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S-scan is a Magnetic Resonance (MR) system that produces transversal, sagittal and coronal and oblique cross-section images of the limbs, joints and spinal column. It is intended for imaging portions of the upper limb, including the hand, wrist, forearm, elbow, arm and shoulder, imaging portions of the lower limb, including the foot, ankle, calf, knee, thigh and hip, imaging of the temporomandibular joint and imaging the cervical spine and the lumbar spine sections as portions of the spinal column.

S-scan 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.

The changes performed on the modified S-scan device, with respect to the cleared version - Sscan K121650 - are due to the improvement of the system performance. These modifications, which do not affect the intended use or alter the fundamental scientific technology of the device, are the following:

• 1. Upgrading of the electronics
• 2. Patient bed unlocking function
• 3. A new software version

This document is a 510(k) summary for the S-scan Magnetic Resonance (MR) system from Esaote S.p.A. It describes a modified version of the S-scan device compared to its cleared predicate (K121650).

Here's an analysis of the provided text regarding acceptance criteria and the study:

Important Note: The provided 510(k) summary is for a modified device, and the changes are described as "improvement of the system performance" due to "Upgrading of the electronics," "Patient bed unlocking function," and "A new software version." Crucially, it states that these modifications "do not affect the intended use or alter the fundamental scientific technology of the device." As a result, this 510(k) relies on the substantial equivalence to the predicate device (K121650) and does not describe a new study with explicit acceptance criteria for a novel AI/software feature with reported device performance results.

Therefore, I cannot directly extract "acceptance criteria and the study that proves the device meets the acceptance criteria" in the typical sense of a new AI algorithm's performance study from this particular document. The document essentially states that because the fundamental scientific technology and intended use are unchanged, a new major performance study against specific acceptance criteria for the new components is not required to demonstrate substantial equivalence for the overall device.

However, I can still extract information related to the device and its intended function, which would implicitly encompass its performance requirements.

1. Table of acceptance criteria and the reported device performance

Based on the provided text, there are no explicit acceptance criteria or reported device performance metrics stated for the modified S-scan's new software/electronics within this 510(k) summary. This is because the submission is a "Special 510(k)" relying on the fundamental equivalence to the predicate, K121650, where performance was presumably established. The modifications are described as improvements that do not alter the fundamental scientific technology or intended use.

The intended function of the device is to produce diagnostic MR images. Therefore, the implicit acceptance criterion is that the modified device must continue to produce diagnostically useful images of equivalent or improved quality compared to the predicate device, as determined by a medical expert.

Regarding the study proving the device meets acceptance criteria:

The document doesn't describe a specific clinical study for the modified S-scan to prove it meets new or modified acceptance criteria as if it were a novel AI algorithm. Instead, the "proof" is based on the argument of substantial equivalence to the predicate device (K121650). The modifications are considered "improvements" that do not alter the fundamental scientific technology. This type of submission (a Special 510(k)) typically relies on verification and validation of the engineering changes to ensure the device continues to meet its established performance specifications, rather than a full-scale clinical trial to re-establish diagnostic accuracy.

Therefore, for aspects 2-9, the answer is largely that this information is not applicable to this specific 510(k) summary because it doesn't describe a new performance study to establish primary diagnostic performance of a new algorithm but rather an upgrade to an existing MR imaging system.

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

• Not applicable. This 510(k) does not describe a new performance study with a test set of images for diagnostic evaluation by a new algorithm. The "test set" for the system itself would be part of the predicate device's original clearance (K121650) and internal engineering verification and validation testing for the upgrades.

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. See point 2.

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

• Not applicable. See point 2.

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 applicable. This 510(k) is for a conventional MR imaging system, not an AI-assisted diagnostic tool.

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

• Not applicable. This 510(k) is for an MR imaging system; it does not involve a standalone algorithm for diagnostic interpretation. The device's output (images) requires interpretation by a medical expert. ("When interpreted by a medical expert trained in the use of MR equipment, the images can provide diagnostically useful information.")

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

• Not applicable for this 510(k) submission. For the original predicate device (K121650), the ground truth for validating MR image quality would typically involve various phantoms, physical measurements, and potentially clinical correlation with other imaging modalities or pathologies if clinical validation was performed.

8. The sample size for the training set

• Not applicable. This device is an MR imaging system; it is not described as involving a machine learning algorithm with a "training set" in this context. The "new software version" likely refers to operational software for the MRI, not an AI diagnostic algorithm.

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

• Not applicable. See point 8.

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