(195 days)
The Spectra Optia® Apheresis System, a blood component separator, may be used to perform therapeutic plasma exchange.
The Spectra Optia® Apheresis System, a blood component separator, may be used to perform Red Blood Cell Exchange (RBCX) procedures for the transfusion management of Sickle Cell Disease in adults and children.
The Spectra Optia® Apheresis System, a blood component separator, may be used to reduce White Blood Cells for patients with leukocytosis at risk for leukostasis.
The Spectra Optia® Apheresis System is an automated centrifugal system that separates whole blood into its cellular and plasma components. The cleared system is comprised of three major subsystems:
- the apheresis machine itself (centrifuge, centrifuge filler, pumps, valves, computerized safety and control systems, etc.)
- a sterile, single-use, disposable blood tubing set
- embedded software
The modifications described in this submission are those required to resolve current obsolescence issues for various electronic components found within the Spectra Optia equipment.
The provided text describes a 510(k) premarket notification for the Terumo BCT, Inc. Spectra Optia® Apheresis System. It focuses on demonstrating substantial equivalence to a predicate device, particularly regarding hardware modifications due to obsolescence. Crucially, the document does not contain information about the device's performance through a clinical study with acceptance criteria in the way one might expect for an AI/ML medical device.
Instead, the "performance data" section states: "A summary of the verification testing and a summary of the validation testing was presented to show that the modified device met all the performance requirements and that the subject device is as safe and performs as well as the predicate device." This refers to engineering verification and validation (V&V) activities for hardware changes, not a clinical study involving human subjects or AI performance metrics.
Therefore, many of the requested details, such as sample size for test sets, expert qualifications, adjudication methods, MRMC studies, standalone performance with ground truth, and training set information for AI, are not applicable or available in this document.
However, I can extract the acceptance criteria (in terms of performance requirements) as implied by the statement regarding meeting "all the performance requirements" and being "as safe and performs as well as the predicate device." The study proving this is the "verification and validation tests" mentioned.
Here's the breakdown of the available and applicable information:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| The modified device meets all performance requirements of the predicate device. | The modified device met all performance requirements. (Based on V&V tests) |
| The modified device performs as well as the predicate device. | The modified device performs as well as the predicate device. (Based on V&V tests and demonstration of substantial equivalence) |
| The modified device is as safe as the predicate device. | The modified device is as safe as the predicate device. (Based on V&V tests and demonstration of substantial equivalence) |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Not applicable/Not provided. The document describes engineering verification and validation for hardware component changes, not a clinical study with a test set of patient data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
- Not applicable/Not provided. No "ground truth" in the context of clinical expert review is mentioned, as this is not a clinical study using patient data for diagnostic classification.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable/Not provided. No adjudication method for a test set is relevant to the type of V&V described.
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/Not provided. This document does not describe an AI/ML device or an MRMC study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable/Not provided. This device is a hardware system, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable/Not provided. The "ground truth" for the engineering verification and validation would be the design specifications and performance characteristics of the original (predicate) device, against which the modified device was tested to ensure it met those pre-defined engineering and functional requirements.
8. The sample size for the training set
- Not applicable/Not provided. This is not an AI/ML device, so there is no training set.
9. How the ground truth for the training set was established
- Not applicable/Not provided. As there is no training set for an AI/ML device, this question is not relevant.
In summary: The provided document is a 510(k) submission for a hardware modification to an existing apheresis system. The "study" proving acceptance criteria is the verification and validation (V&V) tests conducted on the modified system to ensure it performs equivalently to the predicate device, specifically addressing functional and safety requirements rather than clinical performance metrics in a patient population or AI/ML diagnostic accuracy.
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