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The Dynamic MRI Software Option for C-scan, E-scan XQ and E-scan Opera MRI Systems allows the acquisition of MR dynamic image datasets and the post processing display of temporal variations in the acquired datasets, showing changes in contrast over time. Its purpose is to provide time intensity curves that support the diagnostic process. These images when interpreted by a trained physician, yield information that may assist in diagnosis.

The Dynamic MRJ Software Option is a software package intended to be used with the Esaote C-scan. E-scan XO and E-scan Opera MRI systems, cleared via K040877 K032121 and K060956, respectively, The software package allows the acquisition of MR dynamic image datasets and the post processing display of temporal variations in the acquired image datasets, showing changes in image contrast over time.

It provides time intensity data, calculates the interpolation curve of the data, its maximum slope and its asymptotic value. These data, when interpreted by a trained physician, vield information that may assist diagnosis.

C-scan is a Magnetic Resonance (MR) system that produces transversal, sagittal and coronal and oblique cross-section images of the limbs and joints. It is intended for imaging portions of the arm, including the hand, wrist, forearm and elbow, but excluding the upper arm, and imaging portions of the leg, including the foot, ankle, calf and knee, but excluding the thigh.

E-scan XO is a magnetic resonance (MR) system that produces transversal, sagittal and coronal and oblique cross-section images of the limbs and joints. It is intended for imaging portions of the arm, including the hand, wrist, forearm, elbow, upper arm and shoulder, and imaging portions of the leg, including the foot, ankle, calf, knee, thigh and hip.

E-scan Opera is a magnetic resonance (MR) system that produces transversal, sagittal and coronal and oblique cross-section images of the limbs and ioints. It is intended for imaging portions of the arm. including the hand, wrist, forearm, elbow, upper arm and shoulder, and imaging portions of the leg, including the foot, ankle, calf, knee, thigh and hip.

The C-scan, E-scan XO and E-scan Opera MR images correspond to the spatial distribution of protons (hydrogen nuclei) that determine magnetic resonance properties and are dependent on the MR parameters, including spin-lattice relaxation time (T1), spin-spin relaxation time (T2), nuclei density, flow velocity and "chemical shift". When interpreted by a medical expert trained in the use of MR equipment, the images can provide diagnostically useful information.

Here's an analysis of the provided text regarding the acceptance criteria and study information for the Dynamic MRI Software Option for C-scan/E-scan XQ/E-scan Opera.

It's important to note that this 510(k) summary is for a software option that enhances existing MRI systems by enabling dynamic imaging and post-processing of temporal variations. The focus is on demonstrating substantial equivalence to predicate devices rather than a de novo clinical study proving novel diagnostic efficacy. Therefore, typical acceptance criteria and study designs for entirely new diagnostic algorithms might not apply directly in the same way.

Acceptance Criteria and Reported Device Performance

The concept of "acceptance criteria" for this specific 510(k) is primarily centered around demonstrating substantial equivalence to predicate devices, particularly in terms of indications for use and technological characteristics, without introducing new questions of safety or effectiveness. The reported performance is essentially that the device functions comparably to the predicate devices in its ability to acquire and process dynamic MRI data to produce time-intensity curves.

Given the nature of a 510(k) for a software enhancement to an already cleared imaging system, the "acceptance criteria" are implied through comparison with predicate devices, rather than explicit numerical performance targets like sensitivity/specificity for a diagnostic AI model.

Study Information

Based on the provided 510(k) summary, there is no explicit clinical study described for this specific device. The clearance is based on demonstrating "substantial equivalence" to legally marketed predicate devices, which is a common pathway for modifications or enhancements to existing, cleared medical devices.

The information suggests that the device’s performance is validated through engineering comparisons to predicate devices, confirming that the new software option provides similar functionality without altering the fundamental scientific technology or raising new safety/effectiveness concerns.

Here's why specific sections of your request are not directly addressed in this type of submission:

1. Sample size used for the test set and the data provenance: Not applicable. No "test set" in the sense of a clinical trial dataset is described. The assessment is a comparison of technical specifications and intended use against predicate devices.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No "ground truth" derived from expert consensus on a test set is described. The device leverages existing MRI technology, where "ground truth" is typically established by the inherent diagnostic capabilities of MRI when interpreted by a trained physician.
3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. No clinical test set requiring adjudication is mentioned.
4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable. This is not an AI-assisted diagnostic device in the modern sense, but rather a software feature for dynamic imaging. No MRMC study is mentioned.
5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This device is inherently "human-in-the-loop" as it provides data for a trained physician to interpret. It is not an autonomous diagnostic algorithm.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not explicitly stated as part of a validation study for this specific software, as its functionality is based on established MRI principles. The "ground truth" concept is inherent in the predicate MRI systems providing diagnositc information when interpreted by a medical expert.
7. The sample size for the training set: Not applicable. This is not a machine learning or AI algorithm that requires a "training set."
8. How the ground truth for the training set was established: Not applicable.

In summary, the provided document is a 510(k) summary demonstrating substantial equivalence for a software feature (dynamic MRI acquisition and post-processing) for existing MRI systems. It relies on the prior clearance of its predicate devices and the established safety and effectiveness of MRI technology itself, rather than presenting a new clinical study with explicit performance metrics against a defined ground truth.

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