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Scanora 3D is a Cone Beam 3D x-ray system for imaging the head and neck areas, including the ENT and dentomaxillofacial areas, for use in diagnostic support. Dedicated panoramic imaging is an option. A flat panel detector is used to acquire 3D images and an optional CCD sensor to acquire panoramic images. The device is operated and used by qualified healthcare professionals.

Scanora 3D is a Cone beam 3D x-ray system for Dentomaxillofacial and Head & Neck (ENT) imaging. Dedicated panoramic imaging is an option. In CT mode it generates a conical x-ray beam during rotation around a patient's head and produces two dimensional projection images on a flat panel detector. Three dimensional images are then reconstructed and viewed with 3rd party software. In panoramic mode panoramic and TMJ images can be taken in the classical way on a separate CCD detector.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Scanora 3D device:

Acceptance Criteria and Device Performance

The submission primarily focuses on establishing "substantial equivalence" to predicate devices rather than defining explicit performance acceptance criteria with numerical thresholds. The acceptance is based on demonstrating that the new Scanora 3D device is as safe and effective as existing legally marketed devices.

Table of Acceptance Criteria and Reported Device Performance

• Focal spot: 0.5 mm.
• Image detector(s): CMOS Flat Panel + CCD for panoramic imaging.
• 3D imaging technique: Reconstruction from 2D images.
• 3D's Field Of View: H60 x Ø60 mm, H75 x Ø100 mm, H75 x Ø145 mm, H130xØ145 mm – stitched.
• 3D's total viewing angle: 360 degrees.
• Pixel size: CMOS Flat panel: 200 µm; CCD for panoramic imaging: 48 µm.
• Voxel size: 133/200/250/300/350 µm.
• 3D scan time: 10 - 26 sec.
• 3D's effective exposure time: 2.25 - 6 sec. |
  | Indications for Use (similar to predicates) | - Scanora 3D: Cone Beam 3D x-ray system for imaging the head and neck areas, including the ENT and dentomaxillofacial areas, for use in diagnostic support. Dedicated panoramic imaging is an option. Device operated by qualified healthcare professionals. |
  | Safety and Effectiveness (demonstrated via substantial equivalence) | - "Based upon the similar technological/performance characteristics and image comparison as compared to the predicate devices and successful validation of the Scanora 3D software, the clinical performance of the Scanora 3D is deemed to be substantially equivalent to the predicate devices." |
  | Image Quality (comparable to predicates) | - "Bench test image quality comparison between the Scanora 3D and the predicate devices was performed." (Specific metrics or quantitative comparisons are not provided in the summary.) |
  | Software Validation (successful) | - "The Scanora 3D software has been successfully validated to confirm the performance of this device." |

Study Details

The provided document describes a non-clinical study to demonstrate substantial equivalence, rather than a clinical trial with specific performance metrics against an acceptance criterion.

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

   • Test set sample size: Not explicitly stated as a number of images or cases. The study involved a "Bench test image quality comparison." This typically involves phantom images or controlled test objects, not patient data in the context of this submission.
   • Data provenance: Not explicitly stated. Given it's a bench test, the data would originate from the testing environment (e.g., phantom images generated by the device). It is not specified as retrospective or prospective clinical data.

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

   • This information is not provided in the summary. Since the study was a "bench test image quality comparison," it's unlikely that clinical experts were used to establish ground truth in the traditional sense for diagnostic accuracy. Ground truth for bench tests typically involves known physical properties of phantoms or objective measurements.

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

   • None specified. This type of adjudication is typically used in clinical studies involving interpretation of images by multiple readers, which was not described as part of this submission.

4. 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, an MRMC comparative effectiveness study was not done. The document explicitly states: "Clinical testing has not been conducted on this device." This device is an imaging system, not an AI-assisted diagnostic tool, so "human readers improve with AI vs without AI assistance" is not applicable to this submission. The focus is on the imaging system's inherent capabilities.

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

   • A standalone performance evaluation was done. The "Bench test image quality comparison" evaluates the device itself (hardware and reconstruction software) without human diagnostic interpretation being the primary endpoint of the substantial equivalence claim. The "successful validation of the Scanora 3D software" also represents a standalone assessment of the software's functionality.

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

   • For the "Bench test image quality comparison," the ground truth would likely be based on known physical characteristics of test phantoms or objective measurements pertinent to image quality (e.g., resolution, contrast, noise, geometric accuracy). It is not expert consensus, pathology, or outcomes data, as these are related to clinical diagnostic accuracy, which was not assessed in this submission.

7. The sample size for the training set:

   • This information is not applicable/not provided in the context of this submission. This device is an imaging hardware system with reconstruction software. It does not describe an AI model that requires a "training set" in the machine learning sense. The "software validation" refers to confirming that the device's operational software (e.g., for image acquisition, reconstruction, and basic processing) functions as intended and meets specifications, not training a diagnostic algorithm.

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

   • This information is not applicable/not provided for the reasons stated above (not an AI training set).

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Scanora 3D is a dental cone beam computed tomography x-ray system intended to image teeth, jaw and TMJ areas of the skull. A flat panel detector is used to acquire 3D images and an optional CCD sensor to acquire panoramic images. The device is operated and used by dentists and other qualified professionals.

Scanora 3D is a dental cone beam CT for imaging of teeth, jaw and TMJ areas of the skull. In CT mode it generates a pulsed conical x-ray beam during rotation around a patient's head and produces two dimensional images on a flat panel detector. Three dimensional images are then reconstructed and viewed with software. In panoramic mode panoramic and TMJ images can be taken in the classical way on a separate CCD detector.

The provided text is a 510(k) summary for the Scanora 3D dental cone beam CT system. It does not contain information about specific acceptance criteria, a study proving the device meets acceptance criteria, sample sizes, expert qualifications, or details typically found in a clinical study report.

The document focuses on demonstrating substantial equivalence to predicate devices rather than an independent study with predefined acceptance criteria.

Here's a breakdown of what can be extracted and what information is missing:

Information from the document:

• Device Name: Scanora 3D
• Intended Use: "Scanora 3D is a dental cone beam computed tomography x-ray system intended to image teeth, jaw and TMJ areas of the skull. A flat panel detector is used to acquire 3D images and an optional CCD sensor to acquire panoramic images. The device is operated and used by dentists and other qualified professionals."
• Comparison Basis: Substantial equivalence to predicate devices (Planmeca Promax 3D (K060328) and i-CAT Scanner (K061284)).
• Assessment Method: "A non-clinical image quality comparison demonstrated Scanora 3D produces similar image quality to the predicate device."
• Compliance: "Scanora 3D complies with applicable FDA and FDA recognized performance standards."

Missing Information (not found in the provided text):

• A table of specific acceptance criteria (e.g., resolution, contrast, artifact levels) and reported device performance against those criteria.
• Details of any specific study designed to prove the device met acceptance criteria. The document describes a "non-clinical image quality comparison," but no specific study design, methodology, or results are provided.
• Sample size used for a test set.
• Data provenance (country of origin, retrospective/prospective).
• Number of experts used to establish ground truth or their qualifications.
• Adjudication method.
• Results of a multi-reader multi-case (MRMC) comparative effectiveness study or related effect size.
• Results of a standalone algorithm performance study.
• Type of ground truth used (e.g., pathology, outcomes data).
• Sample size for the training set.
• How ground truth for the training set was established.

Summary Table (based on available information):

Missing Study Details:

Since the document relies on substantial equivalence and a "non-clinical image quality comparison" rather than a detailed device performance study against specific acceptance criteria, most of the requested study details are not present.

The 510(k) summary states: "A non-clinical image quality comparison demonstrated Scanora 3D produces similar image quality to the predicate device." This indicates that some form of internal testing was performed to compare image quality, likely using phantom images or cadaveric specimens, but the specific metrics, methods, sample sizes, and expert interpretations (if any beyond internal engineers) are not disclosed in this summary.

Therefore, it's not possible to answer most of the specific questions about sample size, data provenance, expert ground truth, adjudication, MRMC studies, standalone performance, or training set details from the provided text.

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The Digora PCT or Digipod imaging system is indicated for capturing, digitization and processing of extraoral, maxillofacial, cephalometric and podiatric X-ray images stored in imaging plate recording media.

A digital radiography system for imaging plates located in cassettes. The system may be used with x-ray equipment utilizing film or similar cassettes. The image is recorded on reusable imaging plate which substitutes for conventional x-ray film. The x-ray energy absorbed in the imaging plate remains stored as a latent image. When fed to the device the stored energy is released as an optical emission proportional to the stored energy when the imaging plate is stimulated pixel by pixel by a scanning laser. An optical system collects the emission for photoelectronic system, which converts the emission to digital electronic signals. These signals are processed in a computer system which formats and stores the signals.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Digora PCT or Digipod device:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). The study described is a comparison study against a predicate device, focusing on technical performance parameters rather than a clinical trial with patient data.

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

The document does not mention the use of experts to establish ground truth for a test set. The evaluation primarily focuses on direct technical comparisons of objective metrics (dose, spatial resolution) and a general statement about diagnostic capability, rather than an assessment of diagnostic accuracy by human readers.

4. Adjudication Method for the Test Set

No adjudication method is mentioned as there is no indication of human expert review being part of the test set evaluation.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The study focuses on direct technical comparisons between the device and its predicate, not on the improvement of human readers with or without AI assistance.

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

Yes, a standalone performance evaluation was done. The "Performance data" section describes a comparison of the Digora PCT or Digipod directly against the predicate device (Fuji FCR 9000HQ) in terms of dose requirements and spatial resolution. This is an evaluation of the device's inherent technical capabilities, independent of human interpretation.

7. The Type of Ground Truth Used

The ground truth for the technical performance study appears to be objective physical measurements rather than clinical ground truth like pathology or outcomes data.

• For dose comparison, the ground truth was a "known object" and the "equal pixel value" it produced.
• For spatial resolution, the ground truth was the objective measure of line pairs per millimeter (lp/mm).

8. The Sample Size for the Training Set

The document does not mention a training set. The device described is an imaging plate reader, not an AI or machine learning algorithm that requires a training set. The "processing" mentioned refers to conventional image processing, not AI model training.

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

Not applicable, as there is no mention of a training set for an AI/machine learning model.

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The Cranex Novus dental panoramic equipment is indicated for dental radiographic examinations by producing digital radiographs of dentition, TM-joints and other oral structures.

Cranex Novus is a panoramic extraoral source dental x-ray system, which produces digital images of dentition. Cranex Novus utilizes digital image receptor(CCD). The technique factor settings for panoramic examinations are: 60 kVp or 70 kVp, 7 mA DC and max. 9 s.

The provided text for CRANEX NOVUS does not contain sufficient information to fill out the acceptance criteria table or answer most of the detailed questions about the study that proves the device meets acceptance criteria. The document states:

"Verification and validation testing was successfully performed to confirm that Cranex Novus corresponds with the intended use."

However, it does not provide any specifics about this testing, such as:

• Specific acceptance criteria metrics (e.g., image quality measures, diagnostic accuracy).
• Reported device performance against any criteria.
• Sample size or provenance of data.
• Details about expert involvement or ground truth establishment.
• Whether MRMC or standalone performance studies were conducted.
• Description of the training set.

Therefore, most of the requested information cannot be extracted from the given text.

Here is what can be inferred or explicitly stated from the provided text:

Acceptance Criteria and Device Performance:

Additional Information:

1. Sample size used for the test set and the data provenance: Not specified.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified.
3. Adjudication method for the test set: Not specified.
4. 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 specified.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not specified.
6. The type of ground truth used: Not specified.
7. The sample size for the training set: Not specified.
8. How the ground truth for the training set was established: Not specified.

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The Cranex D dental panoramic equipment is indicated for dental radiographic examinations by producing digital radiographs of dentition, TM-joints and other oral structures. The Cranex D is upgradeable for cephalometric radiography and examinations related thereto.

Cranex D is a panoramic extraoral source dental x-ray system, which produces digital images of dentition. The device is upgradeable for cephalometric radiography. Cranex D utilizes digital image receptor(CCD).

Here's an analysis of the provided text regarding the Cranex D device, focusing on acceptance criteria and study details.

Based on the provided text, the Cranex D device is a dental panoramic x-ray system, and the 510(k) submission primarily focuses on establishing its substantial equivalence to predicate devices rather than presenting a detailed clinical study with specific acceptance criteria and performance metrics for a novel AI or diagnostic algorithm.

Therefore, many of the requested points related to AI performance, expert adjudication, MRMC studies, and standalone performance are not applicable or not explicitly mentioned in this document, as the submission deals with an X-ray imaging device itself, not an AI-powered diagnostic tool.

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

The document does not explicitly state quantitative "acceptance criteria" or "reported device performance" in the way one would for a diagnostic algorithm (e.g., sensitivity, specificity thresholds). Instead, the performance is described in terms of its ability to produce digital images of dentition and its equivalence to predicate devices.

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

• Sample Size for Test Set: Not specified. The document states "Verification and validation testing was successfully performed," but does not detail the size or nature of the test set (e.g., number of patients, images).
• Data Provenance: Not specified. This typically isn't detailed in 510(k)s for X-ray equipment itself, but rather for diagnostic software that processes images.
• Retrospective or Prospective: Not specified.

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 information is relevant for evaluating diagnostic output, not for a device that captures images. The "ground truth" for an X-ray machine is its physical and image-quality performance as per engineering and clinical standards, typically assessed through phantom studies and image quality evaluations rather than expert consensus on patient cases.

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

Not applicable. No expert adjudication method is mentioned, as the "test set" in this context likely referred to technical performance evaluations rather than diagnostic interpretation.

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 Cranex D is an X-ray imaging device, not an AI-assisted diagnostic tool. Therefore, no MRMC study comparing human readers with and without AI assistance would have been performed or reported for this submission.

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

Not applicable. The Cranex D is an X-ray imaging device, not an algorithm.

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

The concept of "ground truth" in the diagnostic sense (e.g., pathology) is not applicable to the device itself. For an X-ray machine, "ground truth" relates to its technical specifications and image quality parameters, which would be verified against engineering standards and phantom measurements. The document does not specify the exact methods for verifying these, only that "Verification and validation testing was successfully performed."

8. The sample size for the training set

Not applicable. This device is an X-ray machine, not a machine learning algorithm that requires a training set.

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

Not applicable. As above, this is an X-ray machine, not an AI algorithm requiring a training set with established ground truth.

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The Cranex Basex D and Cranex Excel D dental panoramic equipments are indicated for dental radiographic examinations by producing digital radiographs of dentition, TM-joints and other oral structures.

Cranex Basex D and Cranex Excel D are panoramic extraoral source dental x-ray systems, which produce digital images of dentition. They are modified from the existing Soredex dental panoramic x-ray systems (K880982) by substantially replacing the film image receptor with a digital receptor(CCD). The technique factor settings are constant for the x-ray tube anode voltage (65kV) and current (6 mA DC),

The provided text is a 510(k) summary for the Cranex Basex D and Cranex Excel D dental panoramic x-ray equipment. It states that "Verification and validation testing was successfully performed to confirm that Cranex Basex D and Cranex Excel D correspond with the intended use." However, it does not contain specific details on acceptance criteria, reported performance, sample sizes, ground truth establishment, or any comparative effectiveness studies.

Therefore, most of the requested information cannot be extracted from this document.

Here's what can be stated based on the provided text:

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

   • Acceptance Criteria: Not specified in the document.
   • Reported Device Performance: Not specified in the document beyond a general statement that "Verification and validation testing was successfully performed."

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

   • Not specified in the document.

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 specified in the document.

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

   • Not specified in the 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

   • The document describes a standalone device (dental panoramic x-ray equipment) that produces digital images; it does not mention any AI component or MRMC comparative effectiveness study involving human readers.

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

   • This is a standalone medical device (x-ray equipment). Its performance is inherently "standalone" in the sense that it acquires images. The document does not describe an algorithm with standalone performance; it describes the performance of the imaging system itself.

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

   • Not specified in the document.

8. The sample size for the training set

   • Not specified in the document. (This device is not an AI algorithm that would typically have a "training set" in the machine learning sense).

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

   • Not applicable/Not specified in the document. (As above, this is an imaging device, not an AI algorithm requiring a training set with ground truth in the usual sense).

Summary of available information:

The 510(k) summary for the Cranex Basex D and Cranex Excel D dental panoramic x-ray equipment states that "Verification and validation testing was successfully performed to confirm that Cranex Basex D and Cranex Excel D correspond with the intended use." However, it does not provide any specific details regarding acceptance criteria, performance metrics, study design, sample sizes, ground truth establishment, or any comparative effectiveness studies.

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The Digora Optime imaging system is indicated for capturing, digitization and The Digora Optime Images stored in imaging plate recording media.

A digital radiography system for intra oral imaging plates located in disposable bags. The system may be used with all x-ray equipment which is designed for intra oral radiography. The image is recorded on reusable imaging plate which substitutes for conventional x-ray film. The x-ray energy absorbed in the imaging plate remains stored as a latent image. When fed to the device the stored energy is released as an optical emission proportional to the stored energy when the imaging plate is stimulated pixel by pixel by a scanning laser. An optical system collects the emission for photo electronic system, which converts the emission to digital electronic signals. These signals are processed in a computer system which formats and stores the signals.

Here's an analysis of the provided text to extract information about the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the sample size used for a test set. It mentions a "comparison between a pixel-value of a known object and the spatial resolution," which suggests some form of testing, but details on the number of images or cases are absent.

The data provenance is not specified.

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 on the number of experts used or their qualifications for establishing ground truth. The statement about "diagnostic capability" implies some form of assessment, but the methodology is not detailed.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method used for the test set.

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

The document does not mention an MRMC comparative effectiveness study. It states that "Digora Optime has also been shown to be able to provide images of equivalent or slightly better diagnostic capability to the predicate device Digora." However, it does not elaborate on the study design or report any effect size.

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

The device described is an "imaging plate reader" that processes digital electronic signals and relies on "auxiliary software (such as Digora for Windows K983267), a PC" for further image processing, display, and archiving. While the device itself is a piece of hardware, the term "standalone" in the context of an algorithm or AI typically refers to the performance of the software processing. The document focuses on the technical performance of the imaging plate reader and its output quality, rather than the standalone performance of an AI algorithm in isolation. Therefore, a standalone algorithm-only performance study as typically understood in AI is not described. The performance described is of the entire system as an image acquisition and digitization device.

7. The Type of Ground Truth Used

The ground truth appears to be based on:

• Known object characteristics: For spatial resolution and pixel-value.
• Comparison to a predicate device's performance: For dose and diagnostic capability.

There is no mention of pathology, expert consensus, or outcomes data being explicitly used as ground truth.

8. The Sample Size for the Training Set

The document does not mention any "training set" or "training data" as
this is not an AI/ML device per se but a medical device for image acquisition.

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

Not applicable, as no training set is mentioned in the context of this device.

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The Minray dental x-ray system is intended to be used for dental radiographic examinations by producing radiographs of dentition, jaws and other oral structures on intraoral digital or film image receptor media.

The Minray dental x-ray system is indicated for dental radiographic examinations by producing radiographs of dentition, jaws and other oral structures on intra oral film or digital image receptor media.

Minray is an extraoral source dental x-ray system, which produces dental images on intraoral digital or film image receptors. The x-ray generator operates on high frequency and has an DC output. There are two selectable anode voltages 60 kV and 70 kV. Anode current is constant 7 mA. Exposure time can be selected from 20 ms to 3.2 s.

The provided text is a 510(k) summary for the Minray Dental X-ray System. It describes the device, its intended use, and states that "Verification and validation testing was successfully performed to confirm that Minrav corresponds with the intended use."

However, this document does not contain the detailed performance data, acceptance criteria, sample sizes, ground truth establishment methods, or information about expert involvement that your request asks for. The document is a regulatory submission summary, not a study report.

Therefore, I cannot fulfill your request with the information provided because:

• Acceptance Criteria and Reported Device Performance: No specific acceptance criteria or quantitative performance metrics (like sensitivity, specificity, accuracy) are mentioned in the document. It only states that verification and validation were "successfully performed."
• Sample Size and Data Provenance: No sample size for test sets or data provenance (country, retrospective/prospective) is provided.
• Number and Qualifications of Experts: There is no mention of experts being used to establish ground truth.
• Adjudication Method: No adjudication method is described.
• MRMC Comparative Effectiveness Study: There is no indication of an MRMC study or an effect size for human readers.
• Standalone Performance: While the device is an X-ray system, the document doesn't present an "algorithm only" standalone performance if AI were involved. It's a hardware device.
• Type of Ground Truth: The document does not specify the type of ground truth used for any testing.
• Training Set Sample Size and Ground Truth Establishment: No information on a training set or how its ground truth was established is provided, as this device is an X-ray generator, not an AI/ML algorithm.

To answer your questions, I would need a different type of document, such as a detailed study report or clinical trial results, which are not present in this 510(k) summary.

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The Digora PCT imaging system is indicated for capturing, digitization and processing of extraoral, maxillofacial and cephalometric x-ray images stored in imaging plate recording media.

A digital radiography system for imaging plates located in cassettes. The system may be used with x-ray equipment utilizing film or similar cassettes. The image is recorded on reusable imaging plate which substitutes for conventional x-ray film. The x-ray energy absorbed in the imaging plate remains stored as a latent image. When fed to the device the stored energy is released as an optical emission proportional to the stored energy when the imaging plate is stimulated pixel by pixel by a scanning laser. An optical system collects the emission for photoelectronic system, which converts the emission to digital electronic signals. These signals are processed in a computer system which formats and stores the signals. Further image processing, display and achieving are carried out with an auxilia software (such as Digora for Windows K983267), a PC and a CRT.

The provided text describes the Digora PCT, an imaging plate reader, and its performance compared to a predicate device (Digora) and a conventional film-screen combination.

Here's the information extracted and organized to answer your request:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the sample size (number of images or patients) used for either the physical performance comparison or the diagnostic capability comparison.

The data provenance is not explicitly mentioned as retrospective or prospective, nor is the country of origin. However, the submitter is "Soredex Instrumentarium Corporation Nilsiankatu 10 - 14 00510 Helsinki Finland," suggesting the testing may have been conducted in Finland.

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

The document does not provide details on the number of experts used or their qualifications for establishing ground truth in the diagnostic capability study. It only states that a "comparison... was made to evaluate the ability of the device to provide images of equivalent diagnostic capability."

4. Adjudication Method for the Test Set

The adjudication method is not described in the provided text.

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

The document does not explicitly mention a multi-reader multi-case (MRMC) comparative effectiveness study. It states a "comparison... was made to evaluate the ability of the device to provide images of equivalent diagnostic capability," which could imply a human reader study, but details about its design (MRMC) and effect size are absent.

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

For the Digora PCT, this device is an imaging plate reader, which is a physical device that processes images. It does not appear to be an AI algorithm in the contemporary sense. Therefore, the concept of a standalone AI performance study (without human-in-the-loop) isn't directly applicable in this context. The performance described relates to the image acquisition and processing capabilities of the hardware.

7. The Type of Ground Truth Used

• Physical Performance: For dose and spatial resolution, the "ground truth" was established based on objective measurements against the predicate device (Digora). For dose, it was "pixel value of a known object." For spatial resolution, it was "lp/mm" (line pairs per millimeter).
• Diagnostic Capability: The ground truth for diagnostic capability was based on a comparison to the diagnostic capability of a "cleared film screen combination" (Kodak T-Mat G film/Lanex Regular intensifying screens). This implies that the accepted diagnostic performance of the film-screen combination served as the benchmark. The method by which this diagnostic capability was assessed (e.g., expert interpretation of images for specific pathologies) is not detailed.

8. The Sample Size for the Training Set

The document does not refer to a "training set" as this device is not an AI/ML algorithm that undergoes a distinct training phase. It is a physical device for image acquisition and processing.

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

As this is not an AI/ML device, the concept of a "training set" and associated ground truth establishment does not apply. The device's performance is characterized through physical measurements and comparisons to established imaging technologies.

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