(89 days)
The CellaVision DM1200 with the Advanced RBC Application is an automated cell-locating device, intended for in-vitro diagnostic use.
The CellaVision DM1200 with the Advanced RBC Application automatically locates and presents images of blood cells on peripheral blood smears. The operator identifies and verifies the suggested classification of each cell according to type.
The CellaVision DM1200 with the Advanced RBC Application is intended for blood samples that have been flagged as abnormal by an automated cell counter.
The CellaVision DM1200 with the Advanced RBC Application is intended to be used by skilled operators, trained in the use of the device and in recognition of blood cells.
The CellaVision DM96 with the Advanced RBC Application is an automated cell-locating device, intended for in-vitro diagnostic use.
The CellaVision DM96 with the Advanced RBC Application automatically locates and presents images of blood cells on peripheral blood smears. The operator identifies and verifies the suggested classification of each cell according to type.
The CellaVision DM96 with the Advanced RBC Application is intended for blood samples that have been flagged as abnormal by an automated cell counter.
The CellaVision DM96 with the Advanced RBC Application is intended to be used by skilled operators, trained in the use of the device and in recognition of blood cells.
The Advanced RBC Application is substantially equivalent to the RBC functionality included in the predicate DM Systems. It pre-characterizes the morphology of the red blood cells in a sample based on abnormal color, size, and shape (Poikilocytosis). In addition to that, the Advanced RBC Application also pre-characterizes based on different types of Poikilocytosis and on the presence of certain inclusions.
The DM Systems display the result of the RBC pre-characterization as the percentage of abnormal cells for each morphological characteristic and as an automatically calculated grade (0 - normal through 3 - marked), corresponding to that percentage. It also displays an overview image of the RBC monolayer. The difference between the current RBC functionality and Advanced RBC Application is the analysis technique, which enables the Advanced RBC Application to pre-characterize RBC into 21 morphological characteristics as opposed to the current RBC functionality with 6 morphological characteristics. The cell images are pre-characterized into different groups of morphological characteristics based on size, color, shape and inclusion using segmentation, feature calculation and the deterministic artificial neural networks (ANNs) trained to distinquish between morphology characteristics of red blood cells.
Another difference is that the red blood cells, pre-characterized by the Advanced RBC Application, can be displayed both in an overview and in individual images on the screen, while the current RBC functionality displays the pre-characterized red blood cells in an overview image only.
As in the current RBC functionality, the user reviews the overview image and can change the characterization by manually changing the grades for any morphological characteristic. With the Advanced RBC Application, the user can also view individual cells, grouped by morphological characteristic and change the characterization by reclassifying individual cells.
The provided text describes the CellaVision DM96 and DM1200 with Advanced RBC Application, an automated cell-locating device. Here's a breakdown of the requested information based on the text:
1. A table of acceptance criteria and the reported device performance
The document states that a clinical evaluation was conducted, and the results "met the predefined acceptance criteria" for various metrics. However, the precise quantitative acceptance criteria and the exact reported performance values are not explicitly stated in this summary. The summary only mentions that the results fulfilled the acceptance criteria.
| Metric (Morphology Group) | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| RBC group Size | Overall Agreement, Positive Percent Agreement (PPA), Negative Percent Agreement (NPA) | "fulfilled the acceptance criteria" |
| Groups Color, Shape, Inclusions, and clinical significant morphologies | Efficiency, Sensitivity, Specificity | "fulfilled the acceptance criteria" |
| Individual morphological characteristics | Sensitivity, Specificity | "fulfilled the target limits" |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample size: The document states, "Samples were collected and tested for RBC characterization on DM96 and DM1200 at different laboratories." However, the exact sample size for the clinical evaluation (test set) is not specified.
- Data provenance: The samples were collected "from routine workflow from hospital laboratories" and "in accordance with the target patient population, i.e. from samples flagged as abnormal by an automated cell counter." This suggests prospective collection from clinical settings, but specific countries of origin are not mentioned.
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)
For the clinical evaluation, the "manual microscopy (Reference Method)" was used as the primary comparator for most morphology groups. For the "RBC group Size," an "automated cell counter" was used as a "convenient predicate device."
- The document implies that the ground truth for most RBC characteristics was established by manual microscopy, which would involve human experts. However, the number of experts and their specific qualifications are not provided. The device's intended use states, "The CellaVision DM96/DM1200 with the Advanced RBC Application is intended to be used by skilled operators, trained in the use of the device and in recognition of blood cells," which implies that the reference method would also involve such skilled operators.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
The document does not specify an adjudication method for establishing the ground truth from manual microscopy or for resolving discrepancies between readers (if multiple readers were used). It simply refers to "manual microscopy (Reference Method)" as the comparator.
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, an MRMC comparative effectiveness study was not explicitly described in the provided text. The study conducted was a comparison between the automated device (CellaVision Advanced RBC Application) and manual microscopy (Reference Method), not a study evaluating human reader improvement with AI assistance.
- The device "automatically locates and presents images of blood cells on peripheral blood smears. The operator identifies and verifies the suggested classification of each cell according to type." While the device assists the human, the study's objective was about the equivalence of the device's characterization results to manual microscopy, not the improvement of human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- No, a standalone (algorithm only) performance study was not described. The device is explicitly designed for a human-in-the-loop workflow: "The operator identifies and verifies the suggested classification of each cell according to type." Therefore, the evaluation would inherently include this human interaction. The clinical evaluation compared the "Advanced RBC Application installed on CellaVision DM96 and CellaVision DM1200 (Test Methods)" to the manual method, implying system performance with human verification.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The ground truth used was primarily:
- Expert consensus from manual microscopy for most RBC morphological characteristics.
- Automated cell counter results for the "RBC group Size" (Macrocytes, Microcytes, and Anisocytosis), as manual microscopy was deemed "highly difficult, time consuming and thereby impractical" for this group.
8. The sample size for the training set
The document does not specify the sample size used for the training set of the deterministic artificial neural networks (ANNs). It only mentions that the ANNs were "trained to distinguish between morphology characteristics of red blood cells."
9. How the ground truth for the training set was established
The document does not explicitly state how the ground truth for the training set was established. It mentions that the ANNs were "trained to distinguish between morphology characteristics of red blood cells," implying that labeled data was used for training, but the method of obtaining these labels (e.g., expert annotations, specific pathological confirmation) is not detailed.
§ 864.5260 Automated cell-locating device.
(a)
Identification. An automated cell-locating device is a device used to locate blood cells on a peripheral blood smear, allowing the operator to identify and classify each cell according to type. (Peripheral blood is blood circulating in one of the body's extremities, such as the arm.)(b)
Classification. Class II (performance standards).