(250 days)
Not Found
Yes
The document explicitly states that measurements are an "inferred reflection of the performance of the deep learning algorithm," indicating the use of a deep learning (a subset of AI/ML) approach for segmentation.
No.
The device is used for visualization and analysis of medical images and explicitly states that patient management decisions should not be made based solely on its results, indicating it is a diagnostic aid, not a therapeutic device.
Yes
The device is intended for "visualization and analysis of breast magnetic resonance imaging (MRI) studies" and "supports evaluation of dynamic MR data... performs processing functions (such as image registration, subtractions, measurements, 3D renderings, and reformats)," which are activities associated with diagnostics. While it states that "Patient management decisions should not be made based solely on the results," the overall purpose is to aid in the evaluation of medical images for diagnostic purposes.
Yes
The device description explicitly states that the TumorSight system consists of "proprietary software developed by SimBioSys, Inc. hosted on a cloud-based platform and accessed on an off-the-shelf computer." This indicates that the medical device itself is the software, and it utilizes existing, non-medical device hardware (cloud platform, off-the-shelf computer) for its operation.
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In vitro diagnostics are tests performed on samples taken from the human body, such as blood, urine, or tissue, to detect diseases, conditions, or infections.
- TumorSight Viz Function: TumorSight Viz processes and analyzes medical images (MRI scans) acquired from patients. It does not perform tests on biological samples.
- Intended Use: The intended use clearly states it's for "visualization and analysis of breast magnetic resonance imaging (MRI) studies." This is image analysis, not in vitro testing.
Therefore, TumorSight Viz falls under the category of medical image processing software, not an in vitro diagnostic device.
No
The letter does not mention that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device.
Intended Use / Indications for Use
TumorSight Viz is intended to be used in the visualization and analysis of breast magnetic resonance imaging (MRI) studies for patients with biopsy proven early-stage or locally advanced breast cancer. TumorSight Viz supports evaluation of dynamic MR data acquired from breast studies during contrast administration. TumorSight Viz performs processing functions (such as image registration, subtractions, measurements, 3D renderings, and reformats).
TumorSight Viz also includes user-configurable features for visualizing and analyzing findings in breast MRI studies. Patient management decisions should not be made based solely on the results of TumorSight Viz.
Product codes
QIH
Device Description
TumorSight Viz is an image processing system designed to assist in the visualization and analysis of breast DCE-MRI studies.
TumorSight reads DICOM magnetic resonance images. TumorSight processes and displays the results on the TumorSight web application.
Available features support:
- Visualization (standard image viewing tools, MIPs, and reformats)
- Analysis (registration, subtractions, kinetic curves, parametric image maps, segmentation and 3D ● volume rendering)
- . Communication and storage (DICOM import, retrieval, and study storage)
The TumorSight system consists of proprietary software developed by SimBioSys, Inc. hosted on a cloud-based platform and accessed on an off-the-shelf computer.
Mentions image processing
Yes
Mentions AI, DNN, or ML
The measurements generated from the device result directly from the segmentation methodology and are an inferred reflection of the performance of the deep learning algorithm.
Input Imaging Modality
Magnetic Resonance Imaging (MRI)
Anatomical Site
Breast
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Not Found
Description of the training set, sample size, data source, and annotation protocol
DCE-MRI were obtained from seven hundred thirty-six (736) patients (corresponding to 766 samples when accounting for bilateral disease) were obtained from twelve (12) clinical sites in the U.S. for use in training and tuning the device. Data was collected to ensure adequate coverage of MRI manufacturer and field strength, and to ensure similarity with the broader population of early-stage and locally advanced breast cancer patients in the U.S.
Description of the test set, sample size, data source, and annotation protocol
DCE-MRI were obtained for one hundred sixty-one (161) patients (corresponding to 163 samples when accounting for bilateral disease) were obtained from six (6) clinical sites in the U.S. for use in validating the device. All patients had pathologically confirmed invasive, early stage or locally advanced breast cancer.
Seven (7) U.S. Board Certified radiologists reviewed 163 validation samples to establish the ground truth for the dataset according to predefined guidelines. For each case, two radiologists measured various characteristics about the cancer including longest dimensions along three axes and tumor to landmark (chest, nipple, skin) distances. Each study was reviewed by two radiologists to determine if the candidate segmentation was appropriate. In cases where the two radiologists did not agree on whether the segmentation was appropriate, a third radiologist provided an additional opinion and established a ground truth by majority consensus.
Independence of validation data from training data was ensured by confirming there was no overlap of patients between training/tuning and validation datasets.
The validation samples were tested using both the TumorSight Viz device and the CADstream device.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Performance Tests: SimBioSys has completed performance testing on an independent dataset to ensure TumorSight Viz meets clinically acceptable levels.
The mean absolute error and variability between the automated measurements (Validation Testing) and ground truth for tumor volume (measured in cc) and landmark distances (measured in cm) was similar to the variability between device-to-radiologist measurements and inter-radiologist variability. This demonstrates that the error in measurements is consistent to the variability between expert readers.
Performance data for the automated measurements:
- Tumor Volume (n=157): 6.48 +/- 12.67 cubic centimeters (cc)
- Tumor-to-breast volume ratio (n=157): 0.56 +/- 0.93 %
- Tumor longest dimension (n=163): 1.48 +/- 1.46 centimeters (cm)
- Tumor-to-nipple distance (n=161): 1.00 +/- 1.03 centimeters (cm)
- Tumor-to-skin distance (n=163): 0.63 +/- 0.60 centimeters (cm)
- Tumor-to-chest distance (n=163): 0.94 +/- 1.34 centimeters (cm)
- Tumor center of mass (n=157): 0.735 +/- 1.26 centimeters (cm)
The tumor segmentation was assessed using the Dice coefficient, utilizing both the volumetric and surface Dice coefficients.
Results of Dice and surface Dice:
- Tumor segmentation (n=157) Volume Dice: 0.676 +/- 0.289
- Tumor segmentation (n=157) Surface Dice: 0.873 +/- 0.264
Performance of TumorSight Viz was directly compared to that of CADstream for measurements including tumor longest dimension, tumor to skin distance, tumor to chest distance, and tumor to nipple distance (n=136 for most measurements, n=134 for Tumor to Nipple and Tumor Volume).
Key Results from direct comparison of TumorSight Viz/Ground Truth:
- Longest Dimension: 1.40 cm +/- 1.43 cm (Abs. Distance Error)
- Tumor to Skin: 0.61 cm +/- 0.46 cm (Abs. Distance Error)
- Tumor to Chest: 0.77 cm +/- 0.90 cm (Abs. Distance Error)
- Tumor to Nipple: 0.98 cm +/- 1.06 cm (Abs. Distance Error)
- Tumor Volume: 6.69 cc +/- 13.53 cc (Abs. Distance Error)
All tests met the acceptance criteria.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Not Found
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
Not Found
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
0
Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
SimBioSys, Inc. % John J. Smith, M.D., J.D. Official Correspondent Hogan Lovells US LLP 180 North Lasalle Street. Suite 3250 Chicago, Illinois 60601
Re: K231130
Trade/Device Name: TumorSight Viz Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH Dated: November 21, 2023 Received: November 21, 2023
Dear John J. Smith:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
1
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Wenbo Li for
Daniel M. Krainak, Ph.D. Assistant Director DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
2
Indications for Use
Submission Number (if known)
Device Name
TumorSight Viz
Indications for Use (Describe)
TumorSight Viz is intended to be used in the visualization and analysis of breast magnetic resonance imaging (MRI) studies for patients with biopsy proven early-stage or locally advanced breast cancer. TumorSight Viz supports evaluation of dynamic MR data acquired from breast studies during contrast administration. TumorSight Viz performs processing functions (such as image registration, subtractions, measurements, 3D renderings, and reformats).
TumorSight Viz also includes user-configurable features for visualizing and analyzing findings in breast MRI studies. Patient management decisions should not be made based solely on the results of TumorSight Viz.
Type of Use (Select one or both, as applicable)
Prescription Use (Part 21 CFR 801 Subpart D)
Dver-The-Counter Use (21 CFR 801 Subpart C)
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3
Submitter Details
SimBioSys, Inc. 180 North Lasalle Street, Suite 3250 Chicago IL 60601 United States Contact: Dr. John J. Smith, MD, JD Contact Telephone: (202) 637-3638 Contact Email: john.smith@hoganlovells.com
Details of the Submitted Device
Proprietary Name: TumorSight Viz Common Name: Medical image management and processing system Classification Name: System, Image Processing, Radiological Regulation Number: 892.2050 Product Code: QIH Committee/Panel: Radiology Device Class: II
Type of 510(k) Submission:
Traditional
Identification of the Legally Marketed Predicate Device
Predicate #: K092954
Predicate Trade Name: CADstream Version 5
Product Code: LLZ
Device Description
TumorSight Viz is an image processing system designed to assist in the visualization and analysis of breast DCE-MRI studies.
TumorSight reads DICOM magnetic resonance images. TumorSight processes and displays the results on the TumorSight web application.
Available features support:
- Visualization (standard image viewing tools, MIPs, and reformats)
- Analysis (registration, subtractions, kinetic curves, parametric image maps, segmentation and 3D ● volume rendering)
- . Communication and storage (DICOM import, retrieval, and study storage)
The TumorSight system consists of proprietary software developed by SimBioSys, Inc. hosted on a cloud-based platform and accessed on an off-the-shelf computer.
4
Intended Use and Indications for Use
TumorSight Viz is intended to be used in the visualization and analysis of breast magnetic resonance imaging (MRI) studies for patients with biopsy proven early-stage or locally advanced breast cancer. TumorSight Viz supports evaluation of dynamic MR data acquired from breast studies during contrast administration. TumorSight Viz performs processing functions (such as image registration, subtractions, measurements, 3D renderings, and reformats).
TumorSight Viz also includes user-configurable features for visualizing and analyzing findings in breast MRI studies. Patient management decisions should not be made based solely on the results of TumorSight Viz.
Indications for Use Comparison
CADstream is intended to be used in the visualization, analysis, and reporting of magnetic resonance imaging (MRI) studies. CADstream supports evaluation of dynamic MR data acquired during contrast administration. CADstream performs other user selected processing functions (such as image registration, subtractions, measurements, 3D renderings, and reformats). Although the Indication for Use statement for Tumorsight Viz are not identical to that of the predicate, the differences do not alter the intended use as an image visualization device, nor do they affect the safety and effectiveness of the device relative to the predicate. Both the subject and predicate devices have the same intended use for the visualization and analysis of dynamic magnetic resonance imaging (MRI) studies.
Technological Characteristics
Visualization of dynamic magnetic resonance imaging (MRI) studies is the technological principle for both the subject and predicate devices. It is based on the use of dynamic MRI images in DICOM format which are to be viewed and analyzed by a skilled physician. Both the subject and predicate devices perform the following same technological features:
- . Standard Image Viewing Tools (zoom, pan, window/level)
- Image Post Processing (MIPs, reformats, image registration) ●
- Parametric Maps ●
- Kinetic Curves
- Automatic Volume Segmentation
- Automatic Linear Measurements (distance to nipple, chest, and closest skin surface) ●
- . DICOM Image Import
The following technological features differ between the subject and predicate devices:
- Ability to review additional imaging modalities (mammography and ultrasound)
- Interventional planning ●
- User created collage of study images ●
- Serial comparisons ●
- Customizable reporting ●
5
Performance Tests
SimBioSys has completed performance testing on an independent dataset to ensure TumorSight Viz meets clinically acceptable levels.
DCE-MRI were obtained from seven hundred thirty-six (736) patients (corresponding to 766 samples when accounting for bilateral disease) were obtained from twelve (12) clinical sites in the U.S. for use in training and tuning the device. DCE-MRI were obtained for one hundred sixty-one (161) patients (corresponding to 163 samples when accounting for bilateral disease) were obtained from six (6) clinical sites in the U.S. for use in validating the device. All patients had pathologically confirmed invasive, early stage or locally advanced breast cancer.
Data was collected to ensure adequate coverage of MRI manufacturer and field strength, and to ensure similarity with the broader population of early-stage and locally advanced breast cancer patients in the U.S. Specifically, patient age at diagnosis, breast cancer subtype, T stage, histologic subtype, and race/ethnicity all reflect the broader U.S. population.
| | Training Dataset
(n=390 samples) | Tuning Dataset
(n=376 samples) | Validation Dataset
(n=163 samples) |
|--------------------------------------|-------------------------------------|-----------------------------------|---------------------------------------|
| Age | | | |
| 70 | 21 (5.4%) | 26 (6.9%) | 9 (5.5%) |
| Missing | 2 (0.5%) | 0 (0.0%) | 0 (0.0%) |
| Race/Ethnicity | | | |
| Black† | 73 (18.7%) | 92 (24.5%) | 19 (11.7%) |
| Asian and Pacific Islander† | 20 (5.1%) | 17 (4.5%) | 8 (4.9%) |
| White† | 267 (68.5%) | 226 (60.1%) | 121 (74.2%) |
| American Indian or Alaska
Native† | 6 (1.5%) | 0 (0.0%) | 0 (0.0%) |
| Other | 9 (2.3%) | 3 (0.8%) | 2 (1.2%) |
| Hispanic | 0 (0.0%) | 8 (2.1%) | 6 (3.7%) |
| Missing/Unknown | 22 (5.6%) | 31 (8.2%) | 7 (4.3%) |
- Non-Hispanic
6
The following subgroups present in the dataset were comparable to the U.S. population: cancer subtype, grade, histology, T stage, and N stage.
Images were acquired from sites that utilize standard of care dynamic contrast enhanced MR protocols from GE, Philips, and Siemens scanners with both 1.5T and 3T field strength magnets.
Seven (7) U.S. Board Certified radiologists reviewed 163 validation samples to establish the ground truth for the dataset according to predefined guidelines. For each case, two radiologists measured various characteristics about the cancer including longest dimensions along three axes and tumor to landmark (chest, nipple, skin) distances. Each study was reviewed by two radiologists to determine if the candidate segmentation was appropriate. In cases where the two radiologists did not agree on whether the segmentation was appropriate, a third radiologist provided an additional opinion and established a ground truth by majority consensus.
Independence of validation data from training data was ensured by confirming there was no overlap of patients between training/tuning and validation datasets.
The validation samples were tested using both the TumorSight Viz device and the CADstream device.
The measurements generated from the device result directly from the segmentation methodology and are an inferred reflection of the performance of the deep learning algorithm. For example, the distance from chest or skin is calculated after the deep learning segmentation identifies the region of interest and then the resulting measurement is output.
The mean absolute error and variability between the automated measurements (Validation Testing) and ground truth for tumor volume (measured in cc) and landmark distances (measured in cm) was similar to the variability between device-to-radiologist measurements and inter-radiologist variability. This demonstrates that the error in measurements is consistent to the variability between expert readers. Performance data for the automated measurements is summarized below:
| Measurement Description | Units | Validation Testing
(Mean Abs. Error ± Std.
Dev.) |
|--------------------------------------|------------------------|--------------------------------------------------------|
| Tumor Volume (n=157) | cubic centimeters (cc) | 6.48 ± 12.67 |
| Tumor-to-breast volume ratio (n=157) | % | 0.56 ± 0.93 |
| Tumor longest dimension (n=163) | centimeters (cm) | 1.48 ± 1.46 |
| Tumor-to-nipple distance (n=161) | centimeters (cm) | 1.00 ± 1.03 |
| Tumor-to-skin distance (n=163) | centimeters (cm) | 0.63 ± 0.60 |
| Tumor-to-chest distance (n=163) | centimeters (cm) | 0.94 ± 1.34 |
| Tumor center of mass (n=157) | centimeters (cm) | 0.735 ± 1.26 |
The tumor segmentation was assessed using the Dice coefficient, utilizing both the volumetric and surface Dice coefficients, which together validate the location, volume, and surface agreement with a reference standard.
7
The surface Dice coefficient is particularly useful as a proxy for the accuracy of 3D rendering and surfaceto-surface distances. Additionally, to further assess the tumor segmentation localization accuracy, we used the distance between the centers of mass of the reference standards and device-generated regions.
Results of Dice and surface Dice are summarized below:
| Performance Measurement | Metric | Validation Testing
(Mean ± Std. Dev.) |
|----------------------------|--------------|------------------------------------------|
| Tumor segmentation (n=157) | Volume Dice | 0.676 ± 0.289 |
| | Surface Dice | 0.873 ± 0.264 |
We found that all tests met the acceptance criteria, demonstrating adequate performance for our intended use.
Risk Management
The device risks were managed and controlled following the requirements of ISO 14971 standard. The device hazards were identified, their risk levels were evaluated and mitigation measures were taken to reduce the risk levels. The benefits of the TumorSight Viz software, outweigh the device residual risks.
Substantial Equivalence
TumorSight Viz is comparable to the predicate in terms of intended use, technological characteristics, and principle of operation.
| Predicate Device Comparison | ||
|---|---|---|
| CADstream version 5 | ||
| (predicate) | TumorSight Viz | |
| 510(k) | K092954 | TBD |
| Manufacturer | Merge CAD Inc. | SimBioSys Inc. |
| Regulation Number | 892.2050 | 892.2050 |
| Regulation Name | Medical image management and | |
| processing system | Medical image management and | |
| processing system | ||
| Classification | 2 | 2 |
| Device Common Name | Image Processing System | Image Processing System |
| Product Code | LLZ | QIH |
| Functions | - Extract dynamic contrast | |
| enhanced MRI sequence from | ||
| MRI images for the 3D display | ||
| and visualization of the anatomy | ||
| of patient's breast | - Extract dynamic contrast | |
| enhanced MRI sequence from | ||
| MRI images for the 3D display | ||
| and visualization of the anatomy | ||
| of patient's breast | ||
| CADstream is intended to be | ||
| used in the visualization, | ||
| analysis, and reporting of | ||
| magnetic resonance imaging | ||
| (MRI) studies. CADstream | ||
| supports evaluation of dynamic | ||
| MR data acquired during | ||
| contrast administration. | ||
| CADstream performs other user | ||
| selected processing functions | ||
| (such as image registration, | ||
| subtractions, measurements, 3D | ||
| renderings, and reformats). |
CADstream also includes user-
configurable features for
reporting on findings in breast or
general MRI studies.
Additionally, CADstream assists
users in planning MRM guided
interventional procedures.
When interpreted by a skilled
physician, this device provides
information that may be used for
screening, diagnosis, and
interventional planning. Patient
management decisions should
not be made based solely on
theresults of CADstream.
CADstream may also be used as
an image viewer of multi-
modality, digital images,
including ultrasound and
mammography. CADstream is
not intended for primary
interpretation of digital
mammography images. | TumorSight Viz is intended to
be used in the visualization and
analysis of breast magnetic
resonance imaging (MRI)
studies for patients with biopsy
proven early-stage or locally
advanced breast cancer.
TumorSight Viz supports
evaluation of dynamic MR data
acquired from breast
studiesduring contrast
administration. TumorSight Viz
performs processing functions
(such as image registration,
subtractions, measurements, 3D
renderings, and reformats).
TumorSight Viz also includes
user-configurable features for
visualizing and analyzing
findings in breast MRI studies.
Patient management decisions
should not be made based solely
on the results of TumorSight
Viz. |
| Intended Use | | |
| Data Source (Input) | MRI | MRI |
| Output/Accessibility | Graphic and text results of
breast anatomy are accessed via
a device with internet
connectivity | Graphic and text results of
breast anatomy are accessed via
a device with internet
connectivity |
| Physical Characteristics | "-non-invasive software package
-DICOM compatible" | "-non-invasive software package
-DICOM compatible" |
| Safety | Clinician review and assessment
of analysis prior to use in
planning MRI guided
interventional procedures. | Clinician review and assessment
of analysis prior to use in pre-
operative planning. |
| | Predicate Device Feature Comparison | |
| Feature | CADstream version 5
(predicate) | TumorSight Viz |
| Standard image viewing tools | Yes | Yes |
| MIPs | Yes | Yes |
| Reformats | Yes | Yes |
| Registration | Yes | Yes |
| Subtraction series | Yes | Yes |
| View 3D volume rendering | Yes | Yes |
| Kinetic curves | Yes | Yes |
| Parametric image maps | Yes | Yes |
| DICOM import | Yes | Yes |
| View finding volume | Yes | Yes |
| View finding location | Yes | Yes |
| View finding size | Yes | Yes |
| View kinetic curve with
highest uptake | Yes | Yes |
| View finding distance to
nipple | Yes | Yes |
| View finding distance to skin | Yes | Yes |
| View finding distance to chest | Yes | Yes |
| View adjusted finding size | Yes | No - Segmentation is not
editable, but surgical margins
are editable |
| Interactive rotation of 3D
volume rendering | Yes | Yes |
A table comparing the key features of the subject and predicate devices is provided below:
8
9
Performance of TumorSight Viz was directly compared to that of CADstream for measurements including tumor longest dimension, tumor to skin distance, tumor to chest distance, and tumor to nipple distance. As summarized in the following table, these were comparable to inter-radiologist variability in the same measurements:
| Performance
Measurement | N | Metric | TumorSight
Viz/CADStream | TumorSight
Viz/
Ground
Truth | CADStream
/ Ground
Truth | Interradiologist
Variability |
| ---------------------------- | --- | -------- | ----------------------------- | --------------------------------------- | -------------------------------- | --------------------------------- |
|---|
10
| | | | (Mean
± Std. Dev.) | (Mean ±
Std. Dev.) | (Mean ±
Std. Dev.) | (Mean
± Std. Dev.) |
|----------------------|-----|---------------------------|-----------------------|-----------------------|-----------------------|-----------------------|
| Longest
Dimension | 136 | Abs.
Distance
Error | 1.48 cm
± 1.71 cm | 1.40 cm ±
1.43 cm | 1.11 cm ±
1.52 cm | 1.17 cm
± 1.38 cm |
| Tumor to Skin | 136 | Abs.
Distance
Error | 0.94 cm
± 0.69 cm | 0.61 cm ±
0.46 cm | 0.49 cm ±
0.56 cm | 0.49 cm
± 0.54 cm |
| Tumor to
Chest | 136 | Abs.
Distance
Error | 1.76 cm
± 1.32 cm | 0.77 cm ±
0.90 cm | 1.37 cm ±
1.01 cm | 0.79 cm
± 1.01 cm |
| Tumor to
Nipple | 134 | Abs.
Distance
Error | 0.86 cm
± 1.00 cm | 0.98 cm ±
1.06 cm | 0.80 cm ±
0.86 cm | 0.82 cm
± 0.98 cm |
| Tumor Volume | 134 | Abs.
Distance
Error | 9.54 cc ±
20.89 cc | 6.69 cc ±
13.53 cc | 8.09 cc ±
17.42 cc | N/A |
The differences in error between the mean absolute errors (MAE) for the predicate and subject device are clinically acceptable because they are on the order of one to two voxels for the mean voxel size in the dataset. These differences are clinically insignificant.
Substantial Equivalence Conclusion
The comparison of the features and non-clinical bench performance testing described above demonstrates that TumorSight Viz is substantially equivalent to the predicate device in function. Furthermore, performance testing in an independent dataset of radiologist measurement ground truth demonstrates adequate performance for the intended use.
Additionally, TumorSight Viz measurement outputs were compared directly to CADstream output for 136 cases, and both sets of measurements were directly compared to radiologist measurements. TumorSight Viz compared equivalently to CADstream on all measurements including tumor longest dimension, tumor to skin distance, tumor to chest distance, and tumor to nipple distance.
Non-clinical bench testing, an independent assessment of device performance to radiologist ground truth, and a direct comparison to CADstream demonstrate that TumorSight Viz is substantially equivalent to CADstream