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510(k) Data Aggregation
(21 days)
Velacur One (LI-1100)
Velacur is intended to provide estimates of tissue stiffness generated from shear wave speed measurements (40-70 Hz), ultrasound attenuation and Velacur Determined Fat Fraction (VDFF). The Velacur Determined Fat Fraction combines ultrasound attenuation and backscatter coefficient measurements. The device is indicated to non-invasively determine liver tissue stiffness, attenuation, and Velacur Determined Fat Fraction. VDFF is not intended to be used in pediatric patients. These are meant to be used in conjunction with other clinical indicators in order to aid in clinical management of patients with liver diseases, including hepatic steatosis.
The device is intended to be used in a clinical setting and by trained medical professionals.
The device that is the subject of this submission is the substantially equivalent to that cleared under K233977, Velacur.
Velacur ONE is a portable device intended to non-invasively measure the stiffness and attenuation of the liver via measurement of liver tissue shear modulus and ultrasound attenuation. This is done by measuring the wavelength or wave speed of mechanically created shear waves within the organ of the patient. Attenuation is measured directly via the loss in power of the ultrasound beam and Velacur Determined Fat Fraction is a combination of measured ultrasound attenuation and backscatter.
The device is designed to be used at the point of care, in clinics and hospitals. The device is used by a medical profession, an employee of the clinic/hospital. The activation unit is placed under the patient, while lying supine on an exam bed. The activation unit vibrates at frequencies 40, 50, and 60 Hz causing shear waves within the liver of the patient. The ultrasound transducer is placed on the patient's skin, over the intercostal space, and is used to take volumetric scans of the liver while shear waves are occurring. The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. From the scan data, the device calculates tissue stiffness and attenuation.
Software and hardware changes were made to the device. The intended use of the device is unchanged. The user interface was updated to a more modern platform with the same workflow and outputs. The hardware components have been consolidated, combining the functionality of the computing unit and control unit. The activation unit has been designed to include more voice coils which are distributed throughout the unit. The power output and performance of the activation unit is unchanged.
The provided FDA 510(k) clearance letter and summary for Velacur ONE (LI-1100) focuses on substantiating equivalence to a predicate device (Velacur K233977) through bench testing and human factors testing. It explicitly states that "No clinical or animal testing was performed" for this specific submission, meaning there is no mention of a study involving human or animal subjects to prove the device's performance against clinical acceptance criteria.
Therefore, many of the requested details related to clinical study design, such as sample size for test sets, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, and ground truth types, cannot be extracted from this document as these types of studies were not conducted for the Velacur ONE (LI-1100) submission.
The information provided primarily relates to the bench testing validation of the algorithms, which is a different type of validation than a clinical study.
Here's an analysis of the available information:
1. Table of Acceptance Criteria and Reported Device Performance (Bench Testing)
The document refers to "acceptance criteria" within the context of bench testing against phantoms and comparison to the predicate device.
| Metric | Acceptance Criteria (Implicit from "Less than" or "Greater than" statements) | Reported Device Performance (Velacur ONE) |
|---|---|---|
| Elasticity - Bias vs. CIRS values | Not explicitly stated an absolute numerical acceptance criteria, but "overall bias to the CIRS values was used as a comparison point for both systems to determine the substantial equivalence." The average difference between the bias of Velacur ONE and the predicate was 2.45%. | Average difference between bias of Velacur ONE and predicate: 2.45% |
| Elasticity - Precision (min/max/average) | Not explicitly stated an absolute numerical acceptance criteria, but "met all criteria necessary to support clinical suitability" and compared to predicate. Predicate range: 1.1% to 2.6% (average 2.1%). | Average Precision: 1.7% (min: 0.3%, max: 2.9%) |
| Elasticity - Bland-Altman Correlation | "No value falls outside the 1.96*STD lines." | Excellent correlation; no values outside 1.96*STD lines. |
| Elasticity - Substantial Equivalence | "Results of the two systems both passed the defined acceptance criteria when being compared to each other and are considered substantially equivalent." | Both systems passed and are considered substantially equivalent. |
| Attenuation - Overall Bias | Less than 10% | 9.1% |
| Attenuation - Precision (maximum) | Less than 10% | 0.9% (mean); Less than 10% (maximum) (For Velacur ONE) |
| VDFF - Overall Bias | Not explicitly stated numerical acceptance criteria for overall bias, but compared to predicate (9%) and "clinically meaningful cutoff value for any steatosis of 5%". | 8% (compared to predicate bias of 9%) |
| VDFF - Precision (maximum) | Less than 10% | 5.4% |
| VDFF - Pearson Correlation Coefficient (r) vs. Expected VDFF | Greater than 0.8 | 0.95 |
2. Sample Size and Data Provenance
- Test Set Sample Size:
- Elasticity: 6 Homogeneous phantoms.
- Attenuation: 6 attenuation phantoms.
- VDFF: 6 different phantoms.
- Note: These are phantoms, not patient data.
- Data Provenance: The data is from bench testing using phantoms, not clinical data from patients. Therefore, there is no country of origin or retrospective/prospective classification.
3. Number of Experts and Qualifications for Ground Truth
- Not applicable for this submission. Ground truth for bench testing is established by the known properties of the phantoms (e.g., CIRS values, labeled backscatter and attenuation). There is no mention of experts involved in establishing ground truth for the bench tests.
4. Adjudication Method for the Test Set
- Not applicable for this submission. As there's no clinical test set requiring human interpretation, no adjudication method is mentioned.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- No MRMC study was done. The document explicitly states "No clinical or animal testing was performed."
6. Standalone Performance (Algorithm Only without Human-in-the-Loop)
- The performance data provided (bias, precision, correlation coefficients for elasticity, attenuation, and VDFF) appears to be standalone algorithm performance as measured on phantoms. The stated purpose of these tests is to validate the algorithms. While "User holds the probe against the skin, and software... is shown on the device display to indicate when the location is acceptable," the actual measurement and calculation of stiffness, attenuation, and VDFF are algorithmic. The performance metrics listed directly reflect the algorithm's output against the known phantom values.
7. Type of Ground Truth Used
- Phantom Properties: The ground truth for the bench testing was derived from the known and labeled properties of the reference phantoms (e.g., CIRS values for stiffness, labeled backscatter and attenuation for VDFF, and expected attenuation values).
8. Sample Size for the Training Set
- Not mentioned or applicable for this submission. This submission is a 510(k) for a modified device (Velacur ONE) claiming substantial equivalence to a predicate (Velacur). The focus is on verifying that the changes to the device (hardware consolidation, updated UI, new activation unit) do not negatively impact performance compared to the predicate, and that the algorithms maintain their validated performance. Details about the original training of the algorithms (which would have occurred for the predicate device's clearance) are not part of this specific document.
9. How the Ground Truth for the Training Set Was Established
- Not mentioned or applicable for this submission. Similar to point 8, this information would pertain to the original development and validation of the predicate device's algorithms, not this specific 510(k) for a modified device.
The study proves the device meets the acceptance criteria through extensive bench testing on phantoms, demonstrating that the modified Velacur ONE systems performs equivalently to its predicate (Velacur) and within pre-defined numerical tolerances for accuracy and precision when measuring phantom properties. This approach is common for 510(k) submissions of modified devices where clinical performance has already been established for the predicate.
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(261 days)
Velacur
Velacur is intended to provide estimates of tissue stiffness generated from shear wave speed measurements (40-70 Hz), ultrasound attenuation and Velacur Determined Fat Fraction (VDFF). The Velacur Determined Fat Fraction combines ultrasound attenuation and backscatter coefficient measurements. The device is indicated to non-invasively determine liver tissue stiffness, attenuation, and Velacur Determined Fat Fraction. VDFF is not intended to be used in pediatric patients. These are meant to be used in conjunction with other clinical indicators in order to aid in clinical management of patients with liver diseases, including hepatic steatosis.
The device is intended to be used in a clinical setting and by trained medical professionals.
Velacur is a portable device intended to non-invasively measure the stiffness and attenuation of the liver via measurement of liver tissue shear modulus and ultrasound attenuation. This is done by measuring the wavelength or wave speed of mechanically created shear waves within the orqan of the patient. Attenuation is measured directly via the loss in power of the ultrasound beam.
The device is designed to be used at the point of care, in clinics and hospitals. The device is used by a medical profession, an employee of the clinic/hospital. The activation unit is placed under the patient, while lying supine on an exam bed. The activation unit vibrates at frequencies 40, 50, and 60 Hz causing shear waves within the liver of the patient. The ultrasound transducer is placed on the patient's skin, over the intercostal space, and is used to take volumetric scans of the liver while shear waves are occurring. The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. From the scan data, the device calculates tissue stiffness and attenuation.
Minor hardware and software changes were made to the organ guide (cleared in K223287) was also extended to add more optional overlays on top of the liver overlay to help with optimizing the scan and training users to obtain adequate images. The significant change is the addition of a new output measure for Velacur, an ultrasound derived fat fraction (VDFF).
Here's a breakdown of the acceptance criteria and study details for the Velacur device, as described in the provided FDA 510(k) summary:
1. Table of Acceptance Criteria and Reported Device Performance
The document describes two separate machine learning algorithms: the Velacur Determined Fat Fraction (VDFF) algorithm, the Organ Guide Extension, and the Wave Quality Guide. Each has its own acceptance criteria and performance metrics.
| Feature/Algorithm | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Velacur Determined Fat Fraction (VDFF) | ||
| Correlation (VDFF vs. MRI-PDFF) | Not explicitly stated an "acceptance criterion" value, but implied to be strong based on predicate device testing. | 0.85 [0.77-0.91] (correlation coefficient [95% CI] in validation cohort) |
| AUC for 5% Steatosis Detection | Not explicitly stated an "acceptance criterion" value. | 0.97 [0.89-0.99] (AUC [95% CI] for detection of 5% steatosis) |
| Organ Guide Extension | ||
| Dice Coefficient | > 0.7 | Not explicitly stated the exact achieved value, but implies met acceptance criteria. |
| Pixel Accuracy | > 80% | Not explicitly stated the exact achieved value, but implies met acceptance criteria. |
| Wave Quality Guide | ||
| Dice Coefficient | > 0.7 | Not explicitly stated the exact achieved value, but implies met acceptance criteria. |
| Sensitivity | > 80% | Not explicitly stated the exact achieved value, but implies met acceptance criteria. |
| Specificity | > 80% | Not explicitly stated the exact achieved value, but implies met acceptance criteria. |
2. Sample Size Used for the Test Set and Data Provenance
-
Velacur Determined Fat Fraction (VDFF):
- Test Set Sample Size: 70 new patients
- Data Provenance: From 3 separate sites (with different Velacur operators). Implied to be prospective, as it's separate from the training data. The document states "Data was collected from sites across the US and Canada" for training, and "Evaluation data was collected... from separate patients, sites and collected by different users than the data used for training in order to ensure data independence," suggesting a similar geographical distribution for the test set. Retrospective/prospective not explicitly stated for this particular validation cohort, but the nature of MRI scans for ground truth implies it would be collected alongside the Velacur scans.
-
Organ Guide Extension:
- Test Set Sample Size: More than 800 images from 21 patients.
- Data Provenance: "Evaluation data was collected from volunteers and patients with non-alcoholic fatty liver disease and non-alcoholic steatohepatitis. All patients were recruited from hepatology clinics." Data was collected from sites across the US and Canada (implied to be similar for evaluation as for training). Data for evaluation was explicitly stated to be from "separate patients, sites and collected by different users than the data used for training," indicating an independent, possibly prospective collection for evaluation.
-
Wave Quality Guide:
- Test Set Sample Size: More than 4,000 images from 36 patients.
- Data Provenance: "Evaluation data was collected from volunteers and patients with non-alcoholic fatty liver disease and non-alcoholic steatohepatitis. All patients were recruited from hepatology clinics." Data was collected from sites across the US and Canada (implied to be similar for evaluation as for training). Data for evaluation was explicitly stated to be from "separate patients, sites and collected by different users than the data used for training," indicating an independent, possibly prospective collection for evaluation.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
-
Velacur Determined Fat Fraction (VDFF):
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified. The MRI scans were "assessed to create the final measurement," implying expert interpretation without explicitly stating the number or qualifications.
-
Organ Guide Extension:
- Number of Experts: Not specified.
- Qualifications of Experts: "experts in the field of sonography and/or ultrasound elastography." No specific experience level (e.g., years) is provided.
-
Wave Quality Guide:
- Number of Experts: Not specified.
- Qualifications of Experts: "experts in the field of ultrasound elastography." No specific experience level (e.g., years) is provided.
4. Adjudication Method for the Test Set
The document does not explicitly describe an adjudication method (such as 2+1 or 3+1) for establishing ground truth for any of the algorithms. It generally states that ground truth was established by experts or through MRI-PDFF assessment, implying a single assessment per case or a consensus without detailing the process.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not reported in this document. The studies focus on the standalone performance of the AI algorithms.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
Yes, standalone performance studies were done for all three components:
- Velacur Determined Fat Fraction (VDFF): The reported correlation coefficient and AUC are measures of the algorithm's direct performance against a ground truth (MRI-PDFF).
- Organ Guide Extension: The Dice Coefficient and pixel accuracy measure the algorithm's ability to segment organs directly.
- Wave Quality Guide: The Dice Coefficient, sensitivity, and specificity measure the algorithm's direct ability to identify good quality waves.
7. The Type of Ground Truth Used
- Velacur Determined Fat Fraction (VDFF): MRI Proton Density Fat Fraction (MRI-PDFF). This is considered a highly accurate quantitative measure for liver fat.
- Organ Guide Extension: Manual image segmentation by experts.
- Wave Quality Guide: Manual image segmentation by experts.
8. The Sample Size for the Training Set
- Velacur Determined Fat Fraction (VDFF): 112 patients from 4 sites (used for parameter fitting/training).
- Organ Guide Extension: More than 5,000 patient images.
- Wave Quality Guide: More than 15,000 patient images from 100+ patients.
9. How the Ground Truth for the Training Set Was Established
- Velacur Determined Fat Fraction (VDFF): MRI-PDFF scans were assessed to create the final measurement.
- Organ Guide Extension: Manual image segmentation by experts in the field of sonography and/or ultrasound elastography.
- Wave Quality Guide: Manual image segmentation by experts in the field of ultrasound elastography.
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(28 days)
Velacur
Velacur is intended to provide estimates of tissue stiffness generated from shear wave speed measurements (40-70 Hz) and coefficient of attenuation. The device is indicated to non-invasively determine liver tissue stiffness and attenuation. These are meant to be used in conjunction with other clinical indicators in order to assist in clinical management of patients with liver disease. The device is intended to be used in a clinical setting and by appropriately trained medical professionals.
Velacur is a portable device intended to non-invasively measure the stiffness and attenuation of the liver via measurement of liver tissue shear modulus and ultrasound attenuation. This is done by measuring the wavelength or wave speed of mechanically created shear waves within the organ of the patient. Attenuation is measured directly via the loss in power of the ultrasound beam. The device is designed to be used at the point of care, in clinics and hospitals. The device is used by a medical profession, an employee of the clinic/hospital. The activation unit is placed under the patient, while lying supine on an exam bed. The activation unit vibrates at frequencies 40, 50, and 60 Hz causing shear waves within the liver of the patient. The ultrasound transducer is placed on the patient's skin, over the intercostal space, and is used to take volumetric scans of the liver while shear waves are occurring. The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. From the scan data, the device calculates tissue stiffness and attenuation.
The provided document is a 510(k) premarket notification summary for the Velacur device, which is an ultrasound elastography system. The document focuses on demonstrating substantial equivalence to a predicate device, specifically regarding algorithmic changes for elasticity and attenuation calculations.
Here's an analysis based on the provided text, addressing your questions:
1. A table of acceptance criteria and the reported device performance
| Parameter | Acceptance Criteria (Maximum) | Reported Device Performance |
|---|---|---|
| Elasticity (Homogeneous Phantoms) | ||
| Bias between MRE & Velacur |
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(177 days)
Velacur
Velacur is intended to provide estimates of tissue stiffness generated from shear wave speed measurements (40-70 Hz) and coefficient of attenuation. The device is indicated to non-invasively determine liver tissue stiffness and attenuation. These are meant to be used in conjunction with other clinical indicators in order to assist in clinical management of patients with liver disease.
Velacur is a portable device intended to non-invasively measure the stiffness and attenuation of the liver via measurement of liver tissue shear modulus and ultrasound attenuation. This is done by measuring the wavelength or wave speed of mechanically created shear waves within the organ of the patient. Attenuation is measured directly via the loss in power of the ultrasound beam.
The device is designed to be used at the point of care, in clinics and hospitals. The device is used by a medical profession, an employee of the clinic/hospital. The activation unit is placed under the patient, while lying supine on an exam bed. The activation unit vibrates causing shear waves within the liver of the patient. The ultrasound transducer is placed on the patient's skin, over the intercostal space, and is used to take volumetric scans of the liver while shear waves are occurring. From the scan data, the device calculates tissue stiffness and attenuation.
Here's a breakdown of the acceptance criteria and study details for the Velacur device, as extracted from the provided text:
Velacur Device Performance and Study Details
1. Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Organ Segmentation Guide (for liver segmentation): | |
| Average Dice Score > 0.7 | Average Dice Score > 0.7 |
| Overall pixel-based accuracy > 80% | Overall pixel-based accuracy > 80% |
| Wave Quality Guide (for shear wave detection and segmentation): | |
| Dice Scores ≥ 0.7 | Dice Scores ≥ 0.7 |
| Sensitivity ≥ 80% | Sensitivity ≥ 80% |
| Specificity ≥ 80% | Specificity ≥ 80% |
2. Sample Size for Test Set and Data Provenance
- Test Set Sample Size: More than 1,500 images, from 35-40 patients.
- Data Provenance: Patient data from the US and Canada. The data was collected from sites in the US and Canada.
- Retrospective/Prospective: Not explicitly stated, but the description "Evaluation data was collected from volunteers and patients" suggests it was prospectively collected for evaluation.
3. Number of Experts for Ground Truth and Qualifications
- Organ Segmentation Guide:
- Number of Experts: At least three sonographers.
- Qualifications: All had more than 20 years of experience in abdominal ultrasound imaging.
- Wave Quality Guide:
- Number of Experts: Not specified beyond "all experts."
- Qualifications: All experts hold a masters or PhD in a relevant field and have at least 10 years of experience with ultrasound imaging and elastography.
4. Adjudication Method for Test Set
- Organ Segmentation Guide: Ground truth was established using a pixel-based voting method (implying the consensus of the three sonographers).
- Wave Quality Guide: Ground truth was established through expert consensus.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No information on a Multi-Reader Multi-Case (MRMC) comparative effectiveness study (i.e., comparing human readers with AI vs. without AI assistance) is provided in the document. The study focuses on the standalone performance of the AI algorithms.
6. Standalone (Algorithm Only) Performance
Yes, standalone (algorithm only) performance was done. The reported Dice Scores, pixel accuracy, sensitivity, and specificity are metrics of the algorithm's performance in segmenting organs and detecting/segmenting shear waves independently.
7. Type of Ground Truth Used
Expert consensus based on manual image segmentation.
8. Sample Size for Training Set
More than 5,000 patient images were used for training each algorithm.
9. How Ground Truth for Training Set Was Established
Not explicitly detailed for the training set, but it can be inferred that a similar process of manual image segmentation by experts was used, as described for the validation set. The text states: "Ground truth was established using manual image segmentation by experts in the field of sonography and/or ultrasound elastography," followed by details for both validation algorithms. It is reasonable to assume a similar method was employed for the training data's ground truth.
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