(57 days)
The RET-He parameter on the Sysmex® XE-2100, Automated Hematology Analyzer, determines the hemoglobin of reticulocytes for in vitro diagnostic use in clinical laboratories.
The XE-2100 is an automated hematology analyzer previously cleared by the FDA. The RET-He parameter determines the hemoglobin of the reticulocytes. (Note: XE-Pro and RET Master are required to obtain results described.)
Here's an analysis of the acceptance criteria and the study proving the device meets them, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criterion | Reported Device Performance |
|---|---|
| Accuracy (comparison to predicate method) | Comparison to CHr showed excellent correlation. |
| Equivalent performance to predicate method | Studies were performed to evaluate the equivalency of the RET-He parameter to the predicate method. Results indicated equivalent performance. |
| Substantial Equivalence | The performance data demonstrated substantial equivalence. |
2. Sample Size Used for the Test Set and Data Provenance
The provided text does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). It only mentions that "Studies were performed to evaluate the equivalency of the RET-He parameter to the predicate method."
3. Number of Experts Used to Establish Ground Truth and Their Qualifications
The provided text does not mention using experts to establish ground truth or their qualifications. The study focused on comparing the new device's output (RET-He) to a predicate device's output (CHr).
4. Adjudication Method for the Test Set
The provided text does not describe an adjudication method. Since the study compared a device's output to a predicate device's output, and not to a human-established ground truth, adjudication would likely not be relevant in the same way it is for image interpretation tasks.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is more common for diagnostic devices where human interpretation plays a significant role and AI aims to augment that interpretation. This submission concerns a hematology analyzer, where the device performs the measurement without human-in-the-loop interpretation.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
Yes, the study described is effectively a standalone (algorithm only without human-in-the-loop performance) study. The RET-He parameter is determined by the Sysmex XE-2100 analyzer using its internal methodology, and its performance was evaluated by comparing its results directly to those of the predicate device (Bayer Advia 120). There is no indication of human intervention in interpreting the results from either device for the purpose of this comparison.
7. The Type of Ground Truth Used
The ground truth used in this study was the output of the predicate device (CHr parameter on the Bayer Advia 120 Hematology System). The study aimed to demonstrate "excellent correlation" and "equivalent performance" of the new RET-He parameter to this established predicate method.
8. The Sample Size for the Training Set
The provided text does not specify a sample size for any training set. This type of device (hematology analyzer) likely has its algorithms and parameters established during its initial development and validation, rather than through a separate "training set" in the context of machine learning. The submission focuses on the performance comparison of the developed device.
9. How the Ground Truth for the Training Set Was Established
Since no specific "training set" is mentioned in the context of this 510(k) submission, the question of how ground truth for it was established is not applicable based on the provided text. The device's methodology for deriving reticulocyte parameters is described ("using the reticulocyte forward scattered light signals from the reticulocyte measurement channel and a proprietary Sysmex calculation equation"), implying a deterministic process rather than a machine learning model trained on a ground-truthed dataset.
§ 864.5220 Automated differential cell counter.
(a)
Identification. An automated differential cell counter is a device used to identify one or more of the formed elements of the blood. The device may also have the capability to flag, count, or classify immature or abnormal hematopoietic cells of the blood, bone marrow, or other body fluids. These devices may combine an electronic particle counting method, optical method, or a flow cytometric method utilizing monoclonal CD (cluster designation) markers. The device includes accessory CD markers.(b)
Classification. Class II (special controls). The special control for this device is the FDA document entitled “Class II Special Controls Guidance Document: Premarket Notifications for Automated Differential Cell Counters for Immature or Abnormal Blood Cells; Final Guidance for Industry and FDA.”