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PLANET Onco Dose is a standalone software intended to manage, process, display and analyze anatomical and functional images. It provides tools and functionalities to assist in medical diagnosis and therapy response assessment, to assist in the contouring of regions of interest, and to assist in internal dosimetry computation for radionuclide based therapies. The modalities of these medical imaging systems include CT, MRI, SPECT, PET, XA, planar scintigraphy, RT Struct and RT Dose as supported by ACR/NEMA DICOM 3 standard format.

PLANET Onco Dose is intended for retrospective determination of dose only and should not be used to deviate from approved radioactive products, product dosing and administration instructions.

PLANET Onco Dose is dedicated to be used by qualified medical professionals in Molecular Imaging, and/or Medical Oncology.

PLANET Onco Dose provides the User with the means to segment structures in medical image volumes by providing dedicated delineation, contouring and propagation tools for both tumors and normal tissues (i.e. Regions of Interest (ROI)).

PLANET Onco Dose provides tools to display, co-register (rigid and deformable), perform quantification for assessment and response evaluation of patients undergoing a course of oncology treatment.

PLANET Onco Dose allows import / export of results (contours and dosimetries) to / from any DICOM compliant system (e.g. Treatment Planning Systems, PACS).

PLANET Onco Dose allows to compute in 3D at the radiation doses received by tissues as a result of radionuclide administration. Dose can be computed with or without tissue density correction using two models depending on considered isotopes.

PLANET Onco Dose provided the User with the means to perform modeling of absorption and elimination kinetics of Radiopharmaceutical Therapy (RPT). Time-integrated activity and dose rate can be calculated from three kinds of clinical setups involving full 3D image acquisitions, hybrid 2D/3D image acquisitions and single time point approaches.

PLANET Onco Dose supports isotopes with beta and gamma contributions.

PLANET Onco Dose provides tools for dosimetry comparison for sequential treatments and for dosimetry summation.

PLANET Onco Dose is a software platform dedicated to medical diagnosis aid, contouring, internal dosimetry computation and therapy response assessment, using molecular imaging modalities.

PLANET Onco Dose is a modular software suite composed of three elements:
. PLANET - Core System: reviewing, fusion and registration of multi-modal anatomical (computed tomography (CT), magnetic resonance imaging (MRI), X-ray angiography (XA)) and functional (positron emission tomography (PET), single photon emission computed tomography (SPECT), planar scintigraphy) series;
. PLANET Onco - Oncology Module: contouring of region of interest, tumor segmentation, quantification, therapy response assessment;
. PLANET Dose - Dosimetry Module: pharmacokinetics modeling and internal dosimetry computation for locally regulatory approved pharmaceuticals.

The provided document describes the PLANET Onco Dose (3.2) software, intended for medical image management and processing, dosimetry computation, and therapy response assessment. While it details the device's intended use, technological comparisons, and that performance testing was conducted, it does not provide specific acceptance criteria or the numerical results of performance, functional, or algorithmic testing.

Therefore, I cannot populate the table or answer most of the questions using only the provided text.

Here's what can be extracted and what information is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Test Set Sample Size: Not specified.
• Data Provenance: Not specified. The document states "validation activities under clinically representative conditions" but does not detail the origin (e.g., country, hospital, retrospective/prospective) of the data used for actual testing.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

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

• Not specified.

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:

• Not specified. The document mentions "The critical evaluation of the relevant scientific literature confirms that the choices made for the TRT dosimetry computation methods implemented within PLANET Onco Dose are those recommended by the scientist international community," which might imply comparisons, but it doesn't describe an MRMC study related to human performance improvement with AI assistance for PLANET Onco Dose (3.2) itself.

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

• Yes, implicitly. The document states, "PLANET Onco Dose was submitted to performance, functional and algorithmic testing," and later, "The performance obtained by the demonstration of performances lead to clearly define the area of application of the various internal dosimetry methods." The comparison of its dose computation algorithms with Monte Carlo methods also suggests standalone algorithmic evaluations. However, specific standalone performance metrics are not provided.

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

• Not explicitly stated for all tests. For the dosimetry comparison, it mentions "Dose computation algorithms available in PLANET Onco Dose were compared with Monte Carlo method and the results showed consistency between evaluated methods." This implies Monte Carlo results may have been used as a reference/ground truth for dosimetry algorithm validation. For other functionalities like contouring, it's not specified how ground truth was established, but typically this would involve expert consensus on medical images.

8. The sample size for the training set:

• Not specified. The document does not describe a training set, as it focuses on the performance and validation of the software. This suggests it's likely a rule-based or conventional algorithmic software rather than a deep learning AI model that requires a distinct training phase.

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

• Not applicable/Not specified, as no training set is described.

Summary of Device and Study Information from the Document:

PLANET Onco Dose (3.2) is a standalone software for managing, processing, displaying, and analyzing anatomical and functional images. It assists in medical diagnosis, therapy response assessment, contouring of regions of interest, and internal dosimetry computation for radionuclide-based therapies.

Key Study Information:

• Testing Conducted: Performance, functional, and algorithmic testing, risk management assessment (including cybersecurity), and validation activities under clinically representative conditions.
• Workflows Covered: Standard SIRT, Full SPECT/CT pharmacokinetics for MRT, 2D/3D hybrid pharmacokinetics for MRT, Single time point pharmacokinetics for MRT.
• Dosimetry Algorithm Comparison: PLANET Onco Dose's Voxel S Value dose kernel convolution algorithm and local energy deposition algorithm were compared with the Monte Carlo method, showing "consistency."

The document concludes that the results demonstrate the safety and effectiveness of PLANET Onco Dose (3.2) and that it is substantially equivalent to its predicate devices (PLANET Onco Dose (3.1) and Torch™). However, it lacks the quantitative results of these tests and the specifics of the methods (e.g., sample sizes, expert qualifications) used to establish ground truth or evaluate performance against acceptance criteria.

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ThinkQA Edition 2 software is used to verify that the dose distribution calculated by a treatment planning system for external beam radiation therapy is consistent with treatment plan parameters.

Based on read-in treatment plan data, ThinkQA Edition 2 re-calculates a dose distribution in a three-dimensional representation of a patient or a phantom and provides dose-volume indicators which compare it to the initial dose distribution calculated by the treatment planning system.

ThinkQA Edition 2 is not a treatment planning system. It is a Quality Assurance software only to be used by qualified and trained radiation therapy personnel.

ThinkQA Edition 2 is a standalone software device used within a radiation therapy clinic which is designed to perform secondary dose calculation based on DICOM RT treatment plan data provided by a treatment planning system.

ThinkQA Edition 2 is only meant for quality assurance purpose. It cannot define or transmit any instructions to a delivery device, nor does it control any other medical device.

ThinkQA Edition 2 performs dose calculation verifications for radiation therapy plans by doing an independent calculation of dose distribution in a three-dimensional representation of a phantom. Dose distribution is initially calculated by a treatment planning system which is a software tool that allows to define and transmit treatment plan parameters that will further be used for treatment delivery. Based on treatment plan parameters, ThinkQA Edition 2 re-calculates dose distributions using a proprietary Collapsed Cone Convolution algorithm. It uses CT images (real patient anatomy) to perform dose computation with Collapsed Cone Convolution.

ThinkQA Edition 2 compares the reference TPS dose distribution with its own calculation using specific indicators such as 3D gamma agreement index on significant volumes. ThinkQA Edition 2 computes Gamma Passing Rate for automatic dose areas and anatomical structures: Planning Target Volumes (PTVs) and Organs at Risk (OARs).

Based on these indicators, ThinkQA Edition 2 displays a pass/fail status that informs the user whether or not the acceptance criteria that he has defined are met. The acceptance criteria does not give in any way information that could be used to determine whether or not the treatment plan is clinically relevant. It just evaluates the consistency between treatment plan parameters and the dose distribution computed by the TPS.

ThinkQA Edition 2 has been designed to be compatible with radiotherapy adaptative workflows. This includes a number of mandatory features:

• User interface design, grouping verifications for adaptive plans under a single primary plan verification; .
• . Automatic computation upon reception of DICOM data from the TPS;
• Sufficient speed of computation, compatible with adaptive workflow with patient waiting on couch.

The performance of ThinkQA Edition 2 makes it suitable for the following photon treatment delivery techniques: Static beams, IMRT Step & Shoot, Dynamic IMRT with fixed gantry and Rotational IMRT (VMAT).

In order to guaranty the independence of the secondary dose check, the beam models are not intended to be adjusted to match the user's reference TPS. The user only provides its actual measured dose rate in reference conditions and HU-density conversion table.

ThinkQA Edition 2 runs on workstations or virtual machines with Linux CentOS 7 operating system. Its web interface is accessible from any system supporting the specified in chapter ThinkQA Edition 2 web application. ThinkQA Edition 2 is able to communicate with other equipment installed on the network complying with the DICOM and DICOM RT industry standards.

The FDA 510(k) summary for ThinkQA (Edition 2) describes a software device for quality assurance in radiation therapy. The document outlines comparisons to a predicate device (MU2net) and evidence for substantial equivalence, including performance evaluations.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a formal "acceptance criteria" table with specific quantitative thresholds that the device had to meet for its performance evaluation, nor does it provide detailed numerical outputs beyond qualitative statements. However, it implicitly defines a performance expectation related to dosimetric evaluation:

2. Sample Size for the Test Set and Data Provenance

• Test Set Sample Size: The document refers to "a large variety of plans" for the dosimetric evaluation, but a specific number is not provided. For the beam modeling unique to this submission, there were "three beam qualities (6 MV, 6 MV FFF and Elekta Unity 7 MV FFF) and two primary TPS (RayStation and Monaco)."
• Data Provenance: The document does not specify the country of origin for the data or whether the studies were retrospective or prospective. It implies the data was generated internally for testing and evaluation purposes. The "measured depth dose curves and profiles" suggest real-world or phantom measurements were performed.

3. Number of Experts and Qualifications

• Number of Experts: Not explicitly stated. The studies were likely conducted by the manufacturer's internal team, including physicists and engineers specialized in medical physics and radiation therapy.
• Qualifications of Experts: Not explicitly stated, but the context implies expertise in radiation oncology physics, treatment planning systems, and dose calculation algorithms ("qualified and trained radiation therapy personnel"). The mention of "AAPM working group 219" recommendations suggests adherence to professional standards in radiation oncology physics.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable in the traditional sense of human interpretation of results. The device's performance was evaluated against physical measurements and established dosimetric metrics (e.g., gamma index passing rate, dose difference). The comparison to the predicate device acted as a form of "adjudication" for decision consistency.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• MRMC Study: No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed. This device is a quality assurance software that performs an objective, mathematical comparison of dose distributions rather than aiding human readers in diagnosis or interpretation that would necessitate an MRMC study. Its purpose is to verify consistency based on defined parameters, not to improve human diagnostic performance.

6. Standalone (Algorithm Only) Performance

• Standalone Performance: Yes, the described performance evaluation (dosimetric evaluation, beam modeling) is a standalone assessment of the algorithm's ability to calculate dose distributions and compare them to reference data. The device's output (gamma passing rate, pass/fail status) is based solely on its internal calculations and comparisons, without human intervention in the calculation or the determination of the result itself. Human users then interpret this output.

7. Type of Ground Truth Used

• Ground Truth Type:
  • Measured Data: For beam modeling, the ground truth was "corresponding measured depth dose curves and profiles," indicating physical measurements.
  • Reference Treatment Planning System (TPS) Dose Distribution: For the clinical performance evaluation and comparison, the ground truth was implicitly the dose distribution calculated by the "reference TPS" (RayStation and Monaco), against which ThinkQA's calculations were compared using metrics like the gamma index.
  • Predicate Device Output: For consistency checks, the "decision" (validation or rejection) of the predicate device (MU2net) served as a comparative ground truth.

8. Sample Size for the Training Set

• Training Set Sample Size: The document does not explicitly discuss a separate "training set" in the context of a machine learning model, as the dose calculation for ThinkQA Edition 2 is based on a "proprietary Collapsed Cone Convolution algorithm" and beam models, rather than a data-driven machine learning approach that would necessitate a distinct training phase with labeled data in the same way. The beam modeling process involves systematic adjustments and evaluations, which could be considered an iterative tuning or "training" specific to dose calculation, but a specific "training set size" is not applicable in the typical AI/ML sense.

9. How Ground Truth for the Training Set Was Established

• Ground Truth for Training Set Establishment: Since the core dose calculation algorithm (Collapsed Cone Convolution) is a physics-based model, it does not rely on labeled training data in the way a machine learning algorithm would. The "beam modeling process" involved:
  • Comparison of computed depth dose curves and profiles against "measured depth dose curves and profiles." These physical measurements serve as the ground truth for calibrating and validating the accuracy of the beam models within the CCC algorithm for different beam qualities and TPS.
  • The goal was for the beam models to be independently accurate and not necessarily "adjusted to match the user's reference TPS" to maintain calculation independence.

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EPIgray is a software to be used by radiation oncologist and medical physicist to detect errors in the delivery of high energy X-rays during the course of patient treatment. This product verifies if the reconstructed dose, computed by the system, is in agreement with the planned dose given by the treatment planning system. This product uses the measurements performed by an Electronic Portal Imaging Device (EPID). This product uses the prescription computed by the treatment planning system. This product in not used to give a prescription of the radiation therapy.

EPIgray is comprehensive software that allows the user to perform an in-vivo dosimetry by means of imaging device such as an Electronic Portal Imaging Device (EPID). The product is composed of: EPIgray workstation and In-Vivo Manager tool. Epigray workstation is an extension of an already cleared product: ISOgray planning system (K103146). It uses only two modules of the previously approved system: Information module and Exacor module. In Vivo manager software is a year application intended for in-vivo measurements management. In particular, it allows to retrieve, on a web browser, the result of dose reconstruction by EPIgray workstation based on EPID.

The provided text is a 510(k) premarket notification for DOSIsoft's EPIgray software. It outlines the device's description, intended use, and substantial equivalence to a predicate device. However, it explicitly states that clinical trials were not performed, and therefore, an acceptance criteria table and a comprehensive study demonstrating direct device performance against such criteria are not provided in the document.

The document focuses on non-clinical verification and validation testing to ensure the system works according to requirements, rather than a clinical study with detailed performance metrics.

Here's an analysis of the requested information based on the provided text:

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

This information is not available in the provided text. The document states: "Clinical trials were not performed as part of the development of this product." and "However, algorithm evaluation was performed by Medical Physicists team using measured data in a clinical facility. Evaluation summary is available in tab 13 of this submission." Without access to "tab 13," specific acceptance criteria and reported device performance metrics cannot be tabulated.

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "measured data in a clinical facility" was used for algorithm evaluation, but the size of this dataset is not specified.
• Data Provenance: "measured data in a clinical facility" suggests clinical data, likely retrospective, given no clinical trials were performed. The country of origin is not specified, but since the manufacturer is based in France and the evaluation was done by a "Medical Physicists team," it could be from a French clinical facility or an unspecified international setting.

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

• Number of Experts: Not explicitly stated. The evaluation was performed by a "Medical Physicists team," which implies more than one expert, but an exact number is not given.
• Qualifications of Experts: "Medical Physicists team." Their specific experience (e.g., years of experience) is not mentioned.

4. Adjudication method for the test set:

Not applicable/Not mentioned. Since the evaluation involved a "Medical Physicists team" working with "measured data," it's more likely they were assessing algorithmic accuracy against physical measurements/expected dose rather than adjudicating discrepancies in expert interpretations. No specific adjudication method (like 2+1 or 3+1) is described.

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. The document explicitly states: "Clinical trials were not performed." Therefore, no MRMC comparative effectiveness study was conducted to assess human reader improvement with AI assistance. The intended use of EPIgray is described as a software for error detection and dose reconstruction, which implies a standalone function that outputs warnings, not directly a tool for human readers to improve their diagnostic accuracy in a MRMC setting.

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

Yes, implicitly. The algorithm evaluation by the Medical Physicists team using measured data in a clinical facility suggests a standalone performance assessment. The device's function is described as using EPID images to reconstruct dose and compare it to the planned dose, activating warnings. This is an algorithm-only function without explicit human-in-the-loop performance being evaluated in this submission.

7. The type of ground truth used:

The ground truth appears to be based on physical measurements and planned dose data. The device reconstructs the dose (based on EPID images) and compares it to the "planned dose given by the treatment planning system." The "algorithm evaluation was performed by Medical Physicists team using measured data," suggesting that these measurements (likely independent dosimetry measurements or precise EPID measurements used as a reference) served as a form of ground truth for assessing the accuracy of the reconstructed dose.

8. The sample size for the training set:

Not mentioned. The document focuses on the evaluation (test) phase and does not provide details regarding the training set's sample size.

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

Not mentioned. As the document doesn't discuss the training set, there's no information on how its ground truth was established.

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