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InstaRISPACS / InstaZFP / InstaMobi is a software device (Enterprise Server, Diagnostic Workstation, Physician Zerofoot print Viewer and a Mobile Viewer) used for viewing and manipulating 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 sources) can be displayed, processed, stored and communicated across computer networks using this software. InstaPACS modules 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 cleared monitor that offers at least 5 Megapixel resolution and meets other technical specifications reviewed and accepted by FDA.

InstaRISPACS / InstaZFP / InstaMobi is not intended for diagnostic image review or diagnostic use on mobile devices.

InstaRISPACS / InstaZFP / InstaMobi, 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.

• . InstaRISPACS, is a server-based application for use by Physicians, which comes with the Diagnostic Viewer.
• InstaZFP, is a Zero Foot print viewer for use by Physicians to display images after ● fetching them from the InstaRISPACS server.
• . InstaMobi, is a Mobile application (for iOS & Android), for use by Physicians to fetch images from InstaRISPACS and display them on the mobile device.

In addition, InstaRISPACS, can be integrated with an institution's existing Hospital Information System or Radiology Information System (based on the study of the System), providing seamless access to reports for fully-integrated electronic patient records.

The provided text describes the Meddiff InstaRISPACS / InstaZFP / InstaMobi V5.0 system, a software application for viewing and manipulating medical images. However, it does not contain information about a study that specifically proves the device meets quantifiable acceptance criteria related to its performance metrics (e.g., sensitivity, specificity, accuracy) for image interpretation or against a clinical gold standard.

The document does describe non-clinical performance testing for compliance with standards and the device's functional requirements.

Here's an analysis based on the available information:

Acceptance Criteria and Reported Device Performance

The document clearly states the following under "VII. PERFORMANCE DATA":
"The test results in this 510(k), demonstrate that InstaRISPACS/ InstaZFP/InstaMobi:

• complies with the aforementioned international and FDA-recognized consensus standards and
• FDA guidance document, and
• Meets the acceptance criteria and is adequate for its intended use."

However, the specific "acceptance criteria" for quantifiable device performance (e.g., image quality metrics, processing speed thresholds, diagnostic accuracy) are not explicitly detailed or quantified in the provided text. The "reported device performance" is described as compliance with standards and meeting functional requirements, rather than clinical performance metrics.

Based on the provided text, a table of quantifiable acceptance criteria and device performance cannot be generated. The document focuses on showing substantial equivalence based on technical characteristics and compliance with regulatory standards, rather than a clinical performance study.

Study Details (Based on available information)

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

• Acceptance Criteria: Not explicitly quantifiable clinical or diagnostic performance metrics described. The acceptance criteria mentioned relate to compliance with regulatory standards and functional requirements.
• Reported Device Performance: "complies with the aforementioned international and FDA-recognized consensus standards and FDA guidance document, and Meets the acceptance criteria and is adequate for its intended use." No specific performance numbers (e.g., accuracy, sensitivity, specificity) are reported.

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

• Sample Size: Not specified.
• Data Provenance: Not specified. This was a non-clinical study focused on technical compliance and functional verification, not clinical data evaluation.

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

• Not applicable. This was a non-clinical study; no ground truth was established by experts for a test set of clinical images.

4. Adjudication method for the test set:

• Not applicable. This was a non-clinical study; no image interpretation or adjudication occurred.

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:

• No. The document explicitly states: "InstaRISPACS/ InstaZFP/InstaMobi does not require clinical studies to demonstrate substantial equivalence to the predicate device." Later, it also states: "Diagnosis is not performed by the software but by Radiologists, Clinicians and or referring Physicians. A physician, providing ample opportunity for competent human intervention interprets images and information being displayed and printed." This indicates the device is an image viewing and manipulation system, not an AI-powered diagnostic aid meant to directly improve human reader performance.

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

• No. The device is an image viewing and manipulation system, not an algorithm performing standalone diagnostic tasks. Its performance is assessed in terms of its functionality and compliance with standards.

7. The type of ground truth used:

• Not applicable. As a non-clinical study focusing on functional compliance and technical characteristics, there was no clinical "ground truth" (like pathology or outcomes data) involved in a diagnostic performance evaluation.

8. The sample size for the training set:

• Not applicable. This device is a PACS/RIS software for image management and viewing, not a machine learning model that requires a training set.

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

• Not applicable, as it's not a machine learning model requiring a training set.

Summary of the "Study" (Non-Clinical Performance Testing):

The "study" described in the document is limited to non-clinical performance testing to demonstrate compliance with international and FDA-recognized consensus standards (ISO 14971, IEC 62304, NEMA-PS 3.1 - PS 3.20 DICOM) and FDA guidance documents. It also involved Meddiff's internal verification and validation processes to address intended use, technological characteristics claims, requirement specifications, and risk management results.

The comparison table provided (pages 2-3) primarily highlights technological characteristics and feature parity/differences with predicate and reference devices, rather than a clinical performance study involving patient data. For instance, for "PET-CT fusion viewing" and "Embedded & basic Volume Rendering," it states the subject device was "tested and compared to Reference device #1, (K101342)" and "Data indicated that the subject device was found to be similar to the reference device." This indicates functional equivalence rather than a clinical performance claim.

Conclusion stated by the submitter: Based on these non-clinical tests, the subject device is considered "substantially equivalent" to the predicate device in terms of safety and effectiveness, and no clinical studies were deemed necessary.

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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

"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.

1. 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.

2. 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.

3. 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.

4. 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.

5. 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."

6. 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.

7. 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.

8. 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.

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