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AI-Rad Companion Brain MR is a post-processing image analysis software that assists clinicians in viewing, analyzing, and evaluating MR brain images.

AI-Rad Companion Brain MR provides the following functionalities:
• Automated segmentation and quantitative analysis of individual brain structures and white matter hyperintensities
• Quantitative comparison of each brain structure with normative data from a healthy population
• Presentation of results for reporting that includes all numerical values as well as visualization of these results

AI-Rad Companion Brain MR runs two distinct and independent algorithms for Brain Morphometry analysis and White Matter Hyperintensities (WMH) segmentation, respectively. In overall, comprises four main algorithmic features:

• Brain Morphometry
• Brain Morphometry follow-up
• White Matter Hyperintensities (WMH)
• White Matter Hyperintensities (WMH) follow-up

The feature for Brain Morphometry is available since the first version of the device (VA2x), while segmentation of White Matter Hyperintensities was added since VA4x and the follow-up analysis for both is available since VA5x. The brain morphometry and brain morphometry follow-up feature have not been modified and remain identical to previous VA5x mainline version.

AI-Rad Companion Brain MR VA60 is an enhancement to the predicate, AI-Rad Companion Brain MR VA50 (K232305). Just as in the predicate, the brain morphometry feature of AI-Rad Companion Brain MR addresses the automatic quantification and visual assessment of the volumetric properties of various brain structures based on T1 MPRAGE datasets. From a predefined list of brain structures (e.g. Hippocampus, Caudate, Left Frontal Gray Matter, etc.) volumetric properties are calculated as absolute and normalized volumes with respect to the total intracranial volume. The normalized values are compared against age-matched mean and standard deviations obtained from a population of healthy reference subjects. The deviation from this reference population can be visualized as 3D overlay map or out-of-range flag next to the quantitative values.

Additionally, identical to the predicate, the white matter hyperintensities feature addresses the automatic quantification and visual assessment of white matter hyperintensities on the basis of T1 MPRAGE and T2 weighted FLAIR datasets. The detected WMH can be visualized as a 3D overlay map and the quantification in count and volume as per 4 brain regions in the report.

Here's a structured overview of the acceptance criteria and study details for the AI-Rad Companion Brain MR, based on the provided FDA 510(k) clearance letter:

Acceptance Criteria and Reported Device Performance

Study Details

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

   • White Matter Hyperintensities (WMH) Feature: 100 subjects (Multiple Sclerosis patients (MS), Alzheimer's patients (AD), cognitive impaired (CI), and healthy controls (HC)).
   • White Matter Hyperintensities (WMH) Follow-up Feature: 165 subjects (Multiple Sclerosis patients (MS) and Alzheimer's patients (AD)).
   • Data Provenance: Data acquired from Siemens, GE, and Philips scanners. Testing data had balanced distribution with respect to gender and age of the patient according to target patient population, and field strength (1.5T and 3T). This indicates a retrospective, multi-vendor, multi-national (implied by vendor diversity) dataset.

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

   • Number of Experts: Three radiologists.
   • Qualifications: Not explicitly stated beyond "radiologists." It is not specified if they are board-certified, or their years of experience.

3. Adjudication Method for the Test Set:

   • For each dataset, three sets of ground truth annotations were created manually.
   • Each set was annotated by a disjoint group consisting of an annotator, a reviewer, and a clinical expert.
   • The clinical expert was randomly assigned per case to minimize annotation bias.
   • The clinical expert reviewed and corrected the initial annotation of the changed WMH areas according to a specified annotation protocol. Significant corrections led to re-communication with the annotator and re-review.
   • This suggests a 3+1 Adjudication process, where three initial annotations are reviewed by a clinical expert.

4. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done:

   • No, an MRMC comparative effectiveness study comparing human readers with and without AI assistance was not done. The study focuses on the standalone performance of the AI algorithm against expert ground truth.

5. If a Standalone (i.e. algorithm only without human-in-the loop performance) Was Done:

   • Yes, a standalone performance study was done. The "Accuracy was validated by comparing the results of the device to manual annotated ground truth from three radiologists." This evaluates the algorithm's performance directly.

6. The Type of Ground Truth Used:

   • Expert Consensus / Manual Annotation: The ground truth for both WMH and WMH follow-up features was established through "manual annotated ground truth from three radiologists" and involved a "standard annotation process" with annotators, reviewers, and clinical experts.

7. The Sample Size for the Training Set:

   • The document states that the "training data used for the fine tuning the hyper parameters of WMH follow-up algorithm is independent of the data used to test the white matter hyperintensity algorithm follow up algorithm." However, the specific sample size for the training set is not provided in the given text.

8. How the Ground Truth for the Training Set Was Established:

   • The document implies that the WMH follow-up algorithm "does not include any machine learning/ deep learning component," suggesting a rule-based or conventional image processing algorithm. Therefore, "training" might refer to parameter tuning rather than machine learning model training.
   • For the "fine-tuning the hyper parameters of WMH follow-up algorithm," the ground truth establishment method for this training data is not explicitly detailed in the provided text. It only states that this data was "independent of the data used to test" the algorithm.

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Atellica IM total PSA II (tPSAII) assay is for in vitro diagnostic use in the quantitative measurement of total prostate-specific antigen (PSA) in human serum and plasma (EDTA and lithium-heparin) using the Atellica IM Analyzer.

This assay is indicated as an aid in the detection of prostate cancer in conjunction with a digital rectal exam (DRE) in men aged 50 years and older. Prostate biopsy is required for diagnosis of prostate cancer. This assay is further indicated as an aid in the management (monitoring) of patients with prostate cancer.

The Atellica IM total PSA II (tPSAII) assay consists of:

tPSAII ReadyPack® primary reagent pack

• Lite Reagent (10.0 mL/reagent pack): Unlabeled monoclonal mouse anti-fPSA antibody (~250 ng/mL); monoclonal mouse anti-PSA antibody (~180 ng/mL) labeled with acridinium ester; buffer; bovine serum albumin (BSA); preservative.
• Solid Phase (20.0 mL/reagent pack): Monoclonal mouse anti-PSA antibody (~3.5 μg/mL) labeled with biotin and bound to streptavidin paramagnetic particles; buffer; BSA; bovine gamma globulin (BGG); sodium azide (< 0.1%); preservative.
  • Storage: Unopened at 2–8°C (Until expiration date on product), Onboard (42 days).

tPSAII CAL (2.0 mL/vial): Purified PSA from human seminal fluid in buffer; BSA; NaN3 (< 0.1%).

• Storage: Unopened at 2–8°C (Until expiration date on product), Opened at 2–8°C (30 days), On the system at room temperature (8 hours).

The tPSAII assay will have two configurations: 100 tests kit and 500 tests kit (5 x 100T in the carton).

N/A

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Intended Use / Indications for Use

Indications for Use for MAGNETOM Vida, MAGNETOM Lumina, MAGNETOM Vida Fit, MAGNETOM Sola, MAGNETOM Altea, MAGNETOM Sola Fit, MAGNETOM Viato.Mobile:

The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.

Indications for Use for MAGNETOM Flow.Elite, MAGNETOM Flow.Neo, MAGNETOM Flow.Rise:

The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays, depending on optional local coils that have been configured with the system, the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.

The subject device, MAGNETOM Vida with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Vida with syngo MR XA60A (K231560).

A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• myExam 3D Camera
• BM Contour XL Coil

Modified Hardware:

• RF Transmitter TBX3 3T (TX Box 3)
• MaRS (Measurement and reconstruction system)

Software

New Features and Applications:

• Brachytherapy Support for use with MR conditional applicators
• CS Vibe
• myExam Implant Suite
• DANTE blood suppression
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• BioMatrix Motion Sensor
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• ASNR recommended protocols for imaging of ARIA
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• 3D Whole Heart
• Ghost reduction (Dual polarity Grappa (DPG))
• Fleet Reference Scan
• AutoMate Cardiac (Cardiac AI Scan Companion)
• Complex Averaging
• myExam Autopilot Spine
• myExam Autopilot Brain and myExam Autopilot Knee
• Open Workflow

Modified features and applications:

• GRE_PC
• myExam RT Assist workflow improvements
• Open Recon 2.0
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE
• SPACE Improvement: high bandwidth IR pulse
• SPACE Improvement: increase gradient spoiling

The subject device, MAGNETOM Lumina with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Lumina with syngo MR XA60A (K231560). A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• myExam 3D Camera
• BM Contour XL Coil

Modified Hardware:

• RF Transmitter TBX3 3T (TX Box 3)
• MaRS (Measurement and reconstruction system)

Software

New Features and Applications:

• CS Vibe
• myExam Implant Suite
• DANTE blood suppression
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• BioMatrix Motion Sensor
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• Ghost reduction (Dual polarity Grappa (DPG))
• Fleet Reference Scan
• AutoMate Cardiac (Cardiac AI Scan Companion)
• Complex Averaging
• myExam Autopilot Spine
• myExam Autopilot Brain and myExam Autopilot Knee
• Compressed Sensing Cardiac Cine
• Open Workflow

Modified Features and Applications:

• GRE_PC
• Open Recon 2.0
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE
• SPACE Improvement: high bandwidth IR pulse
• SPACE Improvement: increase gradient spoiling

The subject device, MAGNETOM Lumina with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Lumina with syngo MR XA60A (K231560). A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• myExam 3D Camera
• BM Contour XL Coil

Modified Hardware:

• RF Transmitter TBX3 3T (TX Box 3)
• MaRS (Measurement and reconstruction system)

Software

New Features and Applications:

• CS Vibe
• myExam Implant Suite
• DANTE blood suppression
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• BioMatrix Motion Sensor
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• Ghost reduction (Dual polarity Grappa (DPG))
• Fleet Reference Scan
• AutoMate Cardiac (Cardiac AI Scan Companion)
• Complex Averaging
• myExam Autopilot Spine
• myExam Autopilot Brain and myExam Autopilot Knee
• Compressed Sensing Cardiac Cine
• Open Workflow

Modified Features and Applications:

• GRE_PC
• Open Recon 2.0
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE
• SPACE Improvement: high bandwidth IR pulse
• SPACE Improvement: increase gradient spoiling

The subject device, MAGNETOM Vida Fit with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Vida with syngo MR XA60A (K231560).

A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• myExam 3D Camera
• Beat Sensor
• BM Contour XL Coil

Modified Hardware:

• RF Transmitter TBX3 3T (TX Box 3)
• MaRS (Measurement and reconstruction system)
• Host computers

Software

New Features and Applications:

• Brachytherapy Support for use with MR conditional applicators
• CS Vibe
• myExam Implant Suite
• DANTE blood suppression
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• BioMatrix Motion Sensor
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• ASNR recommended protocols for imaging of ARIA
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• GRE_PC
• Open Recon 2.0
• 3D Whole Heart
• Ghost reduction (Dual polarity Grappa (DPG))
• Fleet Reference Scan
• AutoMate Cardiac (Cardiac AI Scan Companion)
• myExam Autopilot Spine
• myExam Autopilot Brain and myExam Autopilot Knee
• Deep Resolve for EPI
• Deep Resolve for HASTE
• Physiologging
• Complex Averaging
• Open Workflow

Modified features and applications:

• myExam RT Assist workflow improvements
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE
• myExam Angio Advanced Assist (Test Bolus)
• SPACE Improvement: high bandwidth IR pulse
• SPACE Improvement: increase gradient spoiling

The subject device, MAGNETOM Sola with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Sola with syngo MR XA61A (K232535).

A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• BM Contour XL Coil

Modified Hardware:

• MaRS (Measurement and reconstruction system)

Software

New Features and Applications:

• Brachytherapy Support for use with MR conditional applicators
• CS Vibe
• DANTE blood suppression
• BioMatrix Motion Sensor
• SPAIR FatSat Improvements: SPAIR "Abdomen&Pelvis" mode and SPAIR Breast mode
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• ASNR recommended protocols for imaging of ARIA
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• 3D Whole Heart
• AutoMate Cardiac (Cardiac AI Scan Companion)
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• Ghost reduction (Dual polarity Grappa (DPG))
• Fleet Reference Scan
• Deep Resolve Swift Brain
• myExam Autopilot Spine
• Open Workflow
• Complex Averaging
• Open Workflow

Modified features and applications:

• myExam RT Assist workflow improvements
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE
• myExam Angio Advanced Assist (Test Bolus)
• SPACE Improvement: high bandwidth IR pulse
• SPACE Improvement: increase gradient spoiling

The subject device, MAGNETOM Sola with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Sola with syngo MR XA61A (K232535).

A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• BM Contour XL Coil

Modified Hardware:

• MaRS (Measurement and reconstruction system)

Software

New Features and Applications:

• Brachytherapy Support for use with MR conditional applicators
• CS Vibe
• DANTE blood suppression
• BioMatrix Motion Sensor
• SPAIR FatSat Improvements: SPAIR "Abdomen&Pelvis" mode and SPAIR Breast mode
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• ASNR recommended protocols for imaging of ARIA
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• 3D Whole Heart
• AutoMate Cardiac (Cardiac AI Scan Companion)
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• Ghost reduction (Dual polarity Grappa (DPG))
• Fleet Reference Scan
• Deep Resolve Swift Brain
• myExam Autopilot Spine
• Open Workflow

Modified features and applications:

• myExam Implant Suite
• GRE_PC
• myExam RT Assist workflow improvements
• Open Recon 2.0
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE
• SPACE Improvement: high bandwidth IR pulse
• SPACE Improvement: increase gradient spoiling

The subject device, MAGNETOM Altea with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Altea with syngo MR XA61A (K232535).

A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• BM Contour XL Coil

Modified Hardware:

• MaRS (Measurement and reconstruction system)

Software

New Features and Applications:

• CS Vibe
• DANTE blood suppression
• BioMatrix Motion Sensor
• SPAIR FatSat Improvements: SPAIR "Abdomen&Pelvis" mode and SPAIR Breast mode
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• AutoMate Cardiac (Cardiac AI Scan Companion)
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• Ghost reduction (Dual polarity Grappa (DPG))
• Fleet Reference Scan
• Deep Resolve Swift Brain
• myExam Autopilot Spine
• Compressed Sensing Cardiac Cine
• Open Workflow

Modified features and applications:

• myExam Implant Suite
• GRE_PC
• myExam RT Assist workflow improvements
• Open Recon 2.0
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE
• SPACE Improvement: high bandwidth IR pulse
• SPACE Improvement: increase gradient spoiling

The subject device, MAGNETOM Sola Fit with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Sola Fit with syngo MR XA70A (K250443).

A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• BM Contour XL Coil

Modified Hardware:

• MaRS (Measurement and reconstruction system)
• Host computers

Software

New Features and Applications:

• Brachytherapy Support for use with MR conditional applicators
• CS Vibe
• DANTE blood suppression
• BioMatrix Motion Sensor
• SPAIR FatSat Improvements: SPAIR "Abdomen&Pelvis" mode and SPAIR Breast mode
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• ASNR recommended protocols for imaging of ARIA
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• myExam Implant Suite
• GRE_PC
• Open Recon 2.0
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• Deep Resolve Swift Brain
• myExam Autopilot Spine
• Open Workflow

Modified features and applications:

• myExam RT Assist workflow improvements
• myExam Implant Suite
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE
• SPACE Improvement: high bandwidth IR pulse
• SPACE Improvement: increase gradient spoiling

The subject device, MAGNETOM Sola Fit with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Sola Fit with syngo MR XA70A (K250443).

A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• BM Contour XL Coil

Modified Hardware:

• MaRS (Measurement and reconstruction system)
• Host computers

Software

New Features and Applications:

• Brachytherapy Support for use with MR conditional applicators
• CS Vibe
• DANTE blood suppression
• BioMatrix Motion Sensor
• SPAIR FatSat Improvements: SPAIR "Abdomen&Pelvis" mode and SPAIR Breast mode
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• ASNR recommended protocols for imaging of ARIA
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• myExam Implant Suite
• GRE_PC
• Open Recon 2.0
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• Deep Resolve Swift Brain
• myExam Autopilot Spine
• Open Workflow

Modified features and applications:

• myExam RT Assist workflow improvements
• myExam Implant Suite
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE

The subject device, MAGNETOM Viato.Mobile with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Viato.Mobile with syngo MR XA70A (K250443).

A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• BM Contour XL Coil

Modified Hardware:

• MaRS (Measurement and reconstruction system)
• Host computers

Software

New Features and Applications:

• CS Vibe
• DANTE blood suppression
• BioMatrix Motion Sensor
• SPAIR FatSat Improvements: SPAIR "Abdomen&Pelvis" mode and SPAIR Breast mode
• RF pulse optimization with VERSE
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• ASNR recommended protocols for imaging of ARIA
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• myExam Implant Suite
• GRE_PC
• Open Recon 2.0
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• Deep Resolve Swift Brain
• myExam Autopilot Spine
• Open Workflow

Modified features and applications:

• myExam Implant Suite
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE

With the subject software version, Syngo MR XB10, we are also introducing the following new 1.5T devices, which are part of our MAGNETOM Flow. Platform:

MAGNETOM Flow.Elite
MAGNETOM Flow.Neo
MAGNETOM Flow.Rise

The subject device, MAGNETOM Flow.Elite, MAGNETOM Flow.Neo and MAGNETOM Flow.Rise with software Syngo MR XB10, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Sola with syngo MR XA61A (K232535).

A high-level summary of the new and modified hardware and software is provided below:

New Hardware:

• Magnet
• MREF (Magnet Refrigerator)
• Gradient system
• Gradient Coil
• RF System
• System Cover
• Patient Table
• MaRS (Measurement and Reconstruction System)
• Select&GO Display (TPAN_3G) and Control Panel (CPAN_2G)
• Body Coil
• Head/Neck Coil
• BM Head/Neck Coil (with ComfortSound)
• BM Contour S Coil
• BM Contour M Coil
• BM Contour L Coil
• BM Contour XL Coil
• Foot/Ankle Coil
• BM Spine Coil
• iTx Extremity 18 Flare
• Multi-Index MR-RT Positioning (a part of "RT Pro Edition" marketing bundle) (not available for MAGNETOM Flow.Rise)

Modified Hardware:

• Gradient Power Amplifier (GPA)
• SAR Monitoring
• In-Vivo Shim

Software

New Features and Applications:

• CS Vibe
• BioMatrix Motion Sensor
• SPAIR FatSat Improvements: SPAIR "Abdomen&Pelvis" mode and SPAIR Breast mode
• Deep Resolve Boost for FL3D_VIBE and SPACE
• Deep Resolve Sharp for FL3D_VIBE and SPACE
• Preview functionality for Deep Resolve Boost
• EP2D_FID_PHS
• EP_SEG_FID_PHS
• AutoMate Cardiac (Cardiac AI Scan Companion)
• DANTE blood suppression
• SMS Averaging for TSE
• SMS Averaging for TSE_DIXON
• SMS for BLADE without diffusion function
• Ghost reduction (Dual polarity Grappa (DPG))
• Fleet Reference Scan
• Deep Resolve Swift Brain
• Quick Protocols
• myExam Autopilot Spine
• Open Workflow

Modified features and applications:

• myExam Implant Suite
• GRE_PC
• myExam RT Assist workflow improvements (not available for MAGNETOM Flow.Rise)
• Open Recon 2.0
• Deep Resolve Boost for TSE
• "MTC Mode" for SPACE
• SPACE Improvement: high bandwidth IR pulse
• SPACE Improvement: increase gradient spoiling

New (general) Software / Platform / Workflow:

• Select&GO extension (coil-based Iso Centering, Patient Registration at the touch display, Start Scan at the touch display)
• New Startup-Timer
• myExam RT Assist (not available for MAGNETOM Flow.Rise)
• myExam Brain RT-Autopilot (not available for MAGNETOM Flow.Rise)
• Eco Power Mode Pro

Modified (general) Software / Platform:

• Improved Gradient ECO Mode Settings

Furthermore, the following minor updates and changes were conducted for the subject devices MAGNETOM Vida, MAGNETOM Lumina, MAGNETOM Vida Fit, MAGNETOM Sola, MAGNETOM Altea:

• Off-Center Planning Support
• Flip Angle Optimization (Lock TR and FA)
• Inline Image Filter
• Automatic System Shutdown (ASS) sensor (Smoke Detector)
• ID Gain (re-naming)
• Select&Go Display (Touch Display (TPAN))
• Marketing bundle "myExam Companion"

The following minor updates and changes were conducted for the subject devices MAGNETOM Sola Fit and MAGNETOM Viato.Mobile:

• Off-Center Planning Support
• Automatic System Shutdown (ASS) sensor (Smoke Detector)
• ID Gain (re-naming)
• Select&Go Display (Touch Display (TPAN))
• Marketing bundle "myExam Companion"

The following minor updates and changes were conducted for the subject devices MAGNETOM Flow.Elite, MAGNETOM Flow.Neo, MAGNETOM Flow.Rise:

• Off-Center Planning Support
• Flip Angle Optimization (Lock TR and FA)
• Inline Image Filter
• Automatic System Shutdown (ASS) sensor (Smoke Detector)
• ID Gain (re-naming)
• Marketing bundle "myExam Companion"
• Marketing Bundle "RT Pro Edition"(not available for MAGNETOM Flow.Rise)

This FDA 510(k) clearance letter pertains to several MAGNETOM MRI systems with software Syngo MR XB10. The document primarily focuses on demonstrating substantial equivalence to predicate devices through non-clinical testing of new and modified hardware and software features, particularly those involving Artificial Intelligence (AI) such as "Deep Resolve" functionalities.

Here's an analysis of the acceptance criteria and the studies that prove the devices meet them, specifically for the AI features:

1. Table of Acceptance Criteria and Reported Device Performance for AI Features

The document does not explicitly state "acceptance criteria" for the AI features in a numerical format that would typically be seen for a device's performance metrics (e.g., minimum sensitivity, specificity). Instead, the acceptance criteria are implicitly defined by the evaluation methods and the "Test result summary" for each Deep Resolve feature, which aim to demonstrate equivalent or improved image quality compared to conventional methods.

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

Since the document distinguishes between training, validation, and testing datasets, the "test set" here refers to the data used for final evaluation of the AI model's performance.

• Deep Resolve Swift Brain:

  • Test Set Sample Size: The document lists "Validation: 3,616 slices (1.5T validation); 6,048 slices (3T validation)" as part of the split. It also mentions "work-in-progress packages of the network were delivered and evaluated in clinical settings with collaboration partners," implying additional testing, but a specific numerical sample size for this external validation is not provided in detail. However, the initial splits serve as the primary "test set" for performance metrics mentioned.
  • Data Provenance: "in-house measurement," implying retrospective data collected at Siemens' facilities. The document notes that "attributes like gender, age and ethnicity are not relevant to the training data" due to network architecture, but no specific country of origin is stated beyond "in-house."

• Deep Resolve Boost for FL3D_VIBE and Deep Resolve Boost for SPACE:

  • Test Set Sample Size: The document states 19% of 1265 measurements for validation. It also explicitly mentions "collaboration partners (testing)" indicating an external test set, but a specific numerical breakdown for this is not provided.
  • Data Provenance: "in-house measurements (training and validation) and collaboration partners (testing)." This suggests a mix of retrospective data potentially from various countries where Siemens has collaboration, though specific locations are not listed.

• Deep Resolve Sharp for FL3D_VIBE and Deep Resolve Sharp for SPACE:

  • Test Set Sample Size: 30% of the 500 measurements are listed for validation, which serves as a test set. This equates to 150 measurements.
  • Data Provenance: "in-house measurements," implying retrospective data from Siemens' research facilities. Specific country not mentioned.

• Deep Resolve Boost for TSE:

  • Test Set Sample Size: "Additional test dataset for banding artifact reduction: more than 2000 slices."
  • Data Provenance: "in-house measurements and collaboration partners" for training/validation. The "additional test dataset for banding artifact reduction" likely follows the same provenance. Retrospective data.

3. Number of Experts Used and Qualifications for Ground Truth

The document does not explicitly state the number of experts used to establish ground truth or their specific qualifications (e.g., "radiologist with 10 years of experience") for any of the Deep Resolve features.

However, for Deep Resolve Boost for TSE, it mentions:

• "Visual evaluations confirmed statistically significant reduction of banding artifacts... "
• "In addition, the radiologist evaluation revealed no difference in suitability for clinical diagnostics..."

This indicates that radiologists were involved in the evaluation of the Deep Resolve Boost for TSE feature, presumably as experts to establish the clinical suitability. The exact number and their detailed qualifications are not provided. For other features, the ground truth is primarily based on the acquired raw data or manipulated versions of it, without explicit mention of expert review in the ground truth establishment process.

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 or evaluating the test set for any of the AI features. The ground truth for training and validation is derived from the "acquired datasets" which are considered the ground truth due to data manipulation and augmentation from these high-quality source images. For Deep Resolve Boost for TSE, a "radiologist evaluation" is mentioned, implying expert review without detailing a specific adjudication protocol.

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

The document does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done to measure the improvement of human readers with AI assistance versus without AI assistance. The evaluations focus on the standalone performance of the AI algorithms in improving image quality metrics and, in one instance (Deep Resolve Boost for TSE, radiologist evaluation), the suitability for clinical diagnostics, rather than the impact on human reader performance.

6. Standalone (Algorithm Only) Performance

Yes, standalone (algorithm only) performance was done. The descriptions for each Deep Resolve feature focus entirely on the algorithm's performance in terms of quantitative image quality metrics (PSNR, SSIM, NMSE, MSE, LPIPS), visual inspection for artifacts, and improvements over conventional techniques. There is no mention of a "human-in-the-loop" component in the described performance evaluations for these AI features, except for the "radiologist evaluation" for Deep Resolve Boost for TSE which assessed clinical suitability of the output images, not reader performance with the AI.

7. Type of Ground Truth Used

• For Deep Resolve Swift Brain, Deep Resolve Boost for FL3D_VIBE & SPACE, and Deep Resolve Sharp for FL3D_VIBE & SPACE:

  • The ground truth used was the acquired datasets (raw MRI data). The input data for the AI models was then "retrospectively created from the ground truth by data manipulation and augmentation" (e.g., undersampling k-space, adding noise, cropping, creating sub-volumes, cropping k-space to simulate low-resolution input from high-resolution output). This means the AI models were trained to learn the mapping from manipulated (e.g., noisy, low-resolution, undersampled) inputs to the original, high-quality acquired image data.

• For Deep Resolve Boost for TSE:

  • Similar to above, the "acquired training/validation datasets" were considered the ground truth. Input data was generated by "data manipulation and augmentation" (e.g., discarding k-space lines, lowering SNR, mirroring k-space data).

In essence, the AI models are trained to restore or enhance images to resemble the high-quality, fully acquired MRI data that serves as the reference ground truth.

8. Sample Size for the Training Set

• Deep Resolve Swift Brain: 20,076 slices
• Deep Resolve Boost for FL3D_VIBE and Deep Resolve Boost for SPACE: 81% of 1265 measurements. (This equates to approximately 1024 measurements).
• Deep Resolve Sharp for FL3D_VIBE and Deep Resolve Sharp for SPACE: 70% of 500 measurements. (This equates to 350 measurements).
• Deep Resolve Boost for TSE: More than 23,250 slices (93% of the total dataset).

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

For all Deep Resolve features, the ground truth for the training set was established from acquired MRI datasets (either "in-house measurements" or from "collaboration partners"). These acquired datasets are implicitly considered the "true" or "high-quality" images. The AI models are designed to process inputs that mimic suboptimal acquisition conditions (e.g., undersampled k-space, lower SNR, lower resolution) and generate outputs that match these high-quality acquired images, which serve as the ground truth for learning. The process involved:

• Retrospective creation: Input data was created retrospectively from the acquired ground truth data.
• Data manipulation and augmentation: This involved techniques such as:
  • Discarding k-space lines (undersampling).
  • Lowering the SNR level by adding Gaussian noise to k-space data.
  • Uniformly-random cropping of training data.
  • Creating sub-volumes of acquired data.
  • Cropping k-space to generate low-resolution inputs corresponding to high-resolution ground truth.
  • Mirroring of k-space data.

This approach demonstrates an unsupervised or self-supervised learning paradigm where the ground truth is derived directly from the complete and high-fidelity raw data, and the AI is trained to reconstruct or enhance images from degraded inputs to match this ideal ground truth.

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The ADVIA Centaur Anti-Thyroglobulin II (aTgII) assay is for in vitro diagnostic use in the quantitative measurement of autoantibodies against thyroglobulin in human serum and plasma (EDTA, lithium heparin, sodium heparin) using the ADVIA Centaur XP system.

Anti-thyroglobulin (aTg) measurements are used, in conjunction with clinical assessment, as an aid in the diagnosis of autoimmune thyroiditis and Graves' disease.

N/A

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The ADVIA Centaur Anti-Thyroid Peroxidase II (aTPOII) assay is for in vitro diagnostic use in the quantitative measurement of autoantibodies against thyroid peroxidase in human serum and plasma (EDTA and lithium heparin) using the ADVIA Centaur XP system.

Anti-thyroid peroxidase (aTPO) measurements are used, in conjunction with a clinical assessment, as an aid in the diagnosis of autoimmune thyroiditis and/or Graves' disease.

The ADVIA Centaur Anti-Thyroid Peroxidase II (aTPOII) consists of:

• aTPOII ReadyPack® primary reagent pack (Lite Reagent, Solid Phase)
• aTPOII CAL
  Devices sold separately and included in the ADVIA Centaur® Anti-Thyroid Peroxidase II (aTPOII) are:
• ADVIA Centaur aTPOII MCM (MCM 1, MCM 2–4)
• ADVIA Centaur aTPOII QC
• ADVIA Centaur aTPOII DIL ReadyPack ancillary reagent pack

N/A

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AI-Rad Companion Prostate MR is indicated for the processing and annotation of DICOM MR prostate images acquired in adult male populations that demonstrate indications of oncological abnormalities in the prostate.

The AI-Rad Companion Prostate MR software aims to support the radiologist and provides the following functionality:
• Viewing, analyzing, evaluating prostate MR images including DCE, ADC, T2 and DWI
• Hosting application for and provides interface to external Prostate MR AI plug-in device
• Accept/reject/edit the results generated by the plug-in software Prostate MR AI

AI-Rad Companion Prostate MR is a diagnostic aid in the interpretation of prostate MRI examinations acquired according to the PI-RADS standard.

AI-Rad Companion Prostate MR provides quantitative and qualitative information based on bi or multiparametric prostate MR DICOM images. It displays information on the segmented gland, prostate volume, and segmented lesions along with their classifications. This information can be used to support the reading and reporting of prostate MR studies, as well as the planning of prostate biopsies in the case of ultrasound guided MR-US fusion biopsies of the prostate gland.

The primary features of AI-Rad Companion Prostate MR include:
• Display of Automatic Segmentation and volume of the prostate gland as well as display of automatic segmentation, quantification and classification of lesions
• Manual Adjustment of gland and lesion segmentation and editing of lesion scores, diameter, and localization of the automated generated lesions
• Marking of new lesions
• Export of results as RTSS format for import into supporting ultrasound or fusion biopsy planning systems

Based on the provided FDA 510(k) clearance letter for AI-Rad Companion Prostate MR (K252608), there is no specific study described that proves the device meets predefined acceptance criteria for performance metrics (e.g., sensitivity, specificity, accuracy). The document primarily focuses on demonstrating substantial equivalence to a predicate device (AI-Rad Companion Prostate MR K193283) and adherence to non-clinical verification and validation standards for software development and risk management.

The document explicitly states: "No clinical tests were conducted to test the performance and functionality of the modifications introduced within AI-Rad Companion Prostate MR."

Therefore, a table of acceptance criteria and reported device performance, information about sample sizes, expert ground truth establishment, adjudication methods, multi-reader multi-case studies, standalone performance, and training set details are not available in this document as no clinical performance study for the modified device was performed.

The document emphasizes that modifications and improvements were verified and validated through non-clinical tests (software verification and validation, unit, system, and integration tests), which demonstrated conformity to industry standards and the predicate device's existing safety and effectiveness.

Here’s a breakdown of what is stated in the document regarding testing:

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

• Not provided. The document does not include a table of specific clinical acceptance criteria (e.g., target sensitivity or specificity values) or reported device performance metrics against such criteria. The focus is on demonstrating that software enhancements do not adversely affect safety and effectiveness, assuming the predicate device's performance was already acceptable.

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

• Not provided. Since no clinical performance study was conducted for this specific submission, details on test set sample sizes and data provenance are not presented.

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 study is reported, this information is not available.

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

• Not applicable.

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 done. The document explicitly states "No clinical tests were conducted."

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

• Not explicitly stated for the modified device. While the device description mentions automatic segmentation and classification, the overall context emphasizes a "diagnostic aid" that "aims to support the radiologist" and has functionality to "Accept/reject/edit the results generated by the plug-in software Prostate MR AI." This suggests an interactive workflow where standalone performance is not the primary claim for this particular submission. The separate product, "Prostate MR AI (K241770)," which performs the core AI tasks, is likely where standalone performance would be detailed, but not in this document.

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

• Not applicable for this submission, as no new clinical performance study is detailed for the modified device. The original predicate device's performance would have relied on a ground truth, but that information is not part of this document.

8. The sample size for the training set:

• Not provided. Since this submission is for an updated version of an already cleared device and no new clinical performance study is detailed, the training set size for the underlying AI model (likely part of K241770 or the predicate K193283) is not included here.

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

• Not provided. This information would typically be detailed in the original submission for the AI algorithm (likely K241770 or K193283), not in this update focused on software enhancements and substantial equivalence.

In summary, the provided document focuses on demonstrating that the enhancements and modifications to the AI-Rad Companion Prostate MR do not adversely affect the safety and effectiveness of the existing predicate device. It relies on non-clinical software verification and validation, and substantial equivalence arguments, rather than presenting a de novo clinical performance study with new acceptance criteria and results.

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The Atellica IM Thyroglobulin (Tg) assay is for in vitro diagnostic use in the quantitative measurement of thyroglobulin in human serum and plasma (EDTA and lithium heparin) using the Atellica IM Analyzer.

Thyroglobulin measurements are used as an aid in monitoring differentiated thyroid cancer patients who have undergone thyroidectomy with or without radioiodine ablation.

The Atellica IM Thyroglobulin (Tg) assay includes:

• Tg ReadyPack primary reagent pack:
  • Lite Reagent: mouse monoclonal anti-human Tg antibody labeled with acridinium ester (~1.13 μg/mL); bovine serum albumin (BSA); mouse IgG; buffer; stabilizers; preservatives (7.5 mL/reagent pack).
  • Solid Phase: streptavidin-coated paramagnetic microparticles preformed with biotinylated mouse monoclonal antihuman Tg antibody (~267 μg/mL); BSA; mouse IgG; buffer; stabilizers; preservatives (15.0 mL/reagent pack).
• Ancillary Well Reagent: BSA; bovine gamma globulin; buffer; preservatives (6.0 mL/reagent pack).
• Tg CAL: After reconstitution, human thyroglobulin; BSA; buffer; stabilizers; preservatives (2.0 mL/vial).

The following devices are sold separately:

• Atellica IM Tg MCM:
  • MCM 1: After reconstitution, bovine serum albumin (BSA); buffer; stabilizers; preservatives (1.0 mL/vial).
  • MCM 2–5: After reconstitution, various levels of human thyroglobulin; BSA; buffer; stabilizers; preservatives (1.0 mL/vial).

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) summary for the Atellica IM Thyroglobulin (Tg) assay:

Device: Atellica IM Thyroglobulin (Tg) Assay
Purpose: Quantitative measurement of thyroglobulin in human serum and plasma as an aid in monitoring differentiated thyroid cancer patients who have undergone thyroidectomy with or without radioiodine ablation.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document describes various performance characteristics, which serve as acceptance criteria for the device. The reported performance is directly from the summary.

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

• Clinical Performance Test Set Sample Size: 291 serum samples collected from 189 subjects.
• Data Provenance:
  • The document states "A prospective, multi-center study was conducted." This indicates prospective data collection across multiple sites.
  • The country of origin is not explicitly stated in the provided text.
  • All samples were from subjects diagnosed with differentiated thyroid cancer, 6 or more weeks following thyroidectomy or radioiodine ablation.

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

• The document does not specify the number of experts or their qualifications for establishing the ground truth (structural disease). It simply states: "SD [Structural Disease] was established and classified as either positive or negative by cross-sectional or functional imaging results."
• This suggests that the ground truth was derived from standard clinical imaging reports rather than a consensus of independent expert readers specifically for this study.

4. Adjudication Method for the Test Set

• The document does not describe an adjudication method for the test set's ground truth (structural disease). It implies that the imaging results themselves provided the classification. This means there was no adjudication process as typically seen with multiple human readers reviewing images.

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

• No, an MRMC comparative effectiveness study was not done.
• This study is for an in vitro diagnostic (IVD) assay (a lab test), not an AI-assisted imaging or diagnostic tool where human readers work with or without AI. The performance metrics presented are for the analytical and clinical performance of the assay itself, comparing its results to a ground truth (structural disease status), not to human reader performance or improvement with AI.

6. If a Standalone Performance Study Was Done

• Yes, this is effectively a standalone (algorithm only) performance study.
• The Atellica IM Tg assay is an automated in vitro diagnostic device. Its performance characteristics (sensitivity, specificity, precision, linearity, etc.) are evaluated intrinsically, independent of human interpretation of the assay result values. The output is a quantitative measurement of thyroglobulin.

7. The Type of Ground Truth Used

• Ground truth for clinical performance: Structural disease (SD) status obtained from "cross-sectional or functional imaging results."
• Ground truth for analytical performance (LoB, LoD, LoQ, Precision, etc.): Established through laboratory protocols and reference materials (e.g., CLSI guidelines, certified reference materials like BCR CRM 457, spiked samples, control materials).

8. The Sample Size for the Training Set

• The document does not specify a separate training set or its sample size for the Atellica IM Tg assay.
• For IVD assays like this, the "training" is typically inherent in the assay's development and optimization process (e.g., reagent formulation, calibration curve development), which uses various known samples and standards, rather than a distinct, labeled "training dataset" as would be seen for a machine learning algorithm. The performance characteristics studies presented are akin to a "verification/validation set."

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

• As a traditional IVD assay, there isn't a "training set" in the sense of a machine learning model.
• Ground truth for assay development and calibration: This would have been established using reference materials (like BCR CRM 457), characterized control samples, and potentially a large panel of clinically characterized patient samples used during the assay's development and optimization phases. These activities are part of the broader product development lifecycle rather than a distinct "training set" with ground truth generated by experts in the context of a clinical study for submission. Standardization is explicitly noted as traceable to BCR CRM 457, which serves as a primary standard for establishing the quantitative accuracy of the assay.

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The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.

The subject device, MAGNETOM Avanto Fit with software syngo MR XA70A, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Avanto Fit with syngo MR XA50A (K220151).

A high-level summary of the new and modified hardware and software is provided below:

For MAGNETOM Avanto Fit with syngo MR XA70:

Hardware

New Hardware:
myExam 3D Camera
BM Head/Neck 20

Modified Hardware:
Sanaflex (cushions for patient positioning)

Software

New Features and Applications:
myExam Autopilot Brain
myExam Autopilot Knee
3D Whole Heart
HASTE_interactive
GRE_PC
Open Recon
Deep Resolve Gain
Fleet Reference Scan
Physio logging
complex averaging
AutoMate Cardiac
Ghost Reduction
BLADE diffusion
Beat Sensor
Deep Resolve Sharp
Deep Resolve Boost and Deep Resolve Boost (TSE)
Deep Resolve Boost HASTE
Deep Resolve Boost EPI Diffusion

Modified Features and Applications:
SPACE improvement (high band)
SPACE improvement (incr grad)
Brain Assist
Eco power mode
myExam Angio Advanced Assist (Test Bolus)

The subject device, MAGNETOM Skyra Fit with software syngo MR XA70A, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Skyra Fit with syngo MR XA50A (K220589).

A high-level summary of the new and modified hardware and software is provided below:

For MAGNETOM Skyra Fit with syngo MR XA70:

Hardware

New Hardware:
myExam 3D Camera

Modified Hardware:
Sanaflex (cushions for patient positioning)

Software

New Features and Applications:
Beat Sensor
HASTE_interactive
GRE_PC
3D Whole Heart
Deep Resolve Gain
Open Recon
Ghost Reduction
Fleet Reference Scan
BLADE diffusion
HASTE diffusion
Physio logging
complex averaging
Deep Resolve Swift Brain
Deep Resolve Sharp
Deep Resolve Boost and Deep Resolve Boost (TSE)
Deep Resolve Boost HASTE
Deep Resolve Boost EPI Diffusion
AutoMate Cardiac
SVS_EDIT

Modified Features and Applications:
SPACE improvement (high band)
SPACE improvement (incr grad)
Brain Assist
Eco power mode
myExam Angio Advanced Assist (Test Bolus)

The subject device, MAGNETOM Sola Fit with software syngo MR XA70A, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Sola Fit with syngo MR XA51A (K221733).

A high-level summary of the new and modified hardware and software is provided below:

For MAGNETOM Sola Fit with syngo MR XA70:

Hardware

New Hardware:
myExam 3D Camera

Modified Hardware:
Sanaflex (cushions for patient positioning)

Software

New Features and Applications:
GRE_PC
3D Whole Heart
Ghost Reduction
Fleet Reference Scan
BLADE diffusion
Physio logging
Open Recon
Complex averaging
Deep Resolve Sharp
Deep Resolve Boost and Deep Resolve Boost (TSE)
Deep Resolve Boost HASTE
Deep Resolve Boost EPI Diffusion
AutoMate Cardiac
Implant suite

Modified Features and Applications:
SPACE improvement (high band)
SPACE improvement (incr grad)
Brain Assist
Eco power mode

The subject device, MAGNETOM Viato.Mobile with software syngo MR XA70A, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Viato.Mobile with syngo MR XA51A (K240608).

A high-level summary of the new and modified hardware and software is provided below:

For MAGNETOM Viato.Mobile with syngo MR XA70:

Hardware

New Hardware:
n.a.

Modified Hardware:
Sanaflex (cushions for patient positioning)

Software

New Features and Applications:
GRE_PC
3D Whole Heart
Ghost Reduction
Fleet Reference Scan
BLADE diffusion
Physio logging
Open Recon
Complex averaging
Deep Resolve Sharp
Deep Resolve Boost and Deep Resolve Boost (TSE)
Deep Resolve Boost HASTE
Deep Resolve Boost EPI Diffusion
AutoMate Cardiac
Implant suite

Modified Features and Applications:
SPACE improvement (high band)
SPACE improvement (incr grad)
Brain Assist
Eco power mode

Furthermore, the following minor updates and changes were conducted for the subject devices:

Low SAR Protocol minor update (for all subject devices but MAGNETOM Skyra Fit): the goal of the SAR adaptive protocols was to be able to perform knee, spine, heart and brain examinations with 50% of the max allowed SAR values in normal mode for head and whole-body SAR. The SAR reduction was achieved by parameter adaptations like Flip angle, TR, RF Pulse Type, Turbo Factor, concatenations. For cardiac clinically accepted alternative imaging contrasts are used (submitted with K232494).

Implementation of image sorting prepare for PACS (submitted with K231560).

Implementation of improved DICOM color support (submitted with K232494).

Needle intervention AddIn was added all subject device (submitted with K232494).

Inline Image Filter switchable for users: in the subject device, users have the ability to switch the "Inline image filter" (implicite Filter) on or off. This filter is an image-based filter that can be applied to specific pulse sequence types. The function of the filter remains unchanged from the previous device MAGNETOM Sola with syngo MR XA61A (K232535).

SVS_EDIT is newly added for MAGNETOM Skyra Fit, but without any changes (submitted with K203443)

Brain Assist received an improvement and is identical to that of snygo MR XA61A (K232535)

Open Recon is introduced for all systems. The function of Open Recon remains unchanged from the previous submissions (submitted with K221733).

Lock TR and FA in Bold received a minor UI update

Implant Suite is newly introduced for MAGNETOM Sola Fit and MAGNETOM Viato.Mobile, but without any changes (submitted with K232535)

myExam Autopilot Brain and myExam Autopilot Knee are newly introduced for the subject device MAGNETOM AVANTO Fit and are unchanged from previous submissions (submitted with K221733).

myExam Angio Advanced Assist (Test Bolus) received a bug fixing and minimal UI improvements.

The provided text is an FDA 510(k) clearance letter for various MAGNETOM MRI Systems. While it details new and modified software and hardware features, it does not include specific acceptance criteria or a study that "proves the device meets the acceptance criteria" in terms of performance metrics like sensitivity, specificity, or accuracy for a diagnostic task.

Instead, the document focuses on demonstrating substantial equivalence to predicate devices. This is achieved by:

• Stating that the indications for use are the same.
• Listing numerous predicate and reference devices.
• Detailing hardware and software changes.
• Mentioning non-clinical tests like software verification and validation, sample clinical images, and image quality assessment to show that the new features maintain an "equivalent safety and performance profile" to the predicate devices.
• Referencing scientific publications for certain features to support their underlying principles and utility.
• Briefly describing the training and validation data for two AI features: Deep Resolve Boost and Deep Resolve Sharp, but without performance acceptance criteria or detailed results.

Therefore, much of the requested information cannot be extracted from this document because it is not a study report detailing clinical performance against predefined acceptance criteria for a specific diagnostic outcome.

However, I can extract the information related to the AI features as best as possible from the "AI Features/Applications training and validation" section (Page 16).

Acceptance Criteria and Study Details (Limited to AI Features)

1. Table of Acceptance Criteria and Reported Device Performance

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

• Deep Resolve Boost:
  • Test Set Sample Size: Not explicitly stated as a separate "test set" size. The document mentions "training and validation data" for over 25,000 TSE slices, over 10,000 HASTE slices (for refinement), and over 1,000,000 EPI Diffusion slices. It's unclear what proportion of this was used specifically for final testing, or if the "validation" mentioned includes the final performance evaluation.
  • Data Provenance: Retrospective, described as "Input data was retrospectively created from the ground truth by data manipulation and augmentation." Country of origin is not specified.
• Deep Resolve Sharp:
  • Test Set Sample Size: Not explicitly stated as a separate "test set" size. The document mentions "training and validation" on more than 10,000 high resolution 2D images. Similar to Deep Resolve Boost, it's unclear what proportion was specifically for final testing.
  • Data Provenance: Retrospective, described as "Input data was retrospectively created from the ground truth by data manipulation." Country of origin is not specified.

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 definition of "ground truth" for the AI features refers to the acquired datasets themselves rather than expert-labeled annotations. Visual comparisons are mentioned as part of the evaluation, but without details on expert involvement or qualifications.

4. Adjudication method for the test set

This information is not provided in the document. While "visual comparisons" and "visual rating" are mentioned, no specific adjudication method (e.g., 2+1, 3+1) 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, a MRMC comparative effectiveness study demonstrating human reader improvement with AI assistance is not described in this document. The focus of the AI features (Deep Resolve Boost and Deep Resolve Sharp) is on image quality enhancement (denoising, sharpness) and reconstruction rather than assisting human readers in a diagnostic task that can be quantified by an effect size.

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

Yes, the evaluation of Deep Resolve Boost and Deep Resolve Sharp, based on metrics like PSNR, SSIM, and perceptual loss, and "visual comparisons" or "visual rating" appears to be an assessment of the algorithm's performance in enhancing image quality in a standalone capacity, without direct human-in-the-loop interaction for diagnosis.

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

• Deep Resolve Boost: "The acquired datasets (as described above) represent the ground truth for the training and validation." This implies the original, full-quality, unaltered MRI scan data. Further, "Input data was retrospectively created from the ground truth by data manipulation and augmentation. This process includes further under-sampling of the data by discarding k-space lines, lowering of the SNR level by addition Restricted of noise and mirroring of k-space data."
• Deep Resolve Sharp: "The acquired datasets represent the ground truth for the training and validation." Similar to Boost, this refers to original, high-resolution MRI scan data. For training, "k-space data has been cropped such that only the center part of the data was used as input. With this method corresponding low-resolution data as input and high-resolution data as output / ground truth were created for training and validation."

8. The sample size for the training set

• Deep Resolve Boost:
  • TSE: more than 25,000 slices
  • HASTE (for refinement): more than 10,000 HASTE slices
  • EPI Diffusion: more than 1,000,000 slices
• Deep Resolve Sharp: more than 10,000 high resolution 2D images.

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

• Deep Resolve Boost: The ground truth was established by the "acquired datasets" themselves (full-quality MRI scans). The training input data was then derived from this ground truth by simulating degraded images (e.g., under-sampling, adding noise).
• Deep Resolve Sharp: Similarly, the ground truth was the "acquired datasets" (high-resolution MRI scans). The training input data was derived by cropping k-space data to create corresponding low-resolution inputs.

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The TSHL method is an in vitro diagnostic test for the quantitative measurement of Thyroid Stimulating Hormone (TSH, thyrotropin) in human serum and plasma on the Dimension® EXL™ integrated chemistry system with LOCI® Module. Measurements of TSH are used in the diagnosis and monitoring of thyroid disease.

The FT4L method is an in vitro diagnostic test for the quantitative measurement of Free Thyroxine in human serum and plasma on the Dimension® EXL™ integrated chemistry system with LOCI® Module. Measurements of free thyroxine are used in the diagnosis and monitoring of thyroid disease.

The Dimension® LOCI® Thyroid Stimulating Hormone Flex® reagent cartridge (TSHL) and Dimension® LOCI® Free Thyroxine Flex® reagent cartridge (FT4L) assays were cleared under K081074 and K073604, respectively. The components of the cleared assays were modified to reduce biotin interference.

The modified Assays are comprised of the following components:

Dimension® LOCI® Thyroid Stimulating Hormone Flex® reagent cartridge (TSHL): prepackaged liquid reagents in a plastic eight-well cartridge. Wells 1-2 contain Biotinylated TSH antibody (7.5 µg/mL mouse monoclonal), wells 3-4 contain TSH antibody coated Chemibeads (200 µg/mL mouse monoclonal), and wells 5-6 contain Streptavidin Sensibeads (1400 µg/mL recombinant E. coli). Wells 1-6 contain buffers, stabilizers and preservatives. Wells 7-8 are empty.

Dimension® LOCI® Free Thyroxine Flex® reagent cartridge (FT4L): prepackaged liquid reagents in a plastic eight-well cartridge. Wells 1-2 contain Streptavidin Sensibeads (225 µg/mL recombinant E. coli), wells 3-4 contain T3 Chemibeads (200 µg/mL), and wells 5-6 contain FT4 Biotinylated antibody (50 ng/mL mouse monoclonal). Wells 1-6 contain buffers, stabilizers and preservatives. Wells 7-8 are empty.

Test Principle: Both devices use a homogeneous chemiluminescent immunoassay based on LOCI® technology.
For TSHL, it's a sandwich immunoassay where sample is incubated with biotinylated antibody and Chemibeads to form bead-TSH-biotinylated antibody sandwiches. Sensibeads are added and bind to the biotin to form bead-pair immunocomplexes. Illumination at 680 nm generates singlet oxygen from Sensibeads which diffuses into Chemibeads, triggering a chemiluminescent reaction. The resulting signal is measured at 612 nm and is a direct function of TSH concentration.
For FT4L, it's a sequential immunoassay where sample is incubated with biotinylated antibody. T3 Chemibeads are added and form bead/biotinylated antibody immunocomplexes with the non-saturated fraction of the biotinylated antibody. Sensibeads are then added and bind to the biotin to form bead pair immunocomplexes. Illumination at 680 nm generates singlet oxygen from Sensibeads which diffuses into the Chemibeads, triggering a chemiluminescent reaction. The resulting signal is measured at 612 nm and is an inverse function of FT4 concentration.

The document provided is a 510(k) clearance letter from the FDA for two in-vitro diagnostic (IVD) devices: Dimension® LOCI® Thyroid Stimulating Hormone Flex® reagent cartridge (TSHL) and Dimension® LOCI® Free Thyroxine Flex® reagent cartridge (FT4L). It describes the devices, their intended use, and the performance characteristics tested to demonstrate substantial equivalence to previously cleared predicate devices.

However, it's crucial to understand that this document describes a reagent cartridge, which is a laboratory assay, not an AI/ML-driven device or an imaging device. Therefore, many of the requested criteria (e.g., sample size for training/test sets for AI, data provenance like country of origin for AI, ground truth establishment by experts, adjudication methods, MRMC studies, standalone AI performance) are not applicable to this type of device. The document details the performance of the assay itself in measuring biomarker concentrations, not an AI's ability to interpret images or assist human readers.

I will interpret the request based on the information provided for this specific IVD device, noting where certain requested details are not relevant to the nature of the device.

Acceptance Criteria and Study to Prove Device Meets Criteria (for an IVD Reagent Cartridge)

The device in question, a reagent cartridge for quantitative measurement of TSH and FT4, is a laboratory assay, not an AI/ML or imaging interpretation device. Therefore, the "acceptance criteria" and "study" are focused on analytical performance characteristics (accuracy, precision, linearity, interference, detection limits, etc.) compared to a predicate device, rather than diagnostic accuracy metrics of an AI.

1. Table of Acceptance Criteria and Reported Device Performance

For an IVD reagent cartridge, "acceptance criteria" are typically defined by ranges, limits, or statistical agreementsdemonstrating analytical performance comparable or superior to the predicate device and meeting relevant clinical or analytical standards (e.g., CLSI guidelines). The reported performance demonstrates that the modified devices meet these standards.

2. Sample Sizes and Data Provenance for the Test Set

The concept of a "test set" in the context of an IVD reagent cartridge refers to the set of samples used for various analytical performance studies. These are not typically split into "training" and "test" sets as in AI/ML.

• Method Comparison:
  • TSHL: 145 patient samples (serum)
  • FT4L: 146 patient samples (serum)
• Precision (Repeatability): 5 serum samples (TSHL), 3 serum samples (FT4L)
• Precision (Reproducibility): 5 serum samples (TSHL), 3 serum samples (FT4L)
• Linearity: Low and high human serum pools used to create dilution series (TSHL: 12 levels, FT4L: 10 levels)
• Interference (Biotin and HIL): Samples spiked with interferents, specific TSH/FT4 levels tested.
• Dilution Recovery: 7 samples (TSHL)
• Reference Range Verification: "Apparently healthy samples" (specific N not provided, but typically a statistically significant number for verification per CLSI EP28-A3C).
• Matrix Comparison: Samples of various tube types (Serum, lithium heparin, sodium heparin, K2-EDTA plasma)

Data Provenance: The document does not specify the country of origin of the patient samples. The studies are explicitly described as analytical performance studies rather than clinical outcome studies, and they are retrospective (samples tested in the lab, not followed prospectively).

3. Number of Experts and Qualifications for Ground Truth

This is not applicable as the device is a quantitative IVD assay (reagent cartridge), not an AI/ML device requiring expert interpretation of complex clinical data or images. The "ground truth" for this device is the actual concentration of TSH or FT4 in the sample, typically established either by:

• Reference methods (e.g., mass spectrometry, although not explicitly stated as the ground truth method here).
• The predicate device itself (as used in method comparison studies, where the predicate is the "comparison assay").
• Spiking known concentrations into matrices.

4. Adjudication Method for the Test Set

This is not applicable for a quantitative IVD reagent. Adjudication methods (e.g., 2+1, 3+1) are typically used in scenarios where human experts interpret data (like medical images), and their disagreements need to be resolved to establish a definitive ground truth for AI model evaluation.

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

This is not applicable. An MRMC study is designed to evaluate the diagnostic performance of human readers, often with and without AI assistance, on a set of cases. This device is a reagent cartridge that provides a quantitative measurement, not an AI that assists human interpretation.

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

This is not applicable. This device is a reagent cartridge that runs on an automated system, providing a quantitative result. It's inherently "standalone" in providing the measurement, but it's not an "algorithm only" in the sense of an AI interpreting complex data. The performance metrics listed (precision, accuracy relative to predicate, linearity, etc.) are its "standalone" performance.

7. Type of Ground Truth Used

The "ground truth" for this type of quantitative diagnostic test is based on:

• Comparison to a legally marketed predicate device: The current, FDA-cleared versions of the TSHL and FT4L assays (K081074 and K073604) acted as the "gold standard" or comparison method for the method comparison studies.
• Known concentrations: For linearity, recovery, and interference studies, samples were prepared with known concentrations or spiked with known amounts of analytes or interferents.
• Analytically verified samples: Samples used for precision studies have mean values derived from repeated measurements.

8. Sample Size for the Training Set

This is not applicable as the device is a non-AI/ML IVD reagent cartridge. There is no concept of a "training set" for this type of product. The development and optimization of the reagent formulation are internal processes, but they don't involve "training" a model on a dataset in the AI sense.

9. How Ground Truth for the Training Set Was Established

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

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