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The intended use of OLINDA/EXM is to provide estimates (deterministic) of absorbed radiation dose at the whole organ level as a result of administering any radionuclide and to calculate effective whole-body dose. This is dependent on input data regarding bio distribution being supplied to the application.

The OLINDA/EXM® v2.0 is a modification of OLINDA/EXM® v1.1 (K033960) and includes new human models and nuclides. OLINDA/EXM® 2.0 employs a new set of decay data recommended by the International Commission on Radiological Protection (ICRP). OLINDA/EXM® 2.0 introduces a new series of anthropomorphic human body models (phantoms), so new values of Specific Absorbed Fractions (SAF), di (T←S) were generated. These phantoms were based on updated values of the mass of the target region (mr) recommended by the ICRP. The base product design of OLINDA/EXM® V2.0 is the same as for the OLINDA/EXM® V1.1 (K033960).

The provided document is a 510(k) summary for a medical device called OLINDA/EXM v2.0. This document primarily focuses on demonstrating substantial equivalence to a predicate device (OLINDA/EXM v1.1) rather than presenting a detailed clinical study with acceptance criteria and device performance in the way one might expect for a diagnostic or therapeutic AI device.

However, based on the information provided, here's a breakdown of what can be extracted and what is not explicitly stated in the document regarding acceptance criteria and a study:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a formal table of acceptance criteria with corresponding performance metrics like sensitivity, specificity, accuracy, or effect sizes, as would be common for diagnostic algorithms. Instead, the "acceptance criteria" appear to be related to the verification and validation of the software itself and its consistency with the previous version. The performance is described in terms of "good compliance" with the predicate device.

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

This information is not explicitly provided in the document. The "tests for verification and validation" are mentioned, but the specific details of a "test set" (e.g., number of cases, type of data) are not described. Given that the device calculates radiation dose based on input data regarding biodistribution and relies on established models (ICRP decay data, anthropomorphic phantoms), the testing likely involved comparing output values for a range of inputs rather than a clinical dataset of patient images.

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

This information is not explicitly provided. Since the device calculates deterministic radiation doses based on models, the "ground truth" would likely be derived from established physical and biological models, rather than expert interpretation of medical images or clinical outcomes.

4. Adjudication Method for the Test Set

This information is not explicitly provided. Adjudication methods like 2+1 or 3+1 are typically used when human experts are disagreeing on interpretations for a ground truth. This is not applicable to a dose calculation software validating against established models and data.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

This information is not explicitly provided, and it is unlikely such a study was performed or needed given the nature of the device. MRMC studies are typically for diagnostic AI systems where human readers interpret medical images. This device is a software tool for calculating radiation dose.

6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The document implies that the "testing" described for verification and validation was a standalone evaluation of the algorithm's performance against its specifications and the predicate device. The comparison showing "good compliance" between OLINDA/EXM v2.0 and OLINDA/EXM v1.1 suggests an algorithm-only evaluation. However, the exact methodology is not detailed.

7. The Type of Ground Truth Used

The "ground truth" for this device likely refers to:

• Established physical and biological models: The document mentions "new human models and nuclides," "new set of decay data recommended by the International Commission on Radiological Protection (ICRP)," and "updated values of the mass of the target region (mr) recommended by the ICRP." These are the underlying scientific references against which the calculations would be validated.
• Outputs of the predicate device (OLINDA/EXM v1.1): The comparison showing "good compliance" with the predicate device implies that the predicate's outputs served as a reference for validating the new version.

8. The Sample Size for the Training Set

This information is not applicable/provided. OLINDA/EXM v2.0 is a deterministic calculation software based on established physical and biological models, not a machine learning or AI model that requires a "training set" in the conventional sense. It's a software tool that implements mathematical models and data.

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

This information is not applicable/provided for the same reasons as #8. The "ground truth" here is derived from scientific consensus and established data (e.g., ICRP recommendations) that are used as inputs or validation references for the software's calculations, not a "training set" for a learning algorithm.

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The purpose of Olinda EXM is to estimate the radiation dose received by internal organs as a result of administering a radiopharmaceutical.

The personal computer code OLINDA, which is an acronym standing for Organ Level INternal Dose Assessment/EXponential Modeling, calculates radiation doses to different organs of the body from radiopharmaceuticals which are administered systemically (mostly intravenously, but sometimes by oral or inhalation intake routes).

The provided document is a 510(k) summary for the OLINDA EXM software. It describes the software's purpose, intended use, and compares it to two predicate devices (CAMIRD and CDI3). However, it does not contain acceptance criteria or a study that directly proves the device meets specific acceptance criteria in the way typically expected for clinical performance or diagnostic accuracy studies.

Instead, the document establishes substantial equivalence by:

1. Comparing the functional equivalence of OLINDA EXM to existing predicate devices (CAMIRD and CDI3) that were legally marketed prior to the Medical Device Amendments of 1976 or were widely accepted for their purpose.
2. Highlighting improvements and additional features in OLINDA EXM over its predicates, such as a larger number of body models and improved user-friendliness, while maintaining the same core purpose and scientific basis.
3. Referencing peer-reviewed publications for the underlying scientific models, decay data, and dose factors used, demonstrating that the methodology is based on established best practices.

Therefore, many of the requested details, such as specific acceptance criteria performance metrics, sample sizes for test/training sets, expert qualifications, and adjudication methods for a direct performance study, are not present in this type of substantial equivalence submission. This is because the submission focuses on demonstrating that OLINDA EXM is as safe and effective as its predicates, rather than proving a specific diagnostic accuracy or clinical performance metric against a defined threshold.

Here's an attempt to answer the questions based only on the provided text, acknowledging the limitations:

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned, there are no explicit "acceptance criteria" defined in terms of specific performance metrics (e.g., sensitivity, specificity, accuracy) or a direct study demonstrating the device meets those criteria. Instead, the "acceptance" is based on demonstrating substantial equivalence to predicate devices, implying similar functionality and the use of accepted scientific methodologies. The table below summarizes the comparison to predicate devices, which serves as the basis for "performance" in this context.

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

• Sample Size: Not applicable. This is not a study testing the device's diagnostic accuracy or clinical performance against a patient dataset. The "test" is a comparison to predicate devices and the underlying scientific literature.
• Data Provenance: Not applicable. The "data" referenced are scientific models, decay data, and dose factors, which are from peer-reviewed literature and established dosimetry committees.

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

• Not applicable. There is no "test set" in the traditional sense of patient data requiring ground truth established by experts. The "ground truth" for the dose calculations is the established scientific methodology (MIRD method) and published dose factors/decay data, which are derived from comprehensive research and peer review by the international dosimetry community.

4. Adjudication Method for the Test Set

• Not applicable. There was no clinical or diagnostic accuracy test set 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. OLINDA EXM is dosimetry calculation software, not an AI-assisted diagnostic device. Therefore, an MRMC study is not relevant.

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

• Yes, implicitly. The entire submission describes the standalone performance of the OLINDA EXM algorithm in calculating radiation doses based on user input. Its "performance" is evaluated by its adherence to established scientific methods (MIRD) and its ability to replicate or improve upon the functionalities of predicate devices. The outputs (dose per unit input) are the direct result of the algorithm's calculations.

7. The type of ground truth used

• The "ground truth" is based on expert consensus on scientific principles and established physical models within the field of medical internal radiation dosimetry. This includes:
  • The MIRD (Medical Internal Radiation Dose) Pamphlets, which provide standard methodology (Loevinger et al. 1988).
  • Specific absorbed fractions (SAF) for various organs, derived from Monte Carlo simulations using anatomical models (phantoms) like those established by Cristy and Eckerman (1987) and Stabin et al. (1995).
  • Peer-reviewed decay data for radiopharmaceuticals (Stabin and da Luz 2002) and dose factors (Siegel and Stabin 2003).
  • Recommendations from the International Commission on Radiological Protection (ICRP Publication 60, 1991) for radiation weighting factors.

8. The sample size for the training set

• Not applicable. This software uses deterministic physical models and pre-calculated data; it is not a machine learning or AI model trained on a specific dataset. The underlying physics models and parameters are "derived" from extensive research rather than "trained" in the AI sense.

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

• Not applicable for a training set. The "ground truth" for the underlying physical models and data integrated into the software was established through decades of scientific research, experimental measurements, Monte Carlo simulations, and peer-reviewed publications by the international dosimetry community, as referenced in the document.

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