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Mobius3D software is used for quality assurance, treatment plan verification, and patient alignment and anatomy analysis in radiation therapy. It calculates radiation dose three dimensionally in a representation of a patient or a phantom. The calculation is based on read-in treatment plans that are initially calculated by a treatment planning system, and may additionally be based on external measurements of radiation fields from other sources such as linac delivery log data. Patient alignment and anatomy analysis is based on read-in treatment planning images (such as computed tomography) and read-in daily treatment images (such as registered cone beam computed tomography).

Mobius3D is not a treatment planning system. It is to be used only by trained radiation oncology personnel as a quality assurance tool.

Mobius3D is a software product used within a radiation therapy clinic for quality assurance and treatment plan verification. It is important to note that while Mobius3D operates in the field of radiation therapy, it is neither a radiation delivery device (e.g. a linear accelerator), nor is it a Treatment Planning System (TPS). Mobius3D cannot design or transmit instructions to a delivery device, nor does it control any other medical device. Mobius3D is an analysis tool meant solely for quality assurance (QA) purposes when used by trained medical professionals. Being a software only QA tool, Mobius3D never comes into contact with patients.

It appears there's a misunderstanding based on the provided document. The request asks for acceptance criteria and a study that proves the device meets those criteria, including specifics like sample sizes, expert qualifications, and ground truth establishment.

However, the provided FDA 510(k) clearance letter for Mobius3D (4.1) does not contain the detailed performance study results that would prove the device meets specific acceptance criteria.

The 510(k) summary (pages 5-7) primarily discusses:

• Device Description and Intended Use: What Mobius3D is and what it's used for (QA, treatment plan verification, patient alignment).
• Comparison to Predicate Device: How Mobius3D 4.1 differs from 4.0.
• Summary of Performance Testing (Non-Clinical):
  • Mentions software verification and validation, including unit, integration, and end-to-end testing.
  • Highlights MLC Modelling Accuracy testing comparing different Mobius3D versions, measurements, and a Treatment Planning System (Eclipse TPS 16.1).
  • States that "studies and reviews have been performed to assess the accuracy of newly introduced features and modifications" for Rapid Arc Dynamic Support and MLC Tongue and Groove Modelling.
  • Notes conformance to cybersecurity and interoperability requirements.
  • Crucially, it explicitly states: "No animal studies or clinical tests have been included in this pre-market submission." This means there isn't a human-in-the-loop study or a study directly demonstrating clinical performance against ground truth in a clinical setting.
• Use of Consensus Standards: A list of standards the device's design and evaluation conform to.
• Determination of Substantial Equivalence: Varian's conclusion that the device is substantially equivalent to the predicate.

Therefore, many of the specific details requested (Table of acceptance criteria, sample sizes for test sets, number/qualifications of experts for ground truth, adjudication methods, MRMC study, standalone performance, type of ground truth, training set sample size/ground truth establishment) are NOT present in this 510(k) clearance letter.

The letter focuses on the regulatory submission process and the FDA's determination of substantial equivalence based on the provided non-clinical testing and comparison to a predicate device. It doesn't typically include the full, detailed study reports with precise performance metrics and ground truth methodologies. Such details would typically be found in the more extensive technical documentation submitted by the manufacturer to the FDA, but they are summarized at a high level in the public 510(k) summary.

In summary, based only on the provided text, I cannot provide the detailed information requested regarding the specific acceptance criteria and the study that proves the device meets those criteria in the format you've requested. The document indicates non-clinical software testing and accuracy assessments were performed but does not provide the specific metrics or study design details for clinical performance proof.

Ask a specific question about this device

Mobius3D software is used for quality assurance, treatment plan verification, and patient alignment and anatomy analysis in radiation therapy. It calculates radiation dose three-dimensionally in a representation of a patient or a phantom. The calculation is based on read-in treatment plans that are initially calculated by a treatment planning system and may additionally be based on external measurements of radiation from other sources such as linac delivery log data. Patient alignment and anatomy analysis is based on read-in treatment planning images (such as computed tomography) and read-in daily treatment images (such as registered cone beam computed tomography).

Mobius3D is not a treatment planning system. It is only to be used by trained radiation oncology personnel as a quality assurance tool.

Mobius3D (v4.0) is a software product used within a radiation therapy clinic for quality assurance and treatment plan verification. It is important to note that while Mobius3D operates in the field of radiation therapy, it is neither a radiation delivery device (e.g. a linear accelerator), nor is it a Treatment Planning System (TPS). Mobius3D cannot design or transmit instructions to a delivery device, nor does it control any other medical device. Mobius3D is an analysis tool meant solely for quality assurance (QA) purposes when used by trained medical professionals. Being a softwareonly QA tool, Mobius3D never comes into contact with patients.

Mobius3D performs dose calculation verifications for radiation treatment plans by doing an independent calculation of radiation dose is initially calculated by a Treatment Planning System (TPS), which is a software tool that develops a detailed set of instructions (i.e. a plan) for another system (e.g. a linear accelerator) to deliver radiation to a patient. The dose calculation performed by Mobius3D uses a proprietary collapsed cone convolution superposition (CCCS) algorithm.

Mobius3D also performs dose delivery quality assurance for radiation treatment plans by using the measured data recorded in a linear accelerator's delivery log files to calculate a delivered dose. This is presented to the end user in a software component of Mobius3D called MobiusFX. The MobiusFX component is available to users through licensing as an add-on to the core Mobius3D software features.

Mobius3D performs quality assurance of a patient's alignment and anatomy analysis is based on comparison of Cone Beam Computed Tomography (CBCT) images taken immediately before treatment to the images used for treatment planning, which are typically acquired using standard Computed Tomography (CT). This analysis is presented to the end user in an add-on software module within Mobius3D called CBCT Checks.

The provided text describes the regulatory clearance of Mobius3D v4.0 and its equivalence to the predicate device Mobius3D v3.0 (K192424) for quality assurance in radiation therapy. However, it does not contain the specific acceptance criteria or the details of a study that proves the device meets those criteria, as requested.

The document states:

• "No animal studies or clinical tests have been included in this pre-market submission."
• "The predicate device was cleared based only on non-clinical testing, and no animal or clinical studies were performed for the subject device."
• "The non-clinical verification and validation data demonstrates that the subject device should perform as intended in the specified use conditions."

This indicates that the clearance was based on software verification and validation testing, and compliance with certain standards, rather than a clinical study with acceptance criteria in the manner typically associated with diagnostic or prognostic AI devices.

Therefore, many of the requested details, such as sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set details, are not present in this document.

Based on the provided text, here is what can be inferred/stated:

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

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

• Not specified. The document refers to "Software Verification and Validation Testing" and "non-clinical testing," but no details on the size or nature of data used for these tests are provided.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

• Not applicable/Not specified. The ground truth in software verification and validation would typically be established based on functional requirements, design specifications, and expected outputs, rather than expert interpretation of medical images or outcomes data.

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

• Not applicable/Not specified. This is typically relevant for studies involving human interpretation or clinical outcomes, which are not described here.

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: "No animal studies or clinical tests have been included in this pre-market submission." An MRMC study would be considered a clinical test.

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

• Yes, to the extent of "non-clinical verification and validation data." The device is a "software-only QA tool" and "an analysis tool," suggesting its performance was evaluated in a standalone capacity against its specified functional requirements. However, specific metrics of its standalone performance (e.g., accuracy against a gold standard for dose calculation) are not provided.

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

• Software functional requirements and specifications. For "Dose Calculation on CBCT," the "ground truth" for verification would likely involve comparing the software's calculated dose outputs against established physics models, phantom measurements, or validated reference calculation engines for a given input. This is inferred from the "non-clinical testing" description.

8. The sample size for the training set:

• Not specified/Not applicable for this type of submission. Mobius3D uses a "proprietary collapsed cone convolution superposition (CCCS) algorithm" for dose calculation. This is a deterministic physics-based algorithm, not typically a machine learning model that would require a "training set" in the conventional sense of AI/ML.

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

• Not applicable. As a deterministic physics-based algorithm, there isn't a "training set" with ground truth in the machine learning context. The algorithm's parameters and underlying physics models would be based on theoretical principles and empirical validation.

Ask a specific question about this device

Mobius3D software is used for quality assurance, treatment plan verification, and patient alignment and anatomy analysis in radiation therapy. It calculates radiation dose three-dimensionally in a representation of a patient or a phantom. The calculation is based on read-in treatment plans that are initially calculated by a treatment planning system and may additionally be based on external measurements of radiation fields from other sources such as linac delivery log data. Patient alignment and anatomy analysis is based on read-in treatment planning images (such as computed tomography) and read-in daily treatment images (such as registered cone beam computed tomography).

Mobius3D is not a treatment planning system. It is only to be used by trained radiation oncology personnel as a quality assurance tool.

Mobius3D (v. 3.0) is a software product used within a radiation therapy clinic for quality assurance and treatment plan verification. It is important to note that while Mobius3D operates in the field of radiation therapy, it is neither a radiation delivery device (e.g. a linear accelerator), nor is it a treatment planning system (TPS). Mobius3D cannot design or transmit instructions to a delivery device, nor does it control any other medical device. Mobius3D is an analysis tool meant solely for quality assurance (QA) purposes when used by trained medical professionals. Being a software-only QA tool, Mobius3D never comes into contact with patients.

Mobius3D performs dose calculation verifications for radiation treatment plans by doing an independent calculation of radiation dose. Radiation dose is initially calculated by a treatment planning system (TPS), which is a software tool that develops a detailed set of instructions (i.e. a plan) for another system (e.g. a linear accelerator) to deliver radiation to a patient. The dose calculation performed by Mobius3D uses a proprietary collapsed cone convolution superposition (CCCS) algorithm.

Mobius3D also performs dose delivery quality assurance for radiation treatment plans by using the measured data recorded in a linear accelerator's delivery log files to calculate a delivered dose. This is presented to the end user in a software component of Mobius3D called MobiusFX. The MobiusFX component is available to users through licensing as an add-on to the core Mobius3D software features.

Mobius3D performs quality assurance of a patient's alignment and anatomy analysis. This analysis is based on comparison of Cone Beam Computed Tomography (CBCT) images taken immediately before treatment to the images used for treatment planning, which are typically acquired using standard Computed Tomography (CT). This analysis is presented to the end user in an add-on software module within Mobius3D called CBCT Checks.

The provided text discusses the Mobius3D v3.0 device, its intended use, and its classification, but it does not include detailed information regarding specific acceptance criteria for its performance or the study that definitively proves the device meets those criteria with granular data as requested.

Here's a breakdown of what can be extracted and what is missing:

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

Missing. The document states that "Software verification and validation was conducted" and that "The non-clinical data support the safety of the device and the software verification and validation demonstrate that subject device should perform as intended in the specified use conditions." However, no specific performance metrics (e.g., accuracy, precision, sensitivity, specificity) or the acceptance thresholds for these metrics are provided.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Missing. No information on the sample size of any test sets, the origin of data, or whether it was retrospective or prospective is present.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Missing. There is no mention of ground truth establishment, experts involved, or their qualifications.

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

Missing. The document does not describe any adjudication methods.

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

Missing. The document states, "No animal studies or clinical tests have been included with this pre-market submission." This indicates that no MRMC comparative effectiveness study with human readers was conducted or submitted with this application.

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

Partially Addressed / Implied. The device, Mobius3D, is a "software product used within a radiation therapy clinic for quality assurance and treatment plan verification" that "performs dose calculation verifications" and "dose delivery quality assurance." It uses a "proprietary collapsed cone convolution superposition (CCCS) algorithm" for dose calculation. This implies that the dose calculation and QA checks are performed by the algorithm in a standalone manner, generating results for "trained radiation oncology personnel" to review. However, the exact performance metrics of this standalone algorithm are not detailed. The phrase "software verification and validation document that subject device should perform as intended" obliquely refers to studies on the algorithms performance.

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

Missing. No specific type of ground truth is mentioned. Given the nature of the device (dose calculation and QA), the ground truth for performance evaluation would likely involve highly accurate physical measurements or very precise computational models, but this is not specified.

8. The sample size for the training set

Missing. No information about a training set or its sample size is provided. The document focuses on regulatory approval based on "software verification and validation" and comparison to a predicate device.

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

Missing. As no training set is mentioned, there is no information on how its ground truth might have been established.

Summary of available information related to the "study":

The document mentions that "Software verification and validation was conducted" and that "The non-clinical data support the safety of the device and the software verification and validation demonstrate that subject device should perform as intended in the specified use conditions." This suggests that internal testing and validation activities were performed by the manufacturer.

The device is a "Special 510(k) Submission" for a "major" level of concern software device. This indicates that the review focused on demonstrating substantial equivalence to a predicate device (Mobius3D v2.2, K191761) and verifying that changes (like the introduction of the MobiusAdapt module) do not raise new questions of safety or effectiveness. Conformance to standards like IEC 62304, IEC 62366-1, and IEC 61217 is also noted.

In conclusion, while the document confirms that verification and validation were performed to support substantial equivalence, it does not provide the specific details of performance criteria, study design, sample sizes, ground truth establishment, or expert involvement that you have requested.

Ask a specific question about this device

Mobius3D software is used for quality assurance, treatment plan verification, and patient alignment and anatomy analysis in radiation therapy. It calculates radiation dose three-dimensionally in a representation of a patient or a phantom. The calculation is based on read-in treatment plans that are initially calculated by a treatment planning system and may additionally be based on external measurements of radiation fields from other sources such as linac delivery log data. Patient alignment and anatomy analysis is based on read-in treatment planning images (such as computed tomography) and read-in daily treatment images (such as registered cone beam computed tomography).

Mobius3D is not a treatment planning system. It is only to be used by trained radiation oncology personnel as a quality assurance tool.

Mobius3D (v. 2.2) is a software product used within a radiation therapy clinic for quality assurance and treatment plan verification. It is important to note that while Mobius3D operates in the field of radiation therapy, it is neither a radiation delivery device (e.g. a linear accelerator), nor is it a treatment planning system (TPS). Mobius3D cannot design or transmit instructions to a delivery device, nor does it control any other medical device. Mobius3D is an analysis tool meant solely for quality assurance (QA) purposes when used by trained medical professionals. Being a software-only QA tool, Mobius3D never comes into contact with patients.

Mobius3D performs dose calculation verifications for radiation treatment plans by doing an independent calculation of radiation dose. Radiation dose is initially calculated by a treatment planning system (TPS), which is a software tool that develops a detailed set of instructions (i.e. a plan) for another system (e.g. a linear accelerator) to deliver radiation to a patient. The dose calculation performed by Mobius3D uses a proprietary collapsed cone convolution superposition (CCCS) algorithm.

Mobius3D also performs dose delivery quality assurance for radiation treatment plans by using the measured data recorded in a linear accelerator's delivery log files to calculate a delivered dose. This is presented to the end user in a software component of Mobius3D called MobiusFX. The MobiusFX component is available to users through licensing as an add-on to the core Mobius3D software features.

Mobius3D performs quality assurance of a patient's alignment and anatomy analysis. This analysis is based on comparison of Cone Beam Computed Tomography (CBCT) images taken immediately before treatment to the images used for treatment planning, which are typically acquired using standard Computed Tomography (CT). This analysis is presented to the end user in an add-on software module within Mobius3D called CBCT Checks.

This document is a 510(k) premarket notification for the Mobius3D v2.2 software, which is used for quality assurance in radiation therapy. The submission focuses on demonstrating substantial equivalence to a predicate device (Mobius3D v2.0.0).

Based on the provided text, here's an analysis of the acceptance criteria and study information:

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

The document briefly mentions "software verification and validation" and states, "The non-clinical data support the safety of the device and the software verification and validation demonstrate that subject device should perform as intended in the specified use conditions." However, a specific table outlining acceptance criteria and reported device performance metrics is NOT provided in the given text. This information would typically be in a separate section of the 510(k) submission, not in the provided summary.

The document implicitly refers to performance related to "dose calculation verifications" and "dose delivery quality assurance" and "patient alignment and anatomy analysis," but no quantitative performance metrics or acceptance thresholds are given.

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

The document states, "No animal studies or clinical tests have been included with this pre-market submission." This indicates that the safety and effectiveness determination is based on non-clinical data, likely software verification and validation activities. Since no clinical tests were performed, there is no "test set" in the traditional sense of patient data. Therefore, questions about sample size and data provenance (country of origin, retrospective/prospective) are not applicable to this specific submission as described.

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

Since no clinical or human-in-the-loop tests were performed with a test set requiring ground truth, this information is not applicable and not provided in the document. The "ground truth" for a software QA tool like Mobius3D would likely be based on established physics principles, dose calculation standards, and comparisons to known accurate systems or phantoms.

4. Adjudication method for the test set:

Not applicable, as no external test set requiring human adjudication was used for this submission.

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 study was done. The document explicitly states, "No animal studies or clinical tests have been included with this pre-market submission." Mobius3D is described as an analysis tool for quality assurance, not a diagnostic AI system intended to assist human readers in image interpretation. Therefore, a MRMC study investigating human reader improvement with AI assistance is not relevant to the scope of this device as described.

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

While the document doesn't explicitly use the term "standalone performance study," the entire submission suggests an algorithm-only (or software-only) performance evaluation as the basis for substantial equivalence. The "software verification and validation" (V&V) would have evaluated the Mobius3D algorithm's accuracy in dose calculations and analysis functions against expected outputs, likely using simulated data, phantom data, or comparisons to established (predicate) systems.

The changes mentioned, such as "Dose Calculation Reimplemented in C++," would have necessitated thorough verification of the reimplemented algorithm's accuracy as a standalone component.

7. The type of ground truth used:

Given the nature of the device (a quality assurance tool for radiation dose calculation and patient alignment analysis) and the absence of clinical studies, the "ground truth" for the software's performance would likely be established through:

• Physics-based models and established dosimetry principles: For dose calculation verification, the ground truth would be the theoretically correct dose distribution for specific radiation fields and patient geometries.
• Phantom measurements and comparisons: Physical phantoms with known properties would be irradiated, and the measured dose (using ion chambers or film) would serve as a ground truth for comparison with the software's calculations.
• Comparison to predicate device performance: The submission directly compares Mobius3D v2.2 to Mobius3D v2.0.0, implying that the performance of the predicate serves as a benchmark for substantial equivalence.
• Known image registration accuracy standards: For patient alignment and anatomy analysis, the ground truth would relate to the accuracy of image registration algorithms against known transformations or expertly aligned images.

The document does not explicitly state the type of ground truth used, but it can be inferred from the device's function.

8. The sample size for the training set:

This is not applicable and not provided. Mobius3D, as described, performs dose calculations and analysis using a proprietary collapsed cone convolution superposition (CCCS) algorithm and image processing techniques. It is not described as a machine learning/AI model that requires a "training set" in the context of supervised learning from a dataset of clinical cases (e.g., for image classification or segmentation). The software's capabilities are based on deterministic algorithms and physics models, not trained on a large dataset of patient outcomes or expert annotations.

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

Not applicable, as there is no "training set" in the context of supervised machine learning for this device.

Ask a specific question about this device

Mobius3D software is used for quality assurance, treatment plan verification, and patient alignment and anatomy analysis in radiation therapy. It calculates radiation dose three-dimensionally in a representation of a patient or a phantom. The calculation is based on read-in treatment plans that are initially calculated by a treatment planning system, and may additionally be based on external measurements of radiation fields from other sources such as linac delivery log data. Patient alignment and anatomy analysis is based on read-in treatment planning images (such as computed tomography) and read-in daily treatment images (such as registered cone beam computed tomography).

Mobius3D is not a treatment planning system. It is only to be used by trained radiation oncology personnel as a quality assurance tool.

Mobius3D is a software product used within a radiation therapy clinic for quality assurance and treatment plan verification. It is important to note that while Mobius3D operates in the field of radiation therapy, it is neither a radiation delivery device (e.g. a linear accelerator), nor is it a treatment planning system (TPS). Mobius3D cannot design or transmit instructions to a delivery device, nor does it control any other medical device. Mobius3D is an analysis tool meant solely for quality assurance (QA) purposes when used by trained medical professionals. Being a software-only QA tool, Mobius3D never comes into contact with patients.

Mobius3D performs dose calculation verifications for radiation treatment plans by doing an independent calculation of radiation dose. Radiation dose is initially calculated by a treatment planning system (TPS), which is a software tool that develops a detailed set of instructions (i.e. a plan) for another system (e.g. a linear accelerator) to deliver radiation to a patient. The dose calculation performed by Mobius3D uses a proprietary collapsed cone convolution superposition (CCCS) algorithm.

Mobius3D also performs dose delivery quality assurance for radiation treatment plans by using the measured data recorded in a linear accelerator's delivery log files to calculate a delivered dose. This is presented to the end user in a software component of Mobius3D called MobiusFX. The MobiusFX component is available to users through licensing as an add-on to the core Mobius3D software features.

Compared to the previously cleared Mobius3D v 1.3.2 (K140660), Mobius3D v 2.0.0 contains the additional intended use of performing quality assurance of a patient's alignment and anatomy analysis. This analysis is based on comparison of Cone Beam Computed Tomography (CBCT) images taken immediately before treatment to the images used for treatment planning, which are typically acquired using standard Computed Tomography (CT). This analysis is presented to the end user in an add-on software module within Mobius3D called CBCT Checks.

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 state acceptance criteria in a quantitative, measurable format (e.g., "sensitivity must be > X%", "accuracy must be > Y%"). Instead, it describes a functional evaluation.

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

• Sample Size: "anonymized data from 22 different patients over 163 different fractions"
• Data Provenance: The document does not specify the country of origin. It states the data was "anonymized," implying it was real patient data, but it does not clarify if it was retrospective or prospective. Given it was "bench testing" and "anonymized data from 22 different patients over 163 different fractions," it is highly likely to be retrospective real-world patient data.

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

The document does not explicitly state how many experts were used or their qualifications for establishing ground truth in the "Mobius3D CBCT Module Evaluation" study. The study focuses on the module's ability to notify users of differences, not necessarily on the module's accuracy compared to expert consensus. Ground truth, in this context, might implicitly refer to the actual patient positioning/anatomical differences that the module was designed to detect, which would typically be evaluated by a medical physicist or radiation oncologist in a clinical setting, but this is not detailed.

4. Adjudication Method for the Test Set:

The document does not describe any adjudication method (e.g., 2+1, 3+1). The study's focus, as described, is on the module's ability to notify users of differences, rather than a comparison against an adjudicated "correct" answer for each case.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size:

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not reported in the provided text. The study described focuses on the standalone performance of the CBCT module ("ability to notify users") rather than comparing human readers with and without AI assistance.

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

Yes, a standalone study was done for the Mobius3D CBCT module. The "bench testing" described in "Mobius3D CBCT Module Evaluation - Patient Positioning / Anatomical Changes Bench Testing" evaluated the algorithm's performance in identifying potential patient positioning or anatomical differences without human interaction being part of the module's core evaluation. The report demonstrates the module's "ability to notify users," which indicates the algorithm itself is performing the detection and flagging.

7. Type of Ground Truth Used:

The document does not explicitly state the type of ground truth used for the CBCT module evaluation. However, based on the description ("ability to notify users to a potential patient positioning or anatomical difference"), the implied ground truth would be the actual presence of patient positioning shifts or anatomical changes between the planning CT and daily CBCTs. How this actual presence was definitively established is not detailed (e.g., an expert review of the images themselves, comparison to log files, etc.). It's likely an existing clinical assessment that the software is designed to emulate or flag.

8. Sample Size for the Training Set:

The document does not provide any information regarding the sample size used for the training set for Mobius3D or its CBCT module. It mentions the "proprietary collapsed cone convolution superposition (CCCS) algorithm" for dose calculation, which is a physics-based model, not typically "trained" on a dataset in the same way a machine learning algorithm is. For the CBCT module features, if any machine learning was used, the training data is not disclosed.

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

Since no information about a training set is provided, there is no information on how ground truth for a training set was established.

Ask a specific question about this device

Mobius3D software is used for quality assurance and treatment plan verification in radiation therapy. It calculates radiation dose three dimensionally in a representation of a patient or a phantom. The calculation is based on read-in treatment plans that are initially calculated by a treatment planning system, and may additionally be based on external measurements of radiation fields from other sources such as linac delivery log data.

Mobius3D is not a treatment planning system. It is only to be used by trained radiation oncology personnel as a quality assurance tool.

Mobius3D is a software product used within a radiation therapy clinic for quality assurance and treatment plan verification. It is important to note that while Mobius3D operates in the field of radiation therapy, it is neither a radiation delivery device (e.g. a linear accelerator), nor is it a treatment planning system (TPS). Mobius3D cannot design or transmit instructions to a delivery device, nor does it control any other medical device. Mobius3D is an analysis tool meant solely for quality assurance (QA) purposes when used by trained medical professionals. Being a software-only QA tool, Mobius3D never comes into contact with patients.

Mobius3D performs dose calculation verifications for radiation treatment plans by doing an independent calculation of radiation dose. Radiation dose is initially calculated by a treatment planning system (TPS), which is a software tool that develops a detailed set of instructions (i.e. a plan) for another system (e.g. a linear accelerator) to deliver radiation to a patient. The dose calculation performed by Mobius3D uses a proprietary collapsed cone convolution superposition (CCCS) algorithm.

Mobius3D also performs dose delivery quality assurance for radiation treatment plans by using the measured data recorded in a linear accelerator's delivery log files to calculate a delivered dose. This is presented to the end user in a software component of Mobius3D called MobiusFX. The MobiusFX component is available to users through licensing as an add-on to the core Mobius3D software features.

This document largely focuses on the regulatory approval (510(k) clearance) of Mobius3D. While it describes the device's function and intended use, it does not provide detailed information about the specific acceptance criteria, the study design, or the performance outcomes that would typically be found in a clinical or validation study report.

Therefore, I cannot provide a complete answer to your request based on the provided text. The requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth establishment for training sets is not present in this 510(k) summary and FDA letter.

Here's what I can extract and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: Not explicitly stated in the document. The document mentions "detailed technological characteristics and indications for use presented within the full set of submitted documentation for this 510(k) application support the claim that Mobius3D is substantially equivalent to the predicate devices." This implies that performance criteria were likely benchmarked against predicate devices, but the specific numerical targets are not here.
• Reported Device Performance: Not explicitly stated in the document with specific metrics or values (e.g., accuracy, precision). The document states that Mobius3D "performs dose calculation verifications for radiation treatment plans by doing an independent calculation of radiation dose" and "performs dose delivery quality assurance... by using the measured data." This describes its function, not its quantified performance against acceptance criteria.

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

• Sample Size (Test Set): Not mentioned.
• Data Provenance: Not mentioned (e.g., country of origin, retrospective/prospective).

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

• Not mentioned, as the document does not describe the establishment of ground truth for a test set in the context of device performance validation.

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

• Not mentioned.

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 mentioned. This device is described as a QA tool for radiation therapy, an "analysis tool meant solely for quality assurance (QA) purposes." It is not described as a device that directly assists human readers in interpreting images or making a diagnosis in a way that an MRMC study would typically evaluate for AI image analysis tools.

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

• The device itself is an "algorithm only" software for independent dose calculation and QA. Its performance is inherently "standalone" in its primary function of calculating dose. However, the results of its calculation are "presented to the end user" and used by "trained medical professionals." The document does not provide a specific "standalone performance study" report with metrics like accuracy or precision of its dose calculations, compared to a gold standard. It only describes what it does.

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

• Not explicitly mentioned. For a dose calculation system, ground truth would typically refer to highly accurate dosimetry measurements or a gold-standard calculation method. The document only states it performs an "independent calculation of radiation dose" using a "proprietary collapsed cone convolution superposition (CCCS) algorithm."

8. The sample size for the training set:

• Not mentioned.

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

• Not mentioned.

In summary, the provided text from the 510(k) summary and FDA clearance letter focuses on the regulatory aspects, device description, and indications for use. It lacks the technical and scientific details about validation studies, acceptance criteria, and performance results that your request pertains to. Such information would typically be found in a separate validation report or technical documentation submitted as part of the 510(k) application, but not usually in the public summary or clearance letter itself.

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