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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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1417WCC 127um and 1417WCC 140um are indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to replace film or screen based radiographic systems in all general purpose diagnostic procedures. Not to be used for mammography

While 1417WCC 127um digital X-ray detector is identical to 1417WCC (K141566), both 1417WCC 127 um and 1417WCC 140 um are wired/wireless digital solid state X-ray detectors that are based on flat-panel technology. The wireless LAN(IEEE 802.11a/g/n/ac) communication signals images captured to the system and improves the user operability through high-speed processing. These radiographic image detectors and processing unit consist of a scintillator coupled to an a-Si TFT sensor. These devices need to be integrated with a radiographic imaging system. Both devices do not operate as an X-ray generator controller but can be utilized to capture and digitalize X-ray images for radiographic diagnosis. The RAW files can be further processed as DICOM compatible image files by separate console SW (K160579 / Xmaru View V1 and Xmaru PACS/ Rayence Co.,Ltd.) for a radiographic diagnosis and analysis.

The provided text describes Rayence Co., Ltd.'s 510(k) summary for their 1417WCC_127µm and 1417WCC_140µm digital flat panel X-ray detectors. The primary goal of the submission is to demonstrate substantial equivalence to predicate devices, namely 1417WCA (K130935) and 1417WCC (K141566).

Here's an analysis of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with specific thresholds for performance metrics. Instead, it relies on demonstrating "similar" or "superior" performance compared to predicate devices, especially regarding MTF and DQE.

However, based on the provided text, we can infer the performance comparisons made:

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

• Sample Size for Clinical Test Set: Not explicitly stated. The text mentions "sample radiographs of similar age groups and anatomical structures" but does not quantify the number of images or patients.
• Data Provenance: Not explicitly stated. The origin (e.g., country) of the clinical images is not provided. It is not stated whether the study was retrospective or prospective, though the description of taking "sample radiographs" suggests it was likely a prospective acquisition for the purpose of the comparison.

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

• Number of Experts: "a licensed US doctor" is mentioned, implying a single expert.
• Qualifications of Experts: "a licensed US doctor" is the only qualification provided. No specialty (e.g., radiologist) or years of experience are specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The evaluation was performed by a single licensed US doctor, so there was no need for adjudication for consensus among multiple readers.

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

• MRMC Study: No. The study described is a comparison of two devices by a single expert, not an MRMC study comparing human readers with and without AI assistance. The device itself is a digital X-ray detector, not an AI-powered diagnostic tool.

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

• Standalone Performance: Not applicable in the context of an AI algorithm. The device is a hardware detector. However, non-clinical performance (MTF, DQE, NPS) was evaluated for the device itself. This can be considered a "standalone" evaluation of the detector's physical performance characteristics.

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

• Type of Ground Truth: For the clinical evaluation, the "ground truth" was established by the expert opinion of a licensed US doctor based on the visual assessment of diagnostic image quality from sample radiographs. There is no mention of pathology or outcomes data as ground truth. For the technical performance, physical measurements (MTF, DQE) against established standards (IEC 62220-1) served as the ground truth.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. The devices are digital X-ray detectors, not AI algorithms that require training sets.

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

• How Ground Truth for Training Set was Established: Not applicable, as there is no training set for these hardware devices.

Summary of Studies and Evidence:

The submission relies on a combination of technical performance testing and a clinical evaluation to demonstrate substantial equivalence:

• Technical Performance Testing:

  • Standards: IEC 62220-1 for MTF, DQE, and NPS tests.
  • Measurements: MTF and DQE were measured for the 1417WCC_140µm detector and compared to the predicate 1417WCA. The results indicated "similar MTF and DQE performance."
  • Other Tests: Electrical, mechanical, and environmental safety and performance testing according to IEC 60601-1:2005 and IEC 60601-1-2: 2007, which yielded "satisfactory results."
  • Risk Management: FMEA method was used to analyze risks, and identified hazards were reportedly mitigated.

• Clinical Evaluation:

  • Methodology: Sample radiographs of "similar age groups and anatomical structures" were taken using both the 1417WCC_140µm and the predicate 1417WCA device.
  • Assessment: A "licensed US doctor" reviewed the images and rendered an "expert opinion."
  • Findings: The expert found images from the 1417WCC_140µm to be "superior to the same view obtained from a similar patient with the predicate devices," specifically noting better clarity in soft tissues and "little difficulty in evaluating a wide range of anatomic structures necessary to provide a diagnostic review."

The overall conclusion is that based on these non-clinical and clinical considerations, the subject devices are substantially equivalent to the predicate devices in terms of diagnostic image quality, safety, and effectiveness.

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The XR5 diagnostic X-ray system is intended for use on adult and pediatric patients for taking diagnostics radiographic exposure of all body parts and operated by a qualified/trained doctor or technician. The XR5 diagnostic X-ray system is designed to be used with conventional film/screen, CR cassettes or digital detectors. NOT intended for Mammography use.

The XR5 diagnostic X-ray system is used for image capture by using X-rays on a patient's body. The XR5 is a conventional X-ray machine, with an intuitive operation console to provide the user an easy way to manage optimal conditions for quality images. The high frequency generator is capable of delivering the exposition dose appropriate for general X-ray and diagnostic images of a patient. This system is made to use other detector options including: conventional films, CR, or Digital Flat Panel Detectors. Please note that the quality of the image in any detector depends on the manufacture of the receptor device. The XR5 diagnostic X-ray system doesn't provide an AEC feature.

The provided text describes the OSKO, INC. XR5 Diagnostic X-ray System, which is a conventional X-ray machine. However, the document (a 510(k) summary) focuses on demonstrating substantial equivalence to a predicate device (Multix Fusion by Siemens Medical Solutions USA, Inc.) rather than outlining specific acceptance criteria or a dedicated study proving the device meets those specific acceptance criteria in terms of clinical performance metrics.

Instead, the document emphasizes:

• Technical equivalence: Comparing specifications like generator type, image acquisition methods, and the use of FDA-cleared digital detectors.
• Compliance with safety and electrical standards: Referencing IEC 60601-1, IEC 60601-2-54, and EN60601-1-2.
• Performance of individual components: The digital detectors are evaluated based on DQE, MTF, and line resolution, with these parameters serving as indicators of their performance.

Therefore, many of the requested items (e.g., specific acceptance criteria for diagnostic accuracy, sample sizes for test/training sets, expert qualifications, MRMC studies, standalone performance) are not detailed in this type of regulatory submission, as it's not a clinical performance study report for diagnostic accuracy of the overall system.

Here's an attempt to answer the questions based only on the provided text, with many fields explicitly stated as "Not Applicable" or "Not Provided" due to the nature of the document:

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

The document does not explicitly define specific "acceptance criteria" for diagnostic performance of the overall XR5 system as a diagnostic device (e.g., sensitivity, specificity, accuracy for a particular condition). Instead, it relies on demonstrating substantial equivalence to a predicate device by comparing technical specifications and performance of key components (digital detectors). The "reported device performance" primarily refers to the technical specifications and the performance metrics of the digital detectors used with the system.

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 provided. The document states that "Bench performance parameters for the digital detectors are sufficient to demonstrate substantial equivalence to a predicate device" and that "Clinical images are not necessary to establish substantial equivalence based on the previously FDA cleared detectors." This implies that a formal clinical test set with a specific sample size for diagnostic performance was either not conducted or not deemed necessary for this 510(k) submission.
• Data Provenance: Not provided for any clinical data. Non-clinical performance data for the detectors references the IEC 62220-1:2003 Standard.

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/Not provided. No clinical test set to establish ground truth for diagnostic accuracy is described.

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

Not applicable/Not provided. No clinical test set for diagnostic accuracy is described.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

Not applicable/Not provided. This device is a conventional X-ray system, not an AI-powered diagnostic tool, and no MRMC study is mentioned.

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

Not applicable/Not provided. This device is a conventional X-ray system, not an algorithm, and no standalone performance study in this context is mentioned.

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

Not applicable/Not provided for diagnostic accuracy of the overall system. The document does not describe the establishment of clinical ground truth for diagnostic accuracy for the XR5 system itself. For the digital detectors, their performance metrics (DQE, MTF, line resolution) are physics-based measurements rather than clinical ground truth on patient outcomes.

8. The sample size for the training set

Not applicable/Not provided. This device is a hardware X-ray system, not an AI algorithm requiring a training set. The firmware is "programmed with ANSI C language," suggesting traditional software development and testing rather than machine learning training.

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

Not applicable/Not provided. As above, this device is a hardware X-ray system; no training set for an AI algorithm is mentioned.

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