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The L1P-1F intraoral scanner (IOS) system is intended for aid in diagnosis of caries. The L1P-1F system consists of a scanner and a detachable scanner tip which enables scanning using white and blue (fluorescence) Light Emitting Diodes (LEDs). A single-use scanner body sleeve is mounted on the scanner before being introduced into the mouth of a patient for scanning of the teeth.

The interface to the computer is handled by ScanSuite TRIOS which functions as a Hardware Abstraction Layer (HAL). The scan control of, and information from the scanner is handled by the TRIOS module software, which holds the interface to the user.

The L1P-1F system also consists of the TRIOS Patient Monitoring software which aids in diagnosis of occlusal and surface caries.

The functional principle of L1P-1F (TRIOS 5) is to collect images of the object scanned by means of focus scanning, where light from the LEDs travels through the optical system to the object being scanned and back to an image sensor. 3D true colored images of the teeth combined with 2D green and red image as an additional texture are generated by emitting blue and white light in turn.

AI/ML Overview

The provided text describes the 3Shape TRIOS 5 (L1P-1F) intraoral scanner system, which is intended to aid in the diagnosis of caries. The documentation focuses on demonstrating substantial equivalence to a predicate device (DÜRR DENTAL AG – VistaCam iX "Proof" – K150672). However, it does not explicitly provide a table of acceptance criteria and reported device performance in the format requested, nor does it detail a specific study proving the device meets acceptance criteria with all the requested information.

The document discusses key performance attributes tested and compared, which serve as implicit acceptance criteria for establishing substantial equivalence. These include:

Fluorescence scanning
Color Separation
In vitro caries detection study
Spatial resolution

Based on the available information, here's an attempt to structure the response, acknowledging where specific details for the requested categories are not explicitly provided in the document:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria (Implied)	Reported Device Performance
Fluorescence Scanning Performance	The L1P-1F uses two blue LEDs (405 nm) for fluorescence detection, yielding "sufficient performance." The device detects green to red visible light (>435 nm), similar to the predicate device. The blue-violet light causes tooth structures and bacterial metabolites to fluoresce, similar to the predicate.
Color Separation/Categorization for Caries Aid	The L1P-1F presents two severity categories: "Initial" (covering early-stage enamel caries, enamel caries up to enamel/dentine junction, and dentin junction already exceeded from the predicate's classification) and "Moderate/Extensive" (for deep dentin caries). This aligns with ICDAS merged codes.
In vitro Caries Detection Performance	Performance testing demonstrates that L1P-1F is "as safe and effective as a legally marketed device" and "does not raise different questions of safety and effectiveness than the predicate device."
Spatial Resolution Performance	A qualitative comparison shows "the resolution of L1P-1F must be at least as good or better than the predicate device."
Electrical Safety / Electromagnetic Compatibility (EMC)	Complies with IEC 60601-1:2005/AMD1:2012, IEC 60601-1-2:2014, and IEC 62366-1:2015+A1:2020.
Biocompatibility	Evaluated according to relevant ISO 10993-series standards. No biocompatibility concerns were found for materials.
Reprocessing (Scanner tip sterilization, microbial barrier)	Scanner tip is autoclavable. Body Sleeve evaluated for tear resistance, tensile strength, puncture resistance, viral penetration, and synthetic blood penetration. Microbial barrier tested against viral ingress (ASTM F1671/F1671M-22). Reprocessing methods align with AAMI TIR12:2010 and AAMI TIR30:2011+R2016.
Software Verification and Validation	Verification and validation conducted as per FDA guidance "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" and EN 62304:2006+A1:2015.

2. Sample size used for the test set and the data provenance

The document mentions an "In vitro caries detection study" and performance testing, but does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective nature).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document does not provide information regarding the number or qualifications of experts used to establish ground truth for any test sets.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

The document does not specify any adjudication method used for establishing ground truth in a test set.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance

The document does not indicate that an MRMC comparative effectiveness study was done involving human readers with and without AI assistance for the L1P-1F device. The focus is on the device's standalone performance compared to a predicate device.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done

The document describes "Performance Testing" including fluorescence scanning, color separation, in vitro caries detection, and spatial resolution. These tests would inherently involve the device's standalone performance to characterize its technical capabilities, which is then concluded to be "as safe and effective as a legally marketed device." While not explicitly termed "standalone performance study," the non-clinical data and performance testing sections describe the device's intrinsic capabilities.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

The document mentions an "in vitro caries detection study," which suggests that the ground truth would likely be established by a recognized method for in vitro caries assessment, such as histology, micro-CT, or a standardized artificial caries model assessed by experts, but this is not explicitly stated.

8. The sample size for the training set

The document does not specify the sample size for any training set. Given the nature of the device (an intraoral scanner with integrated fluorescence technology), it's possible that machine learning or AI components might be involved in the "TRIOS Patient Monitoring software," but details on specific training sets are absent.

9. How the ground truth for the training set was established

Since no training set details are provided, how its ground truth was established is not mentioned.

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