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The Direct Digitizer, REGIUS SIGMA is an X-ray image reader which uses a stimulable phosphor plate (Plate) as X-ray detector installed in a separate cassette. It reads the image recorded on the Plate and transfers the image data to an externally connected device such as a host computer, an order input device, an image display device, a printer, an image data filing device, and other image reproduction devices. It is designed and intended to be used by trained medical personnel in a clinic, a radiology department in a hospital and in other medical facilities.

This device is not intended for use in mammography.

The Direct Digitizer, REGIUS SIGMA is a compact X-ray image reader which uses a stimulable phosphor plate (Plate) as X-ray detector installed in a cassette, and reads the image recorded on the Plate by inserting a cassette in the entrance slot of this device. By means of laser scan and photoelectric method, this device reads the X-ray image data created in form of a latent image on the Plate exposed by an external X-ray generating device, and converts the read data into digital.

The device is comprised of a reading unit with cassette containing Plate.

The image data transfer to an externally connected device such as a host computer, an order input device, an image display device, a printer, an image data filing device, and other image reproduction devices.

The basic operations of REGIUS SIGMA such as a starting, a shut down, a registration-of-patient, a setting of a various condition are operated with the Medical Image Processing Workstation, ImagePilot (operator console) which is cleared 510(k), K071436.

This 510(k) summary for the Direct Digitizer, REGIUS SIGMA, primarily focuses on demonstrating substantial equivalence to predicate devices through technical comparisons and adherence to safety standards. It does not contain detailed information about acceptance criteria or a specific study proving device performance against such criteria in terms of diagnostic accuracy or clinical effectiveness.

The document states: "The performance test results show that there is no new safety and efficacy issue of the REGIUS SIGMA." However, it does not elaborate on what these performance tests entailed, what specific metrics were measured, nor what were the acceptance criteria for those metrics.

Therefore, many of your requested points cannot be answered from the provided text.

Here's an analysis of what can and cannot be answered:

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

• Cannot be provided. The document does not specify performance acceptance criteria related to diagnostic accuracy or clinical effectiveness, nor does it report specific device performance metrics against such criteria. It mentions meeting safety standards (IEC60601-1 Ed.2, IEC60601-1-2 Ed.3, 21 CFR 1040.10, IEC60825-1) and ISO14971 for risk management, which are general safety and quality standards, not specific performance metrics.

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

• Cannot be provided. The document does not describe any specific clinical or performance test set, its size, or its provenance.

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)

• Cannot be provided. Since no test set is described for diagnostic performance, ground truth establishment methods or expert qualifications are not mentioned.

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

• Cannot be provided. No test set or adjudication method 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

• No MRMC study described. This device is an X-ray image reader (hardware) and does not appear to incorporate AI for diagnostic assistance based on the description. Therefore, an MRMC study comparing human readers with/without AI assistance would not be relevant to this specific device submission as described.

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

• Not applicable/Cannot be determined from the text. This device is hardware for digitizing X-ray images. It's not an AI algorithm.

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

• Cannot be provided. No ground truth for diagnostic performance is mentioned.

8. The sample size for the training set

• Not applicable/Cannot be provided. This is hardware, not a machine learning model, so there is no "training set" in the sense of data used to train an algorithm.

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

• Not applicable/Cannot be provided. As above, no training set for an algorithm is mentioned.

Summary from the document:

The 510(k) submission for the Direct Digitizer, REGIUS SIGMA, focuses on demonstrating substantial equivalence to predicate devices (Direct Digitizer, REGIUS Model 110, and Point-of-Care CR360) based on:

• Similar principles of operation and technological characteristics.
• Performance test results showing no new safety and efficacy issues. (Specific criteria or results are not detailed in this summary).
• Adherence to recognized safety and EMC standards:
  • IEC60601-1 Ed.2 (electrical safety)
  • IEC60601-1-2 Ed.3 (electromagnetic compatibility)
  • 21 CFR 1040.10, IEC60825-1 (radiation safety, specifically laser safety for the reading mechanism)
  • ISO14971 (risk management)

The key takeaway is that this approval is based on demonstrating the new device performs "similarly" to previously cleared devices and meets applicable safety standards, rather than providing a detailed clinical study with specific acceptance criteria for diagnostic performance.

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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 innovaXion FP represents a modification of our own predicate K071402 X3C 1600 plus Digital Radiographic System. We now support the 510(k) cleared Samsung digital panel. The other radiographic equipment is identical to that supplied by Viztek in Ku 102123. We will market the product in four possible configurations:
. innovaXion FP 1600 Plus
innovaXion FP (flat panel as a retrofit package with Magellan FP software) .
. Magellan (software)

Here's a breakdown of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated. The document mentions "Clinical images were acquired" but does not give a specific number.
• Data Provenance: Not explicitly stated regarding country of origin. The study appears to be retrospective in comparison, as "clinical images were acquired and compared to our predicate images," suggesting existing data from the predicate device was used for comparison.

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 abstract does not detail the process of establishing ground truth for the clinical images used in the comparison.

4. Adjudication method (e.g. 2+1, 3+1, none) 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

• No, a multi-reader, multi-case comparative effectiveness study of the device with human readers was not done or described. The study focuses on comparing the new device's images to the predicate device's images.
• This device is a digital X-ray system, not an AI-assisted diagnostic tool, so the concept of human readers improving with AI assistance is not applicable in this context.

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

• The study described is a standalone performance comparison of the device itself (new digital panel and software) against a predicate device, based on acquired clinical images. It assesses image quality and output, not an algorithm's diagnostic performance. Therefore, in a sense, it's a "standalone" evaluation of the imaging system.

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

• The document implies that the ground truth for the clinical images was established by the predicate images themselves serving as the reference. The new device's images were compared to these predicate images to determine if there were "no significant differences between them," implying the predicate images represented an acceptable standard. There's no mention of expert consensus, pathology, or outcomes data being used to establish a separate, independent ground truth.

8. The sample size for the training set

• This information is not applicable as the device is not an AI algorithm that requires a training set in the typical sense. It's a digital X-ray system.

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

• This information is not applicable for the same reason as point 8.

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The DIAMOND-5A,6A,8A Digital Diagnostic X-ray System is indicated for use in generating radiographic images of human anatomy. This device is not intended for mammographic applications.

The digital X-ray imaging system consists of a high voltage (HV) generator, a tube support unit, an X-ray beam limiting device, a wall stand unit, a bucky table unit, a detector, operating software, and a tube, operates on a high-frequency inverter method, and is primarily used in a hospital for diagnosis of diseases in skeletal. respiratory and urinary systems.

The provided 510(k) summary (K102408) for the DRGEM Corporation's DIAMOND-5A, 6A, 8A Digital Diagnostic X-ray System does not contain information related to specific acceptance criteria for device performance or a study demonstrating the device meets such criteria in terms of diagnostic accuracy or clinical effectiveness.

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (Sedecal X-Plus LP Plus Digital, K090238) by showing compliance with electrical, mechanical, environmental safety, and EMC standards, which are considered sufficient for this type of device in the 510(k) pathway.

Therefore, many of the requested details about acceptance criteria, clinical studies, ground truth, and expert involvement are not present in the provided document.

Here's a breakdown of what can be extracted based on the input:

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

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

• Not Applicable / Not Provided. The submission details compliance with engineering and safety standards, not a clinical performance study with a test set of images or patients.

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

• Not Applicable / Not Provided. No clinical performance study requiring ground truth establishment is mentioned.

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

• Not Applicable / Not Provided. No clinical performance study requiring adjudication is mentioned.

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. This is a traditional X-ray imaging system, not an AI-assisted diagnostic device. A MRMC study was not conducted or mentioned.

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

• No. This is a traditional X-ray imaging system, not an algorithm.

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

• Not Applicable / Not Provided. No clinical performance study requiring ground truth is mentioned.

8. The sample size for the training set

• Not Applicable / Not Provided. This is not an AI/machine learning device that would typically have a "training set."

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

• Not Applicable / Not Provided. This is not an AI/machine learning device.

Summary of the Study (as described in the 510(k) summary):

The "study" described in this 510(k) summary is primarily a technical verification and validation (V&V) against recognized electrical, mechanical, environmental, and EMC safety and performance standards (EN/IEC 60601 series). The manufacturer performed these tests to demonstrate that the DIAMOND-5A,6A,8A system operates safely and effectively as an X-ray imaging system, and is substantially equivalent to the predicate device. The results of these tests were deemed "satisfactory," indicating compliance with the standards, which serves as the basis for the safety and effectiveness conclusion. There is no mention of clinical trials or studies related to diagnostic accuracy or clinical outcomes.

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The Direct Digitizer, REGIUS Model 210 is an X-ray image reader which uses a stimulable phosphor plate (Plate) as X-ray detector installed in a separate cassette. It reads the image recorded on the Plate and transfers the image data to an externally connected device such as a host computer, an order input device, an image display device, a printer, an image data filing device, and other image reproduction devices. REGIUS Model 210 also reads the image data of long areas of anatomy and to verify the position for a radiotherapy location. It is designed and intended to be used by trained medical personnel in a clinic, a radiology department in a hospital and in other medical facilities.

This device is not intended for use with FFDM systems

The Direct Digitizer, REGIUS Model 210 is an X-ray image reader which uses a stimulable phosphor plate (Plate) as X-ray detector installed in a separate cassette, and reads the Image recorded on the Plate by inserting a cassette in the entrance slot of this device. By means of laser scan and photoelectric method, this device reads the X-ray image data created in form of a latent image on the Plate exposed by an external X-ray generating device, and converts the read data into digital. REGIUS Model 210 also enables to use of multiple cassette to obtain images of long areas of anatomy and then to present the images as a single composite image (Long Length Imaging feature), and to use Read-Only Cassettes and Exposure-Only Cassettes used for Radiotherapy localization.

Different points between REGIUS Model 210 and REGIUS Model 190, which is approved 510(k) number: K052095 is that REGIUS Model 210 has higher processing capacity than REGIUS Model 190. To increase the processing capacity, the software algorithm is modified. However, the hardware remains unchanged. The exterior appearance is slightly modified.

The basic operations of REGIUS Model 210 such as a starting, a shut down, a registration-of-patient, a setting of a various condition are operated with the optional Image Processing Work Station, REGIUS CONSOLE CS-2000/3000 (510(k) cleared, K051523, July 20, 2005). Then the image data transfer to an externally connected device such as a host computer, an order input device, an image display device, a printer, an image data filing device, and other image reproduction devices.

This document is for a 510(k) premarket notification for a medical device called the "Direct Digitizer, REGIUS Model 210". The document establishes substantial equivalence to a predicate device and includes information about the device's intended use and classification. However, it does not contain the specific details about acceptance criteria, study design, or performance metrics that are requested in your prompt. This is typical for a 510(k) summary, which focuses on regulatory compliance and equivalence rather than detailed clinical trial results.

Therefore, I cannot provide the requested information from the provided text. The document does not describe:

1. A table of acceptance criteria and reported device performance.
2. Sample size used for the test set or data provenance.
3. Number and qualifications of experts for ground truth.
4. Adjudication method for the test set.
5. MRMC comparative effectiveness study or effect size.
6. Standalone performance of the algorithm.
7. Type of ground truth used.
8. Sample size for the training set.
9. How ground truth for the training set was established.

The document primarily focuses on:

• Device Identification: Company, correspondent, submission date, registration number, trade name, classification name, and classification.
• Predicate Device: Direct Digitizer, REGIUS Model 190 (K052095).
• Device Description: An X-ray image reader using a stimulable phosphor plate (Plate) to convert X-ray images into digital data. It also supports Long Length Imaging and Read-Only/Exposure-Only Cassettes for Radiotherapy localization. The key difference from the predicate is a modified software algorithm for higher processing capacity, while hardware remains unchanged.
• Intended Use: For trained medical personnel in clinics, radiology departments, and other medical facilities to read X-ray images from phosphor plates and transfer data to external devices. Not intended for use with FFDM systems.
• Substantial Equivalence: Claimed to be substantially equivalent to the REGIUS Model 190.
• Compliance Standards: IEC 60601-1 (Safety), IEC 60601-1-2 (EMC), 21 CFR 1040.10, IEC 60825-1 (Radiation safety).

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The VeriSuite patient position system is used for verification and correction of the patient's position during a radiotherapy treatment with external beams or charged particles. It is based on stereoscopic X-ray images and DRRs calculated from a CT image series of the treatment region of the patient and information from the treatment planning.

VeriSuite is an image processing system for verification and correction of the patient position during a radiation therapy treatment. The verification or correction is performed by a comparison of X-ray images that are acquired during the treatment with DRRs (digital reconstructed radiographs) calculated from a CT image series of the patient and information from the radiation therapy planning, The correction can also be based on fiducial, radio-opaque markers that are implanted in the patient.

VeriSuite is a system of devices consisting of the VeriSuite software and a number of hardware devices:

• Beam limiting collimator device (Ralco 302)
• X-ray generator (Sedecal XHF 835) -
• X-ray tubes (Varian A277 or A272)
• Flat panel digital imager (Varian 4030E -
  Optional:
  All these hardware devices are legally marketed in the US as listed in previous section D.

This document, a 510(k) submission for VeriSuite 1.8, does not contain information regarding detailed acceptance criteria, the methodology of a study to prove device performance against these criteria, or specific data pertaining to ground truth establishment, expert qualifications, or sample sizes for training and test sets.

The document primarily focuses on:

• Device Identification: Trade names, common names, classification, and product codes of VeriSuite and its components.
• Predicate Device: Details of VeriSuite 1.6 and other predicate devices (X-Ray Generator, X-Ray Tubes, Flat Panel Digital Imager, Collimator).
• Device Description: VeriSuite is an image processing system for verifying and correcting patient position during radiation therapy by comparing X-ray images with DRRs or fiducial markers. It's a system comprising software and legally marketed hardware components.
• Intended Use: Verification and correction of patient position during radiation therapy using stereoscopic X-ray images and DRRs. Emphasizes evaluation and approval by an authorized person, and notes it's not for diagnostic purposes.
• Summary of Technical Considerations: States substantial equivalence to the predicate device.
• FDA Communication: A letter from the FDA confirming the review of the 510(k) premarket notification and determining substantial equivalence for the stated indications for use.
• Indications for Use Statement: A formal statement on the intended use of the VeriSuite patient position system.

Therefore, I cannot provide the requested information as it is not present in the provided text.

To answer your request, the document would need to include sections on:

1. Clinical Performance Study, Validation Study, or Bench Testing: Describing the study design, objectives, and methods for evaluating the device's accuracy and performance.
2. Acceptance Criteria: Specific quantitative thresholds for performance metrics (e.g., accuracy, precision, repeatability) that the device must meet to be considered safe and effective.
3. Study Results: The measured performance of the device against the established acceptance criteria.
4. Sample Size and Data Provenance: Details on the number of cases/patients used, where the data originated (e.g., specific hospitals, countries), and whether it was collected retrospectively or prospectively.
5. Ground Truth Establishment: How the "true" patient position or correction vector was determined for the study data, including the number and qualifications of experts involved, and their adjudication method (e.g., consensus, majority vote).
6. Standalone vs. Reader Study: Whether the device's performance was evaluated independently (algorithm only) or as part of a human-in-the-loop study (MRMC). If MRMC, the effect size of AI assistance on human readers.
7. Training Data: Information on the size and characteristics of the dataset used to train the VeriSuite algorithm (if applicable, as this is an older device submission, specific AI/ML training details might not be explicit in this format).
8. Training Ground Truth: How the ground truth for the training set was established.

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The DRF 4343 is a digital image acquisition system to be used in conjunction with a solid-state detector during radiography or fluoroscopy x-ray examination to capture, digitalize, review images and format images according to DICOM protocol to be sent through network connection. This device is not intended for mammography use.

The DRF 4343 is Intended to capture digital images from a radiographic/fluoroscopic system through a dynamic digital flat panel, to digitalize, archive and review images and to provide a network connection via DICOM protocol to various output (e.g. hardcopy, softcopy and archive) devices which uses a device.

This 510(k) submission for the DRF 4343, an Operator Console and Imaging Workstation for Stationary Digital X-Ray Systems, does not contain information about acceptance criteria or a study that specifically proves the device meets such criteria. Instead, the submission focuses on demonstrating substantial equivalence to predicate devices based on shared indications for use and technological characteristics.

Therefore, many of the requested details cannot be extracted from the provided text.

Here is a breakdown of what can be inferred or what is explicitly missing:

1. Table of Acceptance Criteria and Reported Device Performance:

• No specific acceptance criteria or reported device performance metrics are provided in the document. The submission relies on demonstrating substantial equivalence to predicate devices, implying that if it functions similarly to already approved devices, its performance is acceptable.

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

• Not applicable. The document does not describe a performance study with a test set.

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

• Not applicable. No test set or ground truth establishment is described.

4. Adjudication method for the test set:

• Not applicable. No test set or adjudication method is described.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size:

• No MRMC comparative effectiveness study is mentioned. The submission focuses on device characteristics and substantial equivalence, not comparative effectiveness with human readers.

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

• Not applicable. This device is an operator console and imaging workstation for X-ray systems, not an AI algorithm performing diagnostic tasks. Its function is to capture, digitalize, archive, and review images, which implicitly involves human interaction.

7. The type of ground truth used:

• Not applicable. As there is no performance study or ground truth establishment described.

8. The sample size for the training set:

• Not applicable. This submission does not describe an AI model or a training set.

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

• Not applicable. As there is no AI model or training set described.

Summary of available information related to the device and its approval:

• Device Name: DRF 4343
• Common Name: Operator Console and Imaging Workstation for Stationary Digital X-Ray Systems
• Indication for Use: "The DRF 4343 is a digital image acquisition system to be used in conjunction with a solid-state detector during radiography or fluoroscopy x-ray examination to capture, digitalize, review images and format images according to DICOM protocol to be sent through network connection. This device is not intended for mammography use."
• Predicate Devices: Nical NDR+/DIVA-D (K053029), Siemens AXIOM Luminos dRF (K062623), Shimadzu DAR7000 RADspeed SAFIRE (K050925).
• Rationale for Substantial Equivalence: The DRF 4343 has the same indication for use and similar technological characteristics as the predicate devices, with minor differences not raising new questions regarding safety or effectiveness.

In conclusion, this 510(k) submission establishes substantial equivalence through comparison to existing predicate devices rather than through a dedicated performance study with acceptance criteria and a test set. Therefore, the specific details requested regarding acceptance criteria and study data are not present in the provided document.

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The VeriSuite patient position verification system is used for verification and correction of the patient's position during a radiotherapy treatment with external beams or charged particles. It is based on stereoscopic X-ray images and DRRs calculated from a CT image series of the treatment region of the patient and information from the treatment planning.

Not Found

Here's a breakdown of the acceptance criteria and study information for the VeriSuite device, based on the provided text.

Note: The provided document is a 510(k) premarket notification summary, which primarily focuses on demonstrating substantial equivalence to a predicate device. It does not contain the detailed study protocols, results, or comprehensive acceptance criteria that would typically be found in a full clinical or performance study report. Therefore, much of the requested information (like specific sample sizes for test sets, expert qualifications, adjudication methods, MRMC studies, or detailed ground truth establishment for training data) is not present in this document. The information provided below is extracted directly from the available text.

Acceptance Criteria and Device Performance (Limited Information)

The document states: "We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices..." This indicates that the primary acceptance criterion for the 510(k) submission was demonstrating substantial equivalence to existing predicate devices (specifically, EXACTRAC 5.5 / ExacTrac X-RAY 6D K072506).

Table of Acceptance Criteria and Reported Device Performance

Study Information (Based on Available Text)

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

   • Sample Size: Not specified in the provided document.
   • Data Provenance: Not specified in the provided document. The document primarily focuses on the regulatory review rather than detailed study methodology. It is likely that testing data would have been generated internally by the manufacturer during development and validation, but specific details are absent here.

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

   • Number of Experts: Not specified.
   • Qualifications of Experts: Not specified.

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

   • Not specified.

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 evidence of an MRMC study related to human readers or AI assistance in this document. The VeriSuite system is described as a "patient position verification system" based on X-ray images, implying an automated or semi-automated system for patient positioning rather than an AI-assisted diagnostic tool that would typically involve human readers and diagnostic accuracy studies.

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

   • The description "patient position verification system... It is based on stereoscopic X-ray images and DRRs calculated from a CT image series..." suggests that the system operates in a standalone capacity to perform its verification function. However, the document does not explicitly present a "standalone performance study" with specific metrics or results. The FDA's determination of substantial equivalence implies they reviewed performance data, but the details are not included in this summary.

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

   • The document implies that the "ground truth" for patient position verification would be the actual patient position or a carefully measured, validated reference position. This would likely be established through precise physical phantoms or highly accurate imaging modalities. However, the exact method for establishing ground truth for any testing is not specified in this regulatory filing summary.

7. The sample size for the training set:

   • Not specified. The document does not describe a training set as would be relevant for machine learning models. If the system uses algorithms that were "trained," the details are not in this summary.

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

   • Not applicable/Not specified, as no training set is described in the provided text.

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The PortaVision PVMed DDR 2520 Digital Imaging System is intended for use in generating radiographic images of human anatomy. (The system is not intended to be use for mammography). It is intended to replace film/screen or computed radiography in extremity and general-purpose procedures appropriate to the input field of view. This imager is intended for incorporation into a complete x-ray system by a qualified equipment manufacturer. This device is intended for use by qualified medical personnel and is contraindicated when, in the judgment of the physician, procedures would be contrary to the best interest of the patient.

The PortaVision PVMed DDR 2520 Digital Imaging System consists of two components, an amorphous silicon digital x-ray imager and software for viewing the captured images on a Windows-based computer. The digital imager is composed of an amorphous silicon flat panel imager which uses a large-area amorphous silicon sensor array with a gadolinium oxysulfide scintillator. The PVMed DDR 2520 Digital Imaging System will display high quality images in less that 5 seconds over a wide range of X-Ray dose settings. The System is not intended to be use for mammography.

"The provided text does not contain detailed information about specific acceptance criteria or a dedicated study proving the device meets those criteria. Instead, it focuses on the device's substantial equivalence to a predicate device. Therefore, I cannot extract the requested information directly.

However, I can infer from the text that the primary "acceptance criterion" for this 510(k) submission is substantial equivalence to existing legally marketed devices. The study proving this "acceptance criterion" is the 510(k) submission itself, which presents a comparison of the technological characteristics and intended use of the PortaVision PVMed DDR 2520 Digital Imaging System with those of predicate devices.

Here's an attempt to answer your questions based on the available text, highlighting what's explicitly stated and what cannot be determined:

Acceptance Criteria and Device Performance

Study Details (Based on available information)

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

   • The provided text does not mention a specific test set, its sample size, or data provenance related to a performance study. The submission focuses on a comparison of technical specifications and intended use against a predicate device for substantial equivalence.

2. 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)

   • The provided text does not mention a test set, ground truth establishment, or experts for such a purpose.

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

   • The provided text does not mention a test set or any adjudication method.

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

   • The provided text does not indicate that an MRMC comparative effectiveness study was done. The device described is a digital imaging system, not an AI-assisted diagnostic tool, so such a study would not be expected in this context.

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

   • The provided text does not describe a standalone algorithm performance study. The device is an imaging system designed for use by qualified medical personnel.

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

   • The provided text does not mention a specific ground truth type as no performance study with a test set is detailed. The "ground truth" for this 510(k) submission is essentially the legally marketed status and established safety/effectiveness of the predicate device.

7. The sample size for the training set

   • The provided text does not mention a training set sample size. This type of information is typically relevant for machine learning or AI-based devices, which this imaging system is not described as.

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

   • The provided text does not mention a training set or how a ground truth for it would be established.

In summary: The provided 510(k) summary is for an imaging system seeking substantial equivalence to a predicate device. It primarily relies on demonstrating that the new device shares the same intended use and technological characteristics as the already-cleared predicate, rather than presenting a detailed clinical performance study with a test set, ground truth, or expert evaluations in the manner typically seen for AI/ML-driven diagnostic aids."

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The X3C 2200 is 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 can be performed with patient sitting, standing or lying in the prone or supine positions.

The X3C 2200 (510k submission device) is not intended for mammography.

The X3C 2200 is a modification to Xplorer 2200 where the Xplorer 1000 digital radiographic detector (a previously marketed device covered by 510k K992955) in Xplorer 2200 system is replaced with X3C digital radiographic detector, previously marketed device under K070079. The X3C 2200 system is manufactured by Imaging Dynamics.

This 510(k) submission, K071401, for the X3C 2200 Digital Radiographic System, explicitly states: "No clinical tests conducted." This means that there is no study described in the provided text that proves the device meets specific acceptance criteria based on clinical performance.

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (Xplorer 2200, K063039) through non-clinical tests. The acceptance criteria and "device performance" in this context refer to the device's ability to meet safety, effectiveness, and performance requirements comparable to the predicate device through non-clinical evaluations.

Therefore, the requested information elements related to clinical studies, such as sample size, data provenance, expert ground truth, adjudication, MRMC studies, standalone performance, and training set details, are not applicable or not available from the provided text for this specific submission because no clinical studies were performed.

Here's an attempt to answer the questions based on the available information regarding substantial equivalence and non-clinical testing:

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

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

• Not applicable. No clinical test set or patient data was used as "No clinical tests conducted." The evaluation was based on non-clinical performance, safety, and effectiveness testing of the device itself, likely comparing its specifications and outputs to the predicate device.

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. As no clinical tests were conducted, there was no "test set" requiring ground truth established by medical experts in this submission. The "ground truth" for substantial equivalence was based on meeting engineering and safety standards, and performance specifications benchmarked against the predicate device.

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

• Not applicable. No clinical test set requiring adjudication was used.

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 a digital radiographic system, not an AI-assisted diagnostic tool. Furthermore, no clinical studies (including MRMC) were conducted.

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

• Not applicable. This submission is for a digital radiographic system hardware, not a standalone algorithm. Also, no clinical studies were performed.

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

• The "ground truth" for evaluating this device's substantial equivalence in non-clinical testing would have been based on engineering specifications, performance metrics (e.g., image quality parameters, dose measurements), safety standards (electrical, thermal, mechanical), and biocompatibility testing results, all compared against the established characteristics of the predicate device. It represents verification against technical and regulatory benchmarks, not clinical disease states.

8. The sample size for the training set

• Not applicable. As this device is a hardware system and "No clinical tests conducted," there was no "training set" of data in the context of an AI/ML algorithm being developed or assessed.

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

• Not applicable. There was no training set for this device.

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The X3C 1100 motorized patient table with digital radiographic detector (510k submission device) is integrated into the user's stationary radiography system. This typical configuration permits a qualified/trained doctor or technologist to take a range of head-to-toe 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, lying in the prone or supine positions.

The X3C 1100 (510k submission device) is not intended for mammography.

The X3C 1100 is a modification to Xplorer 1100 where the Xplorer 1000 digital radiographic detector (a previously marketed device covered by 510k K992955) in Xplorer 1100 system is replaced with X3C digital radiographic detector, previously marketed device under K070079. The X3C 1100 system is manufactured by Imaging Dynamics.

This submission (K071408) is for a X3C 1100 motorized patient table with digital radiographic detector. This device is a modification of an existing device, where the digital radiographic detector component has been updated.

The key takeaway is that no clinical studies were conducted for this 510(k) submission. The manufacturer relied on non-clinical tests and demonstrating substantial equivalence to a predicate device (Xplorer 1100, K062417) to meet acceptance criteria.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not applicable. No clinical test set was used for this submission. The evaluation was based on non-clinical tests and comparison to a predicate device.
• Data Provenance: Not applicable for clinical data. Non-clinical test data provenance is not specified beyond being generated by Imaging Dynamics Company Ltd.

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

• Not applicable. No clinical test set requiring expert ground truth establishment was conducted for this submission.

4. Adjudication Method for the Test Set

• Not applicable. No clinical test set requiring adjudication was conducted for this submission.

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

• No MRMC comparative effectiveness study was done. The submission explicitly states: "Clinical tests: No clinical tests conducted."

6. Standalone (Algorithm Only) Performance Study

• Not applicable. This device is a digital radiographic detector integrated into an X-ray system, not a standalone algorithm. Also, no clinical studies were performed.

7. Type of Ground Truth Used

• Not applicable for clinical studies. For the non-clinical tests, the "ground truth" would be established by engineering specifications, regulatory standards, and performance against the predicate device through direct comparison testing.

8. Sample Size for the Training Set

• Not applicable. This device does not appear to involve AI/ML requiring a training set in the context of this submission. The evaluation was primarily engineering-based and comparison to a predicate device.

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

• Not applicable, as no training set was used.

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