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510(k) Data Aggregation
(67 days)
Hepatica (Hepatica v1) is a post-processing medical device software that presents quantified metrics which may contribute to the assessment of a patient's liver health.
Hepatica (Hepatica v1) uses image visualisation and analysis tools to process DICOM 3.0 compliant magnetic resonance image datasets to produce semi-automatic segmented 3D models of the work of Couinaud and the Brisbane 2000 terminology. For each identified Couinaud segment, volumetric data is determined and reported.
Hepatica v1) may also report iron corrected-T1 (cT1) and PDFF calculated using the IDEAL method from multi-slice acquisitions, on a per segment basis, over the whole liver. Both metrical values of different fundamental liver tissue characteristics that can be used as measures of liver tissue health.
Hepatica (Hepatica v1) provides trained clinicians with additional information to evaluate the volume and health of a patient's liver on a segmental basis. It is not intended to replace the established procedures for the assessment of a patient's liver health. However, information gathered through existing diagnostic tests, clinical evaluation of the patient, as well Hepatica (Hepatica v1), may support surgical decision making.
Hepatica v1 is a standalone software device that imports MR datasets encompassing the abdomen, including the liver. Visualisation and display of T1-weighted MR data which can be analysed, and quantitative metrics of tissue characteristics and liver volume are then reported. Datasets imported into Hepatica are DICOM 3.0 compliant and reported metrics are independent of the MRI equipment vendor. It allows for the 3D visualisation of the liver and quantification of metrics (cT1, PDFF and volumetry) from liver tissue and exportation of results and images to a deliverable report. Hepatica v1 supports semi-automatic liver segmentation of T1-weighted volumetric data. Liver segmentation in Hepatica v1 requires the placement of anatomical landmarks to define the outer contours of the liver and can be adjusted by the operator, where necessary. Where available, whole liver and segmental cT1 and PDFF quantitative metrics derived from the predicate device may be presented in the final report. Hepatica uses volumetric datasets to create 2D anatomical views from all supported scanners. Where available, cT1 and PDFF parametric maps are derived from the predicate device. Quantified metrics and images derived from the analysis of liver volume and tissue characteristics are collated into a report for evaluation and interpretation by a clinician.
Here's a breakdown of the acceptance criteria and study information for the Hepatica (Hepatica v1) device, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly state acceptance criteria in a quantitative format (e.g., "accuracy must be >X%"). Instead, it states that the performance testing "demonstrates that Hepatica v1 is at least as safe and effective as the predicate device and does not introduce any new risks."
However, it provides "Upper and Lower Limits of Agreement" from a Bland-Altman analysis, which can be interpreted as the range within which the device's measurements agree with the gold standard. A tighter range indicates higher accuracy. The precision results are also presented as "Upper and Lower limits of Agreement" for repeatability and reproducibility.
The table below summarizes the reported device performance, which implies that these values met the internal acceptance parameters for demonstrating substantial equivalence:
| Metric | Type of Measurement | Reported Device Performance (Upper and Lower Limits of Agreement) |
|---|---|---|
| Volume (% of total liver volume) | ||
| Segment 1 | Accuracy | -0.49% to 0.95% |
| Segment 2 | Accuracy | -3.09% to 5.06% |
| Segment 3 | Accuracy | -5.01% to 3.9% |
| Segment 4a | Accuracy | -4.60% to 4.26% |
| Segment 4b | Accuracy | -5.50% to 2.56% |
| Segment 5 | Accuracy | -1.54% to 3.38% |
| Segment 6 | Accuracy | -4.34% to 4.29% |
| Segment 7 | Accuracy | -3.30% to 1.79% |
| Segment 8 | Accuracy | -3.86% to 5.54% |
| Whole liver | Accuracy | -4.16% to 0.54% |
| Segment 1 | Repeatability | -0.72% to 0.65% |
| Segment 2 | Repeatability | -3.06% to 3.24% |
| Segment 3 | Repeatability | -2.67% to 3.13% |
| Segment 4a | Repeatability | -2.48% to 2.43% |
| Segment 4b | Repeatability | -1.82% to 1.96% |
| Segment 5 | Repeatability | -4.45% to 4.45% |
| Segment 6 | Repeatability | -3.60% to 4.10% |
| Segment 7 | Repeatability | -3.32% to 3.33% |
| Segment 8 | Repeatability | -4.99% to 3.81% |
| Whole liver | Repeatability | -6.15% to 3.78% |
| Segment 1 | Reproducibility | -1.39% to 0.90% |
| Segment 2 | Reproducibility | -3.10% to 3.15% |
| Segment 3 | Reproducibility | -2.41% to 2.06% |
| Segment 4a | Reproducibility | -2.54% to 2.58% |
| Segment 4b | Reproducibility | -1.70% to 1.74% |
| Segment 5 | Reproducibility | -4.97% to 5.94% |
| Segment 6 | Reproducibility | -3.69% to 5.40% |
| Segment 7 | Reproducibility | -4.39% to 3.59% |
| Segment 8 | Reproducibility | -6.23% to 5.04% |
| Whole liver | Reproducibility | -16.6% to 6.95% |
| cT1 | ||
| Segment 1 | Accuracy | -1.13% to 0.61% |
| Segment 2 | Accuracy | -2.38% to 1.56% |
| Segment 3 | Accuracy | -1.51% to 1.31% |
| Segment 4a | Accuracy | -0.77% to 1.10% |
| Segment 4b | Accuracy | -1.32% to 1.13% |
| Segment 5 | Accuracy | -1.11% to 0.87% |
| Segment 6 | Accuracy | -1.00% to 0.83% |
| Segment 7 | Accuracy | -0.88% to 0.64% |
| Segment 8 | Accuracy | -0.91% to 1.09% |
| Whole liver | Accuracy | 0.00% to 0.00% (This suggests perfect agreement or rounding issues) |
| PDFF | ||
| Segment 1 | Accuracy | -0.26% to 0.21% |
| Segment 2 | Accuracy | -0.33% to 0.38% |
| Segment 3 | Accuracy | -0.16% to 0.17% |
| Segment 4a | Accuracy | -0.30% to 0.23% |
| Segment 4b | Accuracy | -0.16% to 0.14% |
| Segment 5 | Accuracy | -0.16% to 0.18% |
| Segment 6 | Accuracy | -0.16% to 0.26% |
| Segment 7 | Accuracy | -0.12% to 0.18% |
| Segment 8 | Accuracy | -0.24% to 0.32% |
| Whole liver | Accuracy | -0.02% to 0.02% |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: The document states that the performance testing used "previously acquired in-vivo data from healthy and non-healthy volunteers." It also mentions "Volunteers participating in the performance testing were representative of the intended patient population." However, a specific number for the sample size (N) of these volunteers or images in the test set is not provided.
- Data Provenance: "Previously acquired in-vivo data." The country of origin is not explicitly stated. It can be inferred that the data is likely from the UK, given the submitter's address (Oxford, UK). The data is retrospective, as it was "previously acquired."
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
- Number of Experts: The document refers to the gold standard as "radiologists." It does not specify the number of radiologists involved in establishing the ground truth.
- Qualifications of Experts: The qualification is "radiologists." No further details on their years of experience or sub-specialty are provided.
4. Adjudication Method for the Test Set
The document states that the "gold standard" is "radiologists." It does not describe any specific adjudication method (e.g., 2+1, 3+1 consensus) used to establish this ground truth. It implies that the radiologists' readings were considered the definitive truth.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The study compared the device's measurements to a "gold standard" (radiologists' assessments), not the performance of human readers with vs. without AI assistance. Therefore, there is no effect size reported for human readers improving with AI assistance.
6. If a Standalone Study Was Done
Yes, a standalone (algorithm only without human-in-the-loop performance) study was done. The performance testing section directly reports on the "Accuracy" and "Precision" of Hepatica v1's measurements (cT1, PDFF, and volumetry) when compared to the gold standard. The device operators are "trained Perspectum internal operators," but the reported metrics are explicitly from the device's output. The statement "The variation introduced by operator measurements are well within the acceptance criteria" also suggests an understanding of the device's standalone performance separate from human interpretation of the reports.
7. The Type of Ground Truth Used
The primary ground truth used for accuracy comparison is expert consensus/interpretation, specifically "radiologists." For cT1 and PDFF, these are quantitative measurements derived from imaging, which radiologists would interpret or measure. For volumetry, it's also based on radiological assessment.
8. The Sample Size for the Training Set
The document does not provide the sample size for the training set. It only mentions the "previously acquired in-vivo data from healthy and non-healthy volunteers" used for performance testing.
9. How the Ground Truth for the Training Set Was Established
Since the training set sample size and its specifics are not mentioned, how its ground truth was established is not described in the provided document.
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