(176 days)
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:
- 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.
- 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.
- 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.
| Feature | Predicate: CAMIRD (Performance) | Predicate: CDI3 (Performance) | OLINDA/EXM (Performance) | Discussion (Equivalence/Improvements) |
|---|---|---|---|---|
| Indications for Use | Estimates absorbed doses to several tissues of a reference patient for a specified radiopharmaceutical dosage. | Estimates absorbed doses to various tissues of a reference patient for specified X-ray procedures. Calculates a "cancer detriment index." | Estimates absorbed doses to several tissues of a reference patient for a specified radiopharmaceutical dosage. (Does NOT calculate "cancer detriment index," but calculates equivalent dose via ICRP radiation weighting factors). | Equivalent in core dose estimation; OLINDA/EXM focuses on radiopharmaceuticals vs. X-ray for CDI3, and does not have the "cancer detriment index" of CDI3. |
| Target Population/Models | Models of an average individual (reference adult male). | Models of average human body "phantom." | Models of average individuals. 10 models available (e.g., adult male, female, 5-year-old, 6-month pregnant woman). Permits varying mass of individual organs for limited patient-specificity. | Equivalent, but OLINDA/EXM has a larger number of phantoms and limited patient-specificity. |
| Design/Algorithm | MIRD method (Loevinger et al. 1988). User specified radiopharmaceutical kinetic parameters and previous Monte Carlo calculated organ contributions. | X-ray examination input parameters combined with previous Monte Carlo calculations of dose per unit input. Algorithm given in Rosenstein (1976). | MIRD method (Loevinger et al. 1988). User specified radiopharmaceutical kinetic parameters and previous Monte Carlo calculated organ contributions. | CAMIRD and OLINDA/EXM use the same MIRD method. CDI3 used a different algorithm for X-ray dosimetry. All use Monte Carlo based calculations. |
| Input/Output | Input: Radionuclide, body model, radiopharmaceutical biokinetics. Output: Dose per unit input. | Input: X-ray Spectra data, Exposure parameters, Projection parameters. Output: Dose to organs in mrad. | Input: Radionuclide, body model, radiopharmaceutical biokinetics. Output: Dose to organs in mSv/MBq and rem/mCi. | OLINDA/EXM and CAMIRD have essentially equivalent input/output for internal dosimetry. CDI3 is for X-ray dosimetry. |
| User Experience/Human Factors | Simpler system, Fortran IV, input driven program. Descriptive paper available. | DOS-based, input driven program. User's manual published by FDA. | User friendly, event driven. Communication tools for error prevention (error messages, help files, user manual, installation tests). Open literature publication in preparation; based on MIRDOSE code (Stabin 1996). | OLINDA/EXM is described as more user-friendly and having more robust error prevention (relative to both predicates). |
| Anatomical Sites | Fewer organs in output (e.g., Adrenals, Fat, Blood, ovaries, Skin, Uterus, Lower Large Intestine). | Fewer organs in output (e.g., lungs, active bone marrow, ovaries, testes, thyroid, uterus, total trunk, breasts). | More tissues included (e.g., Adrenals, Brain, Gall Bladder Wall/Cont, Lower Large Intestine Wall/Cont, Small Intestine, Stomach Wall/Cont, Upper Large Intestine Wall/Cont, Heart Wall/Cont, Kidneys, Liver, Lungs, Spleen, Pancreas, Prostate, Skeleton, Active Marrow, Skin, Thyroid, Thymus, Testes, Urin.Bl. Wall/Cont, Whole Body). | OLINDA/EXM includes a significantly greater number of anatomical sites for dose calculation. |
| Scientific Basis | MIRD method (Loevinger et al. 1988), dose factors from Cristy and Eckerman (1987), Stabin et al. (1995). | Algorithm given in Rosenstein (1976). | MIRD system (Loevinger et al. 1988). Decay data (Stabin and da Luz 2002); Dose factors (Siegel and Stabin 2003); Phantoms (Cristy and Eckerman 1987, Stabin et al. 1995). All extensively peer-reviewed and widely accepted. | All programs are based on established scientific best practices, with OLINDA/EXM referencing more recent and comprehensive peer-reviewed data. |
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.
§ 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).