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For fabrication of temporary fillings and other temporary prosthetics for use until the permanent prosthetic is ready for insertion. intended to temporarily restore carious lesions or structural defects in teeth. Intended for use in cavities, Class I, II, III, IV (inlays and onlays).

MD-Temp Plus is used for temporary filling material. It is supplied in a 20, 30 or 40g jar in either white (tooth-like) or pink (gum-like), and individually boxed. It is intended primarily as a temporary filling material for most cavities or damages but may be used by the dentist for other temporary restorations. MD-Temp plus is water-based temporary filling materials used for part of a tooth or multiple teeth. The curing reaction is the hydration reaction of the gypsum, and the semi-gypsum is cured as it is exposed to saliva or water in the oral cavity.

This document is a 510(k) Premarket Notification for a dental temporary filling material called MD-Temp Plus. It focuses on demonstrating substantial equivalence to a previously cleared predicate device, MD-Temp. The document details non-clinical testing performed to establish safety and effectiveness.

Based on the provided text, it's important to note that this submission is for a dental material (a physical device), not an Artificial Intelligence/Machine Learning (AI/ML) powered medical device. Therefore, many of the requested criteria related to AI/ML device performance (like MRMC studies, human reader improvement with AI, training set details, and expert consensus for ground truth) are not applicable to this type of device submission.

The acceptance criteria and study proving the device meets them are based on physical and chemical performance standards for dental materials, and biocompatibility testing.

Here's an analysis of the provided information, addressing the applicable points:

Acceptance Criteria and Study for MD-Temp Plus (Dental Temporary Filling Material)

This submission focuses on demonstrating substantial equivalence of a new dental material (MD-Temp Plus) to a previously cleared material (MD-Temp) through non-clinical performance and biocompatibility testing. The "acceptance criteria" are the relevant ISO and ASTM standards for such materials, and the "study" involves conducting tests to ensure the device performs within acceptable parameters defined by these standards.

1. Table of Acceptance Criteria and Reported Device Performance

The document states that the device was tested to evaluate its safety and effectiveness according to various standards. While it explicitly lists standards for Biocompatibility, Shelf Life, Compressive Strength, and Setting Time, and mentions others for Flexural Strength and Tensile Strength, it does not provide specific numerical "acceptance criteria" directly from these standards within the document. Instead, it presents the measured performance of both the subject and predicate devices and states that the improvements in the subject device's performance (setting time and compressive strength) are "within the range of the test standards and it doesn't affect the safety and effectiveness."

Here's a table summarizing the reported device performance and the related, implied acceptance criteria based on standard compliance:

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

• Sample Size: The document does not specify the exact sample sizes (e.g., number of specimens) used for each of the physical and chemical tests (compressive strength, setting time, etc.). These numbers would typically be defined by the respective ISO/ASTM standards.
• Data Provenance: The testing was conducted by Meta Biomed Co., Ltd. (the manufacturer) in South Korea, as indicated by the company's address. The data appears to be prospective as it was generated specifically for this 510(k) submission to demonstrate the performance of the MD-Temp Plus device.

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

• Not Applicable. For this type of physical/chemical material testing, "ground truth" is established by adherence to standardized test methods (e.g., ISO, ASTM standards) and measurements conducted in accredited laboratories. It does not involve human experts in the way AI/ML performance evaluation does (e.g., radiologists interpreting images).

4. Adjudication Method for the Test Set

• Not Applicable. Adjudication methods (like 2+1, 3+1 consensus) are used for resolving disagreements in human expert interpretations, particularly in medical image analysis. For material testing, results are typically quantitative measurements, and repeatability/reproducibility are ensured through standardized protocols and calibration.

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

• No. An MRMC study is designed for evaluating the impact of AI on human readers in diagnostic tasks, typically involving medical imaging. This is a physical dental material, so such a study is irrelevant.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Not Applicable. This is not an AI algorithm. Its "performance" is its physical and chemical properties as measured by the non-clinical tests.

7. The Type of Ground Truth Used

• For physical and chemical properties (e.g., setting time, compressive strength): The ground truth is the measured value obtained through standardized laboratory testing procedures (e.g., ISO 3107, ISO 4049, ANSI/ADA 27) using calibrated equipment.
• For biocompatibility: The ground truth is determined by the results of specific biological assays (e.g., cytotoxicity, sensitization, irritation tests) as outlined in the ISO 10993 series.

8. The Sample Size for the Training Set

• Not Applicable. This is not an AI/ML device that requires a "training set." The device is manufactured based on a defined material composition and manufacturing process, and its performance is validated through testing of manufactured lots.

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

• Not Applicable. As there is no training set for an AI/ML model, there is no ground truth establishment for such a set. The "ground truth" during product development (analogous to training for AI) would be the desired material properties and how to achieve them through formulation and manufacturing, which is part of the R&D process prior to formal validation testing.

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