NEUROShield

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In-Med Prognostics L3C Latha Poonamallee 4918 September Street San Diego, California 92110 September 14, 2023 Re: K220034 Trade/Device Name: NEUROShield Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QIH Dated: June 19, 2023 Received: June 20, 2023 Dear Latha Poonamallee: 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 (Act) that do not require approval of a premarket approval application (PMA). 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Robert Sauer Deputy Director OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health Enclosure {2}------------------------------------------------ DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration # Indications for Use 510(k) Number (if known) K220034 Device Name NEUROShield Indications for Use (Describe) The NEUROShield™ medical image processing software is intended for automatic labelling, visualization, and volumetric quantification of the Hippocampus brain structure from a set of MR images. | Type of Use (Select one or both, as applicable) | <span> <span style="text-decoration: overline;">X</span> Prescription Use (Part 21 CFR 801 Subpart D) </span> | <span> Over-The-Counter Use (21 CFR 801 Subpart C) </span> | |-------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------| |-------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------| CONTINUE ON A SEPARATE PAGE IF NEEDED. 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Below "INMED" is the word "PROGNOSTICS" in a smaller font size. Underneath that is the tagline "Imagineering Better Health" in an even smaller font size. Revision: 01 Date: 11 Sept 2023 # 510(k) Summary # I. Submitter | Name | In-Med Prognostics L3C | |------------------|-------------------------------------------------| | Address | 4918 September Street, San Diego, CA 92110, USA | | Contact Person | Dr. Latha Poonamallee | | Telephone Number | +1 (906) 231-1135 | | Email | drlatha@inmed.ai | # II. Device | Device Trade Name | NEUROShield™ | |------------------------|------------------------------------------------| | Common Name | Medical Image Processing Software | | Classification Name | Medical image management and processing system | | Regulation Number | 21 CFR 892.2050 | | Regulation Description | Picture archiving and communications system | | Product Code | QIH | | Classification Panel | Radiology | #### III. Predicate Device: | Device | NeuroQuant | |---------------|--------------------| | 510(k) Number | K170981 | | Manufacturer | CorTechs Labs, Inc | | Product Code: | LLZ | #### IV. Device Description: NEUROShield™ is a fully automated brain geometry-based quantifying analytics tool/cloud platform that uses Al/Deep Net to support physicians as a clinical decision support tool for neurologists and neuroradiologists. NEUROShield™ takes 3D MR images as input and calculates brain volumes that can assist physicians in devising optimal treatment plans. The Al tool branded as NEUROShield™ provides volumetric measurements of the Hippocampus brain structure. It replaces time-consuming manual processes {4}------------------------------------------------ with leading-edge automated technology that accelerates the analysis for clinical and research purposes. Brain Volume Quantification is a wellestablished methodology for differential and enhanced interpretation of medical images. We are using a locked algorithm, and any proposed modifications will be submitted to the FDA for review. #### V. Indications for Use: The NEUROShield™ medical image processing software is intended for automatic labelling, visualization, and volumetric quantification of the Hippocampus brain structure from a set of MR images. # VI. Comparison of Technological Characteristics with the Predicate Device: | Feature | Subject Device | Predicate Device | |---------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Device Name | NEUROShield™ | NeuroQuant | | Organization | In Med Prognostics L3C | CorTechs Labs, Inc | | Classification | Class II | Class II | | Product Code | QIH | LLZ | | Indications for Use | Automatic labelling,<br>visualization, and volumetric<br>quantification of the<br>Hippocampus brain structure<br>from a set of MR images. | Automatic labelling, visualization<br>and volumetric quantification of<br>segmentable brain structures<br>and lesions from a set of MR<br>images. Volumetric data may be<br>compared to reference<br>percentile data. | | Design and<br>Incorporated<br>Technology | • Software as a medical<br>device to be used in the<br>process of Imaging and<br>quantification of the<br>Hippocampus brain<br>structure from a set of MR<br>images.<br>• Fully automated brain<br>geometry-based quantifying<br>analytics tool/cloud platform<br>developed using DeepNet /<br>U-Net methodologies. | • Automated measurement of<br>brain tissue volumes and<br>structures and lesions<br>• Automatic segmentation and<br>quantification of brain structures<br>using a dynamic probabilistic<br>neuroanatomical atlas, with age<br>and gender specificity, based on<br>the MR image intensity. | | Physical<br>Characteristics | • Software package<br>(accessible via web browser)<br>• Operates on off-the-shelf<br>hardware (multiple vendors) | • Software package<br>• Operates on off-the-shelf<br>hardware (multiple vendors) | | Operating System | Supports Windows and Mac<br>OS latest (No older than<br>Catalina) | Supports Linux, Mac OS X and<br>Windows. | | Processing<br>Architecture | An automated internal<br>pipeline that performs:<br>- segmentation<br>- volume calculation<br>- report generation | Automated internal pipeline that<br>performs:<br>- artifact correction<br>- segmentation<br>- lesion quantification | | - volume calculation<br>- report generation | | | | Feature | Subject Device | Predicate Device | | Data Source • | • MRI scanner: 3D T1 MRI<br>scans acquired with specified<br>protocols<br>• NEUROShield requires<br>uncompressed DICOM files<br>as input. | • MRI scanner: 3D T1 MRI<br>scans acquired with specified<br>protocols • NeuroQuant<br>Supports DICOM format as input | | Output | Provides volumetric<br>measurements of<br>Hippocampus brain structure. | Provides volumetric<br>measurements of brain<br>structures and lesions.<br>Includes segmented color<br>overlays and morphometric<br>reports<br>• Automatically compares results<br>to reference percentile data and<br>to prior scans when available<br>• Supports DICOM format as<br>output of results that can be<br>displayed on DICOM<br>workstations and Picture Archive<br>and Communications Systems | | Safety | • Automated quality control<br>functions<br>- Scan protocol verification<br><br>• Results must be reviewed<br>by a trained physician. | • Automated quality control<br>functions<br>- Tissue contrast check<br>- Scan protocol verification<br>- Atlas alignment check<br><br>• Results must be reviewed by a<br>trained physician. | {5}------------------------------------------------ #### VII. Performance Testing: NEUROShield is a machine learning/deep learning algorithm-based device. This algorithm was developed by training the Deep Net Segmentation Models with the help of the training set. #### Specifications of the Training dataset Data was collected from multiple sites across India, between January 2020 to December 2021. The dataset of 186 cases, which was used for training, was carefully gathered and brought together by studying several factors such as variance, Tesla-strength (1.5T, 3T), qualities of image and equipment manufacturers. The collected data was prepared as the ground truth by manual segmentation of the Hippocampus structure by subject matter experts, and this was used as an input to the deep net Segmentation Model. The table below provides the categorization of subjects. {6}------------------------------------------------ | Subgroups | | Count | |----------------------------|------------------|-------| | | Healthy controls | 186 | | Magnetic field<br>strength | 1.5T | 109 | | | 3 T | 77 | | Slice thickness | 1 | 81 | | | 1.2 | 50 | | | 2 | 7 | | | 2.2 | 48 | | Equipment<br>Manufacturers | GE | 57 | | | Siemens | 112 | | | Philips | 17 | #### Validation Study: NEUROShield's performance was evaluated by a validation study summarized as follows: # A. Data Description: The performance testing/ validation dataset was collected from the publicly available ADNI (Alzheimer's Disease Neuroimaging Initiative) dataset. This dataset is independent of the training data and was not used to develop the NEUROShield's algorithm. - Data Size: 280 subjects ● - Study Type: Analytical & Cross-Sectional ● - Data collection type: Retrospective ● - Data Sampling: Stratified Random Sampling . - Recruitment factors: ADNI 1 & ADNI 3 dataset (Alzheimer's Disease ● Neuroimaging Initiative) - MRI Equipment manufacturers: GE medical systems, Philips medical systems, ● Siemens Healthineers. - Magnetic Field Strength: 1.5 & 3 T ● - MRI Sequences/ protocol: 3D T1 MPRAGE ● - . Slice thickness: 1, 1.2 - Approximately equal geographical distribution in USA: East coast, Central US ● regions, West coast. The distribution for age bands is as follows: | Age group | Count | |-----------|-------| | 55-64 | 109 | | 65-69 | 56 | | 70-74 | 50 | | 75-79 | 29 | | 80-84 | 20 | | 85-90 | 16 | {7}------------------------------------------------ The mean age of subjects was found to be 68 ± 8.3 years. | | Subgroups | Count | Mean (mL) | Standard deviation (mL) | |-------------------------|--------------|-------|-----------|-------------------------| | Clinical Sub-groups | ADNI-control | 140 | 6.8 | 1 | | | ADNI-MCI | 70 | 6.6 | 1.1 | | | ADNI-AD | 70 | 5.5 | 1.1 | | Gender | Male | 140 | 6.6 | 1.1 | | | Female | 140 | 6.2 | 1.3 | | Magnetic field strength | 1.5T | 139 | 6.2 | 1.2 | | | 3 T | 141 | 6.7 | 1.1 | | Slice thickness | 1 | 118 | 6.7 | 1 | | | 1.2 | 162 | 6.2 | 1.2 | | US Region | East | 100 | 6.5 | 1.2 | | | West | 87 | 6.3 | 1.3 | | | Central | 93 | 6.5 | 1 | The table below provides the categorization of subjects according to selection criteria: # B. Ground Truth: - 1. 3 US Board Certified Radiologists performed manual segmentation of 280 subjects' MRI Brain scans using a widely accepted segmentation guideline method. This ground truth was combined into one tracing per case by the STAPLE (Simultaneous Truth and Performance Level Estimation) algorithm. The STAPLE-derived ground truth was then compared with segmentation provided by each radiologist and statistical tests were performed to ensure the validity of ground truth. - 2. NEUROShield™ algorithm provided automated segmentation for the Hippocampus brain structure with markings and labelling on all subjects using algorithms and performed segmentation and computed volumes. # C. Statistical Analysis: - 1. Validation of Ground Truth: Ground truth validation using 3 radiologist segmentations was performed by comparing the segmentations obtained by these radiologists with the STAPLE annotations, utilizing Dice coefficient, sensitivity, specificity and Hausdorff distance. Statistical analysis revealed no significant differences between the ground truth and radiologist segmentations (p > 0.05) for all comparisons, supporting the reliability of the ground truth annotations and the consistency of the radiologist segmentations. - 2. Geometric comparison of NEUROShield™ with Ground Truth: Ground Truth was compared with the segmentation output generated by NEUROShield™ and validated using Dice score and Hausdorff distance. NEUROShield passed the criteria for both statistical methods. {8}------------------------------------------------ - 3. Quantitative Comparison of volumes of NEUROShield™ (NS) with Ground Truth: STAPLE-derived ground truth building on the three US Board Certified Radiologists' provided segmentations was used to calculate the volume of the Hippocampus brain structure for all the cases. ITK Snap was used for this purpose. These volumes were compared with the volumes computed by NEUROShield™ using correlation analysis, Bland-Altman plots, and relative volume difference. NEUROShield passed the criteria for all three of the statistical methods, showing correspondence between NEUROShield™ volume and STAPLE volume. - 4. Pass/fail criteria: The pass/fail criteria were defined by selecting thresholds for each measure and performing hypothesis testing for the same. The thresholds for Dice score and Hausdorff distance are 75% and 6.1mm respectively, whereas for correlation and relative volume difference the passing criteria was defined as 0.82 and 24.6% respectively. For mean difference in BA plots, the threshold selected for total hippocampus was 1010 mm3 - 5. Subgroup Error Analysis: For all the different subgroups, like magnetic field strength, gender, slice thickness, clinical subgroups and US geographical regions, the dice score values were above 90% and Hausdorff distance was less than 4 mm which represents a high level of accuracy of NEUROShield™ Hippocampus segmentation. Furthermore, NEUROShield™ passes the criteria both for correlation and relative volume differences for different subgroups. # D. Results: - 1. The average dice coefficient and Hausdorff distance was found to be 0.91 and 3.8 mm respectively. The following table shows the 95% confidence interval for both. | Measure | Threshold | NEUROShield™ 95 %<br>confidence intervals | Criteria<br>(Pass/Fail) | |--------------------|-----------|-------------------------------------------|-------------------------| | Dice | 0.75 | (0.90, 0.92) | Pass | | Hausdorff distance | 6.1 | (3.57, 4.06) | Pass | - 2. The outcomes of subgroup error analysis are as follows: | | Dice score | | | Hausdorff distance (mm) | | | |-----------------------------------------|-------------|--------------|--------------|-------------------------|--------------|--------------| | Clinical subgroups | Control | MCI | AD | Control | MCI | AD | | Measured value | 0.91 | 0.92 | 0.9 | 3.77 | 3.43 | 4.3 | | NEUROShieldTM 95 % confidence intervals | (0.9, 0.92) | (0.91, 0.93) | (0.88, 0.91) | (3.42, 4.13) | (3.03, 3.82) | (3.75, 4.85) | | Criteria | Pass | Pass | Pass | Pass | Pass | Pass | #### a) Clinical subgroups: {9}------------------------------------------------ # b) Gender: | | Dice score | | Hausdorff distance (mm) | | |-------------------------------------------|-------------|-------------|-------------------------|------------| | Gender | Female | Male | Female | Male | | Measured value | 0.91 | 0.91 | 3.92 | 3.71 | | NEUROShield™ 95 %<br>confidence intervals | (0.90,0.92) | (0.90,0.92) | (3.5,4.3) | (3.4,4.02) | | Criteria | Pass | Pass | Pass | Pass | # c) Magnetic field strength: | | Dice score | | Hausdorff distance (mm) | | |----------------------------------------------|-------------|--------------|-------------------------|--------------| | MRI strength | 3T | 1.5T | 3T | 1.5T | | Measured value | 0.92 | 0.9 | 3.66 | 3.9 | | NEUROShield™<br>95 % confidence<br>intervals | (0.92,0.93) | (0.89, 0.91) | (3.36, 3.96) | (3.59, 4.37) | | criteria | Pass | Pass | Pass | Pass | # d) Slice thickness: | | Dice score | | Hausdorff distance (mm) | | |----------------------------------------------|-------------|-------------|-------------------------|-------------| | slice thickness | 1 mm | 1.2mm | 1 mm | 1.2mm | | Average value | 0.92 | 0.9 | 3.5 | 4 | | NEUROShield™<br>95 % confidence<br>intervals | (0.92,0.93) | (0.89,0.91) | (3.21, 3.8) | (3.68,4.41) | | criteria | Pass | Pass | Pass | Pass | # e) US geographical regions: | | Dice score | | | Hausdorff distance | | | |------------------|------------|---------|------------|--------------------|---------|------------| | Region | East US | West US | Central US | East US | West US | Central US | | Average<br>value | 0.91 | 0.9 | 0.92 | 3.78 | 3.94 | 3.73 | {10}------------------------------------------------ | 95 %<br>confidence<br>intervals | (0.9, 0.92) | (0.88, 0.91) | (0.91, 0.93) | (3.37, 4.19) | (3.43, 4.45) | (3.38, 4.09) | |---------------------------------|-------------|--------------|--------------|--------------|--------------|--------------| | Criteria | Pass | Pass | Pass | Pass | Pass | Pass | The analysis of Neuroshield hippocampus segmentation revealed that the overall dice score values were above 90% and Hausdorff distance consistently below 4mm, reflecting a remarkable level of accuracy. These findings affirm the precision in both correlation and relative volume differences for segmenting hippocampal structures. # VIII. Conclusions: This comprehensive evaluation demonstrates the reliability and effectiveness of NeuroShield in hippocampal segmentation. The assessment concludes that Neuroshield is a highly accurate device/tool for its intended use, thereby promising significant contributions to neuroimaging research and clinical applications.