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The AQUARIUS 8600 is intended for use by a qualified doctor or technologist on both adult and paediatric patients for taking diagnostic radiographic exposures of all body parts of the AQUARIUS 8600 provides digital image capture and is intended to replace radiographic film/screen. The x-ray tube and associated equipment are not provided with the proposed sensor. Prescription use only.

The AQUARIUS 8600 is not intended for mammography.

The Aquarius 8600 is a digital radiography sensor which automatically collects x-ray images from an x-ray source. The Aquarius 8600 sensor (flat panel type) collects x-rays and digitizes the images for their transfer and display to a computer. The sensor does not have an x-ray source, which is provided by independent manufacturers. The sensor includes with a flat panel for x-ray acquisition and digitization and a computer (including proprietary processing software) for processing, annotating and storing x-ray images.

This is a 510(k) premarket notification for the AQUARIUS 8600 Digital Radiography Sensor. The core of this submission is to demonstrate the substantial equivalence of the modified device to a previously cleared predicate device.

Based on the provided text, the acceptance criteria and the study proving the device meets those criteria are established through a non-clinical performance evaluation and image comparison rather than a human-in-the-loop clinical trial or a detailed algorithm performance study with predefined metrics like sensitivity/specificity. This is typical for certain types of device modifications or new devices where the primary claim is equivalence in image quality or basic functionality to an existing device.

Here's the breakdown of the information requested, based on the provided document:

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

The document does not explicitly state "acceptance criteria" in the traditional sense of numerical performance thresholds (e.g., specific sensitivity, specificity, or image quality scores). Instead, the acceptance criteria are implicitly met by demonstrating substantial equivalence to predicate devices in terms of:

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Intended for use by a qualified/trained doctor or technologist on both and pediatric patients for taking diagnostic radiographic exposures of the skull, spinal column, extremities, and other body parts on both adult and pediatic patients. Applications can be performed with patient sitting, standing or lying in the prone or supine positions. Not intended for mammography

This device is a medical x-ray image acquisition device. X-rays generated by X-ray generator/ tube that penetrate patient's body are converted to a digital file by the detector. After that the detector sends this digital file to a pc where the companion software has been installed. This software was cleared in our previous submission, K170202. A monitor displays this image. Images can then be transferred via the DICOM protocol. This device is nearly identical to the predicate but now the digital panels have Wi-Fi in addition to Ethernet interfaces. The Aquarius 8600 will be marketed in two possible configurations: Aquarius 8600 1717WCl (tethered or wireless), 17 x 17 inch flat panel as a retrofit package with Magellan software). Aquarius 8600 1417WCl (tethered or wireless), 14 x 17 inch flat panel as a retrofit package with Magellan software).

The provided text is a 510(k) premarket notification for a stationary x-ray system (Aquarius 8600 1417WCI; Aquarius 8600 1717WCI). It describes the device, its similarity to a predicate device, and the non-clinical tests conducted to establish substantial equivalence.

Based on the provided information, no specific acceptance criteria or a dedicated study proving the device meets those criteria are explicitly detailed in a format that would allow for a complete answer to all parts of your request.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (Aquarius 8600 1417TC/1717TC, K170202) and references a cleared flat panel detector (K160810). The testing described is primarily non-clinical.

Here's an analysis of what information can be extracted and what is missing:

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

No explicit table of acceptance criteria is provided. The document states "Performance characteristics" are similar to the predicate and provides some technical specifications (MTF, DQE, Panel Resolution, Pixel Size) for both the predicate and the new device. It notes that the new panels have "slightly better MTF" and "slightly lower DQE," implying these performance characteristics were measured against the predicate's performance rather than predefined acceptance criteria.

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

The document mentions "Clinical images were provided," but explicitly states "these images were not necessary to establish substantial equivalence based on the modifications to the device... but they provide further evidence... that the complete system works as intended."

• Sample Size: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).

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

Not applicable, as the clinical images were not presented as part of a formal study with ground truth established by experts for performance evaluation against a specific clinical claim. They were "further evidence" of system functionality.

4. Adjudication method for the test set

Not applicable, as no formal clinical study with ground truth and expert adjudication is described for the purpose of establishing device performance against acceptance criteria.

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 an x-ray imagine acquisition device, not an AI-powered diagnostic tool. No AI component is mentioned.

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

Not applicable. This device is an x-ray imagine acquisition device, not an algorithm.

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

Not applicable, as no formal clinical study with ground truth for performance evaluation is described. For the non-clinical bench testing, the "ground truth" would be the physical properties and measurements of the device components themselves, following established engineering and physics principles.

8. The sample size for the training set

Not applicable. This is a hardware device (x-ray panel and system), not an AI algorithm requiring a training set.

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

Not applicable. This is a hardware device, not an AI algorithm.

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Intended for use by a qualified/trained doctor or technologist on both adult and pediatric patients for taking diagnostic radiographic exposures of the skull, spinal column, extremities, and other body parts on both adult and pediatic patients. Applications can be performed with patient sitting, standing or lying in the prone or supine positions. Not intended for mammography.

The Aquarius 8600 1717TG and Aquarius 8600 1417TG are digital flat panels, specifically termed solid state digital X-Ray detector. This technology couples a scintillator with an a-Si TFT sensor, and through integration with a radiographic imaging system, x-ray images can be captured and digitalized. The resulting RAW files are DICOM 3.0 compatible allowing image files to be processed by IDC Magellan software.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Device Performance

Study Information:

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

   • Sample Size: Not explicitly stated as a number of images or cases in the provided text for the DQE, MTF, NPS, or visual assessment tests. For the visual assessment, it mentions "laboratory images using phantoms were acquired." These are likely a set of standardized phantom images.
   • Data Provenance: The data for DQE, MTF, and NPS are from "measured" curves, implying direct testing of the device hardware. The visual assessment used "laboratory images using phantoms." This suggests the data is prospectively generated from controlled laboratory settings, not from patient data. The country of origin for the testing is not specified, but the applicant company is located in Canada.

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

   • Number of Experts: One (a single Radiological Technologist).
   • Qualifications: "A Radiological Technologist certified in the United States of America and Canada." Specific experience level (e.g., years) is not provided.

3. Adjudication method for the test set:

   • No adjudication method is described for the visual assessment. A single expert made the determination without mention of a consensus or tie-breaking process. For the DQE, MTF, and NPS, these are quantitative measurements that do not require expert adjudication.

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 MRMC comparative effectiveness study was done. The submission states: "No clinical testing was performed for this special 510(k) submission." The visual assessment mentioned was a comparison of phantom images by a single technologist, not a clinical study involving multiple readers assessing patient cases. Also, this device is an X-ray detector, not an AI-assisted diagnostic tool, so improvement with AI assistance is not applicable in this context.

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

   • This is not applicable as the device is a digital X-ray detector, not a standalone algorithm. Its performance is measured directly through physical parameters (DQE, MTF, NPS) and its ability to produce diagnostic images.

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

   • For the DQE, MTF, and NPS measurements, the "ground truth" is generally considered to be the intrinsic physical properties of the detector, measured against established standards and methodologies.
   • For the visual assessment, the "ground truth" was the subjective opinion of a single certified Radiological Technologist comparing images from the proposed device to the predicate device using phantoms.

7. The sample size for the training set:

   • Not applicable/Not provided. This device is a hardware component (digital flat panel detector) and associated software for image acquisition and processing. It does not employ machine learning or AI models that require specific "training sets." The IDC Magellan software underwent "full system level verification, validation and regression testing" as part of its development, but this is software testing, not ML model training.

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

   • Not applicable, as there is no specific "training set" in the context of machine learning model development for this device. The software validation relies on established software engineering principles and testing against specifications inherent to its function.

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Intended for use by a qualified/trained doctor or technologist on both adult and pediatric patients for taking diagnostic radiographic exposures of the skull, spinal column, chest, abdomen, extremities, and other body parts on both adult and pediatric patients. Applications can be performed with patient sitting, standing or lying in the prone or supine positions. Not intended for mammography.

The Aquarius 8600 1417WC is a digital flat panel (specifically termed solid state digital X-Ray detector), with the option for users to use the detector in either a tethered or wireless mode. This technology couples a scintillator with an a-Si TFT sensor, and through integration with a radiographic imaging system, x-ray images can be captured and digitalized. The resulting RAW files are DICOM 3.0 compatible allowing image files to be processed by IDC Magellan software.

This 510(k) submission describes the Aquarius 8600 1417WC, a digital flat panel X-ray detector. It is a modification of a previously cleared device (Aquarius 8600 1717TC) and integrates a 510(k)-cleared tethered/wireless flat panel detector with existing software and workstation components. The submission focuses on demonstrating substantial equivalence to the predicate device.

Here's an analysis of the provided text in the context of acceptance criteria and supporting studies:

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

The document doesn't explicitly define "acceptance criteria" in a quantitative manner for specific diagnostic tasks. Instead, it compares the technological characteristics and performance metrics of the proposed device (Aquarius 8600 1417WC) with those of the predicate device (Aquarius 8600 1717TC), aiming to demonstrate "similar" or "better" performance, thereby supporting substantial equivalence.

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

• Sample Size for DQE, MTF, NPS: Not explicitly stated as a numerical count of images or measurements. These are physical characteristics of the detector itself, typically measured under controlled laboratory conditions, not on a "test set" of patient images in the traditional sense.
• Sample Size for Diagnostic Similarity: "Laboratory images using phantoms were acquired with the proposed Aquarius 8600 1417WC detector and compared to images acquired with the Aquarius 1717TC predicate device." The number of phantoms or images is not specified.
• Data Provenance: The DQE, MTF, and NPS measurements are laboratory-derived data. The "laboratory images using phantoms" are also laboratory-derived. There is no indication of country of origin for the data; it would likely be from the manufacturer's testing facilities. The tests are non-clinical.

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

• Number of Experts: "A Radiological Technologist certified in the United States of America and Canada has reviewed the images (included in this submission)..." This indicates one radiological technologist was involved.
• Qualifications of Experts: "Radiological Technologist certified in the United States of America and Canada." (No mention of years of experience or specialization beyond general radiology).

4. Adjudication method for the test set:

• No formal adjudication method (e.g., 2+1, 3+1) is described for the image review to establish diagnostic similarity. It appears to be a single reviewer's assessment.

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 device is a digital X-ray detector, not an AI-assisted diagnostic tool. The comparison is between the performance of the proposed detector and a predicate detector, not between human readers with and without AI assistance.

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

• Yes, in spirit, for the detector's physical performance. The DQE, MTF, and NPS measurements represent the standalone performance of the detector hardware. While a human is involved in analyzing the output (e.g., in phantom image review), the core metrics (DQE, MTF, NPS) characterize the intrinsic performance of the detector itself, independent of a diagnostic interpretation by a human.

7. The type of ground truth used:

• For DQE, MTF, NPS: These are objective physical performance metrics measured under controlled laboratory conditions using established methodologies. The "ground truth" is the accurately measured physical response of the detector.
• For Diagnostic Similarity: The "ground truth" is essentially the predicate device's image quality, which is already considered diagnostically acceptable. The expert's role was to confirm that the proposed device's images (of phantoms) were "diagnostically similar" to those of the predicate device. This is a form of expert consensus/comparison against an established benchmark rather than an independent "ground truth" for disease detection.

8. The sample size for the training set:

• Not applicable. This submission is for a digital X-ray detector, which captures images. It does not describe an AI/machine learning model that would require a "training set" of images to learn from. The software (Magellan 3) processes and displays images but is not an AI algorithm in the context of typical training sets.

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

• Not applicable. As no training set for an AI/ML model is described, there's no mention of how ground truth for such a set would be established.

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Intended for use by a qualified/trained doctor or technologist on both adult and pediatric patients for taking diagnostic radiographic exposures of the skull, spinal column, chest, abdomen, extremities, and other and pediatric patients. Applications can be performed with patient sitting, standing or lying in the prone or supine positions. Not intended for mammography.

The Aquarius 8600 1717TC are digital flat panels, specifically termed solid state digital X-Ray detector. This technology couples a scintillator with an a-Si TFT sensor, and through integration with a radiographic imaging system, x-ray images can be captured and digitalized. The resulting RAW files are DICOM 3.0 compatible allowing image files to be processed by IDC Magellan software.

The Aquarius 8600 1717TC and 1417TC represents a modification of our own predicate device cleared under K070079, X3C Digital Radiographic Detector.

The Aquarius 8600 1717TC and 1417TC integrates the 510(k) cleared flat panel detectors (K122173 and K122919) with IDC Magellan software and workstation. There were no changes made to the cleared panels, workstation or software. All components were integrated and tested to make the Aquarius 8600 1717TC and 1417TC medical devices.

The Aquarius 8600 will be marketed in two possible configurations:
Aquarius 8600 1717TC (tethered, 17 x 17 inch flat panel as a retrofit package with Magellan software) referred to as "1717TC" throughout the rest of this document
Aquarius 8600 1417TC (tethered. 14 x 17 inch flat panel as a retrofit package with Magellan software) referred to as "1417TC" throughout the rest of this document.

The provided text describes a 510(k) submission for the Aquarius 8600, a digital flat panel X-ray detector. However, it does not include information about a study that proves a device meets acceptance criteria related to AI/Machine Learning device performance, as there is no AI component mentioned in this submission. The submission is for a radiographic imaging system and focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance data (DQE, MTF, NPS), safety testing, and software lifecycle documentation.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, ground truth establishment, expert adjudication, MRMC study, standalone performance against ground truth, training set details) are not applicable to this specific submission, as they relate to the validation of an AI/ML algorithm rather than a traditional medical imaging hardware component.

I will fill in the relevant information that is present in the document and explicitly state where information is not applicable or not provided.

Acceptance Criteria and Device Performance (Aquarius 8600)

The acceptance criteria here are implicitly defined by demonstrating "substantial equivalence" to a predicate device (IDC X3C Digital Radiographic Detector) through comparable performance metrics and safety standards. The study primarily relies on non-clinical (bench) testing.

1. Table of Acceptance Criteria (based on predicate equivalence) and Reported Device Performance

Note: The increase in NPS values for the Aquarius 8600 at lower spatial frequencies compared to the X3C detector is noted in the table but the document states they have "a similar noise performance profile". This suggests that while raw values may differ, the overall expected noise characteristics for diagnostic purposes were deemed acceptable for substantial equivalence.

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

• Test Set: Non-clinical (phantom) images were used. The document does not specify an exact number of phantom images or specific test scenarios beyond mentioning "Laboratory images using phantoms were acquired."
• Data Provenance: The testing was conducted by Imaging Dynamics Company, Ltd. (IDC) (Canada). The nature of the non-clinical testing (phantoms) means there's no patient data provenance to specify. The study is a pre-market submission for substantial equivalence, relying on bench tests, rather than a clinical trial with retrospective/prospective patient data.

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

• Number of Experts: One expert.
• Qualifications: A "Radiological Technologist certified in the United States of America and Canada." (Note: This is a technologist, not a radiologist, and their role was to review images for diagnostic similarity, not to establish a clinical "ground truth" from patient data.)

4. Adjudication method for the test set:

• Adjudication Method: None explicitly mentioned or applicable beyond the single radiologic technologist's review of phantom images. This was not a multi-reader clinical study requiring adjudication.

5. If a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done:

• MRMC Study: No, an MRMC comparative effectiveness study was not conducted. The submission explicitly states: "No clinical testing was performed for this special 510(k) submission." The evaluation was primarily based on non-clinical performance parameters (DQE, MTF, NPS) and a subjective review of phantom images by one technologist.
• Effect Size of Human Readers Improvement: Not applicable, as no MRMC study with human-in-the-loop AI assistance was conducted.

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

• Standalone Performance: Not applicable. This device is a digital X-ray detector, which is hardware, not an AI algorithm. Its "performance" is measured by physics-based parameters (DQE, MTF, NPS) derived from phantom images, not by an algorithm's diagnostic output against a clinical ground truth.

7. The type of ground truth used:

• Type of Ground Truth: For the quantitative performance metrics (DQE, MTF, NPS), the "ground truth" is established by the standardized measurement methodologies described in relevant international standards and best practices for X-ray detector characterization. For the qualitative image review, the "ground truth" was a subjective assessment by a certified technologist comparing images from the new device to the predicate using phantoms. No clinical "ground truth" (e.g., pathology, clinical outcomes) from patient data was used.

8. The sample size for the training set:

• Training Set Sample Size: Not applicable. This is a hardware device; there is no AI/ML algorithm that requires a "training set" in the context of this 510(k) submission.

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

• Ground Truth Establishment for Training Set: Not applicable, as there is no training set for an AI/ML algorithm.

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