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510(k) Data Aggregation
(112 days)
SCANORA 3DX
Scanora 3Dx 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 3Dx is a Cone Beam Computerized Tomography 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.
The provided text describes a 510(k) submission for the SCANORA 3Dx device, indicating that it is substantially equivalent to a predicate device (SCANORA 3D [K110839]). This type of submission relies on demonstrating similarity to an already approved device rather than presenting new clinical study data to establish effectiveness or meet novel acceptance criteria.
Therefore, the document does not contain a specific table of acceptance criteria and reported device performance based on a dedicated study proving these criteria. Instead, it focuses on comparative technological characteristics and a "preference study" for image quality.
Here's an breakdown of the information that can be extracted, and where information is missing based on your request:
1. Table of Acceptance Criteria and Reported Device Performance:
- Acceptance Criteria: Not explicitly stated as quantifiable metrics for a clinical study. The primary "acceptance" is demonstrated through substantial equivalence to the predicate device.
- Reported Device Performance: The document highlights the technological characteristics of SCANORA 3Dx and compares them to the predicate device. The only "performance" comparison mentioned in a study context is a "preference study" for image quality, but specific metrics from this study are not provided.
Characteristic | SCANORA 3Dx (New Device) | SCANORA 3D [K110839] (Predicate Device) |
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X-ray source | 3D mode: 90 kV, 4-10 mA, pulsed. Pan mode: 60-81 kV, 4-8 mA continuous. kV accuracy +/-5kV. Same x-ray source for 3D and Pan modes. | 3D mode: 90 kV, 4-12.5 mA, pulsed. Pan mode: 60-81 kV, 4-8 mA continuous. kV accuracy +/-5kV. Same x-ray source for 3D and Pan modes. |
Focal spot | 0.5 mm | 0.5 mm |
Image detector(s) | Amorphous Silicon Flat Panel + CCD for panoramic imaging | CMOS Flat Panel + CCD for panoramic imaging |
3D imaging technique | Reconstruction from 2D images | Reconstruction from 2D images |
3D's Field Of View | H50 x Ø50 mm, H50 x Ø100 mm, H80 x Ø100 mm, H140 x Ø100 mm, H80 x Ø165 mm, H140 x Ø165 mm, H180x Ø165 mm - Stitched, H240x Ø165 mm - Stitched | H60 x Ø60 mm, H75 x Ø100 mm, H75 x Ø145 mm, H130xØ145 mm - stitched |
3D's total viewing angle | 360 degrees | 360 degrees |
Pixel size | Amorphous Silicon flat panel: 120 / 240 µm. CCD for panoramic imaging: 48 µm. | CMOS flat panel: 200 µm. CCD for panoramic imaging: 48 µm. |
Voxel size | 100/150/200/250/300/350/400/500 µm | 133/200/250/300/350 µm |
3D scan time | 18 - 34 sec | 10 - 26 sec |
3D's effective exposure time | 2.4 - 6 sec | 2.25 - 6 sec |
Indications for use | 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 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. |
System footprint | H197cm x D140cm x W160cm | H197cm x D140cm x W160cm |
Weight | 310 kg | 310 kg |
Preference Study (Image Quality) | "Results were evaluated by internal reviewers." (No specific metrics or acceptance criteria reported for this study). | (Not applicable for this comparative preference study, as it was the comparison device) |
2. Sample sized used for the test set and the data provenance:
- Test Set Sample Size: "Same phantom" was used for the preference study. The number of images generated is not specified beyond this.
- Data Provenance: The study was conducted by the manufacturer, PaloDEx Group Oy (Finland). The provenance of the phantom data (e.g., country of origin, retrospective/prospective) is not specified.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Number of Experts: "Internal reviewers" evaluated the results of the preference study. The exact number is not stated.
- Qualifications of Experts: Their qualifications are not specified.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- The document only states "results were evaluated by internal reviewers." No specific adjudication method (like 2+1 or 3+1 where disagreements are resolved by a third party) is mentioned. It implies a qualitative "preference" rather than a quantitative ground truth establishment.
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 study was done. The described "preference study" was an image quality comparison between the new device and the predicate device using a phantom, judged by internal reviewers. This is not a comparative effectiveness study involving human readers with and without AI assistance.
- Effect Size: Not applicable as no such study was performed.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- The device is a hardware system (Cone Beam 3D X-ray system) that generates images. The document does not describe any specific algorithm or AI component that would have standalone performance measured without a human-in-the-loop. The mention of "FBP algorithm" refers to a standard image reconstruction technique, not a diagnostic AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- For the "preference study," the ground truth was based on the qualitative "preference" of internal reviewers regarding image quality from a phantom. This is not expert consensus on diagnostic findings, pathology, or outcomes data. It's a subjective assessment of image quality.
8. The sample size for the training set:
- Not applicable. The document describes a medical imaging device (hardware) undergoing a 510(k) process based on substantial equivalence. It does not refer to a machine learning or AI algorithm that would require a "training set" in the context of diagnostic performance evaluation.
9. How the ground truth for the training set was established:
- Not applicable. As above, no training set for an AI algorithm is mentioned or implied.
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(97 days)
SCANORA 3D
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
Acceptance Criteria (Implied) | Reported Device Performance |
---|---|
Technological Characteristics (comparable to predicates) | - X-ray source: 3D mode: 90 kV, 4-12.5 mA, pulsed; Pan mode: 60-81 kV, 4-8 mA continuous; kV accuracy +/-5kV. |
- 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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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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(20 days)
SCANORA 3D
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):
Acceptance Criteria Category | Reported Device Performance |
---|---|
Technological Characteristics | Similar to predicate devices (X-ray generation, detectors, imaging technique, system footprint). |
Image Quality | "Similar image quality to the predicate device" demonstrated via non-clinical comparison. |
Regulatory Compliance | Complies with applicable FDA and FDA recognized performance standards. |
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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