(123 days)
Not Found
Yes
The "Device Description" section explicitly states, "Following the Al processing, the output of the algorithm analysis is transferred to an image review software." This directly indicates the use of Artificial Intelligence.
No
The device is described as an image management and processing system software intended to assist medical specialists by providing automated measurement of brain midline shift from NCCT images. It is explicitly stated that the "device does not alter the original medical image and is not intended to be used as a diagnostic device" and its "results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases." These statements indicate that the device provides information for analysis and assessment, rather than directly treating, preventing, or diagnosing a disease or condition, which are characteristics of a therapeutic device.
No
The "Intended Use / Indications for Use" section explicitly states, "The device does not alter the original medical image and is not intended to be used as a diagnostic device."
Yes
The device description explicitly states that the device "consists of a single module based on an algorithm programmed component" and is "intended to run on a linux-based server in a cloud environment." It receives and processes DICOM images and outputs results to existing image review software (PACS or desktop application). There is no mention of any accompanying hardware being part of the device itself.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs analyze biological samples: In Vitro Diagnostics are designed to examine specimens taken from the human body, such as blood, urine, tissue, etc., to provide information about a person's health.
- This device analyzes medical images: The BriefCase-Quantification device processes and analyzes radiological images (CT scans), not biological samples.
- The intended use is image processing and measurement: The stated intended use is for "automatic measurement of brain midline shift in non-contrast head CT (NCCT) images" and to "assist appropriately trained medical specialists by providing the user with an automated current manual process of measuring midline shift." This is clearly focused on image analysis and measurement, not the analysis of biological materials.
Therefore, while it is a medical device that aids in diagnosis by providing quantitative information from images, it does not fit the definition of an In Vitro Diagnostic.
No
The provided input does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device. The section "Control Plan Authorized (PCCP) and relevant text" is marked "Not Found," indicating the absence of such information.
Intended Use / Indications for Use
BriefCase-Quantification of Midline Shift (MLS) is a radiological image management and processing system software intended for automatic measurement of brain midline shift in non-contrast head CT (NCCT) images, in adults or transitional adolescents aged 18 years and older.
The device is intended to assist appropriately trained medical specialists by providing the user with an automated current manual process of measuring midline shift.
The device provides midline shift measurement from NCCT images acquired at a single time point, and can additionally provide an output with comparative analysis of two or more images that were acquired in the same individual at multiple time points.
The device does not alter the original medical image and is not intended to be used as a diagnostic device. The BriefCase-Quantification results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases. Clinicians are responsible for viewing full images per the standard of care.
Product codes
QIH
Device Description
BriefCase-Quantification is a radiological image management and processing device. The software consists of a single module based on an algorithm programmed component and is intended to run on a linux-based server in a cloud environment.
The BriefCase-Quantification receives filtered DICOM Images, and processes them chronologically by running the algorithm on relevant series to quantify the extent of midline shift. Following the Al processing, the output of the algorithm analysis is transferred to an image review software (the PACS or a desktop application).
The device generates a summary report that includes a preview image of the slice with the largest midline shift. The preview image includes the measured shift, the annotation of the midline, and the annotation of the largest perpendicular distance between the midline and septum pellucidum. Also, the summary report includes a table and a graph showing the measured midline shift over time for patients with multiple scans.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
non-contrast head CT (NCCT) images
Anatomical Site
Brain
Indicated Patient Age Range
adults or transitional adolescents aged 18 years and older.
Intended User / Care Setting
appropriately trained medical specialists
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Aidoc conducted a retrospective, blinded, multicenter, study with the BriefCase-Quantification software to evaluate the software's performance in providing adequate measurements of the midline shift in non-contrast head CT images in 284 cases from 228 unique patients from 6 US-based clinical sites, both academic and community centers, compared to the ground truth, as determined by three neuroradiologists, who independently measured the midline shift, the reference standard was created as the mean of all three measurements. The cases collected for the pivotal dataset were all distinct in time or center from the cases used to train the algorithm.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Aidoc conducted a retrospective, blinded, multicenter, study with the BriefCase-Quantification software to evaluate the software's performance in providing adequate measurements of the midline shift in non-contrast head CT images in 284 cases from 228 unique patients from 6 US-based clinical sites, both academic and community centers, compared to the ground truth, as determined by three neuroradiologists, who independently measured the midline shift, the reference standard was created as the mean of all three measurements.
Primary Endpoints: The algorithm performance showed that the mean absolute error between the ground truth measurement and algorithm was 0.94 mm (95% Cl: 0.74 mm, 1.14 mm) mm.
Secondary Endpoints: A Bland-Altman plot demonstrated an agreement between the ground truth compared to the algorithm output. The mean difference between the two measurements was -0.15 mm, indicating that there is little to no bias between the two measurements.
The mean absolute error in midline shift between the reference for multiple time point testing for the same patient was 1.16 mm (95% Cl: 0.61 mm, 1.71 mm) for the first case and 1.28 mm (95% Cl: 0.68 mm, 1.88 mm) for the follow-up cases.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Mean absolute error between ground truth and algorithm was 0.94 mm (95% CI: 0.74 mm, 1.14 mm).
Mean difference between ground truth and algorithm was -0.15 mm.
Predicate Device(s)
qER-Quant (K211222)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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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.
Aidoc Medical, Ltd. % John Smith Partner Hogan & Lovells U.S. LPP 555 Thirteenth Street NW Washington, DC 20004
Re: K232083
November 13, 2023
Trade/Device Name: BriefCase-Quantification Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH Dated: October 17, 2023 Received: October 17, 2023
Dear John Smith:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
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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 OS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Jessica Lamb Assistant Director DHT8B: Division of Radiologic Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
Indications for Use
510(k) Number (if known)
K232083
Device Name
BriefCase-Quantification
Indications for Use (Describe)
BriefCase-Quantification of Midline Shift (MLS) is a radiological image management and processing system software intended for automatic measurement of brain midline shift in non-contrast head CT (NCCT) images, in adults or transitional adolescents aged 18 years and older.
The device is intended to assist appropriately trained medical specialists by providing the user with an automated current manual process of measuring midline shift.
The device provides midline shift measurement from NCCT images acquired at a single time point, and can additionally provide an output with comparative analysis of two or more images that were acquired in the same individual at multiple time points.
The device does not alter the original medical image and is not intended to be used as a diagnostic device. The BriefCase-Quantification results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases. Clinicians are responsible for viewing full images per the standard of care.
Type of Use (Select one or both, as applicable)
区 Prescription Use (Part 21 CFR 801 Subpart D)
□ Over-The-Counter Use (21 CFR 801 Subpart C)
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Image /page/3/Picture/0 description: The image shows the logo for Aidoc. The logo is in blue and consists of the word "aidoc" in lowercase letters. The dot above the "i" is replaced with an orange circle. The logo is simple and modern.
510(k) Summarv Aidoc Medical, Ltd.'s BriefCase-Quantification K232083
Submitter:
| Aidoc Medical, Ltd.
3 Aminadav St.
Tel-Aviv, Israel
| Phone: | +972-73-7946870 |
|---|---|
| Contact Person: | Amalia Schreier, LL.M. |
| Date Prepared: | November 10, 2023 |
| Name of Device: | BriefCase-Quantification |
| Classification Name: | Medical image management and processing system |
| Regulatory Class: | Class II |
| Product Code: | QIH (21 CFR 892.2050) |
| Primary Predicate Device: | qER-Quant (K211222) |
Device Description
BriefCase-Quantification is a radiological image management and processing device. The software consists of a single module based on an algorithm programmed component and is intended to run on a linux-based server in a cloud environment.
The BriefCase-Quantification receives filtered DICOM Images, and processes them chronologically by running the algorithm on relevant series to quantify the extent of midline shift. Following the Al processing, the output of the algorithm analysis is transferred to an image review software (the PACS or a desktop application).
The device generates a summary report that includes a preview image of the slice with the largest midline shift. The preview image includes the measured shift, the annotation of the midline, and the annotation of the largest perpendicular distance between the midline and septum pellucidum. Also, the summary report includes a table and a graph showing the measured midline shift over time for patients with multiple scans.
Intended Use / Indications for Use
BriefCase-Quantification of Midline Shift (MLS) is a radiological image management and processing system software intended for automatic measurement of brain midline shift in non-contrast head CT (NCCT) images, in adults or transitional adolescents aged 18 years and older.
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The device is intended to assist appropriately trained medical specialists by providing the user with an automated current manual process of measuring midline shift.
The device provides midline shift measurement from NCCT images acquired at a single time point, and can additionally provide an output with comparative analysis of two or more images that were acquired in the same individual at multiple time points.
The device does not alter the original medical image and is not intended to be used as a diagnostic device. The BriefCase-Quantification results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases. Clinicians are responsible for viewing full images per the standard of care.
Comparison of Technological Characteristics
The subject BriefCase-Quantification of Midline Shift (MLS) is substantially equivalent to the predicate qER-Quant (K211222), as explained below.
The subject device and the predicate device are both radiological image management and processing system software. Both devices are artificial intelligence, deep-learning algorithms incorporating software packages for use with compliant scanners, PACS, and radiology workstations. The predicate qER-Quant evaluates images from CT scanners as does the proposed device for BriefCase-Quantification of Midline Shift (MLS). The predicate and subject devices differ in the fact that the predicate device analyzes additional two brain structures, which are Intracranial Hyperdensities and Lateral Ventricles.
The proposed device for BriefCase-Quantification of Midline Shift (MLS) has similar technology and design as the primary predicate device, and similar indications for use as both devices are intended to aid in automation of the current manual process of measuring midline shift. The subject and predicate qER-Quant devices raise the same types of safety and effectiveness questions. A table comparing the key features of the subject device and the predicate device is provided below.
| | Predicate Device
qER-Quant (K211222) | BriefCase-Quantification of Midline
Shift (MLS) |
|---------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Intended Use / Indications
for Use | The qER-Quant device is intended for
automatic labeling, visualization and
quantification of segmentable brain
structures from a set of Non-Contrast
head CT (NCCT) images. The software is
intended to automate the current manual
process of identifying, labeling and
quantifying the volume of segmentable
brain structures identified on NCCT
images. | BriefCase-Quantification of Midline Shift
(MLS) is a radiological image
management and processing system
software intended for automatic
measurement of brain midline shift in
non-contrast head CT (NCCT) images,
in adults or transitional adolescents
aged 18 years and older. |
| | Predicate Device
qER-Quant (K211222) | BriefCase-Quantification of Midline
Shift (MLS) |
| | qER-Quant provides volumes from NCCT
images acquired at a single time point and
provides a table with comparative
analysis for two or more images that were
acquired on the same scanner with the
same image acquisition protocol for the
same individual at multiple time points. | The device is intended to assist
appropriately trained medical specialists
by providing the user with an automated
current manual process of measuring
midline shift. |
| | The qER-Quant software is indicated for
use in the analysis of the following
structures: Intracranial Hyperdensities,
Lateral Ventricles and Midline Shift. | The device provides midline shift
measurement from NCCT images
acquired at a single time point, and can
additionally provide an output with
comparative analysis of two or more
images that were acquired in the same
individual at multiple time points. |
| | | The device does not alter the original
medical image and is not intended to be
used as a diagnostic device. The
BriefCase-Quantification results are not
intended to be used on a stand-alone
basis for clinical decision-making or
otherwise preclude clinical assessment
of cases. Clinicians are responsible for
viewing full images per the standard of
care. |
| Anatomical region of interest | Brain | Brain |
| Target structures analyzed
on NCCT scans | Midline shift, Intracranial hyperdensities,
and lateral ventricles | Midline shift |
| Data acquisition protocol | Non-contrast head CT (NCCT) images | Non-contrast head CT (NCCT) images |
| Midline Shift Measurement | Yes | Yes |
| Interference with standard
workflow | No | No |
| Time point | Single or multiple time points | Single or multiple time points |
| Output | Multiple electronic reports with volumetric
information of brain structures and midline
shift and Annotated DICOM Images | A Summary report with measurement
information of midline
shift
and
annotated images |
| | Predicate Device
qER-Quant (K211222) | BriefCase-Quantification of Midline
Shift (MLS) |
| | | |
| Algorithm | Artificial intelligence algorithm with database of images. | Artificial intelligence algorithm with database of images. |
| Structure | - The qER-Quant software interacts with the user's picture archiving and communication system (PACS) to receive scans and returns the results to the same destination.
- The core processing component is coupled with a pre-processing module to prepare input digital imaging and communications in medicine (DICOMS) for processing by the CNNs and a post-processing module to convert the output into visual and tabular output for users. | - BriefCase-Quantification is hosted on a cloud server and analyzes applicable CT images that are acquired on CT scanner that are forwarded to BriefCase-Quantification
- The results of the analysis are exported and presented to medical specialists for review , to assist in the measurement of MLS. |
Table 1: Key Feature Comparison
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Image /page/6/Picture/0 description: The image shows the logo for Aidoc. The logo is in blue and consists of the word "aidoc" in a sans-serif font. The dot over the "i" is replaced with a small orange circle. The logo is simple and modern.
Performance Data
Pivotal Study Summary
Aidoc conducted a retrospective, blinded, multicenter, study with the BriefCase-Quantification software to evaluate the software's performance in providing adequate measurements of the midline shift in non-contrast head CT images in 284 cases from 228 unique patients from 6 US-based clinical sites, both academic and community centers, compared to the ground truth, as determined by three neuroradiologists, who independently measured the midline shift, the reference standard was created as the mean of all three measurements. The cases collected for the pivotal dataset were all distinct in time or center from the cases used to train the algorithm.
Primary Endpoints
The algorithm performance showed that the mean absolute error between the ground truth measurement and algorithm was 0.94 mm (95% Cl: 0.74 mm, 1.14 mm) mm. Because the mean absolute error estimate is lower than the prespecified performance goal, the study's primary endpoint was achieved.
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Image /page/7/Picture/0 description: The image shows the logo for "aidoc.". The word "aidoc" is written in a bold, sans-serif font, with each letter in a dark blue color. To the right of the "c" is a small, solid orange circle. The logo is simple and modern, with a clean design.
Secondary Endpoints
A Bland-Altman plot demonstrated an agreement between the ground truth compared to the algorithm output. The mean difference between the two measurements was -0.15 mm, indicating that there is little to no bias between the two measurements, demonstrating the study's secondary endpoint was achieved.
The mean absolute error in midline shift between the reference for multiple time point testing for the same patient was 1.16 mm (95% Cl: 0.61 mm, 1.71 mm) for the first case and 1.28 mm (95% Cl: 0.68 mm, 1.88 mm) for the follow-up cases. Because the mean absolute error estimate is lower than the prespecified performance goal, the study's secondary endpoint was achieved.
Thus, the reported similar mean absolute error [the subject device: 0.94 (1.54) mm 0.51 (0.09 - 1.75) mm; the predicate device: 1.37 (1.23) mm 1.15 (0.23 - 2.59) mm] demonstrates that when using the subject BriefCase-Quantification of Midline Shift (MLS) the radiologists may have the same benefits with the qER-Quant.
As can be seen in Table 2 the mean age of patients whose scans were reviewed for BriefCase-Quantification of Midline Shift (MLS) was 64.4 years, with a standard deviation of 20.1 years. Gender distribution was 48.3% male, and 48.8% female (Table 3). Scanner distribution can also be found in Table 4 below.
Table 2: Descriptive Statistics for Age
| Mean | Std | Min | Median | Max | N | |
|---|---|---|---|---|---|---|
| Age | ||||||
| (Years) | 64.4 | 20.2 | 18 | 68 | 90 | 228 |
Table 3: Frequency Distribution of Gender
| Gender | N* | % |
|---|---|---|
| Male | 110 | 48.3% |
| Female | 111 | 48.8% |
- 7 cases had unknown gender defined in the DICOM metadata header and were excluded from the gender distribution
Table 4: Frequency Distribution of Manufacturer
| Manufacturer | N | % |
|---|---|---|
| Siemens | 47 | 20.6% |
| GE | 58 | 25.4% |
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Image /page/8/Picture/0 description: The image shows the logo for "aidoc". The logo is written in a sans-serif font, and the letters are blue. There is a small orange circle to the right of the letter "c".
| Manufacturer | N | % |
|---|---|---|
| Philips | 65 | 28.5% |
| Toshiba | 58 | 25.4% |
| Total | 228 | 100% |
Clinical Subgroups and Confounders: Heart and Vascular, Chronic diseases, Neoplasm, Trauma, Inflammatory, None of the above and Fully Negative.
In summary, performance validation data, combined with a comparison of overall agreement metric with the predicate device demonstrated equivalent performance.
Conclusions
The subject BriefCase-Quantification of Midline Shift (MLS) and the predicate qER-Quant are intended to aid in medical image management and processing of radiological images of the brain. The subject and predicate devices are both software devices with similar technological characteristics and principles of operation, incorporating deep learning AI algorithms that process images. The predicate and subject devices both provide an automated current manual process of measuring midline shift. Both devices provide a summary report and quantitative measurements from NCCT images acquired at a single time point and provide a table with comparative analysis for two or more images that were acquired for the same individual at multiple time points. The BriefCase-Quantification of Midline Shift (MLS) device is thus substantially equivalent to the qER-Quant device (K211222).