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The DMX is a radiographic system used in hospitals, clinics, and medical practices. The DMX enables radiographic exposures of the whole body including: skull, chest, abdomen, and extremities and may be used on pediatric, adult, and bariatric patients. It can also be used for intravenous, small interventions (like biopsy, punctures, etc.) and emergency (trauma, critically ill) applications. Exposures may be taken with the patient sitting, standing, or in the prone position. The DMX is not meant for mammography. The DMX can use a mobile (wired) or portable (wireless) digital detector (not provided with system) for generating diagnostic images by converting x-rays into electronic signals. The DMX is also designed to be used with conventional film/screen or Computed Radiography (CR) cassettes

The DMX System is a permanently-installed diagnostic x-ray system for general purpose radiographic imaging for use in hospitals, clinics, and medical practices. It is intended to produce diagnostic x-ray images of human anatomy.

The DMX System enables radiographic exposures of the whole body including: skull, chest, abdomen, and extremities, and may be used on pediatric, adult, and bariatric patients. Exposures may be taken with the patient sitting, standing, or in the prone position. The resultant images are evaluated by a radiologist within the diagnostic process prior to the development of a treatment plan. It is not intended for fluoroscopy, angiography, or mammography.

The DMX System typically includes a tube support, x-ray tube, radiographic table, radiographic wall stand, and collimator. Systems that include the overhead tube crane provide autotracking of the tube crane based on the position of the radiographic table or wall stand.

The provided text describes a medical device, the DMX radiographic system, and outlines its substantial equivalence to a predicate device, the OTC12D Auto. However, it does not contain information about acceptance criteria or a study proving the device meets specific acceptance criteria in the context of an AI/ML algorithm's performance. The document is a 510(k) summary for an X-ray system, focusing on its safety, effectiveness, and substantial equivalence to an existing device for general radiographic imaging.

Therefore, I cannot provide the requested information regarding acceptance criteria and studies proving an AI device meets them. The document primarily discusses the physical components and regulatory compliance of a conventional X-ray system.

To answer your request, here's what could be inferred if this were an AI device undergoing a performance study:

1. Table of Acceptance Criteria and Reported Device Performance:
The provided text does not contain any acceptance criteria or reported device performance for an AI/ML algorithm. The tables in the document compare components and general functionality of the DMX system to its predicate, not performance metrics like sensitivity or specificity for diagnosis.

2. Sample Size Used for the Test Set and Data Provenance:
Not applicable. The document does not describe a test set or data provenance for an AI/ML algorithm.

3. Number of Experts Used to Establish Ground Truth and Qualifications:
Not applicable. The document does not describe the establishment of a ground truth for an AI/ML algorithm.

4. Adjudication Method for the Test Set:
Not applicable. The document does not describe a test set or adjudication method for an AI/ML algorithm.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
Not applicable. The document does not mention an MRMC study or AI assistance for human readers.

6. Standalone (Algorithm Only) Performance Study:
Not applicable. The document does not mention a standalone performance study for an AI/ML algorithm.

7. Type of Ground Truth Used:
Not applicable. The document does not describe the type of ground truth for an AI/ML algorithm.

8. Sample Size for the Training Set:
Not applicable. The document does not describe a training set for an AI/ML algorithm.

9. How the Ground Truth for the Training Set Was Established:
Not applicable. The document does not describe how ground truth was established for a training set for an AI/ML algorithm.

In summary, the provided FDA 510(k) summary for the DMX X-ray system focuses on the substantial equivalence of its hardware and general functionality to a predicate device. It does not contain any information related to the performance evaluation or clinical studies of an AI/ML device.

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

This is a motorized mobile diagnostic x-ray system. The MDR16 Mobile Direct Radiographic System facilitates X-ray examinations, in situations where it is not possible to transport the patient to a ward with fixed equipment. The unit is stable and precise, yet easy to maneuver due to smooth battery-powered motorization. Electric tube unit and wheel locks, 180º column rotation, and a simple user interface provide for add operator convenience and rapid patient positioning. The MDR17 System allows the acquisition of X-ray images on digital panel, CR, or film, by setting techniques based on anatomic area. Technique presets can be customized. Immediate image display after acquisition, and the possibility of immediate transmission to PACS, help minimize workflow time. Instructions for use are included within the device labeling, and the information provided will enable the user to operate the device in a safe and effective manner. Furthermore, the intended operators of the MDR17 Mobile Direct Radiographic System are health care professionals familiar with and responsible for the x-ray examinations being performed. To minimize electrical, mechanical, and radiation hazards, Del Medical, Inc. adheres to recognized and established industry practice, and all equipment is subject to final performance testing. The digital x-ray panel includes automatic exposure detection. Two different size panels are available: 35 x 43 cm or 24 x 30 cm. The software is compatible with either panel via menu setting.

The provided text does not contain information about acceptance criteria for device performance or a study demonstrating that the device meets such criteria in terms of diagnostic accuracy or clinical outcomes. The document is a 510(k) premarket notification for a mobile X-ray system (MDR17 Mobile Direct Radiographic System), focusing on proving substantial equivalence to a predicate device (RadPRO® Mobile 40kW).

The "Performance Testing" section primarily discusses bench testing for electrical safety, mechanical safety, EMC, and software, and clarifies that clinical testing was not required for a determination of substantial equivalence because the digital X-ray receptor panel had already received FDA clearance.

Therefore, I cannot fulfill the request to provide the acceptance criteria and study details related to device performance in the context of diagnostic accuracy, human reader improvement, or standalone algorithm performance, as this information is explicitly stated as not being required or performed in this submission.

However, I can extract the information provided about the testing that was conducted:

Here's the relevant information based on the provided text, focusing on the evaluations performed for K173018, even though it highlights the absence of clinical performance studies:

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

Since this is a substantial equivalence submission relying on bench testing for safety and electrical/mechanical performance, and not a clinical performance study measuring diagnostic accuracy, there are no specific "acceptance criteria" presented in terms of diagnostic metrics (e.g., sensitivity, specificity, AUC) for the device itself. Instead, the "acceptance criteria" are implied by adherence to recognized consensus standards for safety and electrical characteristics.

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

This information is not provided as no clinical performance study or test set for diagnostic accuracy was conducted or required. The testing referred to is bench testing against engineering standards.

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)

This information is not provided as no clinical performance study requiring expert ground truth establishment was conducted or required.

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

This information is not provided as no clinical performance study requiring adjudication was conducted or required.

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, an MRMC comparative effectiveness study was not done. The submission explicitly states, "Clinical testing is not required for a determination of substantial equivalence." This device is a mobile X-ray system, not an AI-powered diagnostic tool.

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

No, a standalone performance study was not done. This device is a hardware X-ray system, not an algorithm, and clinical testing was not required.

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

This information is not applicable as no clinical performance study requiring ground truth was conducted. For the bench testing, the "ground truth" was adherence to the specifications of the referenced international and national consensus standards.

8. The sample size for the training set

This information is not applicable as this submission is for a hardware medical device (X-ray system), not a machine learning or AI algorithm that requires a training set.

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

This information is not applicable as this submission is for a hardware medical device (X-ray system), not a machine learning or AI algorithm.

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The OTC12D Auto System is a radiographic system used in hospitals, clinics, and medical practices. The OTC12D Auto System enables radiographic exposures of the whole body including; skull, chest, abdomen, and extremities and may be used on pediatric, adult, and bariatric patients. It can also be used for intravenous, small interventions (like biopsy, punctures, etc.) and emergency (trauma, critically ill) applications. Exposures may be taken with the patient sitting, standing, or in the prone position. The OTC12D Auto System is not meant for mammography. The OTC12D Auto System can use a mobile (wired) or portable (wireless) digital detector (not provided with system) for generating diagnostic images by converting x-rays into electronic signals. The OTC12D Auto System is also designed to be used with conventional film/screen or Computed Radiography (CR) cassettes.

The OTC12D Auto System is a permanently-installed diagnostic x-ray system for general purpose radiographic imaging for use in hospitals, clinics, and medical practices. It is intended to produce diagnostic x-ray images of human anatomy.

The OTC12D Auto System enables radiographic exposures of the whole body including: skull, chest, abdomen, and extremities, and may be used on pediatric, adult, and bariatric patients. Exposures may be taken with the patient sitting, standing, or in the prone position. The resultant images are evaluated by a radiologist within the diagnostic process prior to the development of a treatment plan. It is not intended for fluoroscopy, angiography, or mammography.

The OTC12D Auto System typically includes a tube support, x-ray generator, x-ray tube, radiographic table, radiographic wall stand, and collimator. Systems that include the overhead tube crane provide auto-tracking of the tube crane based on the position of the radiographic table or wall stand.

The provided text is a 510(k) summary for the Del Medical, Inc. OTC12D Auto Radiographic System (K152767). It describes the device and claims substantial equivalence to a predicate device, the Siemens Multix Fusion (K121513).

However, this document does not describe a study that explicitly establishes acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, accuracy for detecting a specific condition) for the OTC12D Auto system derived from image analysis. Instead, the document focuses on demonstrating substantial equivalence in terms of safety and technical functionality compared to the predicate device.

Here's an analysis based on the provided text, highlighting what is and isn't available:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes performance in terms of compliance with various consensus standards for safety and general functionality, rather than diagnostic accuracy. The "acceptance criteria" appear to be meeting these standards and demonstrating similar functionality to the predicate.

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

The document does not describe a "test set" in the context of imaging performance data (e.g., a set of patient images to be evaluated for diagnostic accuracy). The testing performed is related to safety and technical standards compliance. Therefore, information about data provenance or sample size for an imaging test set is not available.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

This information is not applicable/not available because no diagnostic performance study (e.g., for detecting a specific disease) is described that would require expert-established ground truth. The device is a radiographic system, and its "performance" in this submission refers to its physical and electrical safety and functional equivalence, not its diagnostic accuracy in interpreting images.

4. Adjudication Method:

Not applicable/not available for the same reasons as point 3.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No MRMC study is mentioned. This submission does not involve AI or algorithms assisting human readers. It describes a conventional X-ray system. Therefore, details about improved human reader performance with or without AI assistance are not applicable/not available.

6. Standalone (Algorithm Only) Performance Study:

No standalone algorithm performance study is mentioned. The device is an X-ray system, not an algorithm for image interpretation. Therefore, this information is not applicable/not available.

7. Type of Ground Truth Used:

Not applicable/not available because no diagnostic performance study is described. The "ground truth" implicitly referred to is compliance with engineering and safety standards, as verified through standard testing procedures.

8. Sample Size for the Training Set:

There is no mention of a "training set" in the context of machine learning or AI. The development and testing of this device relate to hardware and software engineering principles for an X-ray system. Therefore, this information is not applicable/not available.

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

Not applicable/not available for the same reasons as point 8.

Summary of the Study Discussed in the Document:

The study presented in this 510(k) summary is primarily a technical and safety conformance study, rather than a diagnostic performance study. It aims to demonstrate that the OTC12D Auto Radiographic System is substantially equivalent to a legally marketed predicate device (Siemens Multix Fusion) by:

• Comparing Indications for Use: Showing they are identical.
• Comparing Technological Characteristics: Highlighting similarities in components (tube crane, wall stand, table, X-ray tube, collimator, X-ray generator, operator console) and noting that differences do not affect safety or effectiveness.
• Demonstrating Conformance to Consensus Standards: Providing a table of FDA-recognized consensus standards (AAMI ES60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-1-6, IEC 60601-2-54) for electromagnetic compatibility, mechanical and electrical safety, radiation protection, and usability. The document states that testing for verification and validation of the device was found acceptable to support claims of substantial equivalence.
• Risk Management: Stating that identified risks (EMC, mechanical, electrical hazards) were mitigated.

The "study" asserts that "Clinical testing is not required for a determination of substantial equivalence" for this type of device, which further clarifies why diagnostic performance parameters are not provided.

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The DelWorks DR System is intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. DelWorks DR System allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

The DelWorks DR System represents the straightforward integration of a number of digital x-ray receptor panels using digital acquisition software. The DelWorks DR System is compatible with all modern HF generators. DelWorks DR System is a Digital Radiography system, featuring an integrated flat panel digital detector (FPD) The DelWorks DR System is designed to perform digital radiographic examinations as a replacement for conventional film. This integrated platform provides the benefits of PACS with the advantages of digital radiography for a filmless environment and improves cost effectiveness. Many of the compatible panels provide Auto-exposure detection. A synchronization module is available where exposure sync is required. This module connects between the digital panel and the x-ray high voltage generator. It provides "ready" synchronization and optical isolation between the two devices. Some of the detectors feature wireless Wi-Fi connection via a wireless access point. The software features Image Stitching (4 views can be combined into one single view) and other image enhancement features. The system software interacts with and controls technique factors of compatible generators via serial interfaces. DICOM output allows for transmission of images to the hospital radiology information system. The system employs Digital Radiography Operator Console (DROC) software, outputs a DICOM image. A USB "dongle" is provided to assure the authenticity of the software.

The medical device in question is the DelWorks DR System, a digital X-ray system. The documentation provided focuses on establishing its substantial equivalence to a predicate device, the Sedecal Digital Radiographic Upgrade, Model: SDRU-T (K130883), rather than presenting a detailed study with specific acceptance criteria and performance metrics for the DelWorks DR System itself.

Based on the provided text, here's what can be extracted and inferred regarding acceptance criteria and the supporting "study":

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a formal table of quantitative acceptance criteria with corresponding performance metrics for the DelWorks DR System. Instead, it relies on a qualitative assessment of "equal or better image quality" compared to the predicate device.

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

• Sample Size: Not explicitly stated. The document mentions "Clinical images were acquired," implying a set of images, but the number of cases or images is not provided.
• Data Provenance: Not specified. It's unclear where the clinical images were acquired (e.g., country of origin, specific institution) or whether they were retrospective or prospectively collected.

3. Number of Experts Used to Establish Ground Truth and Qualifications

• Number of Experts: "a board certified radiologist" (singular).
• Qualifications of Experts: "board certified radiologist." No mention of years of experience or subspecialty.

4. Adjudication Method for the Test Set

• Adjudication Method: "evaluated by a board certified radiologist." This indicates a single reader evaluation, so no adjudication method (like 2+1 or 3+1) was employed.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• MRMC Study: No, an MRMC comparative effectiveness study was not explicitly described or performed. The evaluation involved a single radiologist making a judgment on diagnostic quality. There is no mention of comparing human readers with and without AI assistance, as the DelWorks DR System itself is a digital imaging system, not an AI-assisted diagnostic tool in the sense of offering interpretations.

6. Standalone (Algorithm Only) Performance Study

• Standalone Performance: Not applicable/not performed in the context of an algorithm's diagnostic performance. The device is a digital X-ray system; its "performance" is tied to image acquisition and display quality for human interpretation. The clinical evaluation focuses on the human interpretation of images produced by the system.
  • Bench Testing: The document does mention "MTF and DQE measurements were supplied by the panel manufacturer in accordance with the FDA guidance document." These are objective, standalone measurements of the detector's physical performance, but they are from the panel manufacturer, not explicitly part of a system-level standalone performance study for the DelWorks DR System as a whole.

7. Type of Ground Truth Used

• Ground Truth: Expert consensus with pathology or outcomes data was not used. The ground truth was based on the qualitative assessment of "good diagnostic quality" by a single board-certified radiologist. This is a form of expert opinion/clinical judgment.

8. Sample Size for the Training Set

• Sample Size: Not applicable/not stated. The DelWorks DR System is an imaging acquisition and display system, not a machine learning algorithm that requires a "training set" in the conventional sense for diagnostic tasks. Its software is configured for image processing and output, but there's no indication of a machine learning-based training process for diagnostic output.

9. How Ground Truth for the Training Set Was Established

• Ground Truth Establishment for Training Set: Not applicable, as there is no mention of a training set for a machine learning algorithm.

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