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The Longitudinal Brain Imaging (LoBI) is a post-processing application to be used for viewing and evaluating neurological images provided by a magnetic resonance diagnostic device.

The LoBI application is intended for viewing, manipulation and comparison of medical imaging and/or multiple time-points. The LoBI application enables visualization of information that would otherwise have to be visually compared disjointedly. The LoBI application provides analysis tools to help the user assess, and document changes in diagnostic and follow-up examinations. The LoBI application is designed to support the workflow by helping the user to confirm the absence or presence of lesions, including evaluation, follow-up and documentation of any such lesions.

The physician retains the ultimate responsibility for making the final diagnosis and treatment decision.

Philips Medical Systems' Longitudinal Brain Imaging application (LoBI) is a post processing software application intended to assist in the evaluation of serial brain imaging based on MR data.

The LoBI application allows the user to view images, perform segmentation of lesions, along with segmentation editing tool and volumetric quantification of segmented volumes and quantitative comparison between time points. LoBI application provides automatic registration between studies from different time points. for longitudinal comparison.

The LoBI application provides a supportive tool for visualization of subtle differences in the brain of the same individual across time, which can be used by clinicians as the assessment of disease progression.

The physician retains the ultimate responsibility for making the final diagnosis based on image visualization as well as any segmentation and measurement results obtained from the application.

The LoBI application is intended to be used for adult population only

Key Features
LoBI application has the following key features:

• 1. Longitudinal comparison between brain images in multiple studies
• 2. Support for multi-slice MR sequences (2D and 3D) and allow user to use basic viewing operations such as: Scroll, pan, zoom, windowing and annotation
• 3. Identify pre-defined data types (pre-sets) and user created hanging layouts
• 4. Automatic registration between studies (same patient, different time-points)
• 5. Single mode: allows reviewing each of the launched studies, showing multiple sequences of the same study, using the whole reading space
• 6. Tissue segmentation and editing tools allowing volumetric measurement of different lesion types
• 7. Lesion management tool allowing matching between lesions in different studies to facilitate the assessment of differences over time
• 8. CoBI feature (Comparative Brain Imaging) a supportive tool for visualization of subtle differences in lesions of the same individual across time for similar sequences. The CoBI feature provides a mathematical subtraction of scans yielding, after bias-field correction and intensity scaling, a colorcoded image of the differences in intensity between two registered scans.
• 9. Results are displayed in tabular and graphical formats.

Here's a summary of the acceptance criteria and study information for the Philips Longitudinal Brain Imaging (LoBI) application, based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance:

The document focuses on demonstrating substantial equivalence to predicate devices and adherence to regulatory standards rather than explicit quantitative acceptance criteria or detailed device performance metrics in a table format. The primary "acceptance criteria" are implied by compliance with:

• International and FDA-recognized consensus standards: ISO 14971, IEC 62304, IEC 62366-1, DICOM PS 3.1-3.18.
• FDA guidance document: "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices."
• Internal Philips verification and validation processes: Ensuring the device "meets the acceptance criteria and is adequate for its intended use and specifications."

Since specific numerical performance criteria (e.g., accuracy, sensitivity, specificity for particular lesion types) and corresponding reported performance are not provided in this 510(k) summary, the table below reflects what is broadly stated.

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

• Test Set Sample Size: Not explicitly stated as a number of cases or images. The validation activities used "real recorded clinical data cases." The quantity of these cases is not specified.
• Data Provenance: The data used for validation consisted of "real recorded clinical data cases." No specific country of origin is mentioned. It is indicated as retrospective, as they are "recorded" data.

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

• This information is not provided in the document. The general statement is that "The physician retains the ultimate responsibility for making the final diagnosis," suggesting human expert involvement in clinical practice, but not explicitly defining how ground truth for the test set was established or by whom.

4. Adjudication Method for the Test Set:

• This information is not provided in the document.

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 comparative effectiveness study was done or reported. The document states explicitly: "The subject of this premarket submission. Longitudinal Brain Imaging (LoBI) application did not require clinical studies to support equivalence." The testing focused on verification and validation of the software's functionality and compliance with standards.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

• The document describes the LoBI application as a "post-processing software application intended to assist in the evaluation of serial brain imaging" and emphasizes that "The physician retains the ultimate responsibility for making the final diagnosis."
• While the software performs automated functions like registration, segmentation, and quantitative comparison, the validation process using "real recorded clinical data cases" seems to focus on the software's ability to provide accurate tools and information that a user would interpret.
• The description of "Full functionality test" and "RMF testing" could involve standalone algorithmic performance evaluation against predefined specifications. However, an explicit "standalone" performance study as a separate regulatory study with defined metrics (e.g., algorithm-only sensitivity/specificity against ground truth) is not detailed in this summary. The focus is on the tool's supportive role for the user.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.):

• The type of ground truth used for the validation data is not explicitly specified. It refers to "real recorded clinical data cases," implying that the medical imaging data came with existing clinical interpretations or diagnoses, which would have implicitly served as a form of reference or "ground truth" for evaluating the software's utility in "confirming the absence or presence of lesions, including evaluation, quantification, follow-up and documentation." However, the method of establishing this ground truth (e.g., expert consensus, pathology) is not detailed.

8. The Sample Size for the Training Set:

• The document does not provide information regarding a distinct training set sample size or how the LoBI application was developed using machine learning or AI. The product description focuses on its functionality as a post-processing application with features like automatic registration and tissue segmentation, which could be rule-based or machine learning-driven, but this is not specified, nor is training data mentioned.

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

• Since a training set is not mentioned, the method for establishing its ground truth is also not provided.

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