The PRE-SURE software system is intended for use as a software interface and image segmentation system for the transfer of DICOM imaging information from a medical scanner to an output file. It is also intended as pre-operative software for surgical planning. For this purpose, the output file may be used to produce a physical replica. The physical replica is intended for adjunctive use along with other diagnostic tools and expert clinical judgement for diagnosis, patient management, and/or treatment selection of genitourinary applications.

Device Description

End Users of the PRE-SURE device receive digital and/or physical patient anatomical models from Lazarus 3D. The physical models are intended for adjunctive use along with other diagnostic tools and expert clinical judgement for diagnosis, patient management, and/or treatment selection of genitourinary applications. Digital models may be viewed by End Users using any program cleared for their intended use.

The PRE-SURE patient modeling system is a method for the creation of patient models. This system will be used exclusively by Lazarus 3D, with some physician input and feedback, to produce models for End Users. Importantly, and unlike other 3D modeling systems, in the PRE-SURE process the design and production of patient models is performed by Lazarus 3D and not by the End User or a third party. The internal process within Lazarus 3D used for creating PRE-SURE patient models includes use of an FDA cleared stand-alone software package. As a part of the PRE-SURE production process, this software is intended for internal use within Lazarus 3D to create digital anatomical models from patient radiological data that can be used by End Users for a variety of uses such as training, education, and pre-operative surgical planning.

The patient specific digital anatomical models may be further used as an input to a 3D printing-based production process performed by Lazarus 3D to create physical patient models. Each individual patient's model can be created rapidly from the patient's radiological data using Lazarus 3D's patented rapid prototyping technology. The resulting physical models of patient anatomy are primarily composed of silicone materials that can be cut, can be sutured, and in some cases can even bleed.

AI/ML Overview

The PRE-SURE software system is intended for use as a software interface and image segmentation system for the transfer of DICOM imaging information from a medical scanner to an output file. It is also intended as pre-operative software for surgical planning. For this purpose, the output file may be used to produce a physical replica. The physical replica is intended for adjunctive use along with other diagnostic tools and expert clinical judgment for diagnosis, patient management, and/or treatment selection of genitourinary applications.

1. A table of acceptance criteria and the reported device performance:

The document summarizes that all performance testing demonstrated conformity to pre-established specifications and acceptance criteria, which were established to prove device performance and substantial equivalence to the predicate device. However, the specific acceptance criteria and detailed reported device performance are not explicitly provided in a quantitative table within the given text. The tests performed aimed to show that:

Acceptance Criteria (Implied)	Reported Device Performance (Summary)
Production Process Accuracy: Physical models match in-silico designs within pre-defined criteria.	Measurements between physical models created using PRE-SURE and in-silico input data "fell within pre-defined acceptance criteria."
Digital and Physical Model Accuracy: PRE-SURE workflow results compare accurately with predicate device results.	Comparisons between PRE-SURE models and predicate device models (from MRI/CT input) "fell within pre-defined acceptance criteria."
Build Envelope Accuracy: Models built with different printer locations and orientations achieve sufficient accuracy.	"Sufficient accuracy can be achieved for models built in any orientation or position" on the 3D printer for genitourinary conditions.
Materials Testing Accuracy & Bonding: Range of materials and combinations produce models of sufficient accuracy and bond well.	"All materials and material combinations produce models of sufficient accuracy for the intended use" and "all tested materials bond well with all other tested materials."
Challenging Cases Accuracy: Complex genitourinary models are reproduced with sufficient accuracy.	The 3D manufacturing process can reproduce "complex genitourinary conditions with sufficient accuracy for the intended use" when testing models of three difficult-to-produce conditions, with volumetric comparison against the digital design using CT scans.

2. Sample size used for the test set and the data provenance:

Production Process Accuracy Study: The document mentions "models of various dimensions" but does not specify the exact sample size. Data provenance is implied to be internal, as it compares physical models created by PRE-SURE against "in-silico input data" (computer models with pre-defined dimensions).
Digital and Physical Model Accuracy Study: "MRI and CT scan input data from actual cases were analyzed." The number of actual cases is not specified. Data provenance is "actual cases," which suggests retrospective patient data, but the country of origin is not mentioned.
Build Envelope Testing - Accuracy Validation: "Models of genitourinary conditions were built." The number of models tested is not specified.
Materials Testing - Accuracy Validation: "Multi-material genitourinary models were produced." The number of models or material combinations tested is not specified.
Testing on Especially Challenging Genitourinary Cases: "Models of three conditions that are difficult to produce for a variety of reasons were manufactured." The sample size here is explicitly three models. Data provenance is not specified beyond "complex genitourinary models."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

The document does not provide information on the number of experts used or their qualifications for establishing ground truth in any of the described studies. The ground truth for the "Production Process Accuracy Study" was "pre-defined in silico" dimensions. For other studies, it seems to rely on comparisons to existing imaging data or digital designs, without explicit involvement of human experts for ground truth establishment.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

The document does not mention any adjudication method being used for the test sets. The studies described are focused on direct measurement comparisons rather than expert interpretation requiring adjudication.

5. 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:

No MRMC comparative effectiveness study involving human readers or AI assistance is mentioned in the provided text. The device, PRE-SURE, is described as a software interface and image segmentation system for creating digital and physical anatomical models for surgical planning and adjunctive use (diagnosis, patient management, treatment selection). It is not presented as an AI-assisted diagnostic tool that directly impacts human reader performance.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

The studies described ("Production Process Accuracy Study," "Digital and Physical Model Accuracy Study," "Build Envelope Testing - Accuracy Validation," "Materials Testing - Accuracy Validation," "Testing on Especially Challenging Genitourinary Cases") appear to evaluate the output of the PRE-SURE system (digital and physical models) based on defined metrics or comparisons. These are standalone evaluations of the system's accuracy in model production, independent of human interpretation or intervention in the evaluation phase, although human feedback is mentioned in the production process ("physician input and feedback").

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

Production Process Accuracy Study: In-silico input data (pre-defined dimensions in computer models).
Digital and Physical Model Accuracy Study: Comparison against the predicate device's output and presumably the original MRI/CT scan input data (although not explicitly pathology or expert consensus).
Testing on Especially Challenging Genitourinary Cases: "Volumetrically compared against the digital design" and original CT scanner data.

Generally, the ground truth appears to be based on engineering specifications (in-silico designs) and direct comparisons against source radiological data or outputs of a legally marketed predicate device, rather than clinical outcomes, pathology, or expert consensus on a diagnosis.

8. The sample size for the training set:

The document does not mention any "training set" or "training" for the PRE-SURE device. This suggests that the device, being an "image segmentation system" and a tool for creating models, might not rely on a machine learning model that requires a distinct training set in the conventional sense, or this information is not disclosed in the provided summary.

9. How the ground truth for the training set was established:

As no training set is mentioned, information on how its ground truth was established is not provided.

Summary

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July 8, 2021

Image /page/0/Picture/1 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 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.

Lazarus, 3D, Inc. % Elisa Maldonado-Holmertz RA/QA Consultant Obelix Consulting 12416 Fairfax Ridge Place AUSTIN TX 78738

Re: K201835

Trade/Device Name: PRE-SURE Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: May 29, 2021 Received: June 2, 2021

Dear Elisa Maldonado-Holmertz:

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 (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely.

For

Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known) K201835

Device Name

PRE-SURE

Indications for Use (Describe)

The PRE-SURE software system is intended for use as a software interface and image segmentation system for the transfer of DICOM imaging information from a medical scanner to an output file. It is also intended as pre-operative software for surgical planning. For this purpose, the output file may be used to produce a physical replical replica is intended for adjunctive use along with other diagnostic tools and expert clinical judgement for diagnosis, patient management, and/or treatment selection of genitourinary applications.

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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Image /page/3/Picture/1 description: The image shows the logo for Lazarus 3D. The logo consists of a blue and orange diamond shape on the left, followed by the words "Lazarus 3D" in black font. Below the company name is the phrase "Operate with confidence" in a smaller, black font.

Section 005 - 510(k) Summary

1. INTRODUCTION

This document contains the 510(k) summary for the PRE-SURE device. The content of this summary is based on the requirements of 21 CFR 807.92.

2. SUBMISSION SPONSOR

Name:	Lazarus 3D, Inc.
Address:	3513 NW Mink PlCorvallis, OR 97330
Phone:	(541) 760 1805
Contact Name:	Dr. Smriti Zaneveld
Contact Email:	Smriti@laz3D.com
Additional Contact:	Dr. Jacques Zaneveld
Additional Email:	Zaneveld@laz3D.com
Submission CorrespondentName:	Obelix Consulting, LLC
Address:	12416 Fairfax Ridge PlaceAustin, TX 78738
Phone:	(512) 431 6069
Contact Name:	Elisa Maldonado-Holmertz
Contact Email:	elisamh@obelixconsult.com

Date Prepared: 7 July 2021

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Device Identification

Type of 510(k) Submission: Traditional Trade Name: PRE-SURE Common Name: System, Image Processing, Radiological Regulation Description: Medical Image Management and Processing System Regulation Number: 21 CFR 892.2050 Product Code: LLZ Class of Device: II Review Panel: Radiology Reason for Submission: New device Prior Related Submissions: None Multiple Devices: None

3. LEGALLY MARKETED PREDICATE DEVICE

The PREoperateive SUrgical REhearsal (PRE-SURE) device is claimed to be substantially equivalent to the following legally marketed device:

. D2P, 3D Systems, Inc. (K183489).
No reference devices were used in this submission.

4. DEVICE DESCRIPTION

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5. INDICATIONS FOR USE

6. SUBSTANTIAL EQUIVALENCE DISCUSSION

PRE-SURE employs similar fundamental technologies as the identified predicate device, including:

. Viewing of medical imaging data in the axial, coronal, and sagittal views
Ability to process, review and analyze medical imaging data
lmage transfer and manipulation via software used for the creation of a 3D object.
Use of the 3D object for diagnosis, patient management and/or treatment selection.

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Image /page/6/Picture/0 description: The image contains the logo for Lazarus 3D. The logo consists of a blue and orange diamond shape on the left, followed by the text "LAZARUS 3D" in a bold, sans-serif font. Below the company name is the tagline "Operate with confidence" in a smaller, regular font.

However, in the PRE-SURE process the analysis of patient data and production of patient models is performed by Lazarus 3D and is provided as a service to End Users. By contrast, the predicate device is sold as a software and hardware package that allows End Users or third parties to produce their own patient models. Additionally, while the predicate patient models are produced in relatively hard materials (e.g., plastics), PRE-SURE physical models can be created in soft silicone materials that can be cut, sutured, and in some cases even bleed. Both devices can be used to create a physical rendering of radiological data for visualization and analysis. However, the additional capabilities of PRE-SURE models may provide new opportunities for pre-surgical planning and rehearsal.

Comparison to Legally Marketed Device:

Manufacturer	Subject Device	Predicate Device	Significant Differences
	Lazarus 3d, Inc.	3D Systems, Inc.
Trade Name	PRE-SURE	D2P	None
510(k) Number	K201835	K183489
Product Code	LLZ	LLZ	None
Regulation Number	892.2050	892.2050	None
Regulation Name	Medical Image Managementand Processing System	Medical Image Managementand Processing System	None
Common Name	System, Image Processing,Radiological	System, Image Processing,Radiological	None
Indications for Use	The PRE-SURE software isintended for use as asoftware interface and imagesegmentation system for thetransfer of DICOM imaginginformation from a medicalscanner to an output file. It isalso intended as pre-operative software forsurgical planning. For thispurpose, the output file maybe used to produce aphysical replica. The physicalreplica is intended foradjunctive use along with	The D2P software is intendedfor use as a softwareinterface and imagesegmentation system for thetransfer of DICOM imaginginformation from a medicalscanner to an output file. It isalso intended as pre-operative software forsurgical planning. For thispurpose, the output file maybe used to produce aphysical replica. The physicalreplica is intended foradjunctive use along with	Nearly identical, except thesubject device is onlyintended for use ingenitourinary applications,while the predicate device isintended for use incardiovascular, craniofacial,gastrointestinal,genitourinary, neurological,and/or musculoskeletalapplications.

Table 12A – Device Comparison Chart: Similarities and Differences

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Manufacturer	Subject DeviceLazarus 3d, Inc.	Predicate Device3D Systems, Inc.	Significant Differences
Trade Name	PRE-SURE	D2P	None
	other diagnostic tools andexpert clinical judgement fordiagnosis, patientmanagement, and/ortreatment selection ofgenitourinary applications.	other diagnostic tools andexpert clinical judgement fordiagnosis, patientmanagement, and/ortreatment selection ofcardiovascular, craniofacial,gastrointestinal,genitourinary, neurological,and/or musculoskeletalapplications.
Material	Non-hazardous silicones,resins, and food products	Plastics	All components of PRE-SUREmodels are certified non-hazardous by OSHA 29 CFR1910.1200.
Sterile	No	No	None

7. NON-CLINICAL PERFORMANCE DATA

The following performance data were provided in support of the substantial equivalence determination:

Production Process Accuracy Study

The purpose of this accuracy study was to evaluate the accuracy of PRE-SURE patient model production processes. Models of various dimensions were created using PRE-SURE from computer models with dimensions pre-defined in silico. Comparisons were made between the physical models created using PRE-SURE and the in-silico input data, revealing that measurements fell within pre-defined acceptance criteria.

Digital and Physical Model Accuracy Study

The purpose of this accuracy study was to compare results from the entire PRE-SURE workflow to those of the predicate device. MRI and CT scan input data from actual cases were analyzed using the predicate and subject devices to create 3D computer models and

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physical models of the patient anatomy. These models were then compared, revealing that measurements fell within pre-defined acceptance criteria.

Build Envelope Testing - Accuracy Validation

The purpose of this study is to define where on the 3D printer, and in what orientation, models can be produced in sufficient accuracy for the intended use. Models of genitourinary conditions were built using 3D prints from different locations the 3D printer build plate, and in different orientations. Results show that sufficient accuracy can be achieved for models built in any orientation or position.

Materials Testing - Accuracy Validation

The purpose of this study is to test the accuracy and bonding of the range of materials included in the build envelope for PRE-SURE physical patient models. Multi-material genitourinary models were produced using combinations of the most difficult to use materials within the PRE-SURE build envelope. Testing shows that all materials and material combinations produce models of sufficient accuracy for the intended use. Additionally, all tested materials bond well with all other tested materials and thus can be used together to form multi-material patient models.

Testing on Especially Challenging Genitourinary Cases

The purpose of this study is to test was to test the accuracy of the subject production process when creating complex genitourinary models. Models of three conditions that are difficult to produce for a variety of reasons were manufactured. These physical models were analyzed using a CT scanner and volumetrically compared against the digital design. Results indicate that the subject 3D manufacturing process can reproduce complex genitourinary conditions with sufficient accuracy for the intended use.

Summary

All performance testing which was conducted as a result of risk analyses and design impact assessments showed conformity to pre-established specifications and acceptance criteria. The acceptance criteria were established in order to demonstrate the device performance and substantial equivalence to the predicate device.

8. STATEMENT OF SUBSTANTIAL EQUIVALENCE

Based on a comparison of the intended use and technological characteristics, the PRE-SURE device is substantially equivalent to the identified predicate device. Minor

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differences in technological characteristics did not raise new or different questions of safety and effectiveness. Additionally, the validation data supports that the system performs in accordance with its intended use and is substantially equivalent to the predicate device.

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).