(90 days)
The Sysmex® UD-10 Fully Automated Urine Particle Digital Imaging Device for locating, digitally storing and displaying microscopic images captured from urine specimens. The Sysmex® UD-10 locates and presents particles and cellular elements based on size ranges. The images are displayed for review and classification by a qualified clinical laboratory technologist on the Urinalysis Data Manager (UDM). This device is intended for in vitro diagnostic use in conjunction with a urine particle counter for screening patient populations found in clinical laboratories.
The Sysmex® UD-10 is a medical device that captures images of cells and particles found in urine with a camera and displays the images on a display screen. The displayed data consists of images of individual particles that are extracted from the original captured whole field images. The device sorts urine particle images based on their size into eight groups (Class 1-8). These images are transferred to the UDM (Urinalysis Data Manager), where the operator enters the classification of the particle images based on their visual examination. The classification of the particles by the operator is a designation of what type of particles are observed (e.g., WBCs, RBCs, casts, bacteria).
The Sysmex UD-10 is a device for locating, digitally storing, and displaying microscopic images captured from urine specimens. It presents particles and cellular elements based on size ranges for review and classification by a qualified clinical laboratory technologist.
Here's an analysis of the acceptance criteria and the studies performed:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly state pre-defined acceptance criteria values for agreement percentages in the precision, repeatability, and method comparison studies (except for the minimum requirement for overall agreement in reproducibility and repeatability). However, it does provide conclusions based on the results meeting statistical thresholds. The carryover study had an acceptance criterion within ±1.00%.
| Study Type | Metric | Acceptance Criteria | Reported Device Performance |
|---|---|---|---|
| Reproducibility | Overall Agreement | Lower 95% Confidence Limit > 80.9% (minimum requirement) | 97.9% (95% CI: 95.2%, 99.1%) |
| Repeatability | Overall Agreement | Lower 95% Confidence Limit > 85.2% (minimum requirement) | 100.0% (95% CI: 97.8%, 100.0%) |
| Carryover | Carryover Effect | Within ±1.00% | RBC: 9.82x10^-23% to 4.16x10^-14% (PASS) |
| BACT: 0.00% to -2.57x10^-6% (PASS) | |||
| WBC: 1.05x10^-12% to 100.00% (FAIL at one site, but deemed clinically insignificant) | |||
| Method Comparison | Overall Agreement (UD-10 vs. Manual Microscopy) | Exceed 85.2% (proposed requirement) | 92.0% (95% CI: 89.8%, 93.7%) |
2. Sample Size and Data Provenance
Reproducibility Study:
- Sample size: 240 evaluations (from 120 samples of abnormal and normal QC material, processed twice a day for a minimum of 5 days).
- Data provenance: Prospective, U.S. clinical sites (4 sites). Commercially available MAS® UA control material was used.
Repeatability Study:
- Sample size: 170 evaluations (from an unspecified number of normal residual urine samples, each assayed in 5 replicates).
- Data provenance: Prospective, U.S. clinical sites (4 sites). Normal residual urine samples, collected without preservatives.
Carryover Study:
- Sample size: Not explicitly stated as a total number of samples, but involved High and Low concentration samples for BACT (4 sites), WBC (3 sites), and RBC (3 sites). Each sample was split into 3 aliquots (3 high, 3 low) and run consecutively. Results are presented for 3 replicates of high and 3 replicates of low samples per parameter per site.
- Data provenance: Prospective, U.S. clinical sites (4 sites for BACT, 3 for WBC and RBC). Residual urine samples, collected without preservatives.
Method Comparison Study:
- Sample size: 746 abnormal and normal urine samples.
- Data provenance: Prospective, U.S. clinical sites (4 sites). Residual urine samples from daily routine laboratory workload, collected without preservatives.
3. Number of Experts and Qualifications for Ground Truth
Reproducibility Study:
- Number of experts: One technologist per site (total of 4 technologists across 4 sites).
- Qualifications: "Technologist." No specific experience level is mentioned.
Repeatability Study:
- Number of experts: Two technologists per sample per site, who independently reviewed and identified particle images.
- Qualifications: "Technologist." No specific experience level is mentioned.
Carryover Study:
- Number of experts: One technologist per site.
- Qualifications: "Technologist." No specific experience level is mentioned.
Method Comparison Study:
- Number of experts: Two technologists per sample per site. One classified elements on the UD-10, and a second performed visual read using manual light microscopy.
- Qualifications: "One technologist" and "a second technologist." No specific experience level is mentioned.
4. Adjudication Method
Reproducibility, Repeatability, and Carryover Studies:
- No explicit adjudication method is described. For repeatability, two technologists independently reviewed images, and "Each technologist's results were treated and recorded as an independent observation."
Method Comparison Study:
- No explicit adjudication method is described. One technologist used the UD-10, and another used manual microscopy. Their results were compared.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
There is no mention of a formal MRMC comparative effectiveness study in the sense of evaluating how much human readers improve with AI vs. without AI assistance. The study compares the UD-10 device's performance (which incorporates digital imaging and sorting for human review) against manual microscopy. The UD-10 is a digital imaging device, not strictly an 'AI' device in the typical sense of providing automated diagnosis or enhanced AI assistance to human readers for diagnostic interpretation (beyond presenting sorted images). The study is essentially a method comparison between the UD-10-assisted workflow and traditional manual microscopy.
6. Standalone Performance (Algorithm Only)
The Sysmex UD-10 is described as a device that "locates and presents particles and cellular elements based on size ranges. The images are displayed for review and classification by a qualified clinical laboratory technologist." This indicates that the device requires human-in-the-loop for classification and is not a standalone diagnostic algorithm. Its performance is implicitly tied to how well technologists can use the displayed images. The "Overall Agreement" metrics in the studies reflect the performance of the system (device + technologist).
7. Type of Ground Truth Used
Reproducibility Study:
- Ground truth: Expected results from commercially available MAS® UA control material (Level 1 and Level 2).
Repeatability Study:
- Ground truth: Reference results provided by screening samples with the Sysmex UF-1000i urine analyzer (K070910).
Carryover Study:
- Ground truth: Determined by Sysmex UF-1000i results for high and low concentration samples.
Method Comparison Study:
- Ground truth: For the initial comparison, manual microscopy was considered the comparative method. For the referee comparison, the Sysmex UF-1000i (K070910) was used as the referee method to evaluate agreement between UD-10 and manual microscopy.
8. Sample Size for the Training Set
The document is a 510(k) summary for a medical device that captures and displays images for human review, not an AI/ML algorithm that requires a "training set" in the conventional sense of machine learning model development. Therefore, there is no mention of a training set sample size. The device uses size ranges to sort images, indicating a rule-based or conventional image processing approach rather than a complex AI model that learns from diverse training data.
9. How the Ground Truth for the Training Set Was Established
As noted above, this device does not appear to involve a machine learning training set in the way a typical AI algorithm would. Thus, this question is not applicable based on the provided information.
§ 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).