ProKnow DS is a patient data archive, information management, and analytics software system with a focus on the data and images specific to radiation oncology patients. Users may upload digital patient data created by other devices to ProKnow DS to securely archive, display, and analyze the data. Users can view and navigate patient images, drawn anatomy, calculated dose, and plan details derived from the source files. Users can create or edit anatomy structures to be used either prospectively (e.g., as an input to treatment planning) or retrospectively (e.g., for data analysis, research, and outcomes studies). Users can extract metrics for any single patient, or across a collection of patients, then view results as tables or graphically. ProKnow DS is to be used as an accessory system to perform data archive, review, and is not to be used for diagnosis, treatment, or as the sole form of plan approval. Users of ProKnow DS should be trained medical professionals including, but not limited to, radiologists, oncologists, physicians, medical technologists, dosimetrists, and physicians. Users should be familiar with the different sources of input data (such as images, structure sets, treatment plans, and calculated dose) as well as how to understand and interpret derived metrics (e.g., dose-volume histograms).
Device Story
ProKnow DS is a cloud-based RT-PACS; archives/manages radiation oncology data. Inputs: DICOM/DICOM RT files (images, structure sets, treatment plans, dose grids) from external imaging/planning systems. Operation: cloud-hosted platform; users upload data for secure storage, visualization, and analysis. Features: interactive viewer for images/dose/DVHs; manual/auto-contouring tools for structure editing; cohort analysis tools for population-based metrics. Output: tabulated results, graphical plots (histograms/scatterplots), and exported DICOM RT structure sets. Usage: clinical/research settings by trained professionals (oncologists, dosimetrists). Benefit: facilitates standardized plan evaluation, peer review, and retrospective outcomes research.
Clinical Evidence
Bench testing only. Verification included unit and end-to-end tests using automated/manual methods and gold-standard datasets. Validation performed by clinical experts in simulated environments and by hospital/vendor partners using representative clinical data. Results confirmed functional specifications, usability, and accuracy of data storage/display.
Technological Characteristics
Cloud-based software system. Connectivity: networked/cloud. Data format: DICOM/DICOM RT. Functionality: image/dose visualization, contouring, metric extraction, cohort analysis. Cybersecurity: cloud-specific controls implemented. No physical materials or energy sources.
Indications for Use
Indicated for radiation oncology patients. Intended for use by trained medical professionals (radiologists, oncologists, physicians, medical technologists, dosimetrists) to archive, display, analyze, and edit patient data (images, anatomy, dose, plans). Not for diagnosis, treatment, or sole plan approval.
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).
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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 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.
January 2, 2019
ProKnow LLC Mr. Salvadore Gerace Chief Technology Officer 121 Central Park Place SANFORD, FL 32771 US
Re: K182855
Trade/Device Name: ProKnow DS Regulation Number: 21 CFR 892.2050 Regulation Name: Picture Archiving And Communications System Regulatory Class: Class II Product Code: LLZ Dated: October 8, 2018 Received: October 10, 2018
Dear Mr. Gerace:
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
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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/CombinationProducts/GuidanceRegulatoryInformation/ucm597488.htm); 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 http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/) and CDRH Learn (http://www.fda.gov/Training/CDRHLearn). 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 (http://www.fda.gov/DICE) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Michael D.'Hara For
Robert A. Ochs. Ph.D. Director Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known) K182855
Device Name ProKnow DS
#### Indications for Use (Describe)
ProKnow DS is a patient data archive, information management, and analytics software system with a focus on the data and images specific to radiation oncology patients. Users may upload digital patient data created by other devices to ProKnow DS to securely archive, display, and analyze the data. Users can view and navigate patient images, drawn anatomy, calculated dose, and plan details derived from the source files. Users can create or edit anatomy structures to be used either prospectively (e.g., as an input to treatment planning) or retrospectively (e.g., for data analysis, research, and outcomes studies). Users can extract metrics for any single patient, or across a collection of patients, then view results as tables or graphically. ProKnow DS is to be used as an accessory system to perform data archive, review, and is not to be used for diagnosis, treatment, or as the sole form of plan approval.
Users of ProKnow DS should be trained medical professionals including, but not limited to, radiologists, oncologists, physicians, medical technologists, dosimetrists, and physicians. Users should be familiar with the different sources of input data (such as images, structure sets, treatment plans, and calculated dose) as well as how to understand and interpret derived metrics (e.g., dose-volume histograms).
| Type of Use (Select one or both, as applicable) | |
|------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|
| <span style="font-size:10px;"> <input checked="true" type="checkbox"/> Prescription Use (Part 21 CFR 801 Subpart D) </span> | <span style="font-size:10px;"> <input type="checkbox"/> Over-The-Counter Use (21 CFR 801 Subpart C) </span> |
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# PREMARKET NOTIFICATION [510(k)] SUMMARY
(Provided in conformance with 21 CFR 807.92)
#### Submitter
ProKnow, LLC 121 Central Park Place Sanford, FL 32771
| Phone: | 844-405-2170 |
|------------------------|----------------------------------------------|
| Fax: | 407-322-7546 |
| Contact Person: | Salvadore Gerace<br>Chief Technology Officer |
| Date Summary Prepared: | October 5, 2018 |
### Device Name and Classification
| Trade Name: | ProKnow DS |
|----------------------|---------------------------------------------------------------------------|
| Common/Usual Name: | Picture Archiving and Communications System<br>(Medical Imaging Software) |
| Classification Name: | System, Imaging Processing, Radiological |
| Regulation Number: | 21 CFR 892.2050 |
| Product Code: | LLZ |
| Regulatory Class: | Class II |
#### Predicate Devices
| K173636 | Velocity | Varian Medical Systems, Inc. |
|---------|------------|------------------------------|
| K101707 | fullAccess | Fulcrum Medical, Inc. |
| K071964 | MIM 4.1 | MIM Software, Inc. |
#### Device Description
ProKnow DS is a Radiation Therapy Picture/Patient Archiving and Communication System (RT-PACS). It allows users to archive, inspect, analyze, and interact with radiation therapy patient data for both retrospective and prospective studies. Its features are centered on two primary areas of interaction: (1) single patient datasets and (2) collections of patient datasets, i.e., patient cohorts. Users are able to import patient data from existing imaging, contouring, and treatment planning systems (via DICOM
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formats). Once imported, patient data is archived for long-term storage and is also available for inspection and analysis (examples of supported inspection and analysis tasks include: visualizing images, structures, and dose distributions; inspecting plan information; inspecting dose volume histograms; and extracting metrics). ProKnow DS also allows users to edit anatomical contour data associated with a patient for use in retrospective studies or to be exported to commercially available radiation treatment planning systems. Once a set of patients have been established in ProKnow DS, users may create collections of related patients allowing them to analyze and correlate dosimetric values of interest and clinical endpoints across large treatment populations.
# Intended Use
ProKnow DS provides a scalable and secure data archive for binary digital imaging and communications in medicine (DICOM) data with a focus on radiotherapy (DICOM RT). The input data objects are created by other medical devices and uploaded to ProKnow DS for storage and processing. These input medical devices may include imaging systems, manual and auto-contouring systems, treatment planning systems, and other medical software/devices that output applicable data.
ProKnow DS has an interactive viewer that can be used to display and analyze patient data such as images (e.g., CT and MR), contoured anatomical structures, treatment plan information, calculated radiation dose grids, and dose volume histograms (DVH).
ProKnow DS provides anatomy contouring tools for the purpose of (1) creating new anatomy structure sets (i.e., a set of user-defined anatomy contours) and (2) editing structure sets created by another system and uploaded to ProKnow DS. The users' new or edited structure sets can be downloaded in the industry standard DICOM RT Structure Set format to serve as an input to other software systems.
ProKnow DS allows the user to create lists of user-defined metrics, and optionally per-metric performance objectives, which can be extracted and viewed per patient dataset. Metrics can be of two types: (1) derived/computed, which are metrics extracted from the input DICOM objects or computed DVH data, and (2) custom, which are user-defined text or numeric fields and their user-supplied values. Tabulated results are displayed and can be used to facilitate and standardize tasks such as plan evaluation and peer review.
ProKnow DS allows the user to define and track "collections" of patient datasets (i.e., cohorts) from which metrics from all patients in the collection can be extracted and analyzed as a population using interactive graphical tools such as histograms and scatterplots.
#### Indications for Use
ProKnow DS is a patient data archive, information management, and analytics software system with a focus on the data and images specific to radiation oncology patients. Users may upload digital patient data created by other devices to ProKnow DS to securely archive, display, and analyze the data. Users can view and navigate patient images, drawn anatomy, calculated dose, and plan details derived from
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the source files. Users can create or edit anatomy structures to be used either prospectively (e.g., as an input to treatment planning) or retrospectively (e.g., for data analysis, research, and outcomes studies). Users can extract metrics for any single patient, or across a collection of patients, then view results as tables or graphically. ProKnow DS is to be used as an accessory system to perform data archive, review, and analysis, and is not to be used for diagnosis, treatment, or as the sole form of plan approval.
Users of ProKnow DS should be trained medical professionals including, but not limited to, radiologists, oncologists, physicians, medical technologists, dosimetrists, and physicians. Users should be familiar with the different sources of input data (such as images, structure sets, treatment plans, and calculated dose) as well as how to understand and interpret derived metrics (e.g., dosevolume histograms).
### Summary of Technological Characteristics
ProKnow DS is substantially equivalent to the identified predicate devices in terms of characteristics, materials, and features; it also has similar technological features, intended use, and indications for use and does not pose any new issues for safety and effectiveness. It is worth noting that ProKnow DS is a cloud-based system, and therefore must address additional Cybersecurity requirements and risks as part of the design process (as compared to desktop-based devices). These have been addressed and are documented in Section 16 and have been demonstrated through verification and validation testing to not pose any new issues for safety and effectiveness.
A detailed comparison to the identified predicate devices can be found in Section 12.
# Summary of Non-Clinical Testing
ProKnow has verified and validated that the ProKnow DS software meets its functional specifications and performance requirements. Verification testing was accomplished using a combination of unit and end-to-end tests; both automated and manual. Verification testing utilized published and analytical gold standard datasets wherever possible. Validation testing was performed by a clinical expert in accordance with the intended clinical use in a simulated clinical environment, as well as by hospital-based and 3rd party vendor validation partners. Validation testing utilized a variety of data types and combinations that were judged to be representative of the types of data the software will encounter in clinical use. The verification and validation test results showed that ProKnow DS met all clinical requirements in terms of usability and accuracy of any/all data stored and displayed. In addition, the test results show that the device is at least as safe and effective as the legally marketed predicate devices.
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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.