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The Planmeca ProMax 3D Max or Maximity is a system intended to produce two-dimensional (2D) and three- dimensional (3D) digital X-ray images of the dento-maxillo-facial, cervical spine and ENT (Ear, Nose, and Throat) regions at the direction of healthcare professionals as diagnostic support for pediatric and adult patients.

The Planmeca ProMax 3D Max or Planmeca Maximity -x-ray unit uses cone beam computed tomography (CBCT) to produce three-dimensional (3D) images of the maxillofacial and ENT anatomies. Two dimensional (2D) images are produced with tomosynthesis method. In CBCT a cylindrical volume of data is captured in one imaging procedure. The data consists of several hundred sample images which are taken from different directions to cover a certain preprogrammed target area. These samples are used for 3D reconstruction (using a separate 3D reconstruction PC) that can be viewed in three dimensions in the Planmeca Romexis program (on a separate PC system). Ethernet computer networking technology is used.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Planmeca ProMax 3D Max and Planmeca Maximity devices:

The provided document is a 510(k) summary for a medical device and, as such, focuses on demonstrating substantial equivalence to a predicate device rather than detailing comprehensive acceptance criteria and exhaustive study results in the manner one might find in a full clinical trial report or a performance study for novel AI/standalone devices.

Here's a breakdown of the requested information based on the provided text, with acknowledgments where information is not present:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state formal acceptance criteria with numerical targets. Instead, it relies on demonstrating that the device's performance for the expanded indications (ENT region) is clinically usable and comparable to the predicate device.

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

• Sample Size for Test Set: Not specified. The document states "clinical images for nose, sinuses, airways, middle ear, temporal bone and vertebrae" were taken, implying a collection of images, but the exact number is not provided.
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective). The term "clinical images" suggests they were acquired from human subjects, but details are lacking.

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

• Number of Experts: "a specialist" (singular).
• Qualifications of Experts: Only stated as "a specialist." No further details (e.g., radiologist, years of experience, specific sub-specialty) are provided.

4. Adjudication Method for the Test Set

• Adjudication Method: "a specialist" reviewed the images. This implies a single-reader assessment rather than a consensus or adjudication process involving multiple readers (like 2+1, 3+1).

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• MRMC Study: No, an MRMC comparative effectiveness study involving human readers with and without AI assistance was not reported or implied. The device is an imaging system, not explicitly an AI diagnostic tool in this context, and the evaluation focused on image quality for diagnostic use.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: No, a standalone algorithm-only performance study was not explicitly reported. The evaluation described is of the image acquisition and reconstruction system providing images for human interpretation. The "diagnostic support" refers to the images themselves, not an automated diagnostic algorithm.

7. Type of Ground Truth Used

• Type of Ground Truth: The ground truth was established by expert clinical review. The "specialist" deemed the images to be of "clinically usable diagnostic quality," indicating a subjective expert assessment of the image data for diagnostic purposes, rather than being compared to a higher standard like pathology or long-term outcomes data.

8. Sample Size for the Training Set

• Sample Size for Training Set: Not applicable/not provided. The document describes a traditional imaging device, not an AI/machine learning algorithm that requires a training set.

9. How Ground Truth for the Training Set Was Established

• Ground Truth for Training Set: Not applicable/not provided, as there is no mention of an AI/machine learning training set.

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Planmeca ProMax 3D Mid, is a panoramic and cephalometric x-ray unit, which uses Cone Beam Volumetric Tomography (CBVT) to produce three-dimensional images of the human teeth, jaws and skull. The device uses cone shaped x-ray beam projected on to a flat panel detector, and the examined volume image is reconstructed to be viewed in 3D viewing stations. The device is to be operated and used by dentists and other legally qualified health care professionals.

The Planmeca ProMax 3D Max is in principle a conventional digital panoramic/tomography xray system with three-dimensional Cone Beam Volumetric Tomography (CBVT) system add on. The product rotates around the patient and takes still images with a flat panel sensor synchronized to x-ray generator pulsing. A 3D reconstruction engine calculates the cylindrical 3-dimensional volume image, which then is viewed in 3D viewing stations.

This document is a 510(k) summary for the Planmeca ProMax 3D Mid, an X-ray system. It primarily focuses on demonstrating substantial equivalence to previously cleared devices rather than presenting a performance study with acceptance criteria.

Based on the provided text, there is no information regarding acceptance criteria or a study that proves the device meets specific performance metrics. The document is a regulatory submission for premarket notification, establishing "substantial equivalence" to predicate devices. It does not contain the detailed technical performance data typically found in a clinical or standalone performance study report.

Therefore, I cannot populate the requested table or provide answers to most of the questions as the information is not present in the provided text.

Here's an overview of what can be extracted based on your request, highlighting the missing information:

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

• No information provided. The document does not specify any quantitative acceptance criteria or report performance metrics (e.g., sensitivity, specificity, resolution, image quality scores) against such criteria.

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

• No information provided. No test set or data provenance is mentioned as there is no performance study described.

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)

• No information provided. Ground truth establishment for a test set is not discussed.

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

• No information provided. No 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

• No information provided. This device is an X-ray imaging system, not an AI-powered diagnostic tool, and no MRMC study or AI assistance is mentioned.

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

• No information provided. This is an imaging device, not an algorithm, so this concept is not applicable in this context. No standalone performance data is presented.

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

• No information provided. No ground truth is discussed as no performance study is detailed.

8. The sample size for the training set

• No information provided. No training set is mentioned.

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

• No information provided. No training set or ground truth establishment is mentioned.

Summary of available information relevant to regulatory submission:

• Device Name: Planmeca ProMax 3D Mid
• Manufacturer: Planmeca Oy (Helsinki, Finland)
• Intended Use: Panoramic and cephalometric x-ray unit using Cone Beam Volumetric Tomography (CBVT) to produce three-dimensional images of human teeth, jaws, and skull. Operated by dentists and other legally qualified healthcare professionals.
• Product Description: Conventional digital panoramic/tomography X-ray system with a 3D CBVT add-on. Rotates around the patient, takes still images with a flat panel sensor, and reconstructs a 3D volume image for viewing.
• Predicate Devices:
  • K060328: Planmeca ProMax 3D
  • K093590: Planmeca ProMax 3D Max
• Regulatory Classification: Class II, Product Code MUH, Regulation Number 872.1800 (Extraoral Source X-Ray System)
• 510(k) Number: K103689
• Date of Submission: December 14, 2010
• FDA Clearance Date: March 17, 2011

The document's purpose is to demonstrate that the Planmeca ProMax 3D Mid is "similar in design, composition and function" and "as safe and effective" as the predicate devices, thereby establishing substantial equivalence for regulatory clearance without requiring a new, full-scale performance study to meet specific acceptance criteria.

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Planmeca Promax 3D Max, is a three dimensional Cone Beam Volumetric Tomography (CBVT) x-ray system, which is intended to produce three-dimensional images of the human teeth, jaw and skull. The device uses cone shaped x-ray beam projected on to a flat panel detector, and the examined volume image is reconstructed to be viewed in 3D viewing stations. The device is to be operated and used by dentists and other legally qualified health care professionals.

The Planmeca Promax 3D Max is in principle a conventional digital panoramic/tomography xray system with three-dimensional Cone Beam Volumetric Tomography (CBVT) system add on. The product rotates around the patient and takes still images with a flat panel sensor synchronized to x-ray generator pulsing. A 3D reconstruction engine calculates the cylindrical 3-dimensional volume image, which then is viewed in 3D viewing stations.

This 510(k) summary for the Planmeca Promax 3D Max does not include information about specific acceptance criteria or a study that directly proves the device meets such criteria.

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (K060328 Planmeca ProMax 3D). This means the manufacturer is asserting that the new device is as safe and effective as a previously cleared device, rather than providing a new, standalone study against specific performance metrics/acceptance criteria.

Therefore, many of the requested details (sample sizes, expert qualifications, ground truth methods, MRMC studies) are not present in this document.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: Not explicitly stated in terms of specific performance metrics (e.g., image resolution, contrast-to-noise ratio, diagnostic accuracy). The acceptance basis is substantial equivalence to the predicate device.
• Reported Device Performance:
  • Intended Use: To produce three-dimensional images of the human teeth, jaw and skull.
  • Function: Uses a cone-shaped x-ray beam projected onto a flat panel detector; produces a 3D reconstructed volume image viewable in 3D stations.
  • Claim: "Planmeca Promax 3D Max is as safe and effective as the predicate device."

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

• Not applicable as no specific performance study with a test set is described. The submission relies on substantial equivalence.

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

• Not applicable as no specific performance study with a ground truth established by experts is described.

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

• Not applicable as no specific performance study with a test set requiring adjudication 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:

• No MRMC comparative effectiveness study is mentioned. This device is an imaging system, not an AI-assisted diagnostic tool in the sense of improving human reader performance.

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

• This device is an imaging system. Its "performance" is implicitly tied to image quality for human interpretation. There is no description of a standalone algorithm performance study independent of image acquisition.

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

• Not applicable as no specific performance study requiring ground truth is described.

8. The sample size for the training set:

• Not applicable as this is not a machine learning/AI device requiring a training set in the typical sense.

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

• Not applicable.

Summary of Approach:

The manufacturer, Planmeca, used the substantial equivalence pathway to demonstrate the safety and effectiveness of the Planmeca Promax 3D Max. This means they compared their new device to a previously cleared predicate device (K060328 Planmeca ProMax 3D) and asserted that it is similar in design, composition, and function, and therefore "as safe and effective." This type of submission does not typically include detailed performance studies with acceptance criteria, sample sizes, and expert review as one might find for novel diagnostic algorithms.

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Planmeca Promax 3D, is a three dimensional Cone Beam Computed Tomography (CBCT) x-ray system, which is intended for dental radiographic examination and diagnosis of diseases of the teeth, jaw, and oral structures. The device uses cone shaped x-ray beam projected on to a flat panel detector, and the examined volume image is reconstructed to be viewed in 3D viewing stations. The device is to be operated and used by dentists and other legally qualified professionals.

The Planmeca Promax 3D is in principle a conventional digital panoramic x-ray system with three-dimensional Cone Beam Computed Tomography (CBCT) system add on. The product rotates around the patient and takes still images with a flat panel sensor synchronized to x-ray generator pulsing. A 3D reconstruction engine calculates the cylindrical 3-dimensional volume image, which then is viewed in 3D viewing stations.

The provided document is a 510(k) summary for the Planmeca Promax 3D, a Cone Beam Computed Tomography (CBCT) x-ray system. This document focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving performance against specific acceptance criteria. Therefore, several requested sections, particularly those pertaining to detailed study design, sample sizes, and expert adjudication, are not explicitly available in the provided text.

Specifically, K060328 is a 510(k) premarket notification for a new device, and its purpose is to demonstrate that the new device is substantially equivalent to a legally marketed predicate device (3D Accu-i-tomo XYZ Slice View Tomograph # K052587). This process typically involves showing that the new device is as safe and effective as the predicate device, often through comparison of design, composition, and technological characteristics, and sometimes through performance data if there are significant differences. However, the exact "acceptance criteria" in the sense of a numerical performance threshold and a detailed study proving the device meets those criteria in an independent clinical trial is not part of this 510(k) summary as provided.

Here's an attempt to answer the questions based on the available information:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly define acceptance criteria with numerical thresholds or report detailed device performance metrics against such criteria. The "acceptance criteria" in the context of this 510(k) submission are implicitly tied to demonstrating substantial equivalence to the predicate device.

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

Not specified. The provided document does not mention any specific test set, its sample size, or data provenance (e.g., country of origin, retrospective/prospective) for a study assessing the device's performance against defined acceptance criteria. The claim of substantial equivalence is made based on design and functional similarity to the predicate device.

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

Not applicable/Not specified. As no specific "test set" or explicit ground truth establishment process is detailed in the provided 510(k) summary, information regarding the number or qualification of experts for this purpose is absent.

4. Adjudication method for the test set

Not applicable/Not specified. There is no mention of a test set or an adjudication method in the provided document.

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

No. The document describes an x-ray system, not an AI-assisted diagnostic tool. Therefore, an MRMC comparative effectiveness study involving AI assistance for human readers is not relevant to this submission and is not mentioned.

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

Not applicable/Not specified. This is a hardware device (x-ray system), not an algorithm or AI. Standalone algorithm performance is not relevant to this submission.

7. The type of ground truth used

Not specified. Given that no specific study with defined acceptance criteria and performance data is detailed, the type of ground truth used is not mentioned. The submission relies on claiming equivalence to a predicate device already on the market.

8. The sample size for the training set

Not applicable/Not specified. This is a medical imaging device, not a machine learning algorithm. Therefore, the concept of a "training set" in the context of AI development is not relevant to this 510(k) submission and no information is provided.

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

Not applicable/Not specified. As this is not an AI/ML device, the concept of a training set and its ground truth establishment is not applicable.

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