(119 days)
The X100HT with Full Field Peripheral Blood Smear (PBS) Application is intended to locate and display images of white cells, red cells, and platelets acquired from fixed and stained peripheral blood smears and assists a qualified technologist in conducting a WBC differential, RBC morphology evaluation, and platelet estimate using those images. For in vitro diagnostic use only. For professional use only.
X100HT with Full Field Peripheral Blood Smear (PBS) Application automatically locates and presents high resolution digital images from fixed and stained peripheral blood smears. The user browses through the imaged smear to gain high-level general impressions of the sample. In conducting white blood cells (WBC) differential, the user reviews the X100HT with Full Field PBS suggested classification of each automatically detected WBC and may manually change the suggested classification of any cell. In conducting red blood cells (RBC) morphology evaluation, the user can characterize RBC morphology on observed images. In conducting platelets estimation, the user reviews each automatically detected platelet and the suggested platelets estimation and may manually change the detections or the estimation. The X100HT with Full Field PBS enables efficient slide loading by providing three cassettes, each can be loaded with up to ten peripheral blood smear slides. The slide loader automatically adds mounting media and coverslips to the slides and loads them into the X100 for scanning and analysis. The X100HT with Full Field PBS is intended to be used by skilled users, trained in the use of the device and in the identification of blood cells.
The provided text describes the regulatory clearance of the Scopio X100HT with Full Field Peripheral Blood Smear (PBS) Application, comparing it to a predicate device (X100 with Full Field PBS Application). While it outlines the device's intended use and the general types of testing performed (software, hardware, EMC, safety), it does not contain explicit details on the acceptance criteria or the specific study results that prove the device meets these criteria for the AI/automation components of the system.
The document primarily focuses on demonstrating substantial equivalence to a predicate device, particularly highlighting the addition of a 'Slide Loader' and minor software modifications for workflow efficiency, rather than a detailed performance study of the AI's diagnostic capabilities. The core image analysis and AI components ("standard mathematical methods, including deterministic artificial neural networks (ANN's) trained to distinguish between classes of white blood cells") are stated to be "identical" to the predicate device. Therefore, a comprehensive performance study as requested, particularly regarding the AI's diagnostic accuracy against a ground truth and comparative effectiveness with human readers, is not present in this document.
However, based on the information provided, here's what can be extracted and inferred, with acknowledgments of missing details:
Acceptance Criteria and Device Performance (Inferred/General)
Since the core AI/analysis technique is stated to be "identical" to the predicate device, it's implied that the performance of the X100HT (regarding cell classification accuracy, etc.) would be similar to what was demonstrated for the predicate device's clearance. The document focuses on the new functionality (slide loader) and how it does not raise new questions of safety or effectiveness, meaning the existing performance of the analytical portion is presumed acceptable.
Table 1: Acceptance Criteria and Reported Device Performance
| Performance Metric Category | Acceptance Criteria (Inferred from Predicate's Clearance, not explicitly stated for X100HT in this doc) | Reported Device Performance (Inferred, as core AI is identical to predicate) |
|---|---|---|
| WBC Differential Accuracy | (Not explicitly stated for X100HT; performance equivalent to predicate expected) | Achieves pre-classified WBC categorization using ANNs, to be reviewed by user. |
| RBC Morphology Evaluation Presentation | (Not explicitly stated for X100HT) | Presents an overview image for examiner characterization. |
| Platelet Estimation Accuracy | (Not explicitly stated for X100HT; performance equivalent to predicate expected) | Automatically locates/counts platelets, provides estimate for user review. |
| Functional Equivalence to Predicate | The device's results (images and suggested classifications) are substantively equivalent to the predicate. | Stated to be "identical" analysis technology to K201301 predicate. |
| Software Functionality (Slide Loader) | Integration of slide loader enhances workflow without compromising core analysis or safety. | Replaces manual steps of mounting media/coverslipping and slide loading. |
| Safety and EMC | Compliance with IEC/EN standards for safety and EMC. | Successfully passed IEC 60601-1-2, FCC Part 15 Subpart B, IEC 61010-2-101, IEC 61010-1, IEC 62471. |
Details on the Study Proving Device Meets Acceptance Criteria:
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Sample Size Used for the Test Set and Data Provenance:
- Not specified in the provided text. The document states "Verification and validation testing was conducted and documentation was updated," but does not list sample sizes for these tests, nor the origin (country) or nature (retrospective/prospective) of the data. Given the device's classification and the focus on "substantial equivalence," it's possible detailed clinical performance data was not a primary requirement for this 510(k), as the core AI was already cleared.
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Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:
- Not specified in the provided text. The document mentions the device "assists a qualified technologist" and is for "skilled users, trained in the use of the device and in the identification of blood cells," but does not detail the experts used for ground truth generation in any validation studies.
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Adjudication Method for the Test Set:
- Not specified in the provided text.
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Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- Not specified in the provided text. The document emphasizes that the user "reviews the suggested classification" and "may manually change the suggested classification," indicating a human-in-the-loop workflow. However, an MRMC study comparing human performance with and without AI assistance is not described.
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Standalone (Algorithm Only) Performance:
- A standalone performance study of the algorithm's accuracy in classifying cells (without human review/override) is not explicitly detailed in the provided text for the X100HT. The description of the device's function clearly outlines a "pre-classified" stage where the ANN suggests classifications, which are then reviewed and potentially modified by a human user. The performance reported is thus implicitly a human-in-the-loop performance, but the standalone accuracy is not quantified.
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Type of Ground Truth Used:
- Not specified in the provided text. Since the device "pre-classifies" cells, the ground truth for training and validating the ANN would likely involve expert consensus or manual expert classification of blood cells. However, this is not explicitly stated.
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Sample Size for the Training Set:
- Not specified in the provided text. The document mentions "deterministic artificial neural networks (ANN's) trained to distinguish between classes of white blood cells," but the size of the training dataset is not provided.
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How the Ground Truth for the Training Set Was Established:
- Not specified in the provided text. Similar to point 6, it can be inferred that expert classification was used, but the specific process (e.g., number of experts, consensus methods) is not described.
Summary of Missing Information:
The provided 510(k) summary focuses almost entirely on demonstrating that the X100HT, with its new slide loader, is substantially equivalent to an already cleared predicate device (K201301). It highlights that the core analytical software and imaging technology responsible for AI-assisted cell classification are "identical" to the predicate. Therefore, details regarding new performance studies for the AI component itself (acceptance criteria, test set sizes, ground truth establishment, MRMC studies) are not present in this document, as the performance aspect of the AI was likely covered in the predicate device's clearance. This document serves to demonstrate that the modifications (primarily the slide loader) do not negatively impact the previously established safety and effectiveness.
§ 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).