(22 days)
Yes
The document explicitly states that the Viz LVO Image Analysis Algorithm is a "locked, artificial intelligence machine learning (AI/ML) software algorithm".
No
The device is a notification-only tool used to identify and communicate images to a specialist, and is not intended for diagnostic use beyond notification. It analyzes images for suspected findings but does not directly treat or prevent a condition.
No
The document explicitly states multiple times that the device is "not for diagnostic use beyond notification" and further clarifies that "Identification of suspected findings is not for diagnostic use beyond notification" and "Image viewing through the mobile application interface is for informational purposes only and is not for diagnostic use." It also states "Viz LVO is limited to analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis."
Yes
The device description explicitly states that Viz LVO is a "combination of software modules" and consists of an "algorithm and mobile application software module." It also mentions the algorithm is hosted on a "Backend Server" and the mobile application is a "software module." There is no mention of any accompanying hardware being part of the device itself.
Based on the provided text, Viz LVO is not an In Vitro Diagnostic (IVD) device.
Here's why:
- IVDs analyze biological samples (like blood, urine, tissue) to provide diagnostic information. Viz LVO analyzes medical images (CT angiograms of the brain).
- The intended use explicitly states it's a "notification-only, parallel workflow tool" and that "Identification of suspected findings is not for diagnostic use beyond notification." This directly contradicts the primary purpose of an IVD, which is to aid in diagnosis.
- The device description emphasizes that the mobile application images are "for informational purposes only and not intended for diagnostic use."
- It states that Viz LVO "should not be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis."
While Viz LVO uses AI to analyze medical images and provides information to clinicians, its stated purpose is to facilitate workflow and communication, not to perform a diagnostic test on a biological sample.
No
The letter does not state that the FDA has reviewed and approved or cleared a PCCP for this specific device.
Intended Use / Indications for Use
Viz LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow.
Viz LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting, and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends review of those images. Images can be previewed through a mobile application. Viz LVO is intended to analyze terminal ICA and MCA-M1 vessels for LVOs.
Images that are previewed through 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. Viz LVO is limited to analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis.
Product codes
QAS
Device Description
Viz LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to analyze images for findings suggestive of a suspected large vessel occlusion and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Viz LVO was previously granted a de-novo as ContaCT (DEN170073); following the granting of the denovo the device name was changed to Viz LVO.
Viz LVO is a combination of software modules that allow for detection and notification of patients with a suspected large vessel occlusion. Viz LVO consists of an algorithm and mobile application software module.
The Viz LVO Image Analysis Algorithm (LVO Detection Algorithm) is a locked, artificial intelligence machine learning (AI/ML) software algorithm that analyzes CTA images of the head for a suspected large vessel occlusion (LVO). The LVO Detection Algorithm is hosted on Viz.ai's Backend Server and analyzes applicable stroke-protocoled CTA images of the head that are acquired on CT scanners and are forwarded to Viz.ai's Backend Server. Upon detection of a suspected LVO, the LVO Detection Algorithm sends a notification of the suspected finding.
The Viz LVO Mobile Notification Software is a software module that enables the end user to receive and toggle notifications for suspected large vessel occlusions identified by the LVO Detection Algorithm. The LVO Mobile Notification Software module is implemented into Viz.ai's generic nondiagnostic DICOM image viewer, Viz VIEW (formerly referred to as the Imaging Viewing Software in the previous submission, DEN170073), which displays CT scans that are sent to Viz.ai's Backend Server. When the Viz LVO Mobile Notification Software module is enabled for a user, the user can receive and toggle the notifications for patients with a suspected LVO, view a unique list of patients with a suspected LVO (as determined by the LVO Detection Algorithm), and view the non-diagnostic CT scan of the patient through the Viz VIEW mobile application. Image viewing through the mobile application interface is for informational purposes only and is not for diagnostic use.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
Computed Tomography Angiography (CTA)
Anatomical Site
brain, Head
Indicated Patient Age Range
Not Found
Intended User / Care Setting
hospital networks and trained clinicians, neurovascular specialist
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
Not Found
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Performance data was not included as part of the premarket notification. Supportive software verification and validation (V&V) testing were provided to demonstrate implementation of the device changes.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Not Found
Predicate Device(s)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.2080 Radiological computer aided triage and notification software.
(a)
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.(b)
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, which consists of the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" in blue, and then the word "ADMINISTRATION" in a smaller font size below that.
Viz.ai, Inc. % Gregory Ramina Director of Regulatory Affairs 201 Mission Street 12th Floor SAN FRANCISCO CA 94105
Re: K223042
October 21, 2022
Trade/Device Name: Viz LVO Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological computer aided triage and notification software Regulatory Class: Class II Product Code: QAS Dated: September 28, 2022 Received: September 29, 2022
Dear Gregory Ramina:
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). 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 located 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.
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 803) for
1
devices or postmarketing safety reporting (21 CFR 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 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Jessica Lamb. 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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510(k) Number (if known)
K223042
Device Name
Viz LVO
Indications for Use (Describe)
Viz LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow.
Viz LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting, and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends review of those images. Images can be previewed through a mobile application. Viz LVO is intended to analyze terminal ICA and MCA-M1 vessels for LVOs.
lmages that are previewed through the mobile application are compressed and are for informational purposes only and not intended for diagnostic use beyond 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. Viz LVO is limited to analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis.
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 a stylized blue logo. The logo is composed of several curved lines that resemble a stylized letter 'V' or a bird in flight. The lines are arranged in a symmetrical pattern, with the top line being the shortest and the bottom line being the longest. The overall design is simple and modern.
510(k) SUMMARY
Viz.ai, Inc.'s Viz LVO
| Applicant Name: | Viz.ai, Inc. |
|---|---|
| 201 Mission St, 12th Floor | |
| San Francisco, CA 94105 |
- Contact Person: Gregory Ramina Director of Regulatory Affairs 201 Mission Street, 12th Floor San Francisco, CA 94105 Tel. (415) 663-6130 Greg@viz.ai
- Date Prepared: September 28, 2022
Device Name and Classification
| Name of Device: | Viz LVO |
|---|---|
| Common or Usual Name: | Radiological Computer-Assisted Triage and Notification Software |
| Classification Panel: | Radiology |
| Regulation No: | 21 C.F.R. § 892.2080 |
| Regulatory Class: | Class II |
| Product Code: | QAS |
Predicate Device
| Manufacturer | Device Name | Application No. |
|---|---|---|
| Viz.ai, Inc. | ContaCT | DEN170073 |
Purpose of Special 510(k)
Viz LVO is a modification to the predicate device, ContaCT. This Special 510(k) was submitted for changes to the Viz LVO indications for use which provide additional information regarding the intended regions analyzed by the Viz LVO device.
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Image /page/4/Picture/0 description: The image shows a blue logo that resembles a stylized letter 'V'. The logo is composed of several horizontal curved lines that create the shape of the 'V'. The top part of the 'V' is formed by two angled lines, and the lower part is formed by curved lines that get progressively shorter towards the bottom.
Intended Use / Indications for Use
Viz LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of care workflow.
Viz LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a prespecified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting, and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends review of those images can be previewed through a mobile application. Viz LVO is intended to analyze terminal ICA and MCA-M1 vessels for LVOs.
Images that are previewed through 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. Viz LVO is limited to analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis.
Device Description
Viz LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to analyze images for findings suggestive of a suspected large vessel occlusion and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Viz LVO was previously granted a de-novo as ContaCT (DEN170073); following the granting of the denovo the device name was changed to Viz LVO.
Viz LVO is a combination of software modules that allow for detection and notification of patients with a suspected large vessel occlusion. Viz LVO consists of an algorithm and mobile application software module.
The Viz LVO Image Analysis Algorithm (LVO Detection Algorithm) is a locked, artificial intelligence machine learning (AI/ML) software algorithm that analyzes CTA images of the head for a suspected large vessel occlusion (LVO). The LVO Detection Algorithm is hosted on Viz.ai's Backend Server and analyzes applicable stroke-protocoled CTA images of the head that are acquired on CT scanners and are forwarded to Viz.ai's Backend Server. Upon detection of a suspected LVO, the LVO Detection Algorithm sends a notification of the suspected finding.
The Viz LVO Mobile Notification Software is a software module that enables the end user to receive and toggle notifications for suspected large vessel occlusions identified by the LVO Detection Algorithm. The LVO Mobile Notification Software module is implemented into Viz.ai's generic nondiagnostic DICOM image viewer, Viz VIEW (formerly referred to as the Imaging Viewing Software in
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Image /page/5/Picture/0 description: The image shows a blue logo with a stylized "V" shape. The "V" is formed by several horizontal lines and curved segments. The top part of the "V" is created by two separate, angled shapes, while the lower part consists of three curved lines that get progressively smaller towards the bottom. The overall design is simple and modern.
the previous submission, DEN170073), which displays CT scans that are sent to Viz.ai's Backend Server. When the Viz LVO Mobile Notification Software module is enabled for a user, the user can receive and toggle the notifications for patients with a suspected LVO, view a unique list of patients with a suspected LVO (as determined by the LVO Detection Algorithm), and view the non-diagnostic CT scan of the patient through the Viz VIEW mobile application. Image viewing through the mobile application interface is for informational purposes only and is not for diagnostic use.
Technological Characteristics
Both the subject and predicate device use the same artificial intelligence, machine learning (A//ML) software algorithm to identify suspected large vessel occlusions (LVOs) on stroke-protocoled CTA imaging of head in the same regions of the large vessels. Additionally, the software algorithm for the subject device is hosted on the same architecture, automatically receives imaging in the same DICOM format, and uses the same mechanisms to identify applicable imaging for analysis as the predicate device. The outputs of the subject and predicate device are the same, i.e., both devices identify suspected large vessel occlusions (LVOs) and both devices send notifications for suspected LVO findings from the same server.
Both the subject and predicate device include the same mobile software functions and outputs which are presented through the same mobile application. The user can receive and toggle the notifications for patients with a suspected LVO, view a unique list of patients with a suspected LVO (as determined by the LVO Detection Alqorithm), and view the non-diagnostic CT scan of the patient through the Viz VIEW mobile application. In addition, imaging viewing of CTA scans analyzed by the subject and predicate device are subject to the same limitations, that is they are limited to informational purposes (for prioritization review only) and are not for diagnostic use.
Where the subject and predicate device differ is that the subject device includes additional information which are embedded into the mobile application interface that inform the user of the limitations of the Viz LVO algorithm. These additional mechanisms implemented in the mobile application to communicate limitations of the subject device are not incorporated into the mobile application interface for the predicate device. Providing additional mechanisms through the user interface to inform the device user of the limitations of the subject device through the user interface provide additional means of promoting information for transparency regarding the limitations of the device. Furthermore, these same limitations are applicable to the predicate device. Supportive software testing demonstrated that the additional information is displayed through the mobile application interface as expected. Thus, the additional information provided through the user interface for the user does not raise any new or different questions of safety or efficacy.
Performance Data and Software Testing
Performance data was not included as part of the premarket notification. Supporting software verification and validation (V&V) testing were provided to demonstrate implementation of the device changes.
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Image /page/6/Picture/0 description: The image shows a stylized blue logo. The logo is composed of several curved and straight lines that form a V-like shape. The lines are arranged in a way that suggests a sense of movement or flight. The logo is simple, modern, and visually appealing.
Substantial Equivalence
The Viz LVO device has the same intended use, and has very similar indications, technological characteristics, and principles of operation as its predicate. Although there are minor differences between Viz LVO and the predicate device indications and the presentation of device limitations and device information available through the mobile application interface, those differences do not raise new questions of safety or efficacy. Thus, the Viz LVO device is substantially equivalent.
| Subject Device | Predicate Device | |
|---|---|---|
| Viz LVO | ContaCT | |
| Application No. | KXXXXXX | DEN170073 |
| Product Code | QAS | QAS |
| Regulation No. | 21 C.F.R. § 892.2080 | 21 C.F.R. § 892.2080 |
| Intended Use / | ||
| Indications for Use | Viz LVO is a notification-only, parallel workflow | |
| tool for use by hospital networks and trained | ||
| clinicians to identify and communicate images of | ||
| specific patients to a specialist, independent of | ||
| standard of care workflow. |
Viz LVO uses an artificial intelligence algorithm to
analyze images for findings suggestive of a pre-
specified clinical condition and to notify an
appropriate medical specialist of these findings in
parallel to standard of care image interpretation.
Identification of suspected findings is not for
diagnostic use beyond notification. Specifically,
the device analyzes CT angiogram images of the
brain acquired in the acute setting, and sends
notifications to a neurovascular specialist that a
suspected large vessel occlusion has been
identified and recommends review of those
images. Images can be previewed through a
mobile application. Viz LVO is intended to analyze
terminal ICA and MCA-M1 vessels for LVOs.
Images that are previewed through 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.
Viz LVO is limited to analysis of imaging data and
should not be used in-lieu of full patient evaluation
or relied upon to make or confirm diagnosis. | ContaCT is a notification-only, parallel workflow
tool for use by hospital networks and trained
clinicians to identify and communicate images of
specific patients to a specialist, independent of
standard of care workflow.
ContaCT uses an artificial intelligence algorithm
to analyze images for findings suggestive of a
pre-specified clinical condition and to notify an
appropriate medical specialist of these findings in
parallel to standard of care image interpretation.
Identification of suspected findings is not for
diagnostic use beyond notification. Specifically,
the device analyzes CT angiogram images of the
brain acquired in the acute setting, and sends
notifications to a neurovascular specialist that a
suspected large vessel occlusion has been
identified and recommends review of those
images. Images can be previewed through a
mobile application.
Images that are previewed through 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. ContaCT is limited to analysis of
imaging data and should not be used in-lieu of
full patient evaluation or relied upon to make or
confirm diagnosis. |
| Anatomical
Region | Head | Head |
Table 1: Substantial Equivalence Table Comparing Subject and Predicate Devices
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| Subject Device | Predicate Device | |
|---|---|---|
| Diagnostic | ||
| Application | Notification-only | Notification-only |
| Notification/ | ||
| Prioritization | Yes | Yes |
| Intended User | Neurovascular Specialist | Neurovascular Specialist |
| DICOM | ||
| Compatible | Yes | Yes |
| Data Acquisition | Acquires medical image data from DICOM | |
| compliant imaging devices and modalities. | Acquires medical image data from DICOM | |
| compliant imaging devices and modalities. | ||
| Supported | ||
| Imaging Modality | Computed Tomography Angiography (CTA) | Computed Tomography Angiography (CTA) |
| Alteration of | ||
| Original Image | No | No |
| Results of Image | ||
| Analysis | Internal, no image marking | Internal, no image marking |
| Preview Images | Initial assessment; non-diagnostic purposes | Initial assessment; non-diagnostic purposes |
| View DICOM Data | DICOM Information about the patient, study and | |
| current image. | DICOM Information about the patient, study and | |
| current image. |