Search Results

ERGO SRS is stcreotactic radiosurgery module for DMLCIV-ERGO (K001163). It is an accessory to linear accelerators used for radiation therapy. It is indicated for use in the planning of 3 dimensional radiation therapy.

ERGO SRS is a stereotactic radiosurgery treatment planning software module for 3D Line USA's ERGO radiotherapy treatment planning system (K001163).

This 510(k) summary (K031281) for ERGO SRS, a stereotactic radiosurgery treatment planning module, does not contain the detailed acceptance criteria or study results typically found in performance studies for AI/ML-driven medical devices.

The document primarily focuses on establishing substantial equivalence to a predicate device (PLATO SRS V2) based on the fact that ERGO SRS is "identical to PLATO SRS V2. It is the same software integrated with 3D Line USA's ERGO system rather than Nucletron's PLATO system."

Therefore, most of the requested information regarding acceptance criteria, study details, sample sizes, ground truth establishment, and MRMC studies is not available in the provided text.

Here's what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance: This information is not provided in the document. The document states that the device is "identical" to the predicate, implying that its performance is presumed to be equivalent to the predicate, but no specific performance metrics or acceptance criteria are listed for the ERGO SRS device itself.

2. Sample size used for the test set and the data provenance: Not provided.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not provided.

4. Adjudication method for the test set: Not provided.

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 provided. This type of study is more common for diagnostic AI tools, whereas ERGO SRS is a treatment planning module.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not explicitly stated, however, as a treatment planning software, it is inherently a "standalone" algorithm in its function of generating plans, which are then reviewed by human clinicians. No performance metrics for this standalone function are provided in this summary.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not provided. For a treatment planning system, ground truth would typically relate to the accuracy of dose calculations, geometric accuracy of planned beams, or clinical outcomes (though outcomes data would be for post-market surveillance rather than 510(k) clearance).

8. The sample size for the training set: Not applicable/provided. This device is described as being "identical" to a previously cleared predicate and is software for treatment planning, not a machine learning model that undergoes "training" in the modern sense.

9. How the ground truth for the training set was established: Not applicable/provided.

In summary: The provided 510(k) summary primarily relies on substantial equivalence to a predicate device by stating the software is "identical" and merely integrated into a different system. It does not contain the detailed performance study results that would typically include acceptance criteria, specific performance metrics, sample sizes, or ground truth establishment methods for an independent evaluation of the ERGO SRS device's performance.

Ask a specific question about this device

The XiO RTP System is used to create treatment plans for any cancer patient for whom external beam radiation therapy or brachytherapy has been prescribed. The system will calculate and display, both on-screen and in hard-copy, either two- or three-dimensional radiation dose distributions within a patient for a given treatment plan set-up.

Optionally, the user may elect to generate plans using Dynamic Conformal Arc Therapy capability. Dynamic Conformal Arc Therapy is a treatment modality in which the gantry rotates in an arc (or multiple arcs) over user-specified angles while the leaves of a multileaf collimator (MLC) continually reshape the beam to conform to the targer.

The XiO Radiation Treatment Planning system accepts a) patient diagnostic imaging data from CT and MR scans, or from films, and b) "source" dosimetry data, typically from a linear accelerator. The system then permits the user to display and define (contour) a) the target volume to be treated and b) critical structures which must not receive above a certain level of radiation, on these diagnostic images.

Based on the prescribed dose, the user, typically a Dosimetrist or Medical Physicist can then create multiple treatment scenarios involving the type, number, position(s) and energy of radiation beams and the use of treatment aids between the source of radiation and the patient (wedges, blocks, ports, etc.). The XiO system then produces a display of radiation dose distribution within the patient, indicating not only doses to the target volume but to surrounding tissue and structures. The "best" plan satisfying the prescription is then selected, one that maximizes dose to the target volume while minimizing dose to surrounding healthy volume. The parameters of the plan are output in hard-copy format for later reference and for placement in the patient file.

This Premarket Notification addresses the addition of support for Dynamic Conformal Therapy. Dynamic Conformal is a treatment modality in which radiation beams are continuously shaped to conform to a target while the gantry rotates and the beam is on. In XiO, the user chooses the target, defines structures to avoid, optional margin(s), and treatment angles. XiO then plans a treatment over a specified arc and with specified beam increments, with the leaves of the multi-leaf collimator (MLC) continually reshaping the beam to conform to the target. The target receives a homogenous dose while the structures designated as "avoidance structures" are avoided absolutely.

Dose calculation is performed using existing, validated algorithms within XiO. Determination of dose at the specified angles is calculated in the same way as conventional and asymmetric arc beams; the calculated dynamic beam dose distribution is determined as the sum of multiple fixed beam dose distributions across the specified arc.

This submission describes the XiO Radiation Treatment Planning System with the added functionality of Dynamic Conformal Therapy. The information provided heavily emphasizes the regulatory process and comparisons to predicate devices rather than detailed performance studies with acceptance criteria.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state specific acceptance criteria in terms of numerical thresholds for dose calculation accuracy or clinical outcomes. Instead, it focuses on the device's ability to calculate dose and conform to targets.

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

• Test Set Sample Size: Not explicitly stated. The document mentions "Algorithm test cases were written and executed." The number of these test cases is not specified.
• Data Provenance: The testing was "executed in-house by CMS customer support personnel." This suggests simulated or internally generated data rather than real patient data. The country of origin is implicitly the US, where Computerized Medical Systems, Inc. is located. It was a retrospective evaluation against defined test cases.

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

• Number of Experts: Not specified. The "Algorithm test cases were written and executed" and "Clinically oriented validation test cases were written and executed" by "CMS customer support personnel." It's unclear if these personnel are qualified medical experts (e.g., medical physicists, dosimetrists) or if external experts were involved in establishing the ground truth for these test cases.
• Qualifications of Experts: Not explicitly stated. While the system's users are described as "typically a Dosimetrist or Medical Physicist," it doesn't confirm if these roles or similarly qualified individuals generated the test cases or the ground truth for them.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified. Since the testing involved "algorithm test cases" and "clinically oriented validation test cases," it's likely a comparison against predetermined correct outputs for those cases rather than an adjudication process involving multiple human observers reviewing complex real-world interpretations.

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

• No, an MRMC comparative effectiveness study was not done. The text explicitly states: "Actual testing in a clinic was not performed as part of the development of this feature." It also adds that such testing "is not required to demonstrate substantial equivalence or safety and effectiveness of the device." Therefore, there is no effect size reported for human readers improving with AI vs. without AI assistance.

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

• Yes, a standalone study was done, as far as the algorithm's performance is concerned. The text highlights "Algorithm test cases were written and executed to ensure that the system is calculating dose correctly for Dynamic Conformal beams." This "algorithm test" would represent a standalone evaluation of the core calculation engine's accuracy against predefined inputs and expected outputs, without direct human intervention in each calculation step.

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth for the "Algorithm test cases" would likely be pre-calculated, theoretical, or established results from known physics principles or established algorithms for radiation dose calculation under specific, controlled parameters. For "Clinically oriented validation test cases," the ground truth would similarly be pre-defined correct treatment plans or dose distributions established by medical physicists/dosimetrists for those specific clinical scenarios. It is not pathology, expert consensus on patient images, or outcomes data.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable/Not provided. Radiation Treatment Planning (RTP) systems like XiO, particularly from this era (2003), typically rely on deterministic physical algorithms for dose calculation rather than machine learning models that require training data sets in the conventional sense. The "algorithms" mentioned are likely physics-based models rather than AI models.

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

• Ground Truth for Training Set: Not applicable. As mentioned above, this system likely operates on deterministic algorithms rather than machine learning, so there isn't a "training set" or corresponding ground truth in the AI context. The algorithms themselves would have been developed and validated against established physics principles and possibly empirical measurements (though those details are not in this summary).

Ask a specific question about this device

EVTOOL software module provides the ability to compare and evaluate the radiation dose delivery to the tumor volume and surrounding organs from generated dose volume histograms and radiobiological values. It expands the DMLC IV-ERGO system, which is a combination of a radiation collimator with multiple tungsten leaves that move during delivery of radiation therapy and a computer based treatment planning and control system.

EVTOOL is a software module that has been designed to expand the features and functions of the DMLC IV- ERGO treatment planning software. The software runs on a silicon graphics workstation and Irix operating system. EVTOOL software is used for comparing and evaluating radiation therapy treatment plans from a quantitative and radiobiological point of view. The software displays one or more stored plans for comparison and analysis. It can display the dose volume histograms of the various plans and organ dose statistics (mean, modal, maximum and minimum dose). It allows the user to input radiobiological corrections in order to enhance the evaluation of the treatment plan. It also optimizes the dose prescription by displaying reference dose and number of treatment fractions. EVTOOL is fully integrated into the ERGO treatment planning environment in order to easily exchange information from the patients' database. The patient information is selected and automatically loaded into the EVTOOL software. From the patient database the user can select one or multiple treatment plans to display and calculate the dose statistics, including dose volume histograms and radiobiological models. The analytical information is displayed in 4 windows with a zoom capability. These windows can display the overall plan and individual organs of interest. EVTOOL provides options for incorporating radiobiological corrections to assist the physician in determining the optimal dose prescription and fractionation based on TCP (Tumor Control Probability), NTCP (Normal Tissue Complication Probability) and UTCP (Uncomplicated Tumor Control Probability) values. This software is a useful tool in evaluating the entire volumetric treatment plan, it is not used to directly treat the patient. It provides the physician with a tool to compare various plan versions side by side in order to determine the most appropriate treatment plan to be used with the DMLC IV equipment. The display of the treatment plans within EVTOOL provides a permanent record and effective control on the actual dose delivered to the patient.

The provided text is a 510(k) Premarket Notification for the EVTOOL software. This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, not for proving a device meets specific acceptance criteria through a clinical study with performance metrics. Therefore, many of the requested details about acceptance criteria and study design are not present in this document.

Here's an attempt to answer the questions based only on the provided text, noting where information is not available:

1. Table of Acceptance Criteria and Reported Device Performance

This document does not define specific quantitative "acceptance criteria" or report "device performance" in terms of clinical outcomes or diagnostic accuracy. The core of this 510(k) is to demonstrate substantial equivalence to a predicate device for its intended use as a radiation therapy planning assessment tool.

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

• Sample Size: Not applicable. This document does not describe a clinical performance study with a test set of patient data to evaluate device performance against ground truth. It describes a software module.
• Data Provenance: Not applicable.

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

• This information is not provided. The document does not detail a study involving expert-established ground truth.

4. Adjudication method for the test set

• This information is not provided.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and what was the effect size of how much human readers improve with AI vs without AI assistance

• No MRMC comparative effectiveness study is mentioned or implied in this document. The EVTOOL is described as a tool to assist physicians in evaluating treatment plans, not necessarily as an AI system designed to improve human reader performance in a diagnostic sense in this context.

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

• No standalone performance study is mentioned. The device is a "software module" that "provides the physician with a tool to compare various plan versions." It's explicitly stated, "it is not used to directly treat the patient."

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

• Not applicable. The document does not describe a study requiring ground truth for performance evaluation. The "ground truth" for this type of software would typically be the accuracy of its calculations and displays based on established physics and radiobiology models, which would be validated through software testing processes, not clinical studies with patient outcomes.

8. The sample size for the training set

• Not applicable. This document describes a software module for radiation therapy planning evaluation, not a machine learning or AI algorithm that requires a training set.

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

• Not applicable.

Ask a specific question about this device