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Nucleus.io is a software-based image management solution and PACS to be used by radiologists, other medical personnel and patients. Nucleus.io is comprised of software modules that provide image receipt, diagnostic viewing, storage, distribution, enhancement, sharing, manipulation, and networking of medical 2D/3D images at distributed locations.

Nucleus.io is a PACS which, when integrated with standard off-the-shelf hardware/software, acts similarly to its predicate device and other industry standard PACS systems. The Nucleus System has the following primary features and functions: Zero-footprint HTML5 medical image acceptance (upload) and transfer of medical images between facilities. Easy, real-time access to images for all participants in the healthcare process, including radiologists, imaging technicians, workflow coordinators, physicians, nurses, and other patient care facilitators. High-speed, zero-footprint diagnostic review of medical images using industry-standard tools for manipulation, annotation, measurement, and comparison. Simultaneous information review with multiple parties, including radiologists and coordinators. Sharing of medical images between healthcare providers, facilities, and patients. Encrypted transmission of medical images through secured wired and wireless networks. Encrypted storage of medical images. Organization and matching of multiple medical images based on patient name, medical record number, facility, etc. Quality assurance review of studies by coordinators and preparation of information for study interpretation by radiologists. Notification of care coordinators that studies need to be transferred to client systems. HIPAA-compliant data management and LDAP security integration with external systems Management of users, roles, permissions, and organization accounts Configuration of image acceptance (upload) and transfer settings. The Nucleus.io System consists of the following primary components: Nucleus.io Image Exchange (iX)™ - Exam acceptance (upload), transfer, sharing, and management. Nucleus.io Viewer (dX)™ - Zero-footprint streaming viewer suitable for diagnostic image review of all modalities. Nucleus.io Infinite Store (iS)™ (formerly Image Store) - Image storage and archiving. Nucleus.io PACS™ - Radiology workflow and worklist features. Nucleus PaaS - Vendor-neutral Class I platform that can be incorporated as a component of other devices.

The document describes the Nucleus.io, a Picture Archiving & Communications System (PACS), and its equivalency to a predicate device, Visage PACS/CS (K082269), particularly concerning the diagnosis of mammography.

Here's an analysis of the provided information regarding acceptance criteria and the study that proves the device meets them:

1. Table of acceptance criteria and the reported device performance:

The document does not provide a formal table of quantitative acceptance criteria and reported device performance metrics in the way one might expect for an AI/ML diagnostic algorithm (e.g., sensitivity, specificity, AUC). Instead, the acceptance criteria are implicitly defined by the goal of demonstrating substantial equivalence to the predicate device, particularly for mammography diagnosis. The reported performance is framed as the availability of features that are comparable to those in the predicate device.

Implicit Acceptance Criteria (based on comparison to predicate device):

• Availability of core PACS functionalities (image receipt, diagnostic viewing, storage, distribution, enhancement, sharing, manipulation, networking).
• Compatibility with various modalities (CT, MR, US, CR, DX, NM, PET, XA).
• Ability to handle uncompressed and non-lossy compressed images for primary image diagnosis in mammography.
• Support for the same mammography-specific viewing features as the predicate (Quadrant Navigation, Next/Previous Prior Exam, Change between 2D, Projection, and 3D (Tomo) Display).
• Meeting general safety and effectiveness requirements for a Class II medical device.

Reported Device Performance (as demonstrated by feature comparison):

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

The document does not describe a clinical performance study with a specific "test set" in the context of an AI/ML algorithm's diagnostic performance evaluation (e.g., a set of mammograms for classification). Instead, the "study" is a feature-by-feature comparison and technical validation against the predicate device.

• Sample size: Not applicable in the context of a dataset for AI evaluation. The "sample" here refers to the device itself and its implemented features.
• Data provenance: Not applicable. The document focuses on the features of the device rather than testing it against a clinical dataset.

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

Not applicable. This device is a PACS/viewer system, not an AI diagnostic algorithm that requires expert-established ground truth for a clinical dataset. The "ground truth" for this submission is established by the functional specifications and features of the predicate device (Visage PACS/CS K082269) and the general requirements for PACS systems.

4. Adjudication method for the test set:

Not applicable. No clinical dataset requiring adjudication was used for this submission.

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 MRMC study was done or described. This is not an AI-assisted diagnostic device that augments human readers but rather a platform for viewing and managing medical images.

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

Not applicable. Nucleus.io is a PACS/viewer, not a standalone diagnostic algorithm.

7. The type of ground truth used:

The "ground truth" for this 510(k) submission, particularly regarding the claim for mammography diagnosis, is the functional equivalency to a legally marketed predicate device. This is demonstrated by showing that Nucleus.io possesses the same relevant features and capabilities as Visage PACS/CS, especially those related to mammography viewing and processing, and that it adheres to industry standards (e.g., DICOM, handling uncompressed/lossless images for primary diagnosis). The risk management and verification/validation processes serve to confirm that the implemented features meet specifications and do not introduce new safety or effectiveness concerns.

8. The sample size for the training set:

Not applicable. This is not an AI/ML device that requires a training set.

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

Not applicable. This is not an AI/ML device that requires a training set.

In summary, this 510(k) submission for Nucleus.io is primarily based on demonstrating substantial equivalence to a predicate PACS system (Visage PACS/CS) by comparing functional features, particularly those supporting mammography diagnosis. It is not an submission for an AI/ML-driven diagnostic device, and therefore the traditional metrics and study designs (e.g., test sets, ground truth establishment, MRMC studies) typically associated with AI performance evaluation are not present in this documentation. The acceptance criteria are qualitative, focusing on feature parity and adherence to general medical device safety and performance standards.

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The Nucleus Image Management System (Nucleus IMS) is a software based PACS, to be used by radiologists and other medical personnel. The Nucleus IMS is comprised of software modules that provide image receipt, diagnostic viewing, storage, distribution, enhancement, sharing, manipulation, and networking of medical 2D/3D images at distributed locations. All modules of the Nucleus IMS are web-based and can operate on off-the-shelf hardware, as needed. The Nucleus IMS consists of the following primary components: Nucleus Viewer with image streaming technology for use by medical professionals for diagnostic and clinical image review-Nucleus Image Exchange (iX) for image acceptance, transfer, and sharing with hospitals/clinics as well as between facilities-and Nucleus Image Store for secure cloud based image storage and management through HIPAA compliant encryption. Nucleus iX integrates with the Nucleus Viewer and Nucleus Image Store. Nucleus.io, a web based class I PaaS device, provides the basis for the system and for vendor neutral applications.

The Nucleus IMS interfaces with health information systems (HIS) using industry-standard image transfer and data exchange protocols—such as DICOM, HL7, and HTML—through web-based networked gateways and local and wide area networks. The Nucleus IMS is compatible with modalities including: Computed Tomography (CT), Magnetic Resonance Imaging (MR), Ultrasound (US), Computed Radiography (CR), Digital Radiography (DX), Nuclear Medicine (NM), Positron Emission Tomography (PT), and X-Ray Angiography (XA). When appropriate, the Nucleus IMS provides and installs software and, optionally, server hardware at client facilitate secure, web-based connections for image transmission to and from hospital central servers via the Internet. Additionally, industry standard HTTPS, VPNs, and other encryption methodologies are utilized to allow for optimal, secure, rapid streaming of image compression and encryption adhere to standard industry protocols. The Nucleus IMS can be used as a full featured PACS or as an independent viewer in clinical settings.

Nucleus Image Management System is not intended for display of mammography imaging for diagnosis.

The Nucleus Image Management System (Nucleus IMS) is a software based PACS, to be used by radiologists and other medical personnel. The Nucleus IMS is comprised of software modules that provide image receipt, diagnostic viewing, storage, distribution, enhancement, sharing, manipulation, and networking of medical 2D/3D images at distributed locations. All modules of the Nucleus IMS are web-based and can operate on off-the-shelf hardware, as needed. The Nucleus IMS consists of the following primary components: Nucleus Viewer with image streaming technology for use by medical professionals for diagnostic and clinical image review-Nucleus Image Exchange (iX) for image acceptance, transfer, and sharing with hospitals/clinics as well as between facilities-and Nucleus Image Store for secure cloud based image storage and management through HIPAA compliant encryption. Nucleus iX integrates with the Nucleus Viewer and Nucleus Image Store. Nucleus.io, a web based class I PaaS device, provides the basis for the system and for vendor neutral applications.

The Nucleus IMS interfaces with health information systems (HIS) using industry-standard image transfer and data exchange protocols—such as DICOM, HL7, and HTML—through web-based networked gateways and local and wide area networks. The Nucleus IMS is compatible with modalities including: Computed Tomography (CT), Magnetic Resonance Imaging (MR), Ultrasound (US), Computed Radiography (CR), Digital Radiography (DX), Nuclear Medicine (NM), Positron Emission Tomography (PT), and X-Ray Angiography (XA). When appropriate, the Nucleus IMS provides and installs software and, optionally, server hardware at client facilitate secure, web-based connections for image transmission to and from hospital central servers via the Internet. Additionally, industry standard HTTPS, VPNs, and other encryption methodologies are utilized to allow for optimal, secure, rapid streaming of image compression and encryption adhere to standard industry protocols. The Nucleus IMS can be used as a full featured PACS or as an independent viewer in clinical settings.

Nucleus Image Management System is not intended for display of mammography imaging for diagnosis.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) submission for the Nucleus Image Management System:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: The document mentions "several full image data sets" were used for the Nucleus Viewer validation. It does not specify an exact number of cases or images.
• Data Provenance: Not explicitly stated. The study appears to be a retrospective technical and performance validation comparing the new device against a predicate, rather than a clinical study with patient outcome data. The country of origin of the data is not specified, but given the company location and FDA submission, it's likely U.S.-based.

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

• Number of Experts:
  • For the Nucleus Viewer validation (diagnostic quality and features): "a licensed Radiologist." (One expert mentioned.)
  • For the Nucleus Image Exchange validation (image exchange features): "a NucleusHealth Customer Service Supervisor." (One expert mentioned.)
• Qualifications:
  • Radiologist: "licensed Radiologist." No specific years of experience are mentioned, but implicitly, a licensed radiologist is qualified to assess diagnostic image quality.
  • Customer Service Supervisor: Their qualification for validating image exchange features is based on their role in NucleusHealth, implying familiarity with system operations.

4. Adjudication Method for the Test Set

• The document implies a none or single-reader adjudication method, as it states validations were performed by a single "licensed Radiologist" for the viewer and a "NucleusHealth Customer Service Supervisor" for the image exchange. There is no mention of multiple readers or consensus processes for resolving discrepancies.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

• No MRMC study was done. The submission explicitly states, "No clinical trials were performed in the development of the device." The study focused on technical performance, feature validation, and substantial equivalence to a predicate device, not on human reader improvement with AI assistance. The device is a PACS system and viewer, not an AI diagnostic algorithm.

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

• This question is not applicable in the typical sense of AI algorithms. The Nucleus Image Management System is a PACS (Picture Archiving and Communications System) and medical image viewer. Its "performance" refers to how well it functions as an image management and viewing system, not as an AI algorithm that provides diagnostic readings independently. The validations focused on system functionality, image quality for diagnostic review (by a human), and data exchange.

7. The Type of Ground Truth Used

• The ground truth was established by expert assessment/consensus against the predicate device's performance.
  • For diagnostic image quality: The licensed radiologist assessed the image quality of the Nucleus Viewer and compared it to "the image quality of the predicate device."
  • For features and functions: The experts validated that the features and functions performed as expected and were substantially equivalent to the predicate.
• It was not pathology, surgical outcomes, or a large-scale clinical outcomes data.

8. The Sample Size for the Training Set

• Not applicable/Not specified. This is a PACS and viewer system, not an AI/machine learning model that undergoes a "training set" process in the typical sense for learning medical image features. Its development followed general software development and quality management procedures (ISO 13485, ISO 14971, FDA QSR).

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

• Not applicable. As noted above, there's no mention of a "training set" as understood in machine learning. The "ground truth" for the device's development (its requirements and expected behavior) would have been established through a Product Requirements Specification (PRS) and validated against through the verification and validation process.

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