The Quicktome Software Suite is composed of a set of modules intended for display of medical images and other healthcare data. It includes functions for image review, image manipulation, basic measurements, planning, 3D visualization (MPR reconstructions and 3D volume rendering) and display of BOLD (blood oxygen level dependent) resting-state MRI scan studies. Modules are available for image processing, atlas-assisted visualization, resting state analysis and visualization, and target export creation, where an output can be generated for use by a system capable of reading DICOM image sets. Quicktome is indicated for use in the processing of diffusion-weighted MRI sequences into 3D maps that represent whitematter tracts based on constrained spherical deconvolution methods and for the use of said maps to select and create exports. Quicktome can generate motor, language, and vision resting state fMRI correlation maps using task-analogous seeds. Typical users of Quicktome are medical professionals, including but not limited to surgeons, clinicians, and radiologists.
Device Story
Quicktome is a cloud-deployed software suite for neurological image processing and planning. It imports DICOM MRI datasets (DWI, T1, T2, BOLD, FLAIR) from PACS; removes PHI; and links data to encryption keys. Clinicians use the software to validate image quality, explore anatomical regions/network templates, and select regions of interest. The device processes diffusion-weighted sequences into 3D white-matter tract maps via constrained spherical deconvolution and generates resting-state fMRI correlation maps for motor, language, and vision networks. Outputs are exported as DICOM images for viewing in hospital PACS or other compatible systems. By providing 3D visualization of white-matter tracts and functional brain networks, the device assists surgeons and clinicians in presurgical planning and post-surgical assessment, potentially improving clinical decision-making and surgical outcomes.
Clinical Evidence
No clinical trials; evidence based on software verification and validation. Performance evaluations of the BOLD processing pipeline included motion/noise correction, skull stripping, co-registration, and correlation matrix computation. Validation compared resting-state fMRI correlation maps to task-based fMRI activation maps. Analytical evaluation showed task-based activation fell within the bounds of resting-state correlation maps. Expert clinician evaluation rated the networks as comparable to task-based fMRI for presurgical planning and post-surgical assessment.
Technological Characteristics
Cloud-deployed software-only package. Operates on off-the-shelf hardware. Complies with IEC 62304, IEC 62366, ISO 14971, and NEMA PS 3.1-3.20. Features include DICOM image viewing, processing, and analysis; constrained spherical deconvolution for tractography; and resting-state fMRI correlation mapping.
Indications for Use
Indicated for medical professionals (surgeons, clinicians, radiologists) to process diffusion-weighted MRI sequences into 3D white-matter tract maps using constrained spherical deconvolution and to generate motor, language, and vision resting-state fMRI correlation maps using task-analogous seeds for surgical planning and assessment.
Regulatory Classification
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.
Special Controls
*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).
Predicate Devices
StealthViz Advanced Planning Application with StealthDTI Package (K081512)
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May 30, 2023
Omniscient Neurotechnology Pty Ltd (08t) % Jennifer Dixon NASA Lead, QA/RA Level 10, 580 George Street Sydney, NSW 2000 AUSTRALIA
Re: K222359
Trade/Device Name: Quicktome Software Suite Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: May 12, 2023 Received: May 15, 2023
Dear Jennifer Dixon:
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
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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 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 (OS) 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 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,
Daniel M. Krainak, Ph.D. Assistant Director Magnetic Resonance and Nuclear Medicine Team DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: 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) K222359
Device Name Quicktome Software Suite
### Indications for Use (Describe)
The Quicktome Software Suite is composed of a set of modules intended for display of medical images and other healthcare data. It includes functions for image review, image manipulation, basic measurements, planning, 3D visualization (MPR reconstructions and 3D volume rendering) and display of BOLD (blood oxygen level dependent) resting-state MRI scan studies.
Modules are available for image processing, atlas-assisted visualization, resting state analysis and visualization, and target export creation, where an output can be generated for use by a system capable of reading DICOM image sets.
Quicktome is indicated for use in the processing of diffusion-weighted MRI sequences into 3D maps that represent whitematter tracts based on constrained spherical deconvolution methods and for the use of said maps to select and create exports. Quicktome can generate motor, language, and vision resting state fMRI correlation maps using task-analogous seeds.
Typical users of Quicktome are medical professionals, including but not limited to surgeons, clinicians, and radiologists.
| Type of Use (Select one or both, as applicable) | |
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Image /page/3/Picture/0 description: The image is a logo for Omniscient Neurotechnology. The logo features the letters "ost" in a stylized font, with the "o" in blue and the "t" in red. To the right of the letters is the company name, "OMNISCIENT NEUROTECHNOLOGY," in a smaller, sans-serif font. The word "OMNISCIENT" is in a bolder font than "NEUROTECHNOLOGY."
# 5.0 510(k) Summary
#### 5.1 Submitter
Omniscient Neurotechnology Pty Ltd (08t) Level 10, 580 George Street Sydney, NSW 2000 Australia
Contact Person: Jennifer Dixon
Date Prepared: May 24th, 2023
#### 5.2 Device
| Name of Device: | Quicktome Software Suite |
|-----------------------|---------------------------------------------------------------------|
| Common or Usual Name: | Neurological Planning and Visualization Software |
| Classification: | Medical image management and processing system<br>(21 CFR 892.2050) |
| Regulatory Class: | Class II |
| Product Code: | LLZ |
#### 5.3 Predicate Device
StealthViz Advanced Planning Application with StealthDTI Package, K081512
This Predicate has not been subject to a design-related recall.
Reference Devices: Quicktome, K203518; Brainlab iPlan Cranial, K113732
#### 5.4 Device Description
Quicktome is a software-only, cloud-deployed, image processing package which can be used to perform DICOM image viewing, image processing, and analysis.
Quicktome can receive ("import") DICOM images from picture archiving and communication systems (PACS), acquired with MRI, including Diffusion Weighted Imaging (DWI) sequences, T1, T2, BOLD, and FLAIR images. Quicktome can also receive Resting State functional MRI (rs-fMRI) blood-oxygen-level-dependent (BOLD) datasets. Once received, Quicktome removes protected health information (PHI) and links the dataset to an encryption key, which is then used to relink the data back to the patient when the data is exported to hospital PACS or other DICOM device.
The software provides a workflow for a clinician to:
- . Select an image for planning and visualization,
- Validate image quality,
- Explore the available anatomical regions, network templates, tractography bundles, and ● parcellations,
- . Select regions of interest,
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Image /page/4/Picture/0 description: The image shows the logo for Omniscient Neurotechnology. The logo features the letters "ost" in a stylized font, with the "o" being a circle that is half blue and half orange. To the right of the letters is the company name, "OMNISCIENT" in all caps, with the word "NEUROTECHNOLOGY" underneath in a smaller font.
- . Display resting state fMRI (BOLD) correlation maps using task-analogous seeds for Motor, Vision and Language networks, and
- . Export black and white and color DICOMs for use in systems that can view DICOM images.
#### 5.5 Indications for Use
The Quicktome Software Suite is composed of a set of modules intended for display of medical images and other healthcare data. It includes functions for image manipulation. basic measurements, planning, 3D visualization (MPR reconstructions and 3D volume rendering), and display of BOLD (blood oxygen level dependent) resting-state MRI scan studies.
Modules are available for image processing, atlas-assisted visualization and segmentation, , resting state analysis and visualization, and target export creation and selection, where an output can be generated for use by a system capable of reading DICOM image sets.
Quicktome is indicated for use in the processing of diffusion-weighted MRI sequences into 3D maps that represent white-matter tracts based on constrained spherical deconvolution methods and for the use of said maps to select and create exports. Quicktome can generate motor, language, and vision resting state fMRI correlation maps using task-analogous seeds.
Typical users of Quicktome are medical professionals, including but not limited to surgeons, clinicians and radiologists.
#### 5.6 Comparison of Technological Characteristics with the Predicate Device
The Quicktome Software Suite is an updated version of a device which has previously been cleared (K203518).
In terms of core functionality, technology, and performance, both Subject and Predicate:
- . Allow import and export of DICOM images to a hospital PACS.
- Contain a graphical user interface to conduct planning and visualization. ●
- . Display MRI anatomical images, as well as tractography constructed from Diffusion Weighted Images, in 2D and 3D views.
- . Register tractography and an atlas to the underlying anatomical images.
- . Allow adding, removing, and editing of objects (including automatically segmented and manually defined regions of interest).
- . Are delivered as software on an off-the-shelf hardware platform.
The above technological characteristics were established in K203518 as equivalent to the predicate device. Said characteristics are unchanged in the Subject device.
The following has been included in this submission:
- . BOLD (Blood-oxygen-level-dependent imaging) signal processing: StealthViz processes task-based fMRI data which allows the user to prepare task-activated maps, whereas the Quicktome Software Suite allows the user to prepare task-analogous (for vision, motor and language tasks) correlation maps using resting-state fMRI data.
This difference was verified and validated and did not lead to any additional questions of safety or effectiveness. Comparison to the predicate device in conjunction with design verification and
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Image /page/5/Picture/0 description: The image shows the logo for Omniscient Neurotechnology. The logo consists of the letters "o&t" in a stylized font, with the "o" in blue and the "t" in red. To the right of the letters is the company name, "OMNISCIENT NEUROTECHNOLOGY", in a smaller, sans-serif font. The word "OMNISCIENT" is in a larger font than "NEUROTECHNOLOGY".
validation activities described in this 510(k) submission support substantial equivalence of Quicktome.
#### 5.7 Performance Data
Software verification and validation testing were conducted and documentation was provided as recommended by the Guidance for Industry and FDA Staff Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices (May 11, 2005).
The software was developed in compliance with the requirements of IEC 62304, IEC 62366, ISO 14971, and NEMA PS 3.1-3.20.
All verification and validation activities required per the verification and validation plan were performed using cloud-based deployment of the software in production-equivalent state.
## Software Verification
- . Testing was conducted on software units and modules. System verification was performed to confirm implementation of functional requirements.
- . Cloud infrastructure verification was performed to ensure suitability of cloud components and services.
- . Algorithm performance verification was conducted to ensure computations were sound.
## Software Validation
- . Summative usability evaluation and design validation were performed by representative users.
- . Performance evaluations were conducted for the BOLD processing pipeline. Evaluations included protocols for motion and noise correction, skull stripping, co-registration of anatomical scans and BOLD series, physiological noise correction, and correlation matrix computation.
- . The resting-state fMRI correlation maps generated by Quicktome were compared to taskbased fMRI activation maps for a range of pre-specified seeds using analytical and expert clinician evaluation.
- o Analytical evaluation demonstrated that activation in a task-based activation map is represented within the bounds of a correlation map generated with restingstate data when using a range of pre-specified seeds and thresholds, supporting substantial equivalence of the two maps.
- Clinicians rated the networks as comparable per the pre-specified acceptance o criteria to task-based fMRI maps for the clinical intended uses of presurgical planning and post-surgical assessment.
#### 5.8 Conclusion
The design verifications conducted support the conclusion that Quicktome performs as intended in the specified use conditions. Quicktome performs in a way that does not raise new questions of safety and effectiveness when compared to currently marketed devices.
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.