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O-MAR is a combination of an acquisition technique and post-processing software intended for use on Achieva and Ingenia, 1.5T & 3T MR Systems. O-MAR is suitable for use on all patients with passive MR Conditional orthopedics implants that are scanned according to the conditions of safe use for the specific MR Conditional implant being scanned. In addition O-MAR is suitable for use on patients without implants that are cleared for MR exams. O-MAR helps reduce artifacts caused by presence of metal in both in-plane and through-plane dimensions compared to conventional MR imaging techniques. Thus O-MAR improves visualization of more tissue in the vicinity of MR Conditional orthopedic implants. When interpreted by a trained physician, images generated by O-MAR provide information that can be useful in determining a diagnosis.

The O-MAR feature has two components. The SEMAC+VAT feature and the MARS+VAT feature. SEMAC+VAT is a Turbo Spin Echo method in combination with VAT (View Angle Tilting) and with multiple z-encodings per excited slice (aka SEMAC) to reduce in-plane and through-plane distortions caused by magnetic field inhomogeneities. MARS is high band width TSE. MARS+VAT can also be referred to as high band width TSE+VAT.

A difference between SEMAC+VAT and MARS+VAT is that SEMAC+VAT also provides through plane as well as in plane artifact reduction, MARS+VAT only provides in plane artifact reduction. SEMAC uses a slice selective TSE acquisition. Multiple z-encodings per excited slice are used to recover off-resonant signal caused by magnetic field inhomogeneities. The output image for each slice represents a combination of the signal acquired at different off-resonant frequencies. SEMAC takes care of corrections in the through-slice direction. The VAT (View angle tilting) technique is used to reduce in-plane distortions. For this, the gradient applied during slice selection is reapplied during the signal readout.

The feature consists of:

• Specific imaging sequence based on multiple overlapping 3D volumes, where the 3D volume aims at capturing the different frequencies caused by the distortion.
• A new calculation function to combine different frequency MR signals into a single . undistorted slice.
• A TSE-based SENSE reference scan, which is more robust towards the metal distortions than standard FFE reference scans
• VAT gradient control in sequences.
• . VAT is combined with SEMAC or MARS. MARS (Metal artifact reduction sequence) is a slice selective high bandwidth TSE sequence which can be achieved with standard settings of the TSE sequences.

The provided text contains information about the Philips Medical Systems O-MAR device (K143253), which is intended to reduce artifacts caused by metal implants in MRI scans. However, it does not explicitly state acceptance criteria in a quantitative table format nor does it provide a formal study comparing the device against these specific acceptance criteria in the way a structured clinical trial report would.

Instead, the document describes the validation process and findings which implicitly demonstrate that the device meets its stated purpose of improving image quality around metal implants.

Here's an attempt to extract and infer the requested information based on the available text:

Acceptance Criteria and Device Performance

Note: The document does not provide a formal table of quantitative acceptance criteria. The "reported device performance" is inferred from the conclusions of the validation studies described.

Detailed Study Information

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

• Test Set Sample Size (Clinical): The text mentions "volunteers that had a knee, hip, or lumbar spine implant." The exact number of volunteers is not specified.
• Test Set Sample Size (Non-Clinical/Phantom): Phantoms containing "three total hip implants with varying materials, one total knee implant and two spine implants (screws and fixation rod, and screws and fixation plate)" were used.
• Data Provenance: The studies were conducted internally by Philips Medical Systems Nederland B.V. The country of origin of the data is not explicitly stated beyond the company's location in "The Netherlands." The studies appear to be prospective, specifically designed to validate the O-MAR feature.

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

• Number of Experts: "A board certified radiologist" (singular) confirmed the findings in the "External Image Evaluation report DHF229248."
• Qualifications: "Board certified radiologist." Specific years of experience are not mentioned.

4. Adjudication method for the test set:

• The text only mentions a single "board certified radiologist" confirming the findings in the external image evaluation. This implies a single-reader assessment rather than a multi-reader adjudication method (like 2+1 or 3+1). For the internal validation, the method for assessing "improved tissue visualization" and "reduced artifacts" is not detailed, but it suggests an internal comparison without external adjudication.

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 is not explicitly mentioned. The document describes a comparison between images generated by O-MAR (MARS+VAT or SEMAC+VAT) and conventional high bandwidth TSE scans, assessed by a single board-certified radiologist. The focus is on the improvement in image quality directly attributable to the O-MAR technique, not on how human readers' diagnostic accuracy changes with vs without AI assistance in the diagnostic workflow. The O-MAR device is characterized as an image acquisition and post-processing software, not an AI-assisted diagnostic tool.

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

• Yes, implicitly. The core of the validation involves comparing the output images of the O-MAR algorithm (MARS+VAT or SEMAC+VAT) to images from conventional high bandwidth TSE scans. The "artifact reduction" and "tissue visualization" are inherent properties of the generated images, representing the algorithm's standalone performance in processing MR signals to produce improved images. The radiologist's review then confirmed this standalone improvement in image quality.

7. The type of ground truth used:

• Expert Consensus/Subjective Assessment: The ground truth for image improvements (reduced artifacts, improved tissue visualization) was established through subjective comparison and assessment by technical evaluators and a "board certified radiologist." For the phantom studies, the reduction of artifact size was also a quantifiable comparison against a baseline. There's no mention of pathology or clinical outcomes data being used as ground truth for this device's validation.

8. The sample size for the training set:

• The document does not specify a training set size. As O-MAR appears to be a rule-based image acquisition/reconstruction technique rather than a machine learning/AI model that requires training, the concept of a "training set" in the context of machine learning might not directly apply here. It's possible the algorithms were developed and refined using internal data, but this is not detailed as a formal "training set."

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

• As no training set is described (see point 8), there is no information on how its ground truth was established.

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