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FerriSmart is indicated to:
· measure liver iron concentration in individuals with confirmed or suspected systemic iron overload;
· monitor liver iron burden in transfusion dependent thalassemia patients with sickle cell disease receiving blood transfusions:
• aid in the identification and monitoring of non-transfusion-dependent thalassemia patients receiving therapy with deferasirox.

FerriSmart is a stand-alone software application that automatically analyses multi-slice, spin-echo MRI data sets encompassing the abdomen to determine the signal decay rate (R>) that is used to characterize iron loading in the liver, which is then transformed by a defined calibration curve to provide a quantitative measure of liver iron concentrations in vivo.

The software application is a measuring medical device intended to be hosted either in a cloudbased or on site hosted platform and used directly by the radiographer. It does not drive the MRI machine and does not come into direct contact with patients.

The key components of FerriSmart are:

• Specific Magnetic Resonance Imaging Protocol: Use of a specific magnetic resonance imaging protocol for acquisition of the raw image data. The imaging protocol is critical to ensure the quality of the end results. Its adherence is verified by the IQC Module, an automated algorithm that checks the correctness of the parameters of the data acquisition protocol.
• FerriSmart AI Analysis Software: Custom-designed image analysis software performing the R2 measurement based on AI (Artificial Intelligence) technology.
• An additional software module (algorithmic) that Liver Iron Measurement: incorporates a calibration curve relating R2 to liver iron concentration (LIC) is added to allow production of a liver iron concentration report.

The result report provides the patient's average LIC reported in micromole and milligram per gram dry weight of liver. The images analysed are included in the report for review by the radiologist. The results are intended to assist in clinical diagnosis, and/or in making decisions concerning clinical management.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Reported Device Performance

LIC Threshold: 3.0 mg Fe/g dry tissue (interrupt deferasirox for NTDT):
Sensitivity: 96% (95% CI 94-97%)
Specificity: 95% (95% CI 92-98%)

LIC Threshold: 3.2 mg Fe/g dry tissue (historical HHC definition, lower optimal for chelation):
Sensitivity: 94% (95% CI 92-96%)
Specificity: 95% (95% CI 92-98%)

LIC Threshold: 5.0 mg Fe/g dry tissue (consider deferasirox for NTDT):
Sensitivity: 91% (95% CI 89-94%)
Specificity: 97% (95% CI 95-99%)

LIC Threshold: 7.0 mg Fe/g dry tissue (upper optimal for chelation, increased risk):
Sensitivity: 92% (95% CI 90-95%)
Specificity: 97% (95% CI 95-98%)

LIC Threshold: 15.0 mg Fe/g dry tissue (greatly increased cardiac risk, increase deferasirox dose):
Sensitivity: 89% (95% CI 85-93%)
Specificity: 98% (95% CI 98-99%)

Overall, most sensitivities and specificities are above 90%, with the exception of specificity at 1.8 mg Fe/g dry tissue (80%) and sensitivity at 15.0 mg Fe/g dry tissue (89%). These exceptions are deemed acceptable for clinical use. |
| Usability | All participants found the product easy to use, fast, and technically reliable (no bugs). |
| Software Verification & Validation | Developed, verified, and validated following Design Control principles and General Principles of Software Validation guidelines. |

Study Information

1. Sample sizes used for the test set and the data provenance:

   • Repeatability Study Test Set: 60 subjects scanned twice. The provenance of this data (country of origin, retrospective/prospective) is not specified.
   • Clinical Study Test Set: 971 datasets from multiple makes and models of MRI scanners. The provenance (country of origin, retrospective/prospective) is not specified.

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

   • The ground truth for the clinical study was the predicate device, FerriScan R2-MRI Analysis System. For the predicate, "human interaction for Region of Interest (ROI) selection" was noted.
   • The text does not specify the number or qualifications of experts involved in establishing the FerriScan results used as ground truth for this FerriSmart study. It only mentions that FerriScan is used "in-house by Resonance Health's analysts."

3. Adjudication method for the test set:

   • The text does not explicitly state an adjudication method (such as 2+1 or 3+1) for the comparison between FerriSmart and FerriScan results, or for the FerriScan results themselves. The ground truth was based on the FerriScan device output.

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:

   • No, an MRMC comparative effectiveness study was not done. The study's clinical performance evaluation was a standalone performance assessment of FerriSmart against a predicate device (FerriScan), not a comparison of human readers with vs. without AI assistance. The user of FerriSmart is stated to be a radiologist, who oversees the report, but the study focuses on the algorithm's performance relative to the predicate.

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

   • Yes, a standalone performance study was done. FerriSmart is described as a "stand-alone software application" which "automatically analyses" MRI data. The clinical study assessed its R2 and LIC measurements and diagnostic performance against the predicate without direct human intervention in the analysis process besides the radiologist reviewing the final report. FerriSmart uses an algorithm for automatic quality checks, whereas the predicate "requires human input" for some checks.

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

   • The ground truth for the study was the results from the predicate device, FerriScan R2-MRI Analysis System. FerriScan itself uses an algorithmic approach with human interaction for ROI selection and aims to provide quantitative measures of LIC, which would ultimately correlate to other clinical ground truths like liver biopsy in its own validation studies (as hinted by the comparison to biopsy error rates).

7. The sample size for the training set:

   • The document states, "FerriSmart AI Analysis Software has been trained on FerriScan data." However, the sample size for the training set is not explicitly provided in the given text.

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

   • The ground truth for the FerriSmart training set was established using data processed by the predicate device, FerriScan R2-MRI Analysis System. The text explicitly states, "FerriSmart AI Analysis Software has been trained on FerriScan data." This implies that the outputs from FerriScan (R2 measurements and LIC values) were used as the target for the AI's learning process.

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