3D-RD-S is intended to estimate radiation absorbed dose (and related quantities) to tissues after administration of a radioactive product. For use with internally administrated radioactive products, 3D-RD-S should not be used to deviate from product dosing and administrations. Refer to the product's prescribing information for instructions.

Device Description

3D-RD-S is a cloud-based software as a medical device (SaMD) that interacts with the user via web browsers (for example Google Chrome). Users are trained healthcare professionals with significant dosimetry knowledge and experience and also responsible for the input of the appropriate values and to make correct interpretation of the output data. 3D-RD-S takes numerical input data in the form of activity in source tissues as a function of time (TAC data) or the integral of the activity (TIA data) in source tissues over time. It then calculates the absorbed dose to a set of target tissues based on the organ sizes and anatomies of a set of standard phantoms. The software provides the user the ability to account for the differences in tissue masses between the phantoms and the subject and model uncertainties in the input data.

Calculation results can be viewed and updated by other users. The software provides the ability to calculate absorbed doses and related radiobiological quantities from input data. The calculations can be made for supported radionuclides based on data in the report 89 from the International Council on Radiation Protection (ICRP). Doses to target tissues are a function of the activity integrated over time (time-integrated activity. TIA) in a set of specified source organs. The software provides two modules for the integration of input time vs. activity curve (TAC) data. First, the user can use curve fitting methods to estimate a curve that passes through the TAC data from a set of supported fitting functions. Visual and numerical indicators of how well the fitting function works with the data are provided. Notifications are given if fitting parameters are non-physical. The TAC data can then be integrated using the fitting function, or by approximating the activity between measured time points with line and assuming activity after the last time-point decays with the radionuclide's physical half-life. If desired, the user can use a combination of the curve fit, linear interpolation between the lines, and exponentially decaying extrapolation based on the physical half-life, to integrate the time-activity curves.

The calculated radiobiological quantities purport to relate physical dose to biological response and are dependent on the specification of radiobiological constants. The guantities supported include the whole-body effective dose and the relative biological effectiveness (RBE) weighted dose. The effective dose is calculated based on ICRP tissue weighting factors. The RBE weighted dose is calculated using user specified RBEs for the different radiation types (standard values are provided as defaults).

3D-RD-S provides total and individual dose estimates for the various particle types, i.e., alpha particles, beta (+ and -) particles, discrete electrons (e.g., Auger electrons), and photons (gamma and x-rays). The resulting doses are plotted in a bar graph and can, along with input data, be exported in a spreadsheet.

AI/ML Overview

The provided document, a 510(k) Summary for the 3D-RD-S device, details the acceptance criteria and the studies conducted to demonstrate its performance.

Here's an analysis of the provided information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes several benchmark tests, each with an implicit or explicit acceptance criterion and the corresponding performance.

Test Type	Acceptance Criteria	Reported Device Performance
Benchmark Test (1):	Absolute percent difference between absorbed dose calculated by 3D-RD-S and OLINDA/EXM v2.0 (predicate) for source tissues < 10%.	"For almost all cases, the difference in source tissues absorbed doses calculated using 3D-RD-S and the predicate was below the 10% threshold." The document also notes that "the reported differences in source and non-source tissues absorbed doses can be primarily attributed to the differences in the sources of data used to generate the S-values...used in 3D-RD-S and the predicate for the dose calculations."
Benchmark Test (2):	Differences in absorbed dose values calculated by 3D-RD-S and those reported in published literature < 5% for each target organ.	"The differences in the absorbed doses calculated using 3D-RD-S and those published in literature were below 5% for each target organ included in the published study and available in 3D-RD-S."
Benchmark Test (3):	Variability in dose outputs by multiple operators processing the data for SNMMI Dosimetry Challenge data. Implicit acceptance: demonstrate acceptable agreement (context suggests within 10% based on the source tissue test).	"Despite the subjectivity in manually drawn VOIs, the final absorbed dose values were found to agree within 10% for all target normal organs."

2. Sample Size Used for the Test Set and Data Provenance:

Benchmark Test (1) (Comparison with Predicate):
- Sample Size: Not explicitly stated as a number of cases or patients. It mentions using "Clinical data, obtained from Rapid's clinical trials dosimetry service business with clinically relevant administered activities."
- Data Provenance: Implied to be retrospective clinical data from "Rapid's clinical trials dosimetry service business." The country of origin is not specified but given the FDA submission, it's likely US-based or from regions with compatible data standards.
- Radionuclides tested: In-111, F-18, Ga-68 (photon emitters); I-131, Lu-177 (beta emitters); Pb-212, Ra-223, Ac-225 (alpha emitters' parents).
Benchmark Test (2) (Comparison with Published Literature):
- Sample Size: Not explicitly stated as a number of cases or patients. It refers to "several published studies" that met specific criteria.
- Data Provenance: Retrospective, derived from "published studies" that used specific phantom models (ICRP 110) and SAF values (ICRP 133).
- Radionuclides tested: F-18, Zr-89, Y-90, I-131, Lu-177, At-211.
Benchmark Test (3) (Inter-operator Variability):
- Sample Size: Data from "two patients (A and B)" from the SNMMI Lu-177 Dosimetry Challenge.
- Data Provenance: Retrospective, from a "SNMMI Lu-177 Dosimetry Challenge (Uribe et al. J Nuc Med. 2021)." This implies a standardized or widely recognized dataset.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:

Benchmark Test (1) & (2): No explicit mention of human experts defining ground truth for these tests. The ground truth for Test (1) is the output of the predicate device (OLINDA/EXM v2.0), and for Test (2), it's the results published in peer-reviewed literature. These are treated as reference standards for comparison.
Benchmark Test (3): "Two (2) analysts" performed the processing. Their qualifications are stated as "background in medical physics and extensive experience in radiopharmaceutical therapy dosimetry." This test assessed inter-operator variability rather than establishing a new ground truth.

4. Adjudication Method for the Test Set:

No explicit adjudication method (e.g., 2+1, 3+1) is described for establishing ground truth or resolving discrepancies for any of the tests.
For Benchmark Test (1), the ground truth is the output of the predicate device.
For Benchmark Test (2), the ground truth is data from published literature.
For Benchmark Test (3), the test itself is designed to measure variability between two independent operators, so there isn't a need for adjudication to establish a "single" ground truth from their different outputs; rather, the agreement between them is the metric of interest.

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 improving with AI vs. without AI assistance was reported.
The device, 3D-RD-S, is a "cloud-based software as a medical device (SaMD)" for absorbed dose calculation. It is not an AI-assisted diagnostic tool for human readers in the traditional sense of image interpretation. It takes numerical input data (TAC or TIA) and calculates absorbed doses.
Benchmark Test (3) involves multiple operators, but it assesses inter-operator variability in processing input data for the software, not how the software assists in human interpretation or decision-making.

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

Yes, implicitly. Benchmark Test (1) and Benchmark Test (2) represent the "algorithm only" performance.
- In Benchmark Test (1), the 3D-RD-S's calculated absorbed doses are compared directly against the predicate device's output, simulating a standalone performance against a benchmark.
- In Benchmark Test (2), 3D-RD-S's outputs are compared against published literature, again a direct algorithmic comparison.
Benchmark Test (3) involves human operators as input providers, but the focus is on the variability of the input provided by humans resulting in differences in the software's output, rather than the software changing human decision making. The software itself performs its calculations in a standalone manner based on the input it receives.

7. The Type of Ground Truth Used:

Benchmark Test (1): The "ground truth" or reference was the output data from a legally marketed device, OLINDA/EXM v2.0 (a type of comparative reference standard).
Benchmark Test (2): The "ground truth" or reference was absorbed dose values reported in published scientific literature, specifically those using ICRP 110 phantoms, ICRP 133 SAF values, and ICRP 107 nuclear decay data (literature-based reference standard/computational comparison).
Benchmark Test (3): This test did not establish a "ground truth" in the traditional sense of a definitive diagnosis or outcome. Instead, it examined the consistency/variability of the device's output when processed by different medical physics experts, using SNMMI Dosimetry Challenge data. The "ground truth" for the input process was likely the raw image data from known patient cases, and the test measured the agreement of the derived dose outputs.

8. The Sample Size for the Training Set:

The document does not provide information about the sample size used for the training set.
Given that 3D-RD-S sounds like a deterministic calculation software based on established physical models (ICRP data, MIRD dose calculations, curve fitting for TAC), it's possible it's not a machine learning/AI model that undergoes "training" on a dataset in the conventional sense. Instead, it might be validated against known physical principles and benchmarked against existing validated tools and literature. The "training" in such a system often refers to the development of the underlying physical models and constants rather than statistical learning from a dataset.

9. How the Ground Truth for the Training Set Was Established:

Since there's no mention of a training set or typical machine learning "training" process, there's no information on how its "ground truth" was established.
The core functioning of 3D-RD-S relies on established scientific data and models, such as:
- ICRP Report 89 for supported radionuclides.
- ICRP 110 phantoms and ICRP 133 SAF values.
- ICRP 107 for nuclear decay data.
- Standard curve fitting methods and trapezoidal integration for TAC data.
  These scientific principles and reference values form the inherent "ground truth" upon which the software's calculations are built.

Summary

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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.

February 22, 2023

Radiopharmaceutical Imaging and Dosimetry, LLC % Nadine Bonds Director of Quality Assurance 1800 Gough St. BALTIMORE MD 21231

Re: K212587

Trade/Device Name: 3D-RD-S Regulation Number: 21 CFR 892.1100 Regulation Name: Scintillation (gamma) Camera Regulatory Class: Class I, reserved Product Code: IYX Dated: January 24, 2023 Received: January 24, 2023

Dear Nadine Bonds:

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

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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 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 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,

Daniel M. Krainak, Ph.D. Assistant Director Magnetic Resonance and Nuclear Medicine 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

510(k) Number (if known) K212587

Device Name 3D-RD-S

Indications for Use (Describe)

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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510(k) Summary

l. SUBMITTER

Radiopharmaceutical Imaging & Dosimetry (Rapid®), LLC 1800 Gough Street Baltimore, MD 21231

Phone: 443-524-7396 Email: nbonds@rapiddosimetry.com

Contact person: Nadine Bonds Date Prepared: February 17, 2023

II. DEVICE

Name of Device: 3D-RD-S Common or Usual Name: 3D-RD-S Classification Name: Scintillation (gamma), Camera Regulatory Class: Class I (21 CFR 892.1100) Product Code: IYX

III. PREDICATE DEVICE

Primary: OLINDA/EXM v2.0, K163687

IV. DEVICE DESCRIPTION

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target tissues are a function of the activity integrated over time (time-integrated activity. TIA) in a set of specified source organs. The software provides two modules for the integration of input time vs. activity curve (TAC) data. First, the user can use curve fitting methods to estimate a curve that passes through the TAC data from a set of supported fitting functions. Visual and numerical indicators of how well the fitting function works with the data are provided. Notifications are given if fitting parameters are non-physical. The TAC data can then be integrated using the fitting function, or by approximating the activity between measured time points with line and assuming activity after the last time-point decays with the radionuclide's physical half-life. If desired, the user can use a combination of the curve fit, linear interpolation between the lines, and exponentially decaying extrapolation based on the physical half-life, to integrate the time-activity curves.

> INDICATIONS FOR USE

3D-RD-S is intended to estimate radiation absorbed dose (and related quantities) to tissues after administration of a radioactive product. For use with internally administrated radioactive products, 3D-RD-S should not be used to deviate from product dosing and administration instructions. Refer to the product's prescribing information for instructions.

VI. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH PREDICATE

As summarized in the table below, the 3D-RD-S technological characteristics compare favorably with the predicate SaMD technological characteristics.

3D-RD-S can be used with any internal radioactivity supplied by any FDA approved radiopharmaceutical, radiopharmaceuticals under development (even before ever administered to humans based on extrapolations of activities in human tissues from, e.g., animal studies), or radionuclides present in the body due to environmental exposure.

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Comparison Summary

Attributes	3D-RD-S	OLINDA/EXM, v2.0	Comments
Indications forUse	3D-RD-S is intended toestimate radiationabsorbed dose (andrelated quantities) totissues afteradministration of aradioactive product.For use with internallyadministratedradioactive products,3D-RD-S should not beused to deviate fromproduct dosing andadministrationinstructions. Refer tothe product'sprescribing informationfor instructions.	The intended use ofOLINDA/EXM is toprovide estimates(deterministic) ofabsorbed radiationdose at the wholeorgan level as a resultof administering anyradionuclide and tocalculate effectivewhole-body dose. Thisis dependent on inputdata regardingbiodistribution beingsupplied to theapplication.	Indications forUse is Equivalent
Product CodeRegulation	IYX / 21 CFR 892.1100	IYX / 21 CFR 892.1100	Product Code /Requlation isEquivalent
Target Population	Adults, Children	Adults, Children,Pregnant women	Target Populationis Equivalent
Input	TIA, TIAC, or TAC	Fraction of injectedactivity in each organor the TIAC	Input Data isEquivalent
RadionucleotidesSupported	Supports 1,252radionucleotides	Over 1000, includingAlpha Emitters	RadionucleotidesSupported isEquivalent
DosimetryCalculation	Whole organ / tissueDosimetry. Tissue S-Values	Whole organ / tissueDosimetry. Tissue S-Values	DosimetryCalculation isEquivalent
Output	Absorbed Dose tables	Absorbed Dose tables	Output Data isEquivalent
TAC Integration	Integration can be donebased on user-selectionof one of 4 fit functions,user specified washouthalf-life, physical decay,or a combination of theabove and trapezoidalintegration. The four fitfunctions constrain theshape of the fit and areselected by the userbased on the data. Theuser can provide, or thesoftware estimate initialvalues, of the fittingparameters. Uncertaintyvalues provided with thedata are used in the	Integration isperformed based onfitting data with up to 3exponentials. Fittingstart and endpoints canbe user specified.Allows specifyingweights for data duringfitting. The data and fitare plotted graphically.	TAC Integrationis Equivalent
Attributes	3D-RD-S	OLINDA/EXM, v2.0	Comments
	fitting. Uncertaintyvalues are used asweights in fitting.Integration is alwaysfrom 0 to infinity. Thefits and integration isdisplayed graphically.
Anatomical Sites	Supports the 79 targetand 43 target tissuesfrom ICRP-133	Supports 26 sourcetissues and 30 targettissues	Anatomical Sitesis Equivalent

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VII. PERFORMANCE DATA

Software Verification and Validation Testing

Tests for verification and validation have been completed following Rapid's design control procedures. A risk analysis was completed, and risk controls have been implemented to mitigate identified hazards.

Benchmark Testing

Rapid performed the following benchmark tests:

(1) Compared absorbed dose estimated from 3D-RD-S to those obtained using OLINDA/EXM v2.0 and inputs representative of the marketed use of 3D-RD-S including TIAC and TAC user input modes.
The objective of the test was to demonstrate equivalence of absorbed dose calculations performed by 3D-RD-S against the predicate. Clinical data, obtained from Rapid's clinical trials dosimetry service business with clinically relevant administered activities, were used to compare absorbed doses calculated by 3D-RD-S to those calculated using the predicate device. This included the following radionuclides: photon emitters used for diagnostic agents (In-111, F-18, Ga-68), beta emitters used in therapy (I-131, Lu-177), and alpha emitters (Pb-212 (betaemitting parent of the alpha-emitters, Bi-212 and Po-212), Ra-223 and Ac-225) used in therapy.

Absorbed doses to source tissues were considered acceptable if the absolute percent difference (defined as the difference divided by the mean multiplied by 100) between the dose calculated by the predicate and the dose from 3D-RD-S was less than 10%.

For almost all cases, the difference in source tissues absorbed doses calculated using 3D-RD-S and the predicate was below the 10% threshold. The reported differences in source and non-source tissues absorbed doses can be primarily attributed to the differences in the sources of data used to generate the S-values (the basis for MIRD dose calculations) used in 3D-RD-S and the predicate for the dose calculations.

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(2) Compared the absorbed dose values obtained using 3D-RD-S to those reported in published literature.
Rapid surveyed several published studies that investigated a variety of radionuclides. Direct comparisons in calculated absorbed dose were made to literature results that meet the following criteria: 1) provided time-integrated activity coefficients (residence times) in specified source organs, 2) used the ICRP 110 phantoms and ICRP 133 SAF values for dose calculations, and 3) used nuclear decay data from ICRP 107. This enabled the ability to do direct comparisons between the absorbed doses for the same set of target tissues. The time integrated activity coefficients were used as direct inputs into 3D-RD-S. Radionuclides were chosen to represent gamma, beta, and alpha emitters such as F-18, Zr-89, Y-90, l-131, Lu-177 and At-211.

The differences in the absorbed doses calculated using 3D-RD-S and those published in literature were below 5% for each target organ included in the published study and available in 3D-RD-S.

(3) Compared 3D-RD-S dose outputs by having two (2) analysts independently process images from SNMMII Dosimetry Challenge data for patients A and B through the dosimetry workflow pipeline.
The objective of this test was to report the variability in the dose outputs as a result of having multiple operators processing the data. The test included SPECT/CT images from two patients (A and B) which were part of the SNMMI Lu-177 Dosimetry Challenge (Uribe et al. J Nuc Med. 2021). Images were acquired at four time points following Lu-177-DOTATATE administration. Source organs included the kidneys, liver, spleen (absent in Patient B), and abdominal tumors (two in Patient A; four in Patient B).

Tests were performed by two analysts with a background in medical physics and extensive experience in radiopharmaceutical therapy dosimetry. The analysts compared 3D-RD-S dose outputs by independently processing images from the SNMMI Dosimetry Challenge data for patients A and B through the dosimetry workflow pipeline (i.e., draw VOls, extract TAC, ... etc.). 3D-RD-S does not provide tools for image analysis, and this was done using an external image analysis package that is not part of this submission. Despite the subjectivity in manually drawn VOIs, the final absorbed dose values were found to agree within 10% for all target normal organs.

VIII. CONCLUSION

In summary, 3D-RD-S has the same intended use and similar technological characteristics that do not raise different questions of safety or effectiveness compared to the predicate device. Therefore, 3D-RD-S is demonstrated to be substantially equivalent to OLINDA/EXM v2.0 and supports its safety and intended use.

Regulation Number and Section

§ 892.1100 Scintillation (gamma) camera.

(a)
Identification. A scintillation (gamma) camera is a device intended to image the distribution of radionuclides in the body by means of a photon radiation detector. This generic type of device may include signal analysis and display equipment, patient and equipment supports, radionuclide anatomical markers, component parts, and accessories.(b)
Classification. Class I (general controls).