(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:
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. 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%).
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-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.
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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.
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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;
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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) |
§ 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).