K241837 · Limbus Ai, Inc. · QKB · Oct 9, 2024 · Radiology
Device Facts
Record ID
K241837
Device Name
Limbus Contour
Applicant
Limbus Ai, Inc.
Product Code
QKB · Radiology
Decision Date
Oct 9, 2024
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.2050
Device Class
Class 2
Attributes
AI/ML, Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K241837 · Oct 9, 2024
Limbus Contour
Limbus Ai, Inc.
Anonymized/pseudo-anonymized patient radiotherapy treatment planning scans; Expert-generated clinical contours; Published clinical literature (Wong et al., 2021)
Retrospective clinical data were used to train and validate machine learning models for automatic contouring. A prospective clinical study was cited to demonstrate the device's performance and clinical utility in routine practice.
Model Training and Validation; Retrospective analysis of clinical radiotherapy treatment planning data
General population of patients receiving radiotherapy treatment; Sample Size: Exceeds 10,000 unique scans; Number of Sites: Multiple international institutions
Dice Similarity Coefficient > reference model's mean minus standard deviation
Mean DSC values provided per structure in performance table
Training and validation scans from anonymized/pseudo-anonymized datasets including public clinical trials and clinical/research partners. >10,000 unique scans.
>1 (in-house clinicians and radiation oncologist)
Benchtop performance testing using randomly selected patient scans not included in training or validation. 10 scans per structure.
>1 (experts at multiple institutions)
Indications for Use
Limbus Contour is a software-only medical device intended for use by trained radiation oncologists, dosimetrists and physicists to derive optimal contours for input to radiation treatment planning. Supported image modalities are Computed Tomography and Magnetic Resonance. The Limbus Contour Software assists in the following scenarios: Operates in conjunction with radiation treatment planning systems or DICOM viewing systems to load, save, and display medical images and contours for treatment evaluation and treatment planning. Creation, transformation, and modification of contours for applications including, but not limited to: transferring contours to radiotherapy treatment planning systems, aiding adaptive therapy and archiving contours for patient follow-up. Localization and definition of healthy anatomical structures. Limbus Contour is not intended for use with digital mammography.
Device Story
Limbus Contour is a standalone software application for automatic segmentation of CT/MRI DICOM images. It uses pre-trained, expert-curated machine learning models to localize and define healthy anatomical structures. The device is operated by radiation oncologists, dosimetrists, and physicists in clinical settings. It does not store or display images; it interfaces with existing radiotherapy treatment planning systems (TPS) or DICOM viewers. Users import DICOM images, and the software exports DICOM RT-Structure sets. The output assists in treatment evaluation, adaptive therapy, and patient follow-up by providing initial contours that require minimal editing, thereby reducing contouring time. The device is a locked algorithm system.
Clinical Evidence
No clinical data. Substantial equivalence is based on bench testing. Performance was validated using an automatic contouring test on controlled datasets of medical scans with manual segmentations. Accuracy was measured using the Sørensen-Dice Similarity Coefficient (DSC). Results for all structures passed, with the lower edge of the 95% confidence interval for DSC exceeding the established reference thresholds derived from published literature.
Technological Characteristics
Software-only device; no physical materials or energy sources. Operates on Windows 10/Server 2016+ with 2GHz+ multicore processor and 16GB RAM (CUDA-capable NVIDIA GPU optional). Connectivity via DICOM 3.0 file system import/export. Algorithm: Locked deep learning model (U-Net/ResUNet architecture) trained via Adam optimization and Sørensen-Dice loss function.
Indications for Use
Indicated for trained radiation oncologists, dosimetrists, and physicists to derive optimal contours for radiation treatment planning using CT or MRI images. Not for use with digital mammography.
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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October 9, 2024
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Limbus AI Inc. Jonathan Giambattista Director - Software 2431 Glamis Place Regina, SK S4N3K9 Canada
Re: K241837
Trade/Device Name: Limbus Contour Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QKB Dated: July 15, 2024 Received: July 15, 2024
Dear Jonathan Giambattista:
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 (that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device"
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(https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about 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-regulatory
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assistance/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,
Locoa Werchner
Lora D. Weidner, Ph.D. Assistant Director Radiation Therapy 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
Submission Number (if known)
K241837
Device Name
Limbus Contour
Indications for Use (Describe)
Limbus Contour is a software-only medical device intended for use by trained radiation oncologists, dosimetrists and physicists to derive optimal contours for input to radiation treatment planning.
Supported image modalities are Computed Tomography and Magnetic Resonance. The Limbus Contour Software assists in the following scenarios:
Operates in conjunction with radiation treatment planning systems or DICOM viewing systems to load, save, and display medical images and contours for treatment evaluation and treatment planning.
Creation, transformation, and modification of contours for applications including, but not limited to: transferring contours to radiotherapy treatment planning systems, aiding adaptive therapy and archiving contours for patient follow-up.
Localization and definition of healthy anatomical structures.
Limbus Contour is not intended for use with digital mammography.
Type of Use (Select one or both, as applicable)
> Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
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# K241837
# 510(k) SUMMARY
This summary of 510(k) safety and effectiveness information is submitted in accordance with the requirements of 21 CFR §807.92:
SUBMITTER -Limbus Al Inc. 2431 Glamis Pl Regina, Saskatchewan, Canada, S4V1A5 Tel: 1-306-502-5982
| Contact Person: | Jon Giambattista |
|-----------------|------------------|
| Date Prepared: | October 9, 2024 |
| II. DEVICE | |
|------------------------------|--------------------------------------|
| Name of Device: | Limbus Contour |
| Classification Name: | Radiological Image Processing System |
| Regulation: | 21 CFR §892.2050 |
| Regulatory Class: | Class II |
| Product Classification Code: | QKB |
III. PREDICATE DEVICE
| Predicate Manufacturer: | Limbus AI, Inc. |
|-------------------------|-----------------|
| Predicate Trade Name: | Limbus Contour |
| Predicate 510(k): | K230575 |
No reference devices were used in this submission.
#### IV. DEVICE DESCRIPTION
Limbus Contour is a stand-alone software medical device. It is a single purposes cross-platform application for automatic contouring (segmentation) of CT/MRI DICOM images via pre-trained and expert curated machine learning models. The software is intended to be used by trained medical professionals to derive contours for input to radiation treatment planning. The Limbus Contour software segments normal tissues using machine learning models and further post-processing on machine learning model prediction outputs. Limbus Contour does not display or store DICOM images and relies on existing radiotherapy treatment planning systems (TPS) and DICOM image viewers for display and modification of generated segmentations. Limbus Contour interfaces with the user's operating system (importing DICOM image .dcm files and exporting segmented DICOM RT-Structure Set .dcm files).
#### V. INDICATIONS FOR USE
Limbus Contour is a software-only medical device intended for use by trained radiation oncologists, dosimetrists and physicists to derive optimal contours for input to radiation treatment planning.
Supported image modalities are Computed Tomography and Magnetic Resonance. The Limbus Contour Software assists in the following scenarios:
- Operates in conjunction with radiation treatment planning systems to load, save, and ● display medical images and contours for treatment evaluation and treatment planning.
- . Creation, transformation, and modification of contours for applications including, but not limited to: transferring contours to radiotherapy treatment planning systems, aiding adaptive therapy and archiving contours for patient follow-up.
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- . Localization and definition of anatomical structures.
Limbus Contour is not intended for use with digital mammography.
#### VI. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE PREDICATE DEVICE
The following characteristics were compared between the subject device and the predicate device in order to demonstrate substantial equivalence:
- Indications for Use The predicate and subject device are identical with the exception . that the predicate has support for MacOS while the subject device does not and the predicate has less structures for automatic contouring available.
- . Materials – The predicate and subject device are software-only devices and do not inherently contain material.
- Design - The predicate and subject device have equivalent designs.
- . Energy Source – The predicate and subject device are software-only devices, powered by the computer system.
- . Performance Testing – The predicate and subject device were both validated using an automatic contouring test to ensure the contours were accurate.
| Item | Limbus Contour v1.8 | Limbus Contour v1.7 - K230575 | Similarities /<br>Differences |
|-----------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|
| Classification<br>Regulation | 892.2050 - Medical image<br>management and processing<br>system | 892.2050 - Medical image<br>management and processing<br>system | Same |
| Product Code | QKB | LLZ | Similar; Both<br>product codes<br>refer to the<br>same CFR<br>892.2050 -<br>Medical image<br>management<br>and<br>processing<br>system |
| Indications for<br>Use | Limbus Contour is a software only<br>medical device intended for use<br>by trained radiation oncologists,<br>dosimetrists and physicists to<br>derive optimal contours for input<br>to radiation treatment planning.<br><br>Supported image modalities are<br>Computed Tomography and<br>Magnetic Resonance. The Limbus<br>Contour Software assists in the<br>following<br>scenarios:<br>• Operates in conjunction with<br>radiation treatment planning<br>systems or DICOM viewing<br>systems to load, save, and display<br>medical images and contours for<br>treatment<br>evaluation and treatment planning.<br>• Creation, transformation, and<br>modification of contours for | Limbus Contour is a software only<br>medical device intended for use<br>by trained radiation oncologists,<br>dosimetrists and physicists to<br>derive optimal contours for input to<br>radiation treatment planning.<br><br>Supported image modalities are<br>Computed Tomography and<br>Magnetic Resonance. The Limbus<br>Contour Software assists in the<br>following<br>scenarios:<br>• Operates in conjunction with<br>radiation treatment planning<br>systems or DICOM viewing<br>systems to load, save, and display<br>medical images and contours for<br>treatment<br>evaluation and treatment planning.<br>• Creation, transformation, and<br>modification of contours for | Same |
| Item | Limbus Contour v1.8 | Limbus Contour v1.7 - K230575 | Similarities /<br>Differences |
| | applications including, but not<br>limited to: transferring contours to<br>radiotherapy treatment planning<br>systems, aiding adaptive therapy<br>and archiving contours for patient<br>follow-up.<br>• Localization and definition of<br>healthy anatomical Structures.<br>Limbus Contour is not<br>intended for use with digital<br>mammography. | applications including, but not<br>limited to: transferring contours to<br>radiotherapy treatment planning<br>systems, aiding adaptive therapy<br>and archiving contours for patient<br>follow-up.<br>• Localization and definition of<br>healthy anatomical Structures.<br>Limbus Contour is not<br>intended for use with digital<br>mammography. | |
| Intended User | Healthcare providers | Healthcare providers | Same |
| Machine<br>Learning<br>Algorithm | Locked algorithm; Deep Learning<br>model | Locked algorithm; Deep Learning<br>model | Same |
| Contouring<br>Modes | Automatic | Automatic | Same |
| Supported<br>Image<br>Modalities | CT; MR | CT; MR | Same |
| Compatible<br>Scanner Models | No Limitation on scanner model,<br>DICOM 3.0 compliance required. | No Limitation on scanner model,<br>DICOM compliance required. | Same |
| Compatible<br>Treatment<br>Planning<br>System | No Limitation on TPS model | No Limitation on TPS model | Same |
| Result<br>Visualization | Limbus Contour has no data<br>visualization. Data processing is<br>automated and does not require user<br>interaction. A control interface is<br>provided for system administration<br>and configuration only.<br>Visualization software must be used<br>to facilitate the review and edit of the<br>generated contours. | Limbus Contour has no data<br>visualization. Data processing is<br>automated and does not require user<br>interaction. A control interface is<br>provided for system administration<br>and configuration only.<br>Visualization software must be used<br>to facilitate the review and edit of the<br>generated contours. | Same |
| Structures<br>Available for<br>Contouring | CT Structures<br>• A_Aorta<br>• A_Aorta_I<br>• A_Celiac<br>• A_LAD<br>• A_Mesenteric_S<br>• A_Pulmonary<br>• Bag_Bowel<br>• Bag_Bowel_Extend<br>• Bag_Bowel_Full<br>• Bag_Bowel_S<br>• Bladder<br>• Body<br>• Bone_Hyoid | CT Structures<br>• A_Aorta<br>• A_Aorta_Base<br>• A_Aorta_I<br>• A_Celiac<br>• A_LAD<br>• A_Mesenteric_S<br>• A_Pulmonary<br>• Atrium_L<br>• Atrium_R<br>• Bowel_Bag<br>• Bowel_Bag_Extend<br>• Bowel_Bag_Full<br>• Bowel_Bag_Superior | Similar; The<br>subject device<br>adds new<br>structures for<br>existing<br>supported<br>image<br>modalities<br>(CT/MR) |
| Item | Limbus Contour v1.8 | Limbus Contour v1.7 - K230575 | Similarities / Differences |
| | Bone_Ilium_L Bone_Ilium_R Bone_Ilium Bone_Mandible Bowel Bowel_Extend Bowel_Full Bowel_S BrachialPlex_L BrachialPlex_R BrachialPlexs Brain Brainstem Breast_L Breast_R Breasts Bronchus Canal_Anal CaudaEquina Cavity_Oral Chestwall_L Chestwall_R Chestwalls Clavicle_L Clavicle_R Cochlea_L Cochlea_R Colon_Sigmoid Cornea_L Cornea_R Duodenum Esophagus Eye_L Eye_R Eyes Femur_Head_L Femur_Head_R Femur_Heads Gallbladder Glnd_Lacrimal_L Glnd_Lacrimal_R Glnd_Submand_L Glnd_Submand_R Glnd_Thyroid GreatVes Heart Hippocampus_L Hippocampus_R Humerus_L Humerus_R Kidney_L Kidney_R Kidneys Larynx Lens_L Lens_R Lips Liver | Bowel Bowel_Extend Bowel_Full Bowel_Superior Bladder Body Body+Mask Bone_Hyoid Bone_Ilium_L Bone_Ilium_R Bone_Ilium Bone_Ischium_L Bone_Ischium_R Bone_Mandible Bone_Pelvic BoneMarrow_Pelvic BrachialPlex_L BrachialPlex_R BrachialPlexs Brain Brainstem Breast_Implant_L Breast_Implant_R Breast_L Breast_R Breasts Bronchus Canal_Anal Carina CaudaEquina Cavity_Oral Cerebellum Chestwall_L Chestwall_R Chestwall Clavicle_L Clavicle_R Cochlea_L Cochlea_R Colon_Sigmoid Cornea_L Cornea_R Duodenum Esophagus Eye_L Eye_R Eyes Femur_Head_L Femur_Head_R Femur_Heads Gallbladder Glnd_Lacrimal_L Glnd_Lacrimal_R Glnd_Submand_L Glnd_Submand_R Glnd_Thyroid GreatVes Heart | |
| Item | Limbus Contour v1.8 | Limbus Contour v1.7 - K230575 | Similarities /<br>Differences |
| | LN_Ax_Sclav_R LN_Ax_L1_L LN_Ax_L1_R LN_Ax_L2_L LN_Ax_L2_R LN_Ax_L3_L LN_Ax_L3_R LN_Sclav_L LN_Sclav_R LN_IMN_L LN_IMN_R LN_Neck_L LN_Neck_R LN_Neck_234_L LN_Neck_234_R LN_Neck_2347AB_L LN_Neck_2347AB_R LN_Neck_IA LN_Neck_IA6 LN_Neck_IB_L LN_Neck_IB_R LN_Neck_II_L LN_Neck_II_R LN_Neck_III_L LN_Neck_III_R LN_Neck_IV_L LN_Neck_IV_R LN_Neck_V_L LN_Neck_V_R LN_Neck_VI LN_Neck_VIIAB_L LN_Neck_VIIAB_R LN_Pelvis Lung_L Lung_R Lungs Musc_Constrict Musc_PecMinor_L Musc_PecMinor_R Musc_Sclmast_L Musc_Sclmast_R OpticChiasm OpticNrv_L OpticNrv_R Pancreas Parotid_L Parotid_R PelvisVessels PenileBulb Pituitary Prostate Prostate+SeminalVes PubicSymphys Rectum Retina_L Retina_R Ribs_L Ribs_R Ribs | Hippocampus_L Hippocampus_R Humerus_L Humerus_R InternalAuditoryCanal_L InternalAuditoryCanal_R Kidney_L Kidney_R Kidneys Larynx Lens_L Lens_R Lips Liver Lung_L Lung_R Lungs Mesorectum Musc_Constrict Musc_PecMinor_L Musc_PecMinor_R Musc_Sclmast_L Musc_Sclmast_R Optics OpticChiasm OpticNrv_L OpticNrv_R Pancreas Parotid_L Parotid_R PelvisVessels PenileBulb Pericardium Pericardium+A_Pulm Pituitary Prostate Prostate+SeminalVes ProstateBed PubicSymphys Rectum Retina_L Retina_R Ribs_L Ribs_R Ribs Sacrum SeminalVes Skin SpinalCanal SpinalCord Spleen Sternum Stomach Trachea Uterus+Cervix V_Venacava_I V_Venacava_S Vagina VB C1 | |
| Item | Limbus Contour v1.8 | Limbus Contour v1.7 - K230575 | Similarities / Differences |
| | Sacrum SeminalVes Skin SpinalCanal SpinalCord Spleen Sternum Stomach Trachea Uterus_Cervix V_Venacava_l V_Venacava_S Vagina Ventricle_L MR Structures Brainstem Cornea_L Cornea_R Eye_L Eye_R Hippocampus_L Hippocampus_R Optics PenileBulb Prostate Retina_L Retina_R SeminalVes | VB_C2 VB_C3 VB_C4 VB_C5 VB_C6 VB_C7 VB_L1 VB_L2 VB_L3 VB_L4 VB_L5 VB_T01 VB_T02 VB_T03 VB_T04 VB_T05 VB_T06 VB_T07 VB_T08 VB_T09 VB_T10 VB_T11 VB_T12 VBs Ventricle_L Ventricle_R Bladder_HDR Bowel_HDR Canal_Anal_HDR Colon_Sigmoid_HDR Rectum_HDR Urethra_HDR Bladder_CBCT Femur_Head_L_CBCT Femur_Head_R_CBCT LN_Pelvics_CBCT Prostate_CBCT Rectum_CBCT SeminalVes_CBCT MR Structures Bladder Brainstem Cornea_L Cornea_R Eye_L Eye_R Femur_Head_L Femur_Head_R Hippocampus_L Hippocampus_R Optics PenileBulb PubicSymphys Prostate Rectum Retina_L Retina_R | |
| Item | Limbus Contour v1.8 | Limbus Contour v1.7 - K230575…
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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.
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Exact vs. fuzzy search: what's the difference?
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You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
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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.
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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.
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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.