(265 days)
inHEART MODELS comprises a suite of medical imaging software modules that are intended to provide qualified medical professionals with tools to aid them in reading, interpreting, and treatment planning, inHEART MODELS accepts DICOM compliant medical images acquired from a variety of imaging devices, including CT and MR*. The software is designed to be used by qualified medical professionals (including physicians, cardiologists, radiologists, and technicians) and the users are solely responsible for making all final patient management decisions.
- inHEART Models AI software module is indicated for adults only and is designed for CT images only.
inHEART MODELS is a suite of medical image processing software tools that enables 3D visualization and analysis of anatomical structures.
This software suite is composed of three software as a medical device components:
-
. inHEART MODELS AI: a medical image processing software for automatic 3D modelling, used to pre-process medical images (acquired only by CT devices).
This software module uses a machine-learning based approach with the following characteristics: -
Training dataset: 796 cases (3D CT original images and the segmentation । masks) from previously manually performed segmentations (time period 2018-2022); origins of the data are public and private clinical and hospital institutions located in US (40%) and Europe (60%).
-
-Training process: Machine learning algorithm (UNet) is trained applying data augmentation (including patch mirroring) and regularization (including Instance Normalization, Dropout, Data Augmentation, Weight Initialization, Leaky ReLU Activation) methods. Loss functions (soft dice loss and binary cross entropy) and optimization methods (stochastic gradient descent) are used during learning over a fixed number of 1000 epochs, each consisting of 250 iterations with a batch size of 2.
-
Data anonymized prior to its processing by inHEART team, therefore no । personal data (gender, age, ethnicity) is exploitable. CT scanner manufacturers include Siemens (40%). GE Medical Systems (30%). Toshiba (10%) and other manufacturers (20%) among which Philips and Canon.
-
inHEART MODELS Shaper: a standalone image processing software used to . generate digital 3D models of the patient heart from medical images acquired by CT and/or MR devices and;
-
inHEART MODELS Explorer: a web-based 3D visualization software that permits . display, review, analysis, annotation and export of the cardiac 3D models generated from inHEART MODELS Shaper.
Specifically, these software modules read DICOM compatible pre-operative CT and MR images acquired by commercially available imaging devices. These images are then processed to generate 3D models of the anatomy to allow qualified medical professionals to display, review, analyze, annotate, interpret, export, and plan therapeutic interventions.
inHEART MODELS software suite also includes two non-device Medical Device Data Systems (MDDS) modules that are only intended to transfer, store and convert formats.
Here's a breakdown of the acceptance criteria and the study proving the device's performance, based on the provided text:
Acceptance Criteria and Study Details for inHEART MODELS
The inHEART MODELS AI software module's performance was evaluated to ensure its automated segmentation capabilities, when reviewed and edited by expert users, yield results comparable to those obtained using the previously cleared predicate device alone.
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria are defined based on the objective of providing an initial segmentation that accelerates the process for expert segmenters, rather than replacing manual expert segmentation entirely. The reported performance metrics are computed between the revised segmentations made by experts based on AI results and the Ground Truth (GT).
| Metric | Acceptance Criteria (for acceptance without manual correction) | Overall Reported Device Performance (Mean) | Overall Reported Device Performance (Median) |
|---|---|---|---|
| Dice Coefficient | > 0.9 | 0.94 | 0.94 |
| Average Symmetric Surface Distance (ASSD) | < 5 mm | 1.17 mm | 1.05 mm (calculated from median of individual structures) |
| Volumetric Analysis (Absolute Difference) | < 20 mL | 9.18 mL | 6.85 mL (calculated from median of individual structures) |
| Volumetric Analysis (Relative Difference) | Not explicitly stated for acceptance without manual correction, but for main chambers: <10% after correction. | 7% | 4.5% (calculated from median of individual structures) |
Note on Volumetric Analysis: The table in the document provides values for individual structures. The "Overall Reported Device Performance" rows above are calculated as the average/median of the means and medians respectively across all listed structures from the provided table.
Individual structure performance:
| Structure | DICE (Median) | DICE (Mean) | DICE (StdDev) | ASSD (Median) | ASSD (Mean) | ASSD (StdDev) | Volume diff. (mL) (Median) | Volume diff. (mL) (Mean) | Volume diff. (mL) (StdDev) | Volume diff. (%) (Median) | Volume diff. (%) (Mean) | Volume diff. (%) (StdDev) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aorta | 0.95 | 0.93 | 0.10 | 0.64 | 0.77 | 0.54 | 3.95 | 4.74 | 4.07 | 5% | 8% | 11% |
| Left Atrium | 0.95 | 0.95 | 0.02 | 1.16 | 1.24 | 0.61 | 5.97 | 7.84 | 8.98 | 3% | 5% | 6% |
| Left Ventricle Endocardium | 0.97 | 0.97 | 0.02 | 0.97 | 0.97 | 0.02 | 4.92 | 6.36 | 5.32 | 2% | 3% | 3% |
| LV Epicardium | 0.97 | 0.97 | 0.01 | 0.71 | 0.76 | 0.30 | 7.22 | 10.10 | 9.96 | 2% | 3% | 2% |
| Pulmonary Artery Trunk | 0.93 | 0.91 | 0.07 | 1.41 | 2.02 | 2.15 | 7.38 | 10.84 | 11.38 | 9% | 14% | 20% |
| Right Atrium & Inf. Vena Cava | 0.93 | 0.92 | 0.04 | 1.17 | 1.30 | 0.57 | 7.28 | 9.87 | 10.12 | 4% | 6% | 6% |
| Right Ventricle Endocardium | 0.92 | 0.91 | 0.05 | 1.22 | 1.25 | 0.56 | 9.89 | 14.99 | 14.98 | 7% | 11% | 12% |
| RV Epicardium | 0.94 | 0.93 | 0.03 | 0.95 | 1.06 | 0.45 | 6.42 | 8.67 | 8.07 | 4% | 4% | 4% |
2. Sample Size and Data Provenance
- Test Set Sample Size: 100 CT cases.
- Data Provenance (Test Set): Randomly selected from the time period year -2023 to ensure independence from training datasets. The sources are similar to the training dataset, including new clients. The overall geographic origin for training data (which implies similar origins for test data) is US (40%) and Europe (60%).
- Retrospective/Prospective: Not explicitly stated, but the selection from a time period "year -2023" for testing suggests a retrospective approach.
3. Number and Qualifications of Experts for Ground Truth
- Number of Experts: Two external experts.
- Qualifications of Experts: Radiologists. No specific years of experience are detailed, but they are referred to as "external experts" and were tasked with evaluating concordance of manual segmentations.
4. Adjudication Method for the Test Set
The ground truth was established by "Approval by external experts (radiologists) of segmentations previously obtained with the predicate device, that will constitute the Ground Truth (GT)". This implies a consensus or agreement method, but the specific adjudication method (e.g., 2+1, 3+1) is not explicitly stated. It seems the two experts had to agree for the segmentations to form the GT.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
An MRMC study was not explicitly described in terms of human readers improving with AI vs. without AI assistance. The study compares the performance of the AI-assisted, expert-reviewed results against the originally expert-segmented predicate device results (Ground Truth). The stated "effect size" is the performance metrics (Dice, ASSD, Volume difference) demonstrating that the AI-assisted workflow, after expert review and editing, is substantially equivalent to the manual predicate workflow. The purpose of the AI module is to accelerate the process for the expert segmenter by providing an initialization.
6. Standalone (Algorithm Only) Performance
Yes, a form of standalone performance was assessed as part of the study: "Comparison of unprocessed outputs of the new automated software module results with the GT to establish the internal validation of the tool performance". However, the specific metrics for this direct AI output (without expert correction) are not separately provided in the summary table. The provided table (under "Performance testing results") shows the metrics after expert review and revision based on AI results.
7. Type of Ground Truth Used
The ground truth (GT) was established through expert consensus/approval of segmentations previously obtained using the predicate device. This is referred to as "Approval by external experts (radiologists) of segmentations previously obtained with the predicate device, that will constitute the Ground Truth (GT)".
8. Sample Size for the Training Set
- Training Dataset: 796 cases (3D CT original images and segmentation masks).
9. How the Ground Truth for the Training Set Was Established
The ground truth for the training set consisted of "previously manually performed segmentations". It is implied these manual segmentations were performed by qualified personnel, similar to how the predicate device was used to establish the test set GT. The document does not specify the number of experts or the exact process (e.g., consensus) for generating the training set ground truth, but it strongly suggests expert-generated manual segmentations.
{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.
inHEART, SAS Audrey Labeque Quality and Regulatory Affairs Manager IHU LIryc - Hôpital Xavier Arnozan-Avenue du Haut Lévêque Pessac. 33600 France
February 29, 2024
Re: K231683 Trade/Device Name: inHEART Models Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QIH, LLZ Dated: January 25, 2024 Received: January 25, 2024
Dear Audrey Labeque:
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 medical devices and radiation-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.
Jessica Lamb
Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
{2}------------------------------------------------
Indications for Use
510(k) Number (if known) K231683
Device Name inHEART MODELS
Indications for Use (Describe)
inHEART MODELS comprises a suite of medical imaging software modules that are intended to provide qualified medical professionals with tools to aid them in reading, interpreting, and treatment planning, inHEART MODELS accepts DICOM compliant medical images acquired from a variety of imaging devices, including CT and MR*. The software is designed to be used by qualified medical professionals (including physicians, cardiologists, radiologists, and technicians) and the users are solely responsible for making all final patient management decisions.
- inHEART Models AI software module is indicated for adults only and is designed for CT images only.
CONTRAINDICATIONS:
This product is not intended for use with or for the primary diagnostic interpretation of Mammography images.
| Type of Use (Select one or both, as applicable) |
|---|
| ------------------------------------------------- |
X Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
{3}------------------------------------------------
Image /page/3/Picture/0 description: The image shows the logo for inHEART. The logo consists of a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is a gradient of blue and white, and the word "inHEART" is in a light blue sans-serif font. The "E" in HEART is stylized with three horizontal lines.
K231683
510(k) Premarket Notification inHEART MODELS
510(k) Summary
| Submitter's Name: | inHEART, SAS |
|---|---|
| Address: | IHU Liryc – Hôpital Xavier ArnozanAvenue du Haut Lévêque33600 Pessac, France |
| Contact:Telephone:Fax: | Audrey Labèque, Quality and Regulatory Affairs Manager+33 5 35 38 19 72+33 5 57 10 28 86 |
| Date: | February 29, 2024 |
| Trade Name: | inHEART MODELS |
| Model No: | N/A |
| Regulation Description: | Medical Image Management and Processing System |
| Regulation number: | 21 CFR 892.2050 |
| Product Code: | Primary product code : QIHSecondary product code : LLZ |
| Regulatory Class: | Class II |
| Predicate Device: | K220727 – inHEART MODELS, inHEART |
{4}------------------------------------------------
Image /page/4/Picture/0 description: The image contains the logo for inHEART. The logo consists of a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is rendered in shades of blue, with a gradient effect that gives it a three-dimensional appearance. The word "inHEART" is written in a sans-serif font, also in shades of blue, and is positioned to the right of the heart shape.
1. Device Description
inHEART MODELS is a suite of medical image processing software tools that enables 3D visualization and analysis of anatomical structures.
This software suite is composed of three software as a medical device components:
-
. inHEART MODELS AI: a medical image processing software for automatic 3D modelling, used to pre-process medical images (acquired only by CT devices).
This software module uses a machine-learning based approach with the following characteristics: -
Training dataset: 796 cases (3D CT original images and the segmentation । masks) from previously manually performed segmentations (time period 2018-2022); origins of the data are public and private clinical and hospital institutions located in US (40%) and Europe (60%).
-
-Training process: Machine learning algorithm (UNet) is trained applying data augmentation (including patch mirroring) and regularization (including Instance Normalization, Dropout, Data Augmentation, Weight Initialization, Leaky ReLU Activation) methods. Loss functions (soft dice loss and binary cross entropy) and optimization methods (stochastic gradient descent) are used during learning over a fixed number of 1000 epochs, each consisting of 250 iterations with a batch size of 2.
-
Data anonymized prior to its processing by inHEART team, therefore no । personal data (gender, age, ethnicity) is exploitable. CT scanner manufacturers include Siemens (40%). GE Medical Systems (30%). Toshiba (10%) and other manufacturers (20%) among which Philips and Canon.
-
inHEART MODELS Shaper: a standalone image processing software used to . generate digital 3D models of the patient heart from medical images acquired by CT and/or MR devices and;
-
inHEART MODELS Explorer: a web-based 3D visualization software that permits . display, review, analysis, annotation and export of the cardiac 3D models generated from inHEART MODELS Shaper.
Specifically, these software modules read DICOM compatible pre-operative CT and MR images acquired by commercially available imaging devices. These images are then processed to generate 3D models of the anatomy to allow qualified medical professionals to display, review, analyze, annotate, interpret, export, and plan therapeutic interventions.
inHEART MODELS software suite also includes two non-device Medical Device Data Systems (MDDS) modules that are only intended to transfer, store and convert formats.
{5}------------------------------------------------
Image /page/5/Picture/0 description: The image contains the logo for "inHEART". The logo consists of a stylized heart shape on the left, rendered in shades of blue, with the word "inHEART" to the right of the heart shape. The text is also in shades of blue, matching the color scheme of the heart shape.
inHEART MODELS complies with the following standards:
- ISO, 14971 Third Edition 2019-12, Medical devices - Application of Risk Management to medical devices
- ISO, 15223-1 Third Edition 2016-11-01, Medical devices Symbols to be used ● with information to be supplied by the manufacturer - Part 1: General requirements
- IEC, 62304 Edition 1.1 2015-06 CONSOLIDATED VERSION: Medical device ● software - Software life cycle processes
- . IEC, 62366-1 Edition 1.1 2020-06 CONSOLIDATED VERSION: Medical devices - Part 1 : application of usability engineering to medical devices
- IEC, /TR 80002-1 Edition 1.0 2009-09, Medical device software Part 1 : ● Guidance of the application of ISO 14971 to medical devices
- IEC, 82304-1 Edition 1.0 2016-10, Health software Part 1 : General . requirements for product safety
- IEC 81001-5-1 Edition 1.0 2021-12, Health software and health IT systems . safety, effectiveness and security - Part 5-1 Security - Activities in the product life cycle
2. Indications for Use
inHEART MODELS comprises a suite of medical imaging software modules that are intended to provide qualified medical professionals with tools to aid them in reading, interpreting, reporting, and treatment planning. inHEART MODELS accepts DICOM compliant medical images acquired from a variety of imaging devices, including CT and MR*. The software is designed to be used by qualified medical professionals (including physicians, cardiologists, radiologists, and technicians) and the users are solely responsible for making all final patient management decisions.
- inHEART Models Al software module is indicated for adults only and is designed for CT images only.
CONTRAINDICATIONS:
This product is not intended for use with or for the primary diagnostic interpretation of Mammography images.
{6}------------------------------------------------
Image /page/6/Picture/0 description: The image contains the logo for inHEART. The logo consists of a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is rendered in shades of blue, with a gradient effect that gives it a three-dimensional appearance. The word "inHEART" is written in a sans-serif font, also in shades of blue, with the "in" slightly darker than the "HEART".
3. Comparison of technological characteristics with the predicate device
| Technologicalcharacteristics | inHEART MODELS(this submission) | inHEART MODELS(K220727)Predicate |
|---|---|---|
| Basic imaging tools | ||
| Processing tools | ||
| Filtering tools | Yes | Yes |
| Reformat tools | Yes | Yes |
| Meshing tools | Yes | Yes |
| Registration tools | Yes | Yes |
| Visualization tools | ||
| 2D viewer | Yes | Yes |
| 3D viewer | Yes | Yes |
| Export capabilities | Yes | Yes |
| Reporting of results | Yes | Yes |
| Advanced imaging tools | ||
| Segmentation | Yes(manually, semi-automated andfully automatedsome segmentations areautomated using the newsoftware module "inHEARTModels Al") | Yes(manually and semi-automated) |
| Quantitative analysis | Yes | Yes |
| Product characteristics | ||
| Mode of operation | Standalone and web-basedsoftware suite | Standalone and web-basedsoftware suite |
| Operating system | macOS for imaging processingsoftware moduleWindows or macOS for web-based platform and compatiblewith following browser: GoogleChrome, Apple Safari (formacOS), Microsoft Edge (forWindows) | macOS for imagingprocessing software moduleWindows or macOS forweb-based platform andcompatible with followingbrowser: Google Chrome,Apple Safari (for macOS),Microsoft Edge (forWindows) |
| IT network | A standard internet connection isneeded for the web-basedplatform. | A standard internetconnection is needed for theweb-based platform. |
| Input data | DICOM compliant medicalimages acquired from a variety ofimaging devices including, CT,MR | DICOM compliant medicalimages acquired from avariety of imaging devicesincluding CT MB |
Table 1 Device Features and Technical Characteristic comparison matrix
{7}------------------------------------------------
Image /page/7/Picture/0 description: The image shows a logo with a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is composed of two overlapping sections, with the left section being a lighter shade of blue and the right section being a darker shade of blue. The word "inHEART" is written in a sans-serif font, with each letter being a slightly different shade of blue.
The following technological differences exist between the subject and predicate device:
- The predicate uses a combination of manual and semi-automated processing . and segmentation. The proposed device uses fully automated reformatting (reslice tool) and segmentation steps using a new software module "inHEART MODELS AI", followed by review and additional manual and semi-automated processing and segmentation through existing and already cleared software module "inHEART MODELS Shaper".
The original processing and updated processing sequences have been validated to demonstrate that the outputs are substantially equivalent.
The indications for Use statement for the subject and predicate devices is similar.
4. Performance data and assessment
The following performance data were provided in support of the substantial equivalence determination:
Software verification and validation testing were conducted on all ● inHEART MODELS software modules and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices."
inHEART MODELS was considered as a "moderate" level of concern.
In addition, accuracy of segmentations for inHEART MODELS was . compared to ground truth and to predicate device inHEART MODELS (K220727). In this study, the ability of the new automated software module was assessed to perform initial segmentations of medical images that, in conjunction with predicate device, allow to produce results comparable to what is obtained using FDAapproved predicate device alone.
The study consists in the following steps:
- Approval by external experts (radiologists) of segmentations previously obtained with the predicate device, that will constitute the Ground Truth (GT) 2. Comparison of unprocessed outputs of the new automated software module results with the GT to establish the internal validation of the tool performance 3. Comparison of new automated software module segmentations after their review and edition by expert users using predicate device with the GT validated in step 1 to establish substantial equivalence to the predicate and proposed device.
Details about this performance validation study:
- Testing dataset: 100 CT cases were randomly selected on the time period year -2023 to ensure independence of training/testing datasets; the sources are similar to the training dataset including new clients. In order to use this as a ground truth, two external experts evaluated the concordance of the manual segmentations for the task in which the use of this software is inscribed.
- Testing criteria: since the objective is to provide the expert segmenter with an initialization of the segmentation required for producing the 3D models, the
{8}------------------------------------------------
Image /page/8/Picture/0 description: The image contains the logo for inHEART. The logo consists of a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is rendered in shades of blue, with a gradient effect that gives it a three-dimensional appearance. The word "inHEART" is written in a sans-serif font, also in shades of blue, and is positioned to the right of the heart shape.
criteria used for performance are Dice coefficient (>0.9 for acceptance without manual correction), Average Symmetric Surface Distance (ASSD) (<5mm for acceptance without manual correction), a volumetric analysis of the produced model (<20 mL for acceptance without manual correction, <15mL absolute and <10% relative after correction for the main chambers). These thresholds are defined considering that the purpose of this module is not to replace manual expert segmentation but to accelerate its process. A subgroup analysis was performed on scanner manufacturers, region, CT quality, and different etiology information provided for the processing of the patient's case by our experts (including pathologies or implanted devices).
- Performance testing results:
The following table depict corresponding DICE and ASSD scores and volume quantification for each structure among the 100 cases of this study, computed between the revised segmentations made by experts based on Al results versus GT.
| DICE | ASSD | Volume diff. (mL) | Volume diff. (%) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Median | Mean | StdDev | Median | Mean | StdDev | Median | Mean | StdDev | Median | Mean | StdDev | |
| Aorta | 0.95 | 0.93 | 0.10 | 0.64 | 0.77 | 0.54 | 3.95 | 4.74 | 4.07 | 5% | 8% | 11% |
| Left Atrium | 0.95 | 0.95 | 0.02 | 1.16 | 1.24 | 0.61 | 5.97 | 7.84 | 8.98 | 3% | 5% | 6% |
| LeftVentricleEndocardium | 0.97 | 0.97 | 0.02 | 0.97 | 0.97 | 0.02 | 4.92 | 6.36 | 5.32 | 2% | 3% | 3% |
| LVEpicardium | 0.97 | 0.97 | 0.01 | 0.71 | 0.76 | 0.30 | 7.22 | 10.10 | 9.96 | 2% | 3% | 2% |
| PulmonaryArtery Trunk | 0.93 | 0.91 | 0.07 | 1.41 | 2.02 | 2.15 | 7.38 | 10.84 | 11.38 | 9% | 14% | 20% |
| Right Atrium& Inf. VenaCava | 0.93 | 0.92 | 0.04 | 1.17 | 1.30 | 0.57 | 7.28 | 9.87 | 10.12 | 4% | 6% | 6% |
| RightVentricleEndocardium | 0.92 | 0.91 | 0.05 | 1.22 | 1.25 | 0.56 | 9.89 | 14.99 | 14.98 | 7% | 11% | 12% |
| RVEpicardium | 0.94 | 0.93 | 0.03 | 0.95 | 1.06 | 0.45 | 6.42 | 8.67 | 8.07 | 4% | 4% | 4% |
Average Dice score is 0.94, average ASSD is 1.17mm, average volume variations is 9,18mL and 7%.
All validation criteria were met, and the performance evaluation study demonstrated that output segmentations and measurements on these segmentations for inHEART MODELS were substantially equivalent to previously cleared legally marketed software devices.
{9}------------------------------------------------
Image /page/9/Picture/0 description: The image contains a logo with a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is rendered in shades of blue, with a gradient effect that gives it a three-dimensional appearance. The word "inHEART" is written in a sans-serif font, also in shades of blue, with a gradient that matches the heart shape. The overall design is clean and modern, suggesting a focus on health or medical technology.
4. Conclusion
No new safety or efficacy issues were introduced by inHEART MODELS compared to the predicate device.
inHEART MODELS has similar intended use, similar labeling, similar indications for use and clinical application tools as those of the cleared predicate device inHEART MODELS (K220727).
Furthermore, performance data demonstrate that the functionality, output and clinical usage of inHEART MODELS is substantially equivalent to the predicate device.
§ 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).