K232436 · Ischemaview, Inc. · QAS · Oct 25, 2023 · Radiology
Device Facts
Record ID
K232436
Device Name
Rapid SDH
Applicant
Ischemaview, Inc.
Product Code
QAS · Radiology
Decision Date
Oct 25, 2023
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.2080
Device Class
Class 2
Attributes
AI/ML, Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K232436 · Oct 25, 2023
Rapid SDH
Ischemaview, Inc.
Retrospective clinical head CT images from multiple medical centers
A retrospective, blinded, multinational study was conducted to evaluate the performance of the Rapid SDH AI algorithm in identifying hemispheric subdural hemorrhage in routine clinical CT scans.
Retrospective, blinded, multinational study; Retrospective, blinded, multinational study
Patients undergoing head CT scans; Sample Size: 310 samples (147 positive, 163 negative); Number of Sites: 14 sites listed (e.g., Gradient, Riverside Regional Medical Center, Augusta University Medical Center, etc.)
Not applicable for this study
Sensitivity and Specificity for identifying hemispheric SDH; median processing time
Rapid SDH is a radiological computer aided triage and notification software indicated for use in the triage and notification of hemispheric SDH in non-enhanced head images. The device is intended to assist trained radiologists in workflow triage by providing notification of suspected findings of hemispheric Subdural Hemorrhage (SDH) in head CT images. Rapid SDH uses an artificial intelligence algorithm to analyze images and highlight cases with suspected hemispheric SDH on a server or standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected hemispheric SDH findings include compressed preview images, that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device. The results of Rapid SDH are intended to be used in conjunction with other patient information and based on professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.
Device Story
Rapid SDH is an AI/ML-based radiological computer-aided triage and notification software. It processes non-enhanced head CT (NCCT) images to detect suspected hemispheric subdural hemorrhage (SDH). Operating in parallel to standard clinical workflows, it analyzes images on a server or desktop application. When a suspected finding is identified, the device sends a priority notification to clinicians, including compressed preview images for informational purposes. It does not alter original images or remove cases from the standard worklist. Radiologists use the notification to prioritize their review of full, non-compressed images on a diagnostic viewer. The device assists in workflow triage, potentially reducing time-to-exam-open for suspected SDH cases.
Clinical Evidence
Retrospective, blinded, multinational study (N=310; 147 positive, 163 negative). Truth established by three expert neuroradiologists. Primary endpoint: sensitivity >80%. Results: Sensitivity 0.924 (95% CI: 0.871-0.956), Specificity 0.987 (95% CI: 0.954-0.996), AUC 0.995. Secondary endpoint: median notification time 45 seconds (range 33-107s). Subgroup analysis provided for age, gender, SDH subtype, volume, slice thickness, and manufacturer.
Technological Characteristics
Software-only device; AI/ML neural network algorithm. Operates on NCCT images. Complies with DICOM (NEMA PS 3.1-3.20), ISO 14971 (risk management), and IEC 62304 (software lifecycle). Connectivity via server/standalone desktop application; supports email and mobile notifications. Cybersecurity controls include vulnerability assessments, SBOMs, and penetration testing.
Indications for Use
Indicated for triage and notification of hemispheric SDH in non-enhanced head CT images for patients >21 years old. Validated for hemispheric SDH ≥ 1ml. Contraindicated for use with contrast-enhanced scans. Excludes subdural hygroma, empyema, and effusion mimics. Not for diagnostic use.
Regulatory Classification
Identification
Radiological computer aided triage and notification software is an image processing prescription device intended to aid in prioritization and triage of radiological medical images. The device notifies a designated list of clinicians of the availability of time sensitive radiological medical images for review based on computer aided image analysis of those images performed by the device. The device does not mark, highlight, or direct users' attention to a specific location in the original image. The device does not remove cases from a reading queue. The device operates in parallel with the standard of care, which remains the default option for all cases.
Special Controls
Radiological computer aided triage and notification software must comply with the following special controls: 1. Design verification and validation must include: i. A detailed description of the notification and triage algorithms and all underlying image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, how the algorithm affects or relates to clinical practice or patient care, and any algorithm limitations. ii. A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide effective triage (e.g., improved time to review of prioritized images for pre-specified clinicians). iii. Results from performance testing that demonstrate that the device will provide effective triage. The performance assessment must be based on an appropriate measure to estimate the clinical effectiveness. The test dataset must contain sufficient numbers of cases from important cohorts (e.g., subsets defined by clinically relevant confounders, effect modifiers, associated diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals for these individual subsets can be characterized with the device for the intended use population and imaging equipment. iv. Standalone performance testing protocols and results of the device. v. Appropriate software documentation (e.g., device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results). 2. Labeling must include the following: i. A detailed description of the patient population for which the device is indicated for use. ii. A detailed description of the intended user and user training that addresses appropriate use protocols for the device. iii. Discussion of warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (e.g., poor image quality for certain subpopulations), as applicable. iv. A detailed description of compatible imaging hardware, imaging protocols, and requirements for input images. v. Device operating instructions. vi. A detailed summary of the performance testing, including: test methods, dataset characteristics, triage effectiveness (e.g., improved time to review of prioritized images for pre-specified clinicians), diagnostic accuracy of algorithms informing triage decision, and results with associated statistical uncertainty (e.g., confidence intervals), including a summary of subanalyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.
*Classification.* Class II (special controls). The special controls for this device are:(1) Design verification and validation must include:
(i) A detailed description of the notification and triage algorithms and all underlying image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, how the algorithm affects or relates to clinical practice or patient care, and any algorithm limitations.
(ii) A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide effective triage (
*e.g.,* improved time to review of prioritized images for pre-specified clinicians).(iii) Results from performance testing that demonstrate that the device will provide effective triage. The performance assessment must be based on an appropriate measure to estimate the clinical effectiveness. The test dataset must contain sufficient numbers of cases from important cohorts (
*e.g.,* subsets defined by clinically relevant confounders, effect modifiers, associated diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals for these individual subsets can be characterized with the device for the intended use population and imaging equipment.(iv) Stand-alone performance testing protocols and results of the device.
(v) Appropriate software documentation (
*e.g.,* device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results).(2) Labeling must include the following:
(i) A detailed description of the patient population for which the device is indicated for use;
(ii) A detailed description of the intended user and user training that addresses appropriate use protocols for the device;
(iii) Discussion of warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (
*e.g.,* poor image quality for certain subpopulations), as applicable;(iv) A detailed description of compatible imaging hardware, imaging protocols, and requirements for input images;
(v) Device operating instructions; and
(vi) A detailed summary of the performance testing, including: test methods, dataset characteristics, triage effectiveness (
*e.g.,* improved time to review of prioritized images for pre-specified clinicians), diagnostic accuracy of algorithms informing triage decision, and results with associated statistical uncertainty (*e.g.,* confidence intervals), including a summary of subanalyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.
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Image /page/0/Picture/0 description: The image shows 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 in blue, with the words "U.S. FOOD & DRUG ADMINISTRATION" in blue as well. The FDA is a federal agency responsible for regulating and supervising the safety of food, drugs, and other products.
iSchemaView, Inc. Jim Rosa SVP Regulatory and Quality 1120 Washington Ave. Suite 200 Golden, Colorado 80401
October 25, 2023
Re: K232436
Trade/Device Name: Rapid SDH Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological Computer Aided Triage And Notification Software Regulatory Class: Class II Product Code: OAS Dated: October 5, 2023 Received: October 5, 2023
Dear Jim Rosa:
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.
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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).
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-regulatory
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assistance/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 DHT 8B: Division of Radiological Imaging Devices and Electronic Products OHT 8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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#### Indications for Use
510(k) Number (if known) K232436
Device Name Rapid SDH
#### Indications for Use (Describe)
Rapid SDH is a radiological computer aided triage and notification software indicated for use in the triage and notification of hemispheric SDH in non-enhanced head images. The device is intended to assist trained radiologists in workflow triage by providing notification of suspected findings of hemispheric Subdural Hemorrhage (SDH) in head CT images. Rapid SDH uses an artificial intelligence algorithm to analyze images and highlight cases with suspected hemispheric SDH on a server or standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected hemispheric SDH findings include compressed preview images, that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device.
The results of Rapid SDH are intended to be used in conjunction with other patient information and based on professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.
#### Contraindications/Exclusions/Cautions:
· Rapid SDH is one input to physician diagnosis for patients >21 years old undergoing screening for hemispheric SDH, both acute and chronic.
· Rapid SDH is validated against hemispheric SDH ≥ 1ml.
- Subdural hygroma, subdural empyema, and subdural effusion mimics were not included in the validation data set.
- · Excessive patient motion may lead to artifacts that make the scan technically inadequate.
· For use with non-contrast scans. Presence of intravenous contrast may lead to false positive indication of suspected hemispheric SDH.
• Identification of suspected findings is not for diagnostic use beyond notification. Images that are previewed through email and the mobile application are compressed and are for informational purposes only and not intended for diagnostic use beyond notification.
• Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests.
Type of Use (Select one or both, as applicable)
> Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
#### CONTINUE ON A SEPARATE PAGE IF NEEDED.
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#### 510(k) Summary
#### iSchemaView, Inc.'s Rapid SDH
This document contains the 510(k) summary for the iSchemaView Rapid SDH. The content of this summary is based on the requirements of 21 CFR Section 807.92(c).
#### Applicant Name and Address:
| Name: | iSchemaView, Inc. |
|-------------------|------------------------------------------------------------------|
| Address: | 1120 Washington Ave<br>Ste. 200<br>Golden, CO 80401 |
| Official Contact: | Jim Rosa<br>Phone: (303) 704-3374<br>Email: rosa@ischemaview.com |
#### August 11, 2023 Summary Preparation Date:
#### Device Name and Classification:
| Trade Name: | Rapid SDH |
|--------------------------|---------------------------------------------------------------------------|
| Common Name: | Radiological Computer-Assisted Triage And<br>Notification Software (CADt) |
| Classification: | II |
| Product Code: | QAS |
| Regulation No: | 21 C.F.R. §892.2080 |
| Classification<br>Panel: | Radiology Devices |
#### Predicate Devices:
The iSchemaView Rapid is claimed to be substantially equivalent to the following legally marketed predicate device: Rapid ICH (K221456).
#### Device Description:
Rapid SDH is a radiological computer-assisted triage and notification software device. The Rapid SDH module is a Non-Contrast Computed Tomography (NCCT) processing module which operates within the integrated Rapid Platform to provide triage and notification of suspected hemispheric sub-dural hemorrhage (SDH). The Rapid SDH module is an Al/ML module. The output of the module is a priority notification to clinicians indicating the suspicion of SDH based on positive findings. The Rapid SDH module uses the basic services supplied by the Rapid Platform including DICOM processing, job management, imaging module execution and imaging output including the notification and compressed image.
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iSchemaView - Traditional 510(k) Rapid SDH 510(k) Summary
#### Indications for Use:
Rapid SDH is a radiological computer aided triage and notification software indicated for use in the triage and notification of hemispheric SDH in non-enhanced head images. The device is intended to assist trained radiologists in workflow triage by providing notification of suspected findings of hemispheric Subdural Hemorrhage (SDH) in head CT images.
Rapid SDH uses an artificial intelligence algorithm to analyze images and highlight cases with suspected hemispheric SDH on a server or standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected hemispheric SDH findings. Notifications include compressed preview images, that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device.
The results of Rapid SDH are intended to be used in conjunction with other patient information and based on professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.
Contraindications/Exclusions/Cautions:
- Rapid SDH is one input to physician diagnosis for patients >21 years old undergoing screening for . hemispheric SDH, both acute and chronic.
- . Rapid SDH is validated against hemispheric SDH ≥ 1ml.
- . Subdural hygroma, subdural empyema, and subdural effusion mimics were not included in the validation data set.
- . Excessive patient motion may lead to artifacts that make the scan technically inadequate.
- . For use with non-contrast scans. Presence of intravenous contrast may lead to false positive indication of suspected hemispheric SDH.
- . Identification of suspected findings is not for diagnostic use beyond notification. Images that are previewed through email and the mobile application are compressed and are for informational purposes only and not intended for diagnostic use beyond notification.
- Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer . and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests.
#### Comparison of Technological Characteristics:
Rapid SDH does not raise new questions of safety or effectiveness compared to the previously cleared predicate, Rapid ICH (K221456). Both devices use machine learning algorithms to determine the presence of intracranial hemorrhage and notify clinicians to the suspicion without removing the case from normal workflow processing. Rapid SDH has a minor difference from Rapid ICH, regarding a singular indication for the hemispheric sub-
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# 510(k) Summary
dural hemorrhage (SDH) subtype vs multiple hemorrhage types within the predicate. Based on the comparison the subject device is substantially equivalent to the predicate device. The features are compared in the following table:
| Substantial Equivalence Table | | | |
|-------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Comparison<br>Feature | Rapid ICH (K221456) | Rapid SDH | |
| Indications<br>for Use | Rapid ICH is a radiological<br>computer aided triage and<br>notification software indicated for<br>use in the analysis of non-enhanced<br>head CT images. The device is<br>intended to assist hospital networks<br>and trained radiologists in<br>workflow triage by flagging and<br>communication of suspected<br>positive findings of pathologies in<br>head CT images, namely<br>Intracranial Hemorrhage (ICH).<br><br>Rapid ICH uses an artificial<br>intelligence algorithm to analyze<br>images and highlight cases with<br>detected ICH on a standalone<br>desktop application in parallel to<br>the ongoing standard of care image<br>interpretation. The user is<br>presented with notifications for<br>cases with suspected ICH findings.<br>Notifications include compressed<br>preview images that are meant for<br>informational purposes only and<br>not intended for diagnostic use<br>beyond notification. The device<br>does not alter the original medical<br>image and is not intended to be<br>used as a diagnostic device.<br><br>The results of Rapid ICH are<br>intended to be used in conjunction<br>with other patient information and<br>based on professional judgment, to<br>assist with triage/prioritization of<br>medical images. Notified clinicians<br>are responsible for viewing full<br>images per the standard of care. | Rapid SDH is a radiological<br>computer aided triage and<br>notification software indicated for<br>use in the triage and notification of<br>hemispheric SDH in non-enhanced<br>head images. The device is<br>intended to assist trained<br>radiologists in workflow triage by<br>providing notification of suspected<br>findings of hemispheric Subdural<br>Hemorrhage (SDH) in head CT<br>images.<br><br>Rapid SDH uses an artificial<br>intelligence algorithm to analyze<br>images and highlight cases with<br>suspected hemispheric SDH on a<br>server or standalone desktop<br>application in parallel to the<br>ongoing standard of care image<br>interpretation. The user is<br>presented with notifications for<br>cases with suspected hemispheric<br>SDH findings. Notifications<br>include compressed preview<br>images, that are meant for<br>informational purposes only and<br>not intended for diagnostic use<br>beyond notification. The device<br>does not alter the original medical<br>image and is not intended to be<br>used as a diagnostic device.<br><br>The results of Rapid SDH are<br>intended to be used in conjunction<br>with other patient information and<br>based on professional judgment, to<br>assist with triage/prioritization of | |
| | | | medical images. Notified<br>clinicians are responsible for<br>viewing full images per the<br>standard of care.<br><br>Note: See limitations in IFU<br>statement above |
| Stroke/Head | Hemorrhagic Stroke/Head | Hemispheric Sub-Dural<br>Hemorrhage/Head | |
| Removal of<br>cases from<br>worklist<br>queue | No | No | |
| Primary<br>Imaging<br>Modalities | NCCT | NCCT | |
| Technical<br>Implementati<br>on | ML/AI/Neural Network | ML/AI/Neural Network | |
| Segmentation<br>of ROI | No, the device does not highlight or<br>direct a user's attention to a specific<br>location in the image file. | No, the device does not highlight or<br>direct a user's attention to a specific<br>location in the image file. | |
| Preview<br>Images | Presentation of a preview of the<br>study for initial assessment not<br>meant for diagnostic purposes.<br><br>The device operates in parallel with<br>the standard of care, which remains. | Presentation of a preview of the<br>study for initial assessment not<br>meant for diagnostic purposes.<br><br>The device operates in parallel with<br>the standard of care, which remains. | |
| Primary<br>User(s) | Radiologist | Radiologist | |
| Alteration of<br>original<br>image data<br>base | No | No | |
| Alters<br>Standard of<br>Care<br>Workflow | In parallel to | In parallel to | |
| Notification/<br>Prioritization | Yes - PACS, Workstation | Yes - PACS, Workstation, email,<br>mobile | |
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# 510(k) Summary
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510(k) Summary
## Performance Standards:
Rapid has been developed in conformance with the following standards, as applicable:
| ISO 14971:2019 | Application of Risk Management to Medical Devices |
|--------------------|---------------------------------------------------------|
| IEC 62304:2015 | Medical device software – Software lifecycle processes |
| IEC 62366:2015 | Application of Usability Engineering to Medical Devices |
| NEMA PS 3.1 - 3.20 | Digital Imaging and Communications in Medicine (DICOM) |
Rapid has been designed to meet the cybersecurity requirements using design Vulnerability Assessments, SBOM's, and PEN Testing.
## Performance Data:
Rapid complies with DICOM (Digital Imaging and Communications in Medicine) - Developed by the American College of Radiology and the National Electrical Manufacturers Association. NEMA PS 3.1 - 3.20.
iSchemaView conducted a retrospective, blinded, multinational study with Rapid SDH with the primary endpoint to evaluate the software's performance in identifying CT scans containing sub-dural intracranial hemorrhage (SDH). The performance data is derived from 310 samples with 147 positives and 163 negatives. Truth was established using three (3) expert neuro-radiologists.
The primary endpoint of the study was to exceed 80% performance goal. Sensitivity (Se) was measured at Se: 0.924 (95% CI: 0.871 - 0.956) and Sp: 0.987 (95% CI: 95477 - 0.996). The RoC/AUC analysis using Rapid SDH Volume estimate as a predictor of Suspected SDH is AUC: 0.995 (0.986, 1.0):
Image /page/9/Figure/10 description: The image is a plot of sensitivity versus 1-specificity, also known as a receiver operating characteristic (ROC) curve. The x-axis represents 1-specificity or the false positive rate, ranging from 0 to 1.00. The y-axis represents sensitivity or the true positive rate, also ranging from 0 to 1.00. The curve is close to the top left corner, indicating a high level of accuracy.
In addition, a secondary endpoint was to show median processing time to notify the clinician of 45 seconds with min of 33 seconds and maximum of 107 seconds.
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# 510(k) Summary
## Performance across subtype differentiation shows:
| Gender | Measure | N | Estimate | Lower 95% CI | Upper 95% CI |
|--------|-------------|-----|----------|--------------|--------------|
| Female | Sensitivity | 43 | 0.930 | 0.814 | 0.976 |
| Female | Specificity | 67 | 0.985 | 0.920 | 0.997 |
| Male | Sensitivity | 103 | 0.932 | 0.866 | 0.967 |
| Male | Specificity | 84 | 0.988 | 0.936 | 0.998 |
Performance Metrics by Gender
# Performance Metrics by Age Groups
| Age Group | Measure | N | Estimate | Lower 95% CI | Upper 95% CI |
|---------------|-------------|----|----------|--------------|--------------|
| Age ≤ 50 | Sensitivity | 18 | 0.778 | 0.548 | 0.910 |
| | Specificity | 26 | 1.000 | 0.871 | 1.000 |
| 50 < Age < 70 | Sensitivity | 51 | 0.922 | 0.815 | 0.969 |
| | Specificity | 55 | 1.000 | 0.935 | 1.000 |
| Age ≥ 70 | Sensitivity | 80 | 0.950 | 0.878 | 0.980 |
| | Specificity | 62 | 0.968 | 0.891 | 0.991 |
#### Performance by SDH Subtype: Chronic, Acute, Mixed
| Type | Measure | N | Estimate | Lower 95% CI | Upper 95% CI |
|---------|-------------|----|----------|--------------|--------------|
| Chronic | Sensitivity | 47 | 0.915 | 0.801 | 0.966 |
| Acute | Sensitivity | 48 | 0.875 | 0.753 | 0.941 |
| Mixed† | Sensitivity | 62 | 0.968 | 0.890 | 0.991 |
#### Performance by Hemorrhage Mix
| Hemorrhage Subtype | Measure | N | Estimate | Lower 95% CI | Upper 95% CI |
|---------------------|-------------|-----|----------|--------------|--------------|
| Subdural Only | Sensitivity | 119 | 0.933 | 0.873 | 0.966 |
| Subdural + Other | Sensitivity | 38 | 0.895 | 0.759 | 0.958 |
| Other, non-subdural | Specificity | 50 | 1.00 | 0.929 | 1.00 |
#### Performance Metrics by Volume
| Volume | Measure | N | Estimate | Lower 95% CI | Upper 95% CI |
|-----------|-------------|-----|----------|--------------|--------------|
| < 10 ml | Sensitivity | 29 | 0.724 | 0.543 | 0.853 |
| ≥ 10.0 ml | Sensitivity | 128 | 0.969 | 0.922 | 0.988 |
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## 510(k) Summary
| Slice Thickness | Measure | N | Estimate | Lower 95% CI | Upper 95% CI |
|---------------------------|-------------|----|----------|--------------|--------------|
| Slice Thickness ≤ 2.5 | Sensitivity | 47 | 0.936 | 0.828 | 0.978 |
| | Specificity | 67 | 1.000 | 0.946 | 1.000 |
| 2.5 < Slice Thickness < 5 | Sensitivity | 39 | 0.974 | 0.868 | 0.995 |
| | Specificity | 34 | 1.000 | 0.898 | 1.000 |
| Slice Thickness = 5 | Sensitivity | 67 | 0.985 | 0.920 | 0.997 |
| | Specificity | 60 | 1.000 | 0.940 | 1.000 |
#### Performance Metrics by Slice Thickness
#### Performance Metrics by Manufacturer
| Manufacturer | Measure | N | Estimate | Lower 95% CI | Upper 95% CI |
|--------------|-------------|----|----------|--------------|--------------|
| GE | Sensitivity | 52 | 0.942 | 0.844 | 0.980 |
| GE | Specificity | 35 | 1.000 | 0.901 | 1.000 |
| PHILIPS | Sensitivity | 19 | 0.789 | 0.567 | 0.915 |
| PHILIPS | Specificity | 41 | 1.000 | 0.914 | 1.000 |
| TOSHIBA | Sensitivity | 47 | 0.915 | 0.801 | 0.966 |
| TOSHIBA | Specificity | 35 | 1.000 | 0.901 | 1.000 |
| SIEMENS | Sensitivity | 39 | 0.974 | 0.868 | 0.995 |
| SIEMENS | Specificity | 42 | 0.952 | 0.842 | 0.987 |
#### Site based information.
Many of the sites have inclusion of either positive or negative cases (blinded information during validation), for the positive case biased sites Se is provided; for the non-positive case sites Sp is provided in those sites where enough samples are included to provide statistical relevance:
| Source | TP | FP | FN | TN | Total | Measure | Estimate | 95%<br>LCI | 95%<br>UCI |
|--------------------------------------|----|----|----|----|-------|---------|----------|------------|------------|
| Gradient | 59 | 0 | 4 | 1 | 64 | Se | 0.937 | 0.848 | 0.975 |
| Riverside Regional Medical<br>Center | 5 | 1 | 0 | 37 | 43 | Sp | 0.974 | 0.865 | 0.995 |
| Image Core Lab | 8 | 0 | 3 | 25 | 36 | Sp | 1.000 | 0.867 | 1.000 |
| Augusta University Medical<br>Center | 0 | 0 | 2 | 31 | 33 | Sp | 1.000 | 0.890 | 1.000 |
| Ascension | 31 | 0 | 0 | 0 | 31 | Se | 1.000 | 0.890 | 1.000 |
| D3 | 1 | 0 | 0 | 27 | 28 | Sp | 1.000 | 0.875 | 1.000 |
| Segmed | 22 | 0 | 1 | 0 | 23 | Se | 0.957 | 0.790 | 0.992 |
| Baptist | 0 | 0 | 1 | 13 | 14 | Sp | 1.000 | 0.772 | 1.000 |
| Hospital de Clinicas de POA | 4 | 0 | 0 | 10 | 14 | Sp | 1.000 | 0.722 | 1.000 |
| Stanford CA | 7 | 0 | 1 | 3 | 11 | Se | 0.875 | | |
{12}------------------------------------------------
510(k) Summary
| Source | TP | FP | FN | TN | Total | Measure | Estimate | 95% LCI | 95% UCI |
|------------------------------|----|----|----|----|-------|---------|----------|---------|---------|
| Ospedale Regionale di Lugano | 7 | 1 | 0 | 0 | 8 | Se | 1.000 | | |
| NYU | 0 | 0 | 0 | 3 | 3 | | | | |
| Flagler Hospital | 0 | 0 | 0 | 1 | 1 | | | | |
| MUSC | 1 | 0 | 0 | 0 | 1 | | | | |
The performance validation for achievement of effective triage by the Rapid SDH image analysis algorithm as well as effective notification functionality of the Rapid SDH application, as compared to the standard of care for improved time-to-exam-open of a notified case was met.
#### Prescriptive Statement:
Caution: Federal law restricts this device to sale by or on the order of a physician.
#### Safety & Effectiveness:
Rapid SDH has been designed, verified and validated in compliance with 21 CFR, Part 820.30 requirements. The device has been designed to meet the requirements associated with EN ISO 14971:2012 (risk management) and the software development process conforms to ISO 62304:2015.
#### Conclusion:
In conclusion, iSchemaView's Rapid SDH is substantially equivalent in technological characteristics, safety, and performance characteristics to the legally marketed predicate device, Rapid SDH (K221456).
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Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.
