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System for patient positioning and fixation on the treatment couch, including transportation of the patient from preparation site and/or diagnostic surveys to the treatment unit

The PatLog 1 0 Pattent Handling System is a combination of separate components that facılıtates setup of the patient on a Patıent Table Plate, transport to diagnostic devices, and/or to the treatment room and back after the treatment The Pattent Table Plate 1s docked on the patient table bases at each unt and undocked for the transport between stations with the Transport Trolley
The system consists of the following components

• Patient table plate
• Docking unit
• Transport trolley

The provided text describes a 510(k) summary for the "PatLog 1.0 Radiotherapy Patient Handling System." It focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria or a dedicated study proving performance against such criteria. The document explicitly states: "The technological characteristics and the intended use are substantially the same for Pat-Log Patient Handling system as for Hercules Radiation Therapy Couch and ATLAS Couch Top."

Consequently, most of the requested information regarding acceptance criteria, specific study details, sample sizes, ground truth establishment, expert involvement, and MRMC studies is not available in the provided text. The submission is a regulatory filing for market clearance based on substantial equivalence, not a scientific publication detailing performance studies.

Here's a breakdown of what can be extracted and what cannot:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a table of acceptance criteria or specific performance metrics (e.g., accuracy, precision, error rates) for the PatLog 1.0 system. The basis for clearance is demonstrating "substantial equivalence" to existing predicate devices, implying that its performance is expected to be comparable to those devices, but no quantitative performance data for PatLog 1.0 is given.

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

Not applicable. The filing is a 510(k) submission based on substantial equivalence. It does not describe a clinical performance study with a dedicated test set in the way a diagnostic AI might. The focus is on technological characteristics and intended use being similar to the predicate devices.

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

Not applicable. As no performance study with a test set aiming to establish "ground truth" for the PatLog 1.0 is described, there's no mention of experts or their qualifications for this purpose.

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

Not applicable. No test set requiring expert adjudication is described 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:

Not applicable. The PatLog 1.0 is a patient handling system, not an AI-powered diagnostic or assistive tool for human readers. Therefore, an MRMC comparative effectiveness study is irrelevant to this device type, and no such study is mentioned.

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

Not applicable. The PatLog 1.0 is a physical patient handling system, not an algorithm.

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

Not applicable. No performance study requiring the establishment of a specific "ground truth" (in the context of diagnostic accuracy, for example) is described. The "ground truth" relevant to this submission is the established safety and effectiveness of the predicate devices.

8. The sample size for the training set:

Not applicable. The PatLog 1.0 is a physical device, not a machine learning algorithm that requires a training set.

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

Not applicable. As there’s no training set for an algorithm, there’s no ground truth establishment for it.

Summary regarding the requested information:

The provided document is a 510(k) summary for a "Radiotherapy Patient Handling System." This type of regulatory submission focuses on demonstrating "substantial equivalence" to legally marketed predicate devices, primarily by comparing technological characteristics and intended use. It does not include detailed performance studies with acceptance criteria, test sets, ground truth establishment, or expert evaluations in the manner that would be expected for a diagnostic or AI-driven medical device. Therefore, most of the questions cannot be answered from the provided text.

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