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The ScanX Swift 2.0 is intended to be used for scanning and processing digital images exposed on Phosphor Storage Plates (PSPs) in dental applications.

The ScanX Swift View 2.0 is intended to be used for scanning and processing digital images exposed on Phosphor Storage Plates (PSPs) in dental applications.

The ScanX Swift 2.0 and ScanX Swift View 2.0 are dental devices that scan photostimulable phosphor storage plates that have been exposed in place of dental X- Ray film and allows the resulting images to be displayed on a personal computer monitor and stored for later recovery. It will be used by licensed clinicians and authorized technicians for this purpose. The device is an intraoral Plate Scanner, which is designed to read out all cleared plates of the sizes 0, 1, 2, 3, and 4. The phosphor plates are made of rigid photostimulable material. Intraoral phosphor plate x-ray (also known as phosphor storage plate or PSP x-ray) eliminates the need for traditional film processing for dental radiography. Phosphor storage plates can convert existing film based imaging systems to a digital format that can be integrated into a computer or network system. The intraoral Plates are put into the mouth of the patient, exposed to X-rays and then are read out with the device. The read-out-process is carried out with a 639nm Laser. The laser beam is moved across the plate by an oscillating MEMS mirror. The laser beam stimulates the top coating of the plates, which consists of x-ray sensitive material. Depending on the exposed dose, the coating emits different levels of light. These light particles are then requisitioned by an optical sensor (Photo Multiplier Tube/ PMT) and transferred into an electrical output signal is digitalized and is the data for the digital X-ray image. The data is transmitted via an Ethernet link to a computer. Before the plate is discharged, the remaining data is erased by a LED-PCB. The user chooses which size of plate he has to use and prepares the device by inserting the appropriate plate insert into the device. He then exposes the plate and then puts the plate directly into the insert by pushing it out of the light protection envelope. The user closes the light protection cover and starts the read out process. After the read out process the picture is transmitted to the connected PC, the picture can be viewed and the IP is erased and ready to use for the next acquisition. The main difference between the two models is on the ScanX Swift View 2.0 the display is larger, has touch capability, and can show a preview of the scan image. The device firmware is based on the predicate firmware and is of a moderate level of concern.

The provided text is a 510(k) summary for a medical device (ScanX Swift 2.0, ScanX Swift View 2.0), which focuses on demonstrating substantial equivalence to a predicate device. It does not contain information about acceptance criteria for a specific clinical endpoint or a study proving a device meets such criteria.

Instead, it discusses the technological characteristics, safety, and performance of the device in comparison to a predicate device based on non-clinical testing and engineering principles. The document explicitly states:

• "Summary of clinical performance testing: Not required to establish substantial equivalence."

Therefore, I cannot provide a table of acceptance criteria and reported device performance from a clinical study, nor details about sample sizes, ground truth establishment, or multi-reader multi-case studies, as this information is not present in the provided text.

However, I can extract information related to non-clinical performance testing and technical characteristics, which are used to establish substantial equivalence.

Here's an analysis based on the available information:

Key Takeaways from the Document:

• Device Type: Phosphor Storage Plate (PSP) scanner for dental X-ray images.
• Purpose: Scan exposed PSPs, process digital images, and display/store them.
• Approval Basis: Substantial equivalence to a predicate device (ScanX Edge K202633).
• No Clinical Study: Clinical performance testing was explicitly stated as "Not required to establish substantial equivalence." This means the FDA cleared the device based on non-clinical data and comparison to a legally marketed predicate.

Information Related to Device Performance and Equivalence (Non-Clinical):

The document compares the subject devices (ScanX Swift 2.0, ScanX Swift View 2.0) to the predicate device (ScanX Edge) based on various technical specifications and non-clinical performance metrics.

1. Table of "Acceptance Criteria" (Technical Specification Comparison) and Reported Device Performance (as listed for the subject devices):

Since no acceptance criteria are explicitly stated as pass/fail for a clinical endpoint, I will present the comparative technical specifications as the basis for demonstrating equivalence and "performance" in this context. The "acceptance criteria" here are effectively the predicate device's performance, and the subject device's performance is compared against it for substantial equivalence.

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

• Not explicitly stated for performance testing. The document refers to non-clinical performance testing (MTF, DQE, noise power spectrum) in accordance with IEC 6220-1:2003, which would involve imaging phantoms or test objects.
• Data Provenance: Not specified, but given the manufacturer is German (DURR DENTAL SE), the non-clinical testing likely occurred in a controlled lab environment, presumably in Germany or where their R&D facilities are located. These tests are inherently "prospective" in the sense that they are conducted to characterize the specific device.

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

• Not applicable. The submission states no clinical performance testing was required. For non-clinical tests like MTF/DQE, ground truth is established by the design of the test phantom and the known physical properties being measured.

4. Adjudication method for the test set (for clinical studies):

• Not applicable. No clinical studies were performed.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• No. The document explicitly states: "Summary of clinical performance testing: Not required to establish substantial equivalence." Therefore, no MRMC study was performed.

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

• The device itself is a standalone imaging acquisition and processing system. The performance metrics (MTF, DQE) are inherently standalone measurements of the device's image quality output.
• The ScanX Swift View 2.0 model has a "Stand-Alone-Mode" where it can operate without a connection to a computer, generate image data, and store it on a USB stick. This is a functional feature, not a separate performance study.

7. The type of ground truth used:

• For the non-clinical image quality performance metrics (MTF, DQE, noise power spectrum), the ground truth is established by physical standards and phantoms as defined by the IEC 6220-1:2003 standard. These involve known patterns and controlled radiation exposures to objectively measure the imaging system's capabilities.

8. The sample size for the training set:

• Not applicable. As this is a 510(k) for a hardware device (PSP scanner) and not an AI/ML algorithm requiring a training set in the typical sense, there is no mention of a "training set" for image processing algorithms. The image processing algorithms used within the device are stated to be "the same as cleared in K192743 for the imaging software VisionX," implying they are established and validated algorithms, not newly trained ones for this specific device.

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

• Not applicable, as there is no training set discussed for this device submission.

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The intraoral sensor is intended to convert x-ray photons into electronic impulses that may be stored, viewed and manipulated for diagnostic use by dentists.

The subject device SensorX device is an intraoral x-ray sensor for dental applications. It detects the x-rays and performs the image acquisition, digitizes the image and makes it available for the PC. The x-ray sensor is connected to the computer via the sensor cable, and if required, the USB extension. The x-ray sensor is equipped with protective cover sheaths (previously 510(k) cleared) and placed in the mouth of the patient. For patient comfort, the ergonomic design is based on human intraoral anatomy. SensorX enables high resolution with a minimum radiation dose. It is connected to a computer to produce an image almost instantaneously following exposure. The primary advantage of direct sensor systems such as SensorX, is the speed with which images are acquired. SensorX is activated via the imaging software VisionX (K192743) OR DBSWIN (K203287).

The provided document is a 510(k) Premarket Notification from DÜRR DENTAL SE for their device, SensorX. It primarily focuses on demonstrating substantial equivalence to a predicate device (DEXIS Titanium / KaVo IXS HD) rather than providing detailed acceptance criteria and a study proving the device meets those criteria in a traditional sense (e.g., a clinical trial with statistical endpoints).

Therefore, some of the requested information, particularly regarding specific performance metrics against pre-defined acceptance criteria, multi-reader multi-case studies, and detailed ground truth methodologies for a test set, is not explicitly present in this document. The document primarily relies on non-clinical data (i.e., technical specifications and compliance with standards) and a general statement about clinical images.

However, I can extract the available information as requested:

1. Table of Acceptance Criteria and Reported Device Performance

As specific, quantifiable acceptance criteria with corresponding performance results akin to a clinical trial are not presented in this 510(k) summary, I will infer the "acceptance criteria" from the technological characteristics compared to the predicate device, as substantial equivalence is the goal. The reported "device performance" will be the SensorX's specifications.

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

The document does not explicitly mention a "test set" in the context of an algorithm's performance with a specified sample size. Instead, it refers to "actual dental images were provided which showed excellent resolution and contrast" as part of the non-clinical data. The provenance of these images (e.g., country of origin, retrospective or prospective) is not specified.

3. 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 document. The document states a "clinical evaluation was performed" and "actual dental images were provided," but it does not detail how ground truth was established for these images, nor the number or qualifications of any experts involved.

4. Adjudication Method for the Test Set

This information is not provided 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 does not mention any MRMC comparative effectiveness study. The SensorX is an intraoral x-ray sensor, not an AI-assisted diagnostic tool.

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

The SensorX device is a hardware component (an intraoral x-ray sensor) that captures images, not a standalone algorithm. Its performance is evaluated based on its technical specifications and image quality, not as an AI algorithm.

7. The Type of Ground Truth Used

The document states that "actual dental images were provided which showed excellent resolution and contrast." This implies an expert assessment of image quality, but the specific type of ground truth (e.g., expert consensus on specific pathologies, pathology reports, or patient outcomes data) is not detailed. Given the device's function as an imaging sensor, the ground truth would likely relate to image quality parameters such and resolution, contrast, and diagnostic interpretability by dentists, evaluated by experts.

8. The Sample Size for the Training Set

The document does not describe the use of a "training set" in the context of an AI algorithm, as the SensorX is a hardware device.

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

This is not applicable, as the document does not describe a training set for an AI algorithm.

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