The Infrascanner is indicated for the detection of traumatic supratentorial hematomas of greater than 3.5 mL in volume that are less than 2.5 cm from the brain surface, as an adjunctive device to the clinical evaluation in the acute hospital setting of patients 18 years old or greater with suspected traumatic supratentorial hematoma. The device is indicated to assess patients for CT scans but should not serve as a substitute for these scans. The Infrascanner is indicated for use by Physicians, or under the direction of a physician, who has been trained in the use of the device.
Device Story
Infrascanner Model 2500 is a noninvasive near-infrared spectroscopy (NIRS) device for detecting traumatic supratentorial intracranial hematomas. It measures regional differences in intracranial hemoglobin absorbance; hematomas exhibit different hemoglobin concentrations compared to normal brain tissue. The device uses a sensor with two light guides placed on the patient's head; it performs an examination in approximately two minutes. Operated by physicians or trained personnel in acute hospital settings, the device provides output to assist in assessing the need for CT scans. It does not replace CT imaging. The device features a miniaturized design, microcontroller unit (MCU), and updated software to guide users and improve measurement accuracy on varying skin tones. Benefits include rapid, point-of-care assessment for head trauma patients.
Clinical Evidence
No clinical data provided. Bench testing only. Performance evaluated using a multi-layered solid and liquid optical phantom mimicking human tissue (intralipid for scattering, ink for absorption, ovine blood for hematoma). Testing assessed repeatability, reproducibility, and agreement across hematoma sizes (5 mL, 50 mL) and depths (0-3 cm). Skin color effects were evaluated using neutral density filters to simulate optical density (OD) ranges for light and dark skin. Results confirmed substantial equivalence to the predicate.
Technological Characteristics
Noninvasive NIRS device. Uses near-infrared light to measure hemoglobin absorbance. Components: Class I NIR-based sensor, two disposable light guides, MCU-based processing. Connectivity: USB charger. Software: Embedded, includes tutorial and secure boot. Materials: Silicon (phantom), carbon black, titanium dioxide. Dimensions: Miniaturized housing compared to predicate. Sterilization: Not specified.
Indications for Use
Indicated for detection of traumatic supratentorial hematomas >3.5 mL and <2.5 cm from brain surface in patients ≥18 years old with suspected hematoma in acute hospital settings. Adjunctive to clinical evaluation; not a substitute for CT scans. Contraindications not specified.
Regulatory Classification
Identification
A Near Infrared (NIR) Brain Hematoma Detector is a noninvasive device that employs near-infrared spectroscopy that is intended to be used to evaluate suspected brain hematomas.
Special Controls
In addition to the general controls of the Act, the Infrascanner is subject to the following special controls:
*Classification.* Class II (special controls). The special controls for this device are:(1) The sale, distribution, and use of this device are restricted to prescription use in accordance with § 801.109 of this chapter;
(2) The labeling must include specific instructions and the clinical training needed for the safe use of this device;
(3) Appropriate analysis/testing should validate electromagnetic compatibility (EMC), electrical safety, and battery characteristics;
(4) Performance data should validate accuracy and precision and safety features;
(5) Any elements of the device that may contact the patient should be demonstrated to be biocompatible; and,
(6) Appropriate software verification, validation, and hazard analysis should be performed.
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InfraScan, Inc. % Angela Mallery Principal Product Development Strategist NAMSA 400 US-169 Minneapolis, Minnesota 55441
Re: K200203
Trade/Device Name: Infrascanner Model 2500 Regulation Number: 21 CFR 882.1935 Regulation Name: Near Infrared (NIR) Brain Hematoma Detector Regulatory Class: Class II Product Code: OPT Dated: June 11, 2020 Received: June 12, 2020
Dear Angela Mallery:
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
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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 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,
Jay Gupta Assistant Director DHT5A: Division of Neurosurgical, Neurointerventional and Neurodiagnostic Devices OHT5: Office of Neurological and Physical Medicine Devices 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) K200203
Device Name Infrascanner Model 2500
### Indications for Use (Describe)
The Infrascanner is indicated for the detection of traumatic supratentorial hematomas of greater than 3.5 mL in volume that are less than 2.5 cm from the brain surface, as an adjunctive device to the clinical evaluation in the acute hospital setting of patients 18 years old or greater with suspected traumatic supratentorial hematoma. The device is indicated to assess patients for CT scans but should not serve as a substitute for these scans. The Infrascanner is indicated for use by Physicians, or under the direction of a physician, who has been trained in the use of the device.
Type of Use (Select one or both, as applicable):
| <span style="font-family: Arial, sans-serif;">☑</span> Prescription Use (Part 21 CFR 801 Subpart D) |
|-----------------------------------------------------------------------------------------------------|
| ☐ Over-The-Counter Use (21 CFR 801 Subpart C) |
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# 510(k) SUMMARY K200203
July 8, 2020
| Submitter's Name, Address, Telephone<br>Number, Contact Person and Date<br>Prepared | InfraScan, Inc. 3508 Market Street<br>Philadelphia, PA 19104<br>Phone: 215-387-6784<br>Facsimile: 215-386-2327<br>Contact Person: Baruch Ben Dor, CEO |
|-------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Name of Device and Name/Address of<br>Sponsor | Infrascanner Model 2500<br>InfraScan, Inc.<br>3508 Market Street<br>Philadelphia, PA 19104 |
| Common or Usual Name | Near Infrared (NIR) Brain Hematoma Detector |
| Classification Name | OPT (21 C.F.R. §882.1935) |
| Predicate Devices | InfraScan Infrascanner Model 2000 (K120949) |
| Indications for Use | The Infrascanner is indicated for the detection of traumatic supratentorial<br>hematomas of greater than 3.5 mL in volume that are less than 2.5 cm from the<br>brain surface, as an adjunctive device to the clinical evaluation in the acute<br>hospital setting of patients 18 years old or greater with suspected traumatic<br>supratentorial intracranial hematoma. The device is indicated to assess patients for<br>CT scans but should not serve as a substitute for these scans. The Infrascanner is<br>indicated for useby Physicians, or under the direction of a physician, who has<br>been trained in the use of the device |
#### Technological Characteristics
The device is a noninvasive device, which uses near-infrared spectroscopy ("NRS") to provide early information about the possible development of traumatic supratentorial intracranial hematomas in patients presenting to hospitals with head trauma. This technology in volves comparing regional differences in absorbance of NIRS to hematoma evaluation is based on the principle that intracranial hemoglobin concentration will differ where a hematoma is present, compared to hemoglobin concentrations in normal intracranialregions. The systemconsists of a Class I NIR-based sensor is optically coupled to the patient's head through two disposable light guides in a "hairbrush" configuration. Examination with the Infrascanner is performed through placement of the sensor on designated areas of the head thatrepresent the most common locations for traumatic hematoma. The examination is designed to be performed within two minutes.
Specifically, Model 2500 is the same device as the Infrascanner Model 2000 with following two categories of modifications:
- Scanner miniaturization ●
- . Systemenhancements
| Summary of the technological characteristics of the new device in comparison to those of the predicate device | | | | | | | | | | | | | |
|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--|--|--|--|--|--|--|--|--|--|--|
| | Itemized description | Reason for change | | | | | | | | | | | |
| 1. | Improved battery charging | To improve charging of depleted rechargeable batteries | | | | | | | | | | | |
| 2. | Update Battery icon | The NiMH battery's charge cycle shifts over time | | | | | | | | | | | |
| 3. | Add Tutorial Software | To add on-screen instructions to guide the user when making scans | | | | | | | | | | | |
| 4. | Modify Timing and Length | To reduce error and repeated measurements -. Increasing the number of pulses and timing reduces the number of errors and the need to make repeated measurements on dark skin and dark hair. | | | | | | | | | | | |
| | | Predicate Current Device Laser Pulses 6 pulses 10 pulses Laser Timing 100 msec On / 200 msec off 200 msec On / 100 msec off | | | | | | | | | | | |
| 5. | Add feedback LED indicator | To provide feedback to the user when measurements are active and when they are completed. | | | | | | | | | | | |
| 6. | Reduced size of device with a smaller display on the front of the unit, removal of single board computer, and design of housing and shield. | To make the device smaller. The scanner miniaturization involved arranging of components inside the scanner.<br>Electronic circuit size was reduced by implementing some of the analog circuits in digital.<br>The Windows CE 6.0 single board computer was replaced by a small microcontroller unit (MCU). | | | | | | | | | | | |
| 7. | Incremental upgrades to the device. | Upgraded measurement buttons to rubber sealed switches.<br>Upgraded to permanent internal rechargeable battery and addition of snap retention.<br>Upgrade to USB charger. | | | | | | | | | | | |
| 8. | Changed laser drive signal from pulsed square wave to sinusoid and digital lock-in amplifier | To reduce space, power and improve accuracy; higher sample rate | | | | | | | | | | | |
| 9. | Upgrade to software | Addition of secure boot, updated architecture, upgraded screen graphics | | | | | | | | | | | |
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## Performance Data
Bench testing demonstrated that device functioned. Testing comparing to the predicate was conducted using a hematoma model to provide an approximation of human tissue. Testing included repeatability and reproducibility. Results were consistent with the expected result. Performance was substantially similar for both models across a range of depths and sizes of hematomas, and for skin types. Additional laboratory testing demonstrated the comparability of the device and its predicate over the range of optical densities.
Four types of tests were conducted in order to evaluate substantial equivalence between Infrascanner Model 2500.
- Repeatability / Reproducibility to assess the degree of agreements conducted on the same device. The repeatability and reproducibility test data in volved repeat observations with three different systems for each of the two models. Model hematomas of 5 mL and 50 mL were evaluated at depths of shallow and deep ranges at 0 cm, and 3 cm
- A greement test to assess the degree of agreement between measurements conducted by Model 2000. The agreement test data were collected for one systemof each model for hematomas of size 5 mL and 50 mL and depths of 0-3cm below the CSF.
- Skin color test to assess theeffect of the skin color on the measurements conducted by Model 2000. The ● evaluation of the potential impact of skin color was performed for both models with hematoma size of 5 mL at depths of 0 and 2 cm, and without a model hematoma in the tank. The thickness of the film filters (0.1 mm) is similar to the thickness of human skin. Neutral Density Filters were used in to reduce light transmission similar to the behavior of skin color differences. Us ing those filters the OD values in the new lab tests covered the range of 5-5.8 OD to simulate lightskinned patients and 6.3-7.1 OD to simulate dark skinned subjects.
The test data sets support the conclusion that the models 2500 and 2000 are substantially equivalent across a range of simulated hematoma sizes, depths, and for light and dark skin and for adult and infant age groups.
A 4-comers approach was used for the selection and testing of the simulated hematoma size and depth and for the simulated adult age group
- Small (5 ml) and large (50 ml) hematomas
- Superficial (0 cm) and deep (2 and 3cm) hematomas
- . Adult (>18 years old) ages were tested
A mixed multi-layered solid and liquid optical head phantommimicking human tissue was used in the test. For brain tissue optical parameters simulation of an intralipid was used to control the scattering properties and a calibrated ink to control absorption properties. Including the layers of skin, scalp, skull and CSF with the liquid brain layer and blood to simulate brain hematoma.
Silicon was selected for building the phantomdue to a close match to the mechanical properties of tissue. Carbon black was used as the absorbing agent, and Titanium Dioxide was used as the scattering agent. The optical absorption and scattering properties of each layer were confirmed further by optical frequency-domain measurement systems. The CSF layer were those of water. Thin neutral density (ND) Wratten 2 film filters were placed over the signal level to OD values observed in the clinical studies for patients with differents kin color. The thickness of the thickness of human skin. Using those filters, the OD values in the new lab tests covered the range of OD to simulate light-s kinned patients and OD to simulate dark skinned subjects. The attenuation values of the filters were selected to match the OD values observed in the clinical studies. The brain model was filled with water, intralipid for scattering and a black ink for absorption. This mixture created a simulation of brain tissue. Our approachis to use ovine whole blood as a hematoma. Following prior FDA guidance, a flat hematoma model was used in this test. The flat hematoma model was built using a rectangular frame, inserted into a ball, and filled with blood. The rectangular frame forced the shape of the hematoma to remain relatively flat.
# Substantial Equivalence
The subject device is as safe andeffective as the predicate device has the same indication for use, technological characteristics, and principles of operation as its predicate device.
The enhancements (such as size of the physical device, the type of charging station) of the Model 2500 raise no new issues of safety or effectiveness. Bench data demonstrate the substantially equivalent to the predicate.
### Conclusion
Based on the intended use, technological characteristics, comparison to the predicate device and performance testing, the modified device is substantally equivalent to the predicate device and raises no additional or different questions of safety or effectiveness
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.