather than a clinical performance study. The document states, "Diagnosis is not performed by the software but by Radiologists, Clinicians and referring Physicians. A physician, providing ample opportunity for competent human intervention interprets images and information being displayed and printed." This indicates that human experts are responsible for interpretation, but it doesn't describe their role in establishing a ground truth for testing the software's performance in a diagnostic capacity.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not applicable / not provided. The type of testing performed did not involve a clinical ground truth adjudication process.
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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:
- No, an MRMC comparative effectiveness study was not done. This submission is for a PACS system, which is a tool for viewing and managing images, not an AI-assisted diagnostic algorithm in the sense that would require an MRMC study to show improved reader performance. The device's role is to display and manipulate images for human interpretation, not to provide diagnostic findings or assist with them through AI.
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Not applicable / not done. The device itself is a PACS system; its "performance" is in its ability to display, process, store, and communicate images reliably and without error, facilitating human interpretation. It is not an algorithm that produces a diagnostic output on its own. The document explicitly states: "Diagnosis is not performed by the software but by Radiologists, Clinicians and referring Physicians."
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Not applicable / not specified for clinical performance. The ground truth for the nonclinical system validation would be whether the software performs its specified functions (e.g., displaying an image correctly, performing window/level adjustments, storing data, communicating across networks) as designed, based on engineering requirements and test protocols.
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The sample size for the training set:
- Not applicable / not provided. This device is a PACS software, not an AI algorithm that undergoes a "training" phase with a dataset.
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How the ground truth for the training set was established:
- Not applicable / not provided. As this is not an AI algorithm requiring a training set, the concept of establishing ground truth for training is irrelevant to this submission.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).