Search Results

The E-scan is intended for diagnostic nuclear magnetic resonance imaging of the hip, knee, ankle, foot, shoulder, elbow, wrist, hand, calf, thigh, arm and forearm. The device produces transverse, sagittal, coronal and oblique cross-sectional images, displaying the internal structure of the limbs and joints being imaged. The images that are produced correspond to the spatial distribution of protons (hydrogen nuclei) that check the magnetic resonance properties and depend upon the MR parameters (spin-lattice relaxation time (T1), spin-spin relaxation time (T2), nuclei density, flow velocity and chemical shift). If interpreted by a medical expert, these images can provide diagnostically useful information.

The E-scan is a magnetic resonance diagnostic device. The Multipurpose Flexible Receiving Coil improves the system performance and does not alter the fundamental scientific technology of the cleared device.

The provided 510(k) summary does not contain the detailed information typically required to describe acceptance criteria and a study proving a device meets them in the context of an AI/ML medical device submission. This document pertains to an MRI system (E-Scan) and a new receiving coil, filed in 2001, long before the widespread use and regulatory frameworks for AI/ML in medical devices.

Therefore, many of the requested fields cannot be directly extracted from the provided text. I will address what information is available and explain why other fields are missing or not applicable.

Here's an analysis based on the provided text:

Acceptance Criteria and Study for E-Scan MRI System (Receiving Coil)

The submission focuses on establishing substantial equivalence to a predicate device, primarily through demonstrating that the addition of a "Multipurpose Flexible Receiving Coil" does not alter the fundamental scientific technology of the cleared device (Esaote E-Scan K001894). The acceptance criteria are implicitly tied to maintaining the safety and effectiveness profile of the predicate device.

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: Not specified. The document does not describe a clinical study or test set in the way an AI/ML validation would. It primarily focuses on the technical characteristics of the new coil and its intended use.
• Data Provenance: Not applicable. There's no mention of specific data used for a test set that would have provenance like country of origin or whether it was retrospective/prospective.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The submission states that images, "If interpreted by a medical expert, these images can provide diagnostically useful information," but doesn't detail their role in a specific test for the coil.

4. Adjudication method for the test set:

• Adjudication method: Not applicable. No specific test set or adjudication process 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:

• MRMC Study: No, an MRMC study was not done.
• Effect Size of AI assistance: Not applicable. This submission is for an MRI system and a mechanical coil, not an AI/ML algorithm.

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

• Standalone Performance: Not applicable. This is not an AI/ML algorithm. The device produces images that "If interpreted by a medical expert, these images can provide diagnostically useful information," clearly indicating human interpretation is part of its intended use.

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

• Type of Ground Truth: Not explicitly stated as part of a formal validation study. For an MRI system, the "ground truth" for image quality and diagnostic utility is typically established by comparing the images produced to established anatomical knowledge, clinical expectations, and the ability of human experts to make diagnoses from them. No specific methodology for establishing such ground truth in the context of this specific submission (for the new coil) is detailed beyond its intended use for diagnostic imaging.

8. The sample size for the training set:

• Sample Size: Not applicable. This is not an AI/ML algorithm that required a training set.

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

• Ground Truth Establishment: Not applicable. This is not an AI/ML algorithm that required a training set.

Summary of what can be gleaned about the "study" for this device:

The "study" for this 510(k) submission primarily involved demonstrating that the new Multipurpose Flexible Receiving Coil is consistent with the established safety and effectiveness of the predicate E-Scan MRI system (K001894). The key "performance" claim is that the new coil "improves the system performance and does not alter the fundamental scientific technology of the cleared device," and that it can be used for various anatomical regions, including those that might be challenging with other coils (e.g., painful or plastered limbs). This substantial equivalence argument is based on technical specifications and comparison to existing devices rather than a formal clinical trial or AI/ML validation study.

Ask a specific question about this device

The MR system is an imaging device, and is intended to provide the physician with physiological and clinical information, obtained non-invasively and without the use of ionizing radiation. The MR system produces transverse, coronal, sagittal, oblique, and curved cross-sectional images that display the internal structure of the head, body, or extremities. The images produced by the MR system reflect the spatial distribution of protons (hydrogen nuclei) exhibiting magnetic resonance. The NMR properties that determine the image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2), and flow. When interpreted by a trained physician, these images provide information that can be useful in diagnosis determination.

The AIRIS Operating System Software is revised to Version 4 to increase the clinical utility of the AIRIS in the stationary configuration. The MRP-7000 Operating System Software is revised to Version 4 to increase the clinical utility of the MRP-7000 in both stationary and mobile configurations.

Version 4 Operating System revisions include automatic per patient RF Gain calibration for improved fat suppression, daily- or per-patient x- y- and z-axis gradient offsets for regional shimming, MR cholangiography sequences (MRCP) for improved imaging of the biliary tract, Fluoroscopic MR imaging sequences for 'nearreal-time' imaging, FLAIR (fast low-angle inversion recovery) sequence for suppression of CSF signal, segmented K-space SARGE sequence for time-improved cardiac imaging, addition of rephasing to several FSE sequences, addition of RS (RF Spoiled) SARGE sequence, improved method for body return artifact rejection, submillimeter slice thickness for 3DTOFMRA sequences, reduced slice interval for 3D TOF/GE/SARGE/SE acquisitions, high-definition imaging by 512 matrix reconstruction, short TE SE sequences (TE=9, 10ms), addition of rephasing to 3D SARGE sequence, 'whole echo' 3DTOFMRA, non-linear window for MRA, brightness normalization for selected images with the same acquisition parameters within a patient study, and ACR/NEMA/DICOM 3 support.

In addition, the MRP-7000 and AIRIS Operating System Software are modified to change the maximum SAR limit from 0.4 W/kg to 1.0 W/kg as permitted under the International Electrotechnical Commission (IEC) standard Part 2: Particular Requirements for the Safety of Magnetic Resonance Equipment for Medical Diagnosis.

This document describes the 510(k) premarket notification for the Hitachi Version 4 Operating System Software for AIRIS and MRP-7000 MRI devices. The primary focus of the submission is to increase the maximum Specific Absorption Rate (SAR) limit from 0.4 W/kg to 1.0 W/kg, aligning with the International Electrotechnical Commission (IEC) standard Part 2: Particular Requirements for the Safety of Magnetic Resonance Equipment for Medical Diagnosis. The submission also details various software revisions to enhance clinical utility.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly defined in terms of specific performance metrics (e.g., accuracy, sensitivity, specificity) for the imaging capabilities. Instead, the primary "acceptance criterion" addressed in this 510(k) is the compliance with a higher SAR limit based on an internationally recognized safety standard. The device's "performance" in this context refers to its ability to operate safely at the higher SAR level.

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

The document does not describe a specific test set or clinical study with a defined sample size for evaluating the Version 4 Operating System Software or the change in SAR limit.

The data provenance for the SAR limit change is based on the International Electrotechnical Commission (IEC) standard IEC-601-2-33. The submission references an existing international standard and the FDA's supposed acceptance of its provisions, rather than presenting new clinical or performance data from a specific study.

For the new software features, the document states they "increase the clinical utility" and are revisions to existing systems. There is no mention of specific sample sizes or data provenance for proving the efficacy or performance of these new features. It's implied that these are incremental improvements to an already cleared device, not requiring new clinical performance studies for their functionality.

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. As there is no described test set or clinical study to evaluate the device's diagnostic performance for which ground truth would need to be established, this detail is absent. The submission primarily focuses on safety compliance (SAR limit) and functional enhancements to an existing device rather than diagnostic accuracy.

4. Adjudication Method for the Test Set

This information is not applicable as no specific test set requiring adjudication is described in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, If So, What Was the Effect Size of How Much Human Readers Improve with AI vs without AI Assistance

This information is not applicable and no such study was performed or is mentioned. The device in question is an MRI system's operating software, not an AI-assisted diagnostic tool.

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

This information is not applicable. The device is an MRI system's operating software, which requires human operation and interpretation. It is not an algorithm that would typically be evaluated in a standalone performance study in the context of diagnostic accuracy. The "algorithm-only" aspect mentioned refers to the safety calculation for SAR, which is part of the system's inherent design and safety features, not a diagnostic algorithm.

7. The Type of Ground Truth Used

For the primary claim concerning the SAR limit increase, the "ground truth" used is the IEC-601-2-33 standard itself, which defines the safety parameters and acceptable SAR levels. This is a consensus-based international safety standard, rather than clinical outcomes or pathology data.

For the other software features, no specific ground truth is mentioned, as no formal performance testing in the conventional sense (e.g., against pathology) is described for these enhancements. The improvements in "clinical utility" would likely be assessed through engineering verification and validation against design specifications and potentially internal clinical evaluations, but not a large-scale ground truth study.

8. The Sample Size for the Training Set

This information is not applicable and not provided. The document describes an update to an MRI system's operating software and a change in its SAR limit. This is not a machine learning or AI-driven device that requires a training set in the typical sense for image interpretation or diagnosis.

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

This information is not applicable as no training set for a machine learning model is described.

Ask a specific question about this device