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For dental clinics treatment to irradiate polymer-based restorative materials to cure them. The instrument must only be used in hospital environments, clinics or dental offices, by qualified practitioners.

The LED Curing Lights (Model: DB686 HALO) is an oral device for repairing teeth. It uses the principle of light curing to make the dental repair resin material solidify rapidly under the action of light wave in the specific wavelength range (385~515nm), so as to fill the tooth cavity or bond the bracket. It is a cordless pen-style device, and consists of handpiece, LED cure tip, charging base, power adapter, eyes protector, eye protector unit and disposable protective sleeve. The LED Curing Lights protects the handpiece and LED cure tip from gross contamination and prevent cross infection between patients by applying the disposable protective sleeve. The disposable protective sleeve (patient contact part) is made of PP material.

The provided FDA 510(k) clearance letter and summary for the LED Curing Light (DB686 HALO) describes a device that uses light to cure dental materials. It is crucial to understand that this submission primarily focuses on demonstrating substantial equivalence to predicate devices based on non-clinical performance and safety data, rather than conducting a comparative effectiveness study with human readers or presenting clinical trial data.

Therefore, many of the requested points, particularly those related to clinical studies, human reader performance, expert consensus, and ground truth establishment from patient data, are not applicable to this type of 510(k) submission for a non-diagnostic, non-AI device. The device is a direct energy device (light source) that acts on materials, not a diagnostic AI device that interprets images.

Here's an analysis based on the provided document:

Acceptance Criteria and Device Performance (Based on Non-Clinical Testing)

The "acceptance criteria" here are implicitly the standards and specifications that the device must meet to demonstrate substantial equivalence to its predicate devices. The "reported device performance" are the results of the non-clinical tests proving compliance with these standards.

1. Table of Acceptance Criteria and Reported Device Performance

Study Details (Focus on Non-Clinical Demonstrations)

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

• For a device like an LED curing light, the "test set" and "data provenance" refer to the physical devices and materials tested in the non-clinical studies.
• The document does not specify the exact sample size (number of devices or material samples) used for each non-clinical test. This information would typically be detailed in the full test reports submitted to the FDA, but is summarized in the 510(k) summary.
• Data Provenance: The tests are described as "Non-clinical data" and "All nonclinical testing performed on new devices." This implies that the tests were conducted on the manufacturer's own (proposed) devices and materials as part of their design verification and validation activities. The country of origin for the data generation (testing laboratories) is not explicitly stated, but the applicant is based in China. The testing would be considered prospective in the sense that it was conducted specifically for this 510(k) submission.

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

• Not Applicable. This device is an active medical device (light source) for material polymerization and caries detection, not a diagnostic imaging AI algorithm. Therefore, there is no "ground truth" based on expert image interpretation or patient outcomes in the context of diagnostic accuracy, nor were human experts involved in establishing a "ground truth" for the performance testing of the device's physical parameters (e.g., light intensity, wavelength, electrical safety, biocompatibility, curing efficacy as measured by ISO standards). The "ground truth" for these tests is defined by the technical specifications and standards themselves.

4. Adjudication Method for the Test Set:

• Not Applicable. As there are no human readers or expert interpretations involved in the stated non-clinical performance and safety testing, there is no adjudication method required.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done:

• No. An MRMC study is designed to evaluate how AI assistance impacts human reader performance (e.g., radiologists interpreting images). This device is a light curing unit, not a diagnostic AI system. Its clearance is based on demonstrating substantial equivalence in its ability to cure dental materials and meet safety standards, not on improving human diagnostic accuracy.

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

• Not Applicable. This is not an algorithm or software-only device. Its performance is measured as a standalone physical device (its light output, safety, biocompatibility, and ability to cure materials as per ISO standards).

7. The Type of Ground Truth Used:

• The "ground truth" for this device's acceptance is based on engineering and performance standards (e.g., ISO 10650, ISO 4049 for curing performance; IEC 60601 series for electrical safety; IEC 62471 for photobiological safety; ISO 10993 series for biocompatibility). The device's measured parameters must fall within acceptable ranges defined by these standards, and its performance must be comparable to the predicate devices.
• For the Caries Detection Mode (EAQ product code), while it's a diagnostic aid, the document doesn't detail specific "ground truth" for its diagnostic performance, rather it implies functional equivalence based on violet light emission for fluorescent reaction.

8. The Sample Size for the Training Set:

• Not Applicable. This is not an AI/machine learning device that requires a "training set" of data.

9. How the Ground Truth for the Training Set was Established:

• Not Applicable. As there is no training set for an AI model, this question is irrelevant to this device.

In summary, the 510(k) for the LED Curing Light (DB686 HALO) is a traditional submission focused on demonstrating technical conformity to established safety and performance standards and substantial equivalence to existing predicate devices through non-clinical testing. It does not involve AI, diagnostic image interpretation, multi-reader studies, or clinical trials for comparative effectiveness.

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High-Speed Air Turbine Handpieces:
It is intended for removing carious material, excess filling material, cavity and crown preparation, finishing tooth preparations and restorations, root canal preparations and polishing teeth.

Straight Handpieces:
It is intended for removing carious material, excess filling material, cavity and crown preparation, finishing tooth preparations and restorations, root canal preparations and polishing teeth.

Geared Angle Handpieces:
It is intended for removing carious material, excess filling material, cavity and crown preparation, finishing tooth preparations and restorations, root canal preparations and polishing teeth.

Air Motors:
It is intended for removing carious material, excess filling material, cavity and crown preparation, finishing tooth preparations and restorations, root canal preparations and polishing teeth.

The proposed device is used to hold rotary instruments such as burs and drills for cutting, grinding, and drilling operations. The dental handpieces are hand-held instruments driven by air motor, thus driving the rotation of dental attachments for the purpose of drilling and tooth cutting. Some models include an electric connection to power an LED light

This document describes the regulatory submission for dental handpieces (High-Speed Air Turbine, Straight, Geared Angle Handpieces, and Air Motors). The goal of the submission is to prove the substantial equivalence of the proposed device to existing predicate devices, not to prove clinical safety or effectiveness for a new medical device. Therefore, a traditional "acceptance criteria" and "study that proves the device meets acceptance criteria" as one might see for a diagnostic AI device is not applicable here.

Instead, the submission focuses on non-clinical testing and comparison to predicate devices to demonstrate that the new device is as safe and effective as those already on the market.

Here's an analysis based on the provided document, addressing the prompt's points where applicable, and explaining why others are not relevant in this context:

1. Table of Acceptance Criteria and Reported Device Performance

For this type of device (dental handpiece), "acceptance criteria" are typically defined by compliance with recognized international standards and performance benchmarks relative to the predicate devices. The document does not present a formal "acceptance criteria table" with specific thresholds for outcomes related to a diagnostic or therapeutic AI. Instead, it demonstrates compliance through non-clinical testing against standards and comparison to predicate device specifications.

The "performance" of the device is implied by its adherence to these standards and functional similarity to the predicate.

Here's a table summarizing the differences identified and the justification for substantial equivalence, which acts as the "performance" verification in this context:

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

• Test Set: Not applicable for a traditional "test set" in the context of an AI/diagnostic algorithm. The "testing" here refers to bench testing (non-clinical) of physical devices against engineering specifications and international standards. The sample size would refer to the number of physical units tested, but this detail is not provided in a P(K) summary, as it's standard engineering verification.
• Data Provenance: Not applicable in the sense of patient data. The "data" comes from engineering measurements and tests performed on the physical dental handpieces.

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

• Not applicable. Ground truth, in this context, is established by adherence to international engineering standards (e.g., ISO, IEC, ANSI/AAMI) and direct comparison of physical properties with legally marketed predicate devices. No human expert consensus on medical image interpretation or clinical outcomes is needed for this type of device.

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

• Not applicable. This concept pertains to expert review and consensus in diagnostic studies, which is not relevant here.

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

• Not applicable. This device is a mechanical dental instrument, not an AI or diagnostic tool that assists human readers. No MRMC study was performed. The "Clinical Test Conclusion" (Page 6, Section 8) explicitly states: "No clinical study is included in this submission."

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

• Not applicable. This is not an algorithm; it's a mechanical device.

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

• The "ground truth" for this submission is based on:
  • International Standards: Adherence to established standards such as ISO 14457 (Dentistry - Handpieces and motors), IEC 60601 series (Medical electrical equipment), ISO 10993 series (Biological Evaluation of Medical Device), etc.
  • Predicate Device Specifications: Direct comparison of the proposed device's specifications and performance to those of the legally marketed predicate devices (K181691 and K202786). The argument for "Substantial Equivalence" is built on demonstrating that any differences do not raise new questions of safety or effectiveness.
  • Bench Testing Results: Data derived from physical performance tests (e.g., bur extraction force, speed measurements, biocompatibility tests).

8. The sample size for the training set:

• Not applicable. There is no "training set" as this is not an AI/machine learning device.

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

• Not applicable. No training set for an AI model.

In summary:

This FDA 510(k) submission for dental handpieces is a pre-market clearance based on substantial equivalence to existing devices. The "acceptance criteria" are met by demonstrating compliance with recognized performance standards and by showing that any differences from the predicate devices do not introduce new safety or effectiveness concerns, primarily through non-clinical bench testing and adherence to international engineering and safety standards. Clinical studies or AI-specific performance metrics (like MRMC, standalone algorithm performance, or expert ground truthing) are not required or relevant for this type of device submission.

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C-SMART-I PRO, C-SMART-I PILOT, C-SMART-MINI AP:
The Endo Motor device is an endodontic treatment motorized handpiece with root canal measurement capability. It can be used to enlarge the canals while monitoring the position of the canal. It can be used as a low-speed motorized handpiece and device for measuring canal length. This device must only be used in hospital environments, clinics or dental offices by qualified dental personnel.

C-Smart-mini:
The Endo Motor device is an endodontic treatment motorized handpiece. It can be used to enlarge canals. It can be used as a low-speed motorized handpiece. This device must only be used in hospital environments, clinics or dental offices by qualified dental personnel.

C-SMART-I PRO: The Endo Motor device C-SMART-I PRO is a low-speed rotating oral equipment mainly used for root canal preparation and root canal measurement. The product is a portable device powered by built-in lithium batteries and charged by the adapter. LCD displays parameters such as speed, torque, working mode, apex position, etc. Users can also set and modify by keys, and provide design of factory initialization, calibration and functional check of the apex locator. The Endo Motor device is an endodontic treatment motorized handpiece with root canal measurement capability. It can be used to enlarge the canals while monitoring the position of the file tip inside the canal. It can be used as a low-speed motorized handpiece and device for measuring canal length. This device must only be used in hospital environments, clinics or dental offices by qualified dental personnel. The Endo Motor device C-SMART-I PRO is intended to be sterilized prior to use. The material composition of root canal files that can be used with the Endo Motor device C-SMART-I PRO is Nickel titanium (NiTi). These files are not included in the submission. There are three working modes as: M1: Apex locator only. M2: Motor only. M3: (Dual mode) Motor with apex location function.

C-SMART-I PILOT: The Endo Motor device C-SMART-I PILOT is a low-speed rotating oral equipment mainly used for root canal preparation and root canal measurement. The product is a portable device powered by built-in lithium batteries and charged by the adapter. LCD displays parameters such as speed, torque, working mode, apex position, etc. Users can also set and modify by keys, and provide design of function check, calibration, factory reset and can connect handpiece to control unit via Bluetooth. The Endo Motor device is an endodontic treatment motorized handpiece with root canal measurement capability. It can be used to enlarge the canals while monitoring the position of the file tip inside the canal. It can be used as a low-speed motorized handpiece and device for measuring canal length. This device must only be used in hospital environments, clinics or dental offices by qualified dental personnel. The Endo Motor device C-SMART-I PILOT is intended to be sterilized prior to use. The material composition of root canal files that can be used with the Endo Motor device C-SMART-I PILOT is Nickel titanium (NiTi). These files are not included in the submission. There are three working modes as: Endo motor mode: root canal preparation. Apex locator mode: root canal length measurement. Multi-function mode: undertake root canal measurement and preparation.

C-SMART-MINI AP: The Endo Moto device C-SMART-MINI AP is a low-speed rotating oral equipment mainly used for root canal preparation and root canal measurement. The product is a portable device powered by built-in lithium batteries and charged by the adapter. LCD displays parameters such as speed, torque, apex position, etc. Users can also set and modify by keys, and provide design of functional check, calibration, set dominant hand and factory reset. The Endo Motor device is an endodontic treatment motorized handpiece with root canal measurement capability. It can be used to enlarge the canals while monitoring the position of the file tip inside the canal. It can be used as a low-speed motorized handpiece and device for measuring canal length. This device must only be used in hospital environments, clinics or dental offices by qualified dental personnel. The Endo Motor device C-SMART-MINI AP is intended to be sterilized prior to use. The material composition of root canal files that can be used with the Endo Motor device C-SMART-MINI AP is Nickel titanium (NiTi). These files are not included in the submission. There are three working modes as: Endo motor: Prepare the root canal, without apex locator function. Apex Locator: Measure the length of the root canal, without motor function. Multi-function: Measuring the length while root canal preparation.

C-Smart-mini: The Endo Motors device C-Smart-mini is a low-speed rotating oral equipment mainly used for root canal preparation. The product is a portable device powered by built-in lithium batteries and charged by the adapter. LCD displays parameters such as speed, torque, rotary files program, etc. Users can also set and modify by keys, and provide design of calibration and screen display for right- or left-handed user. The Endo Motor device is an endodontic treatment motorized handpiece. It can be used to enlarge the canals. It can be used as a low-speed motorized handpiece. This device must only be used in hospital environments, clinics or dental offices by qualified dental personnel. The Endo Motor device C-Smart-mini is intended to be sterilized prior to use. The material composition of root canal files that can be used with the Endo Motor device C-Smart-mini is Nickel titanium (NiTi). These files are not included in the submission.

The provided text does not describe the acceptance criteria and the study that proves the device meets the acceptance criteria. Instead, it is a 510(k) premarket notification for an "Endo Motor" device, outlining its features and comparing it to a predicate device to claim substantial equivalence.

While the document references "Accuracy Testing (Internal test methods to demonstrate the apex position measurement accuracy of ±0.5mm)" among its non-clinical tests, and explicitly states "No clinical study is included in this submission," it does not provide the detailed information requested regarding acceptance criteria and a study proving those criteria are met for the device's performance.

Therefore, I cannot extract the requested information from the provided text.

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For root canal cleaning. The instrument must only be used in hospital environments, clinics or dental offices, by qualified practitioners.

The Endo Ultrasonic Activator is mainly used for root canal cleaning.It mainly contain handpiece, sleeve, wrench, adapter and tip. The ultrasonic frequency generated by the CPU is driven by the drive circuit to drive the piezoelectric ceramic transducer, using the reverse piezoelectric effect to produce the ultrasonic vibration, motivating the working tip to produce the resonance, and using the cavitation and sound flow effect generated by the ultrasonic vibration to wash the root canal swing.

The provided text describes the regulatory clearance of a medical device, the "Endo Ultrasonic Activator," and its substantial equivalence to a predicate device. It contains a comparison table of characteristics and analysis of differences, but it does not describe specific acceptance criteria and a study proving the device meets those criteria in the typical format one would expect for an AI algorithm's performance.

This document is a 510(k) summary for a physical medical device (an ultrasonic activator for root canal cleaning), not an AI/ML powered device. Therefore, the requested information components related to AI/ML device performance (like sample sizes for test/training sets, data provenance, expert ground truth, MRMC studies, standalone performance, etc.) are not applicable and are not present in the provided text.

The "Non-Clinical Test Conclusion" and "Substantially Equivalent (SE) Comparison" sections describe how the device meets various safety and performance standards relevant to non-AI medical devices.

Here's an attempt to extract relevant information while acknowledging the non-AI nature of the document:

1. Table of Acceptance Criteria and Reported Device Performance

For a physical medical device, "acceptance criteria" are typically compliance with recognized standards. The "reported device performance" is demonstrated through testing against these standards and comparison to a predicate device.

2. Sample size used for the test set and the data provenance
Not Applicable (N/A). This document refers to the testing of a physical medical device, not an AI/ML algorithm that would typically have a "test set" of data. The testing involved compliance with various engineering and safety standards, likely through bench testing and material evaluations.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
N/A. No ground truth establishment by experts for a test set is described as this is not an AI/ML device.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
N/A. No test set or corresponding adjudication method is described.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
N/A. This is not an AI/ML device, so no MRMC study or AI assistance effect size is discussed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
N/A. This is not an AI/ML device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
N/A. No ground truth is described in the context of an AI/ML algorithm. The "truth" for this device's performance is its compliance with engineering, safety, and biocompatibility standards, and demonstrating the same fundamental operating principle as a legally marketed predicate device.

8. The sample size for the training set
N/A. This is not an AI/ML device.

9. How the ground truth for the training set was established
N/A. This is not an AI/ML device.

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For light curing polymerization of dental composites, luting materials, cements and other light cured materials.

The LED Curing Light is used for light curing polymerization of dental composites, luting materials, cements and other light cured materials. The device is a cordless pen style, LED light polymerization device for use by dental professionals in dental offices or dental laboratories.

The LED Curing Light protect the handpiece from gross contamination and prevent cross infection between patients by applying the single use protective sleeve. The protective sleeve (patient contact part) is made of PP material.

DB686 NANO:
The LED Curing Light DB686 NANO adopts the principle of ray radiation to solidify the light sensitive resin by shooting at it in a short time. It is composed of handpiece, cure tip, battery pack, charging base, adapter and protective sleeve. The handpiece contains the Rotary switch, Indicator light and Start key.

The LED Curing Light DB686 NANO has one mode namely: Curing light mode.

DB686 SWIFT:
The LED Curing Light DB686 SWIFT adopts the principle of ray radiation to solidify the light sensitive resin by shooting at it in a short time. It is composed of handpiece, cure tip, battery, charging base, adapter and protective sleeve. The handpiece contains the Power/Start button, Mode/ Timer button and LED Display.

The LED Curing Light DB686 SWIFT integrates three modes namely: soft up mode, high power mode and orthodontic mode.

The provided text describes a 510(k) premarket notification for a medical device called "LED Curing Light" (models DB686 NANO and DB686 SWIFT). It aims to demonstrate substantial equivalence to a predicate device (D-Lux+) and a reference device (Bluephase Style 20i) rather than presenting a study where the device meets specific acceptance criteria in a clinical or performance assessment.

Therefore, much of the requested information (acceptance criteria table, sample size, ground truth, expert qualifications, MRMC study, standalone performance) is not available in this document. The document focuses on regulatory compliance and comparison to existing devices.

Here's an attempt to extract the relevant information based on the prompt's structure:

1. A table of acceptance criteria and the reported device performance

This document does not present a table of acceptance criteria and reported device performance in the typical sense of a clinical study or a specific performance benchmark for the device itself. Instead, it demonstrates compliance with recognized medical device standards and outlines the specifications of the proposed device compared to predicate devices to establish substantial equivalence.

The "acceptance criteria" here are essentially the standards the device was tested against to confirm its safety and effectiveness, inferred from the non-clinical tests. The "reported device performance" is given in terms of features and conformity to these standards.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not specify a "test set" in the context of clinical data or performance data with a specific sample size. The tests conducted are non-clinical, related to compliance with standards (e.g., biological evaluation, electrical safety). The nature of these tests does not typically involve sample sizes in the same way clinical studies do. The data provenance is implied by the testing against international standards, but specific country of origin or retrospective/prospective nature isn't stated for the non-clinical tests.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. This document refers to non-clinical tests and demonstrations of compliance with standards, not a study involving expert-established ground truth for a test set of data.

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

Not applicable. There is no mention of a test set requiring adjudication in the context of this 510(k) submission.

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

Not applicable. The device is an "LED Curing Light," which is a physical device used for polymerization, not an AI-assisted diagnostic or interpretative tool. Therefore, an MRMC study or AI-related effectiveness is not relevant.

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

Not applicable. The device is a physical LED curing light and does not involve an algorithm working in "standalone" mode.

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

Not applicable. For the non-clinical tests, "ground truth" would be defined by the technical specifications of the device and the requirements of the standards themselves (e.g., a certain current tolerance for electrical safety, or lack of cytotoxic effect in a cell culture test). There is no "expert consensus" or "pathology" in the context of this device's non-clinical testing.

8. The sample size for the training set

Not applicable. This is a 510(k) submission for a physical medical device, not an AI/machine learning model, so there is no training set.

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

Not applicable. As there is no training set, this question is not relevant.

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C-Sailor Pro: This device is intended for use in dental oral surgery and dental implant. The main unit is designed to be used with a specific dental micromotor that drives dental handpieces fitted with appropriate tools to cut hard tissues in the mouth. It must only be used in hospital environments, clinics or dental offices by qualified dental personnel.

C-PUMA MASTER: The Dental Electrical Motor is intented for use in dental implant. The main unit is designed to be used with a specific dental micromotor that drives dental handpieces fitted with appropriate tools to the mouth. This device is designed for use by a trained professional in the filed of general dentistry.

The proposed device is used to provide the driving force of dental mobile phone for dental surgery. The functions corresponding to the dental operation steps are preset through the host or foot switch, and the electric energy and signal are transmitted to the motor through the motor cable. The motor drives the mobile phone, and the mobile phone drives the dental operation instruments to perform the operation.

The Dental Implantation Systems(C-Sailor Pro) consists of the Foot Control, AC Electrical Cord, Motor (With Cable), Handpiece Stand, Tube Holder, Spare Fuse, Handle (Foot control), and Stand for use with specific Motors. The Dental Electrical Motors(C-PUMA MASTER) consists of the Control Unit, Electrical Motor, Adaptor, Power Cord, Handpiece Stand and Motor Shaft Plug for use with specific Motors.

The provided text describes a 510(k) premarket notification for "Dental Implantation Systems, Dental Electrical Motors." This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, primarily through non-clinical testing and comparison of technical specifications.

It's crucial to understand that this document does not describe a study involving an AI/ML algorithm or its performance criteria. The device in question is a dental electromechanical system, not a software-as-a-medical-device (SaMD) or an AI-enabled device that would require the types of acceptance criteria and performance studies detailed in the prompt's request.

Therefore, many of the requested points, such as "effect size of how much human readers improve with AI vs without AI assistance," "standalone (i.e. algorithm only without human-in-the-loop performance)," "number of experts used to establish ground truth," and "sample size for training set," are not applicable to this submission.

However, I can extract information related to the closest concept of "acceptance criteria" and "study" as presented for this type of medical device submission.

Acceptance Criteria and Device Performance (as inferred from a 510(k) for an electromechanical device)

For this type of device, "acceptance criteria" are typically the standards compliance and functional equivalence to the predicate device. The "study" proving this involves non-clinical bench testing to demonstrate adherence to specific performance and safety standards, and a comparison of key technical specifications with the predicate device.

Here's an interpretation based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document does not specify a "sample size" in terms of patient data or clinical cases, as no clinical study was conducted. For non-clinical bench testing, the "sample size" would refer to the number of devices or components tested. This is typically determined by the testing standard requirements but is not explicitly stated here (e.g., "1 device tested for electrical safety," etc.).
• Data Provenance: The data comes from non-clinical bench testing performed by the manufacturer (Foshan COXO Medical Instrument Co., Ltd.) in China. The testing validates compliance with international standards (e.g., ANSI, IEC, ISO). The tests were conducted to verify that the device "met all design specifications" and was "Substantially Equivalent (SE) to the predicate device." It is retrospective in the sense that it's a report of completed tests, not prospective patient enrollment.

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

• Not Applicable. For this type of electromechanical device and 510(k) submission, "ground truth" as established by medical experts for diagnostic accuracy is not relevant. The "ground truth" in this context is the compliance with engineering and safety standards, verified through objective laboratory measurements and tests, and the functional specifications of the predicate device.

4. Adjudication Method for the Test Set

• Not Applicable. Adjudication methods (like 2+1, 3+1) are used to resolve discrepancies in expert readings for diagnostic accuracy studies. This submission relies on objective engineering and performance conformity with standards and the predicate device.

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

• No. No clinical study, and therefore no MRMC study, was conducted or submitted. The document explicitly states: "No clinical study is included in this submission."

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

• Not Applicable. This is an electromechanical dental device, not an algorithm. Therefore, "standalone algorithm performance" is not a concept relevant to this submission.

7. The Type of Ground Truth Used

• The "ground truth" for this submission is based on:
  • Compliance with recognized international standards (e.g., ANSI, IEC, ISO) for medical device safety, electrical performance, EMC, biocompatibility, and specific dental equipment requirements.
  • Technical specifications and performance data of the legally marketed predicate device (NAKANISHI INC.'s Surgic Pro, Surgic Pro+ K173905).
  • Bench test results demonstrating the proposed device's adherence to its design specifications and functional equivalence.

8. The Sample Size for the Training Set

• Not Applicable. There is no "training set" in the context of an AI/ML algorithm. This is an electromechanical device.

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

• Not Applicable. As there is no training set, there is no ground truth establishment for one.

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The Root Apex Locator is used to detect the apex of root canal. This device must only be used in hospital environments, clinics or dental offices by qualified dental personnel.

The Root Apex Locator C-ROOT I is a oral equipment used for root canal measurement. The device includes a TFT colour display with touch panel displays parameters such as battery status, connection status of test wire and apex position, etc. Users can also set and modify the sound level, brightness level, DR'S CHOICE via a touch panel, and provide a functional check of the device and cable.

The Root Apex Locator is a dental device used to detect the apex of the root canal. The acceptance criteria and the study proving the device meets these criteria are detailed below, primarily based on the accuracy testing.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document mentions "Internal test method" for accuracy testing. It does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective nature of the data).

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

The document does not specify the number of experts used or their qualifications for establishing ground truth for the test set. It only mentions "Internal test method" for accuracy.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for the accuracy test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. The study focuses on the device's standalone accuracy and compliance with various non-clinical standards, and substantiates equivalence to a predicate device. There is no mention of human readers improving with AI assistance, as this is not an AI-powered device.

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

Yes, a standalone performance test was done for the device's accuracy. The "Accuracy Testing" section explicitly states that the "Internal test method demonstrated that the apex position measurement accuracy of the proposed Root Apex Locator C-ROOT I meets the requirement of ±0.5mm." This indicates a measurement of the device's intrinsic performance.

7. The Type of Ground Truth Used

The type of "ground truth" for the accuracy testing is implied to be a precise measurement of the actual apex position, against which the device's measurement is compared. The document does not specify if this was established by expert consensus, pathology, or outcomes data. However, for a root apex locator, the ground truth would typically be a verified measurement of the true working length (e.g., direct measurement on extracted teeth or high-resolution imaging).

8. The Sample Size for the Training Set

The device described is a medical instrument (Root Apex Locator), not an AI/ML algorithm that typically requires a 'training set'. Therefore, the concept of a training set and its sample size is not applicable in this context. The performance evaluation is based on non-clinical testing for accuracy, safety, and compliance with standards.

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

As this is not an AI/ML algorithm, there is no training set and thus no ground truth establishment for a training set. The device's functionality is based on bioelectrical principles for sensing the root apex, not on learned patterns from a training dataset.

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