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The ACR | LAB Urine Analysis Test System is comprised of a smartphone application, a proprietary Color-Board, and ACR Reagent Strips. It is intended for the semi-quantitative detection of albumin and creatinine in urine, as well as the presentation of their ratio. The ACR | LAB Urine Analysis Test System is intended for in-vitro diagnostic use by a healthcare professional in a point of care setting. These results may be used in conjunction with clinical evaluation as an aid in the diagnosis for kidney function.

The ACR | LAB Urine Analysis Test System is comprised of a smartphone application, a proprietary Color-Board and ACR Reagent Strips. It is intended for the semi-quantitative detection of albumin and creatinine in urine, as well as the presentation of their ratio. The device is provided as a kit that is comprised of a canister of 100 FDA-cleared urine test strips (ACON Laboratories Inc. Mission Urinalysis Reagent Strips (Microalbumin/Creatinine) K150330), 10 Color-Boards, and a User Manual. The ACR | LAB Urine Analysis Test System also consists of a smartphone application for use on iPhone 7 device (iOS 12), and an image recognition algorithm running on the Backend. The software component of the ACR | LAB consists of both an application (App) and a Backend server (Backend). The App instructs the professional user how to accurately perform the test. The App conducts a series of boundary condition analyses, and if the scan is approved, sends the information to the Backend for complete analysis and results classification. Once analyzed, the results are securely transmitted to a patient Electronic Medical Record for review by a healthcare professional. The patients do not have access to the results at any point during the testing process.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The core acceptance criteria are based on the agreement between the ACR | LAB Urine Analysis Test System and the predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer). The study aimed for high percentages of exact match and ±1 color block match.

| Metric (Agreement with Predicate Device) | Acceptance Criteria (Implicit from "high levels of accuracy") | Reported Device Performance (ACR | LAB) |
| :--------------------------------------- | :----------------------------------------------------------- | :-------------------------------------- |
| Albumin | High Exact Match % | 89% Exact Match |
| Albumin | High ±1 Color Block Match % | 100% ±1 Color Block Match |
| Creatinine | High Exact Match % | 84% Exact Match |
| Creatinine | High ±1 Color Block Match % | 100% ±1 Color Block Match |
| Albumin-Creatinine Ratio | High Exact Match % | 93% Exact Match |
| Albumin-Creatinine Ratio | High ±1 Color Block Match % | 100% ±1 Color Block Match |

Note: The document explicitly states that the primary acceptance criteria for the method comparison study were the percent of exact match and ±1 color block match. While specific numerical targets for "high levels of accuracy" are not given as explicit "acceptance criteria," the reported performance exceeding predicate device agreement in these metrics is implicit evidence of meeting those criteria.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size:
  • Native Urine Samples: 375 subjects
  • Contrived Samples: 60 samples
  • Total Samples for Clinical Performance: 435 samples (375 native + 60 contrived)
• Data Provenance: The study evaluated native urine samples from 375 subjects as well as 60 contrived samples at three U.S. clinical sites. This indicates the data is prospective (newly collected for the study) and from the United States.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The document refers to the predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer) as the "ground truth" or reference for comparison.

• Number of "Experts" (for ground truth): The ground truth was established by readings from the predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer). Two separate lab technicians measured each urine sample, one using the iPhone 7 device (ACR | LAB) and the second using the predicate device (U120 Ultra).
• Qualifications of "Experts": The document states "Two separate lab technicians were responsible for measuring each urine sample." Their specific qualifications (e.g., years of experience, certifications) are not explicitly mentioned, but they are identified as "lab technicians."

4. Adjudication Method for the Test Set

The adjudication method appears to be none in the traditional sense of multiple human experts reviewing and deciding. Instead, the study directly compared the results of the ACR | LAB device against the results obtained from the predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer). Each sample was tested once by the ACR | LAB and once by the predicate device, and the agreement between these two measurements was assessed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Improvement

• Was an MRMC study done? No, a traditional MRMC comparative effectiveness study was not done. This study is focused on the performance of a clinical diagnostic device, where consistency with a reference device is key, rather than an AI-assisted interpretation by multiple human readers.
• Effect size of human readers improve with AI vs without AI assistance: This information is not applicable/not provided, as the study design was a direct comparison of the new device to a predicate device, not an assessment of human reader performance with and without AI assistance. The ACR | LAB system itself includes the smartphone app and image recognition algorithm as central components of its operation, so human interaction is inherent, but not a separate "with vs. without AI assistance" arm for human readers.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The device description indicates that the "ACR | LAB Urine Analysis Test System is comprised of a smartphone application, a proprietary Color-Board, and ACR Reagent Strips." It also mentions that "The App instructs the professional user how to accurately perform the test. The App conducts a series of boundary condition analyses, and if the scan is approved, sends the information to the Backend for complete analysis and results classification."

This suggests that the device does not operate purely standalone (algorithm-only without human-in-the-loop). A healthcare professional is involved in:
* Performing the physical test (dipping the strip).
* Operating the smartphone application.
* Placing the strip on the Color-Board for scanning.

The algorithm on the Backend performs the complete analysis and classification, but this is initiated and guided by the human user through the app. Therefore, it's a human-in-the-loop system, and no standalone algorithm-only performance is documented separately.

7. The Type of Ground Truth Used

The ground truth for the clinical performance study was established by comparison to a legally marketed predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer). The aim was to demonstrate substantial equivalence, meaning the new device's results should align closely with those of the established predicate.

8. The Sample Size for the Training Set

The document does not specify the sample size used for the training set for the image recognition algorithm. It focuses on the validation studies.

9. How the Ground Truth for the Training Set Was Established

The document does not explicitly describe how the ground truth for the training set was established. It broadly mentions the software validation and hazard analysis but doesn't detail the data labeling process for the algorithm's training. It is common for such systems to be trained on a large dataset of images with corresponding known (e.g., laboratory-confirmed) values for albumin and creatinine, but this specific information is not provided here.

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