STRATASYS FDM MEDMODELER SYSTEM by PALADIN MEDICAL, INC.

The Stratasys FDM MedModeler is indicated as an image processing accessory, used to create three dimensional models from 3D surface representation data or 2D contour data as a diagnostic tool, as a pre-operative planning tool, and to enhance communication with patients, other professionals or students.

Device Description

The Stratasys FDM MedModeler produces anatomical models for use in a variety of medical applications using CT and MRI imaging data. The four main parts of the FDM system, as displayed in Figure 1 (previous page) are 1) the QuickSlice Software, 2) FDM Hardware, 3) Modeling Materials and a 4) Computer Workstation.

AI/ML Overview

Here's an analysis of the provided text regarding the Stratasys FDM® MedModeler System, focusing on acceptance criteria and study details:

This device is not an AI/ML powered device. It is a system for creating physical 3D models from imaging data. Therefore, many of the typical questions related to AI/ML device studies (like MRMC studies, standalone algorithm performance, number of experts for ground truth, and training set details) are not applicable or described in the provided 510(k) summary. The summary focuses on the safety and performance of the model generation process itself, rather than diagnostic accuracy.

Acceptance Criteria and Reported Device Performance

The provided 510(k) summary is very limited regarding specific, quantifiable acceptance criteria typical for diagnostic accuracy studies. The criteria are broadly defined around the system's intended function.

Acceptance Criterion	Reported Device Performance
Safety of the system	"Hazard/Risk Analysis demonstrates that the safety of the Stratasys FDM MedModeler is acceptable and that identified potential risks are within acceptable limits for likelihood of occurrence and severity of hazards."
Performance as intended for model generation	"The model generation report demonstrates that the FDM MedModeler performed as intended and within system requirements for CAD, CT and MRI image modeling, and produced satisfactory models."
Compliance with software and hardware validation requirements	"Software development information, software validation and hardware validation information are also provided according to FDA guidance requirements."

Study Details (Where Applicable)

Given the nature of the device (a 3D modeling system rather than a diagnostic AI), many of these categories are not explicitly addressed in the provided summary.

Sample size used for the test set and the data provenance: Not explicitly stated. The summary mentions "CAD, CT and MRI image modeling" data but does not specify the number of cases or their origin.
Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable or not specified. The "ground truth" here would relate to the geometric accuracy and usability of the physical models compared to the original imaging data. There's no mention of expert radiologists or similar medical professionals evaluating model accuracy in the way they would evaluate diagnostic images.
Adjudication method for the test set: Not applicable or not specified.
If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable. This is not an AI diagnostic device for human readers.
If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable in the context of typical AI diagnostic devices. The performance of the FDM MedModeler system itself (the "algorithm only," if you consider the software and hardware combined) was assessed based on its ability to produce "satisfactory models" per the model generation report.
The type of ground truth used: The ground truth appears to be the original 2D contour or 3D surface representation data from CT/MRI, against which the generated 3D physical models were compared for "satisfactory" replication and adherence to "system requirements."
The sample size for the training set: Not applicable. This is not a machine learning device that uses a "training set" in the conventional sense. The "training" here would be the development and calibration of the system itself.
How the ground truth for the training set was established: Not applicable.

Summary

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971290
June 20, 1997

510(k) Summary

SUBMITTER:

Submitted on behalf of:

Company Name: Address:

STRATASYS, Inc. 14950 Martin Drive Minneapolis, MN 55344-2020

by:

Paladin Medical, Inc. P.O. Box 560 Stillwater, MN 55082

CONTACT PERSON: Elaine Duncan

DATE SUMMARY PREPARED: April 3, 1997

Stratasys FDM® MedModeler System TRADE NAME: Radiology Accessory COMMON NAME:

SUBSTANTIALLY EQUIVALENT TO: The Stratasys FDM MedModeler System is substantially equivalent to the SurgiCAD image processing accepted under premarket notification K924630.

DESCRIPTION of the DEVICE: The Stratasys FDM MedModeler produces anatomical models for use in a variety of medical applications using CT and MRI imaging data. The four main parts of the FDM system, as displayed in Figure 1 (previous page) are 1) the QuickSlice Software, 2) FDM Hardware, 3) Modeling Materials and a 4) Computer Workstation.

INDICATIONS FOR USE: The Stratasys FDM MedModeler is indicated as an image processing accessory, used to create three dimensional models from 3D sufface representation data or 2D contour data as a diagnostic tool, as a pre-operative planning tool, and to enhance communication with patients, other professionals or students.

CLINICAL INFORMATION and SAFETY and EFFECTIVENESS: HazardRisk Analysis demonstrates that the safety of the Stratasys FDM MedModeler is acceptable and that identified potential risks are within acceptable limits for likelibood of occurrence and severity of hazards. The model generation report demonstrates that the FDM MedModeler performed as intended and within system requirements for CAD, CT and MRI image modeling, and produced satisfactory models. Software development information, software validation and hardware validation information are also provided according to FDA guidance requirements.

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ang majallu som vide

Food and Drug Administration 9200 Corporate Boulevard Rockville MD 20850

JUN 20 1997

Stratasys, Inc. c/o Elaine Duncan, RAC, M.S.M.E. President Paladin MedicalsM, Inc. P.O. Box 560 Stillwater, MN 55082-0560

Re: K971290

Stratasys FDM® MedModeler System Radiology Accessory Dated: April 3, 1997 Received: April 7. 1997 Unclassified/Procode: 90 LLZ

Dear Ms. Duncan:

We have reviewed your Section 510(k) notification of intent to market the device referenced above and we have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing, and prohibitions against misbranding and adulteration.

If your device is classified (see above) into either class III (Special Controls) or class III (Premarket Approval), it may be subject to such additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 895. A substantially equivalent determination assumes compliance with the Good Manufacturing Practice for Medical Devices: General (GMP) regulation (21 CFR Part 820) and that, through periodic GMP inspections, the Food and Drug Administration (FDA) will verify such assumptions. Failure to comply with the GMP regulatory action. In addition, FDA may publish further announcements concerning your device in the Federal Register. Please not: this response to your premarket notification does not affect any obligation you might have under sections 531 tirough 542 of the Act for devices under the Electronic Product Radiation Control provisions, or other Federal laws or regulations.

This letter will allow you to begin marketing your device as described in your 510(k) premarket notification. The FDA finding of substantial equivalence of your device to a legally marketed predication for your device and thus, permits your device to proceed to the market.

If you desire specific advice for your device on our labeling regulation (21 CFR Part 801 and additionally 809.10 for in vitro disgnostic devices), please contact the Office of Compliance at (301) 594-4591 for Radiology devices, or 594-4613 for Ear, Nose and Throat devices. Additionally, for question on the promotion and advertising of your device, please contact the Office of Compliance at (301) 594-4639. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). Other general information on your responsibilities under the Act may be obtained from the Division of Small Manufacturers Assistance at its toll-free number (800) 638-2041 or (301) 443-6597 or at its Internet address "http://www.fda.gov/cdrh/dsmamain.html".

Sincerely yours.

Ollain'

Lillian Yin, Ph.D. Director, Division of Reproductive, Abdominal, Ear, Nose and Throat, and Radiological Devices Office of Device Evaluation Center for Devices and Radiological Health

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510(k) Number (if known)

Device Name: Stratasys FDM® MedModeler System

Indications for Use: -- --------------------

(Please Do Not Write Below This Line-Continue On Another Page If Needed) Concurrence of CDRH, Office of Device Evaluation (ODE)

Prescription Use

Over -The-Counter Use _

(Copiona: Format 1-2-96)

Ylmid h. Segmen
(Division Sign-Off)

Division of Reproductive, Abdominal, ENT, and Radiological Devices

510(k) Number K971290

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Regulation Number and Section

§ 892.2050 Medical image management and processing system.

(a)
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.(b)
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).