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Vantage Orian 1.5T systems are indicated for use as a diagnostic imaging modality that produces cross-sectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.

MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:

·Proton density (PD) (also called hydrogen density) ·Spin-lattice relaxation time (T1) ·Spin-spin relaxation time (T2)

·Flow dynamics

·Chemical Shift

Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Orian (Model MRT-1550) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian uses 1.4 m short and 3.8 tons light weight magnet. It includes the Pianissimo™ technology (scan noise reduction technology). The design of the gradient coil and the WB coil of the Vantage Orian 1.5T provides the maximum field of view of 55 x 50 cm. The Model MRT-1550/AC, AD, AG, AH includes the standard gradient system and Model MRT-1550/AK, AL, AO, AP includes the XGO gradient system.

This system is based upon the technology and materials of previously marketed Canon Medical Systems MRI systems and is intended to acquire and display cross-sectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body. The Vantage Orian MRI System is comparable to the current 1.5T Vantage Orian MRI System (K202767), cleared January 15th, 2021.

The provided document is a 510(k) summary for the Canon Medical Systems' Vantage Orian 1.5T MRI system, specifically for an extension of the Compressed SPEEDER (2D) maximum acceleration factor. The study described focuses on demonstrating that the extended acceleration factors (3.0 and 4.0) maintain equivalent performance to the previously cleared acceleration factor of 2.5.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria in numerical form for metrics like sensitivity, specificity, or image quality scores. Instead, the acceptance criterion for the study appears to be a qualitative equivalence between the higher acceleration factor images and the predicate 2.5 acceleration factor images.

Note: The document describes a preference study rather than a study assessing diagnostic accuracy directly. The acceptance criteria are therefore stated in terms of preference and equivalent performance.

2. Sample Size and Data Provenance

• Sample Size for Test Set: 34 studies
• Data Provenance: The document does not explicitly state the country of origin or whether the data was retrospective or prospective. It mentions "volunteer clinical imaging" which suggests prospective data collection.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Three board-certified radiologists per anatomy.
• Qualifications of Experts: Board-certified radiologists. (No mention of years of experience).

4. Adjudication Method

The document describes a "Human observer study" where radiologists assessed "preference." It does not specify a formal adjudication method (like 2+1 or 3+1 consensus) for establishing a single "ground truth" for the test set. Instead, it suggests individual preferences were aggregated to determine if there was a clinically relevant difference in preference. The phrasing "demonstrated no clinically-relevant difference in preference" implies that a consensus or aggregation of these preferences led to this conclusion.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study assessing human readers' improvement with AI vs. without AI assistance was not explicitly described. This study was a comparison of different acceleration factors using the same AI reconstruction (Compressed SPEEDER 2D). The AI (AiCE Reconstruction Processing Unit) is a component of the device, and the study assessed the impact of varying one of its parameters (acceleration factor) on image preference. It was not a comparison of human readers using AI versus not using AI.

6. Standalone (Algorithm Only) Performance

The study was a "Human observer study," meaning it involved human interpretation of the images produced by the algorithm. It does not explicitly mention a standalone (algorithm only) performance evaluation without human-in-the-loop. The focus was on how humans perceive the images generated by the different acceleration factors.

7. Type of Ground Truth Used

The "ground truth" in this context is indirect. It is not pathology, outcomes data, or a pre-established "correct diagnosis." Instead, the "ground truth" for the performance comparison was the preference of board-certified radiologists for one set of images (higher acceleration) compared to another (predicate 2.5 acceleration). The goal was to establish that there was no clinically relevant difference in preference, suggesting visual equivalence.

8. Sample Size for Training Set

The document does not provide information on the sample size used for the training set of the AiCE Reconstruction Processing Unit. The study described focuses on validating the extension of an existing feature (Compressed SPEEDER 2D) and implies no changes to the core AiCE software or hardware.

9. How Ground Truth for Training Set Was Established

The document does not provide information on how the ground truth for the training set of the AiCE Reconstruction Processing Unit was established.

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Vantage Orian 1.5T systems are indicated for use as a diagnostic imaging modality that produces cross-sectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.

MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:

·Proton density (PD) (also called hydrogen density)

·Spin-lattice relaxation time (T1)

·Spin-spin relaxation time (T2)

·Flow dynamics

·Chemical Shift

Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Orian (Model MRT-1550) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian uses 1.4 m short and 3.8 tons light weight magnet. It includes the Pianissimo™ technology (scan noise reduction technology). The design of the gradient coil and the WB coil of the Vantage Orian 1.5T provides the maximum field of view of 55 x 50 cm. The Model MRT-1550/AC, AD, AG, AH includes the standard gradient system and Model MRT-1550/AK, AL, AO, AP includes the XGO gradient system. The AiCE Reconstruction Processing Unit for MR is included with this system for the processing of images for various anatomical regions.

This system is based upon the technology and materials of previously marketed Canon Medical Systems MRI systems and is intended to acquire and display cross-sectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body. The Vantage Orian MRI System is comparable to the current 1.5T Vantage Orian MRI System (K193021), cleared June 3ºº, 2020.

Here's an analysis of the provided text regarding the acceptance criteria and the study that proves the device meets those criteria:

The document describes a 510(k) premarket notification for the "Vantage Orian 1.5T, MRT-1550, V6.0 with AiCE Reconstruction Processing Unit for MR." The primary focus of this submission is the addition of anatomical regions to the cleared AiCE (Artificial intelligence-based Clear Engine) Deep Learning Reconstruction technology, with no changes to the underlying software or hardware.

Therefore, the acceptance criteria and study data provided mostly relate to demonstrating that the AiCE Deep Learning Reconstruction, when applied to these new anatomical regions, maintains or improves image quality compared to existing methods.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a formal "acceptance criteria" table with specific numerical targets. Instead, it describes general goals for AiCE's performance relative to other filters and a predicate device.

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

• Test Set Sample Size: 55 studies (for the human observer study).
• Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). It mentions "volunteer clinical imaging," suggesting prospective data acquisition, but this is not fully confirmed.

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

• Number of Experts: 6 board-certified radiologists.
• Qualifications: "Board certified radiologists." No specific years of experience are mentioned.

4. Adjudication Method for the Test Set

The document does not explicitly mention an adjudication method (such as 2+1 or 3+1 consensus). It states that the human observer study demonstrated a "statistical preference of AiCE when compared to other performance filters," which implies individual reader assessments were used and then analyzed statistically. It does not describe how disagreements, if any, were resolved to establish a single ground truth from the radiologists' readings.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

Yes, a multi-reader, multi-case (MRMC) comparative effectiveness study was done.

• Effect Size of Human Readers Improve with AI vs. Without AI Assistance: The document states that the study "demonstrated a statistical preference of AiCE when compared to other performance filters" and that AiCE performed "either at the same level or above the performance of the commercially available predicate device." However, a specific effect size or quantitative measure of improvement for human readers with AI assistance is not provided. It only indicates a preference and equivalent/superior performance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Yes, a standalone performance assessment (bench testing) was done.

• Performance: A "model observer study" was used to determine that image low contrast detectability was "maintained or improved." Additionally, "other bench testing of SNR and contrast performance" was conducted. Specific quantitative results (e.g., exact SNR values, contrast ratios) for these standalone assessments are not provided.

7. The Type of Ground Truth Used

For the model observer study and bench testing, the ground truth would likely be simulated data or objective phantom measurements for low contrast detectability, SNR, and contrast. For the human observer study, the "ground truth" implicitly relies on the expert judgment/preference of the 6 board-certified radiologists when comparing images, rather than a definitive pathological or outcomes-based ground truth. Since the study's objective was to demonstrate preference and equivalent/superior performance relative to other filters, the radiologists' comparative assessment served as the evaluative benchmark.

8. The Sample Size for the Training Set

The document does not provide information on the sample size used for the training set for the AiCE Deep Learning Reconstruction.

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

The document does not provide information on how the ground truth for the training set was established for the AiCE Deep Learning Reconstruction. This information is typically proprietary to the manufacturer and not always detailed in 510(k) summaries for modifications that don't alter the core algorithm.

Ask a specific question about this device

Vantage Orian 1.5T systems are indicated for use as a diagnostic imaging modality that produces cross-sectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.

MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:

·Proton density (PD) (also called hydrogen density)

• ·Spin-lattice relaxation time (T1)
  ·Spin-spin relaxation time (T2)

·Flow dynamics

·Chemical Shift

Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Orian (Model MRT-1550) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian uses 1.4 m short and 4.1 tons light weight magnet. It includes the Canon Pianissimo™ and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole body coil of the Vantage Orian provides the maximum field of view of 55 x 50 cm. The Model MRT-1550/A3, A4, A7, A8 includes the standard gradient system.

This system is based upon the technology and materials of previously marketed Canon Medical Systems MRI systems and is intended to acquire and display cross-sectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body. The Vantage Orian MRI System is comparable to the current 1.5T Vantage Orian MRI System (K193021), cleared June 3, 2020 with the following modifications.

The provided document is a 510(k) summary for the Vantage Orian 1.5T, MRT-1550, V6.0 MRI System. This submission is for modifications to an already cleared device (K193021) and primarily focuses on safety and performance parameters typical for an MRI system, rather than AI/algorithm-driven diagnostic performance.

The document states:

• "No change from the previous predicate submission, K193021." regarding "IMAGING PERFORMANCE PARAMETERS".
• "image quality testing was completed which demonstrated that the subject device meets predetermined acceptance criteria. Image quality metrics were performed to assess signal-to-noise ratio, two-dimensional geometric distortion, image uniformity, and slice thickness."

Therefore, the acceptance criteria and study detailed below relate to physical device performance and image quality, not an AI algorithm's diagnostic accuracy or effectiveness in clinical interpretation. Since this is an MRI system and not an AI-powered diagnostic device, many of the requested elements for AI/algorithm studies (like sample size for test sets and training sets, AI effect size on human readers, adjudication methods, number of experts for ground truth, etc.) are not applicable in the context of this 510(k) submission.

Here is the information directly applicable from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a "test set" in the context of patient data or clinical images for evaluating diagnostic performance. The tests described are "bench testing" and "image quality testing." These likely refer to tests conducted on phantoms or test objects, not human patient data. Therefore, details like data provenance or sample size of patient cases are not provided as they are not relevant to the type of testing performed for this device modification.

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

Not applicable. The "ground truth" here would relate to physical image quality measurements from phantoms or engineering specifications, not expert diagnostic consensus on patient images.

4. Adjudication Method

Not applicable. No expert adjudication process is described for the image quality testing details provided.

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

Not performed/Not applicable. This is a 510(k) for an MRI system modification, not an AI diagnostic algorithm. The document makes no mention of studies involving human readers or AI assistance.

6. Standalone (Algorithm Only) Performance Study

Not applicable. This is a medical device (MRI system), not an AI algorithm. The performance evaluation is for the system's ability to acquire images, not interpret them.

7. Type of Ground Truth Used

The ground truth for the image quality testing would be based on physical phantom measurements and engineering specifications for parameters like SNR, geometric distortion, uniformity, and slice thickness.

8. Sample Size for the Training Set

Not applicable. This is a hardware modification submission for an MRI system, not an AI algorithm requiring a training set.

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

Not applicable. As there's no AI algorithm training set, there's no ground truth established for it.

Ask a specific question about this device

Vantage Orian 1.5T systems are indicated for use as a diagnostic imaging modality that produces cross-sectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.

MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:

·Proton density (PD) (also called hydrogen density)

• ·Spin-lattice relaxation time (T1)
• ·Spin-spin relaxation time (T2)
• ·Flow dynamics
• ·Chemical Shift

Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Orian (Model MRT-1550) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian uses 1.4 m short and 3.8 tons light weight magnet. It includes the Pianissimo™ technology (scan noise reduction technology). The design of the gradient coil and the WB coil of the Vantage Orian 1.5T provides the maximum field of view of 55 x 50 cm. The Model MRT-1550/AC, AD, AG, AH includes the standard gradient system and Model MRT-1550/AK, AL, AO, AP includes the XGO gradient system.

AiCE is an optional noise reduction algorithm that improves image quality and reduces thermal noise by employing Deep Convolutional Neural Network methods. AiCE is designed to remove Gaussian distributed noise in MR images for reducing contributions of thermal noise. In order to train a DCNN that can learn a model that represents thermal noise, the training datasets are created by adding Gaussian noise of different amplitudes to high-SNR images acquired with large number of averages. The device is targeted for Brain and knee regions. This software and its associated hardware are used on Canon MRI systems that are designed to communicate with the AiCE Reconstruction Processing Unit for MR.

This system is based upon the technology and materials of previously marketed Canon Medical Systems MRI systems and is intended to acquire and display cross-sectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body. The Vantage Orian 1.5T, MRT-1550, V6.0 with AiCE Reconstruction Processing Unit for MR is comparable to the current 1.5T Vantage Orian MRI System (K193021), cleared June 3rd, 2020 with the following modifications.

The provided text describes the Canon Medical Systems Corporation's Vantage Orian 1.5T, MRT-1550, V6.0 with AiCE Reconstruction Processing Unit for MR. Here's a breakdown of the acceptance criteria and the study details:

1. Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" in a tabulated format with specific numerical targets. Instead, it describes performance goals and how the device performed against them. The key performance goals for AiCE are:

• Improved Image Quality and Reduced Thermal Noise: Achieved by employing Deep Convolutional Neural Network methods.
• Maintained or Improved Low Contrast Detectability: Verified through a model observer study.
• Increased Signal-to-Noise Ratio (SNR) and Maintained Contrast: Demonstrated through measurements on clinical brain and knee images.
• Performance at or Above Predicate Device: Indicated by the human observer study's finding of a statistical preference for AiCE.

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

• Sample Size for Test Set: 160 image data sets for the human observer study.
• Data Provenance: Not explicitly stated, but the mention of "volunteer clinical imaging" suggests it was likely prospective data collected from volunteers. The regions targeted were "Brain and knee regions." Given the manufacturer is based in Japan, and the U.S. agent is in California, the data could originate from various geographical locations. The document does not specify the country of origin or if it was retrospective.

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

• Number of Experts: 6 board certified radiologists.
• Qualifications of Experts: Board certified radiologists. The document does not specify their years of experience.

4. Adjudication Method for the Test Set

• The document does not specify an adjudication method like 2+1 or 3+1 for establishing ground truth from the expert readers. It states the human observer study "demonstrated a statistical preference of AiCE when compared to other performance filters," implying a comparative assessment rather than a consensus-driven ground truth establishment for a diagnostic task.

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

• Yes, a human observer study was done. The document states: "Additionally, a human observer study was conducted with 6 board certified radiologists and 160 image data sets that demonstrated a statistical preference of AiCE when compared to other performance filters."
• Effect Size: The document mentions "a statistical preference of AiCE" and that AiCE performed "either at the same level or above the performance of the commercially available predicate device." However, it does not provide a specific quantitative effect size (e.g., AUC difference, sensitivity/specificity improvement, or change in reader confidence scores) for how much human readers improved with AI vs. without AI assistance. The study seems to have focused on whether AiCE images were preferred or performed better, implying an improvement or at least equivalence.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• Yes, a standalone study was done in the form of a "model observer study" and direct measurements.
  • "AiCE deep learning reconstruction underwent performance (bench testing) using a model observer study to determine that image low contrast detectability was maintained or improved."
  • "In order to quantify the increase in SNR with AiCE over standard protocols, SNR measurements of sample clinical brain and knee images were obtained. Additionally, contrast was measured using the absolute signal intensity differences between two tissues." These are measurements of the algorithm's direct output on image quality metrics.

7. Type of Ground Truth Used

• For the standalone tests (model observer, SNR/contrast measurements): The ground truth was based on objective image quality metrics (low contrast detectability, SNR, contrast). For training the DCNN, high-SNR images acquired with a large number of averages were considered the "high quality" reference from which noisy images were created.
• For the human observer study: The "ground truth" was the "statistical preference" of the 6 board-certified radiologists when comparing AiCE images to images from other performance filters. This isn't a traditional diagnostic ground truth (like a biopsy result) but rather a preference-based assessment of image quality and clinical utility from experienced readers.

8. Sample Size for the Training Set

• The document states: "In order to train a DCNN that can learn a model that represents thermal noise, the training datasets are created by adding Gaussian noise of different amplitudes to high-SNR images acquired with large number of averages."
• The specific sample size (number of images or cases) for the training set is not provided.

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

• The ground truth for the training set was established through a synthetic process:
  • "High-SNR images acquired with large number of averages" were used as the reference "clean" images.
  • "Gaussian noise of different amplitudes" was then "added" to these high-SNR images to create noisy counterparts.
  • The DCNN was trained to learn how to transform the noisy images back to the high-SNR (ground truth) images, effectively modeling and removing the noise.

Ask a specific question about this device

Vantage Orian 1.5T systems are indicated for use as a diagnostic imaging modality that produces cross-sectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.

MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:

·Proton density (PD) (also called hydrogen density)

• ·Spin-lattice relaxation time (T1)
• ·Spin-spin relaxation time (T2)
• ·Flow dynamics
• ·Chemical Shift

Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Orian (Model MRT-1550) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian uses 1.4 m short and 3.8 tons light weight magnet. It includes the Pianissimo™ technology (scan noise reduction technology). The design of the gradient coil and the WB coil of the Vantage Orian 1.5T provides the maximum field of view of 55 x 50 cm. The Model MRT-1550/AC, AD, AG, AH includes the standard gradient system and Model MRT-1550/AK, AL, AO, AP includes the XGO gradient system.

This system is based upon the technology and materials of previously marketed Canon Medical Systems MRI systems and is intended to acquire and display cross-sectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body. The Vantage Orian MRI System is comparable to the current 1.5T Vantage Orian MRI System (K182282), cleared October 19th, 2018 with the following modifications.

The provided text is a 510(k) summary for the Canon Medical Systems Vantage Orian 1.5T MR system (Model MRT-1550, V6.0). It outlines modifications made to a previously cleared device, specifically the addition of "Compressed SPEEDER" (compressed sensing) and "T2 Map Using Pre-Contrast Pulses" features, and an operating system upgrade (Windows 10).

Based on the provided text, the study focuses on evaluating the imaging performance of the new features, particularly "Compressed SPEEDER". The acceptance criteria and the study that proves the device meets them can be extracted as follows:

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

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

• Sample Size:
  • For Compressed SPEEDER and T2 Map: "utilizing phantoms and volunteer images". No specific number of phantoms or volunteers is mentioned.
  • For diagnostic review of Compressed SPEEDER: "representative images" were reviewed. No specific number of images is given.
• Data Provenance: Not explicitly stated, but it's implied to be internal testing by Canon Medical Systems, likely in Japan (where the manufacturer is located) or the US (where Canon Medical Systems USA is located). The text does not specify if the data was retrospective or prospective. Given the nature of a 510(k) submission for device modification, it's highly probable these were prospective tests specifically conducted for the submission.

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

• Number of Experts: Not explicitly stated. The text mentions "American Board Certified Radiologists" (plural).
• Qualifications of Experts: "American Board Certified Radiologists". No specific years of experience are mentioned.

4. Adjudication method for the test set

• The text states, "Reviewers provided detailed assessments of image degradation, diagnostic performance, lesion conspicuity, and clinical utility." It does not mention a specific adjudication method (e.g., 2+1, 3+1) if multiple radiologists were involved, or whether they reached a consensus.

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 comparative effectiveness study is mentioned, nor is there any claim of AI assistance improving human reader performance. The "Compressed SPEEDER" feature is described as an accelerated fast scan technique, not an AI-assisted diagnostic tool for interpretation. This submission is for a conventional MRI system with new scan sequences, not an AI/ML-driven diagnostic device.

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

• The device is an MRI system. The "performance" being evaluated is the quality of the images generated by the system's new sequences. While the system operates "standalone" in generating images, the evaluation of "diagnostic quality" inherently involves human interpretation. The text describes "image quality testing" (presumably objective metrics using phantoms) and "review by American Board Certified Radiologists" (human-in-the-loop assessment of diagnostic utility).

7. The type of ground truth used

• Phantom Data: For technical image quality metrics (SNR, unfolding error, etc.), phantoms were used, which provide a known, controlled ground truth.
• Volunteer Images: For assessing the functionality and appearance of T2 maps and general image quality with Compressed SPEEDER. In this context, the "ground truth" for assessment would likely be the expected normal anatomy and the visual assessment of correct image formation by experts.
• Expert Consensus (Implicit/Assumed): For the "diagnostic quality" assessment by American Board Certified Radiologists, their collective judgment and experience serve as the de-facto ground truth for evaluating image utility in a clinical context. There's no mention of external pathology or outcomes data being used as ground truth for this specific 510(k) amendment, as the changes are to image acquisition methods, not a new diagnostic indication or algorithm.

8. The sample size for the training set

• This information is not provided in the 510(k) summary. The "Compressed SPEEDER" feature uses "compressed sensing," which is typically an image reconstruction algorithm, not a deep learning model that requires a "training set" in the common sense of AI/ML. If there were any machine learning components, details about training data would likely be separate from the performance evaluation of the final product. The text describes it as combining "parallel imaging... and compressed sensing," implying algorithmic rather than data-driven training.

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

• As a "training set" for an AI/ML model is not explicitly mentioned or implied to be part of this submission's new features, the method for establishing its ground truth is not provided. Compressed sensing is a mathematical reconstruction technique, not an AI model that learns from a labeled dataset.

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