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510(k) Data Aggregation
(26 days)
Adaptiiv Medical Technologies, Inc.
TrueFit/TrueFlex Bolus is indicated for and intended to be placed on the patient's skin as an accessory to attenuate and/or compensate the external beam (photon or electron) radiation during the treatment of various types of cancer.
The device is for a single patient's use only and can be reused throughout the entirety of the treatment course.
The device is designed by the radiation therapy professional using patient imaging data as input and must be verified and approved by the trained radiation therapy professional prior to use.
The device is restricted to sale by on the order of a physician and is by prescription only.
TrueFit/TrueFlex Bolus is a 3D printed patient-matched radiation therapy accessory that expands the application of external beam radiation therapy by providing a patient-specific fit.
Patient imaging data from the treatment planning system (TPS) are used as inputs to generate digital design of the radiation therapy bolus (TrueFlex) by 3D Bolus Software Application (K213438), previously developed by Adaptiv. The resulting output Stereolithography (STL) file is compatible with the third-party 3D printers. A TrueFit Bolus is 3D printed by MJF technology using polyamide or polyurethane material. A Final TrueFlex Bolus device is manufactured by filling a mould with silicone.
The bolus is used in radiation therapy when a patient requires the total prescription dose to be delivered on or near the skin surface. The bolus acts as a tissue-equivalent material placed on the patient skin to account for the buildup region of the treatment beam.
This document, a Special 510(k) Summary for K243057, does not contain the detailed information necessary to fully answer all aspects of your request regarding acceptance criteria and a study proving the device meets those criteria. The provided text is a regulatory submission focused on demonstrating substantial equivalence to a predicate device rather than a comprehensive report of a clinical performance study.
However, I can extract and present the information that is available within the document:
1. A table of acceptance criteria and the reported device performance
The document mentions "acceptable spatial fidelity" and "acceptable physical and radiological properties" as performance outcomes, but it does not specify quantitative acceptance criteria for these. It states that tests "verified that the chosen methods performed as intended" and "did not affect the overall safety and effectiveness of the device."
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Spatial fidelity ensuring precise fit and accurate radiation delivery | Acceptable spatial fidelity |
| Physical and radiological properties enabling use during radiation therapy treatment according to the plan | Acceptable physical and radiological properties |
| Safety and effectiveness comparable to predicate device | Performance testing results demonstrate substantial equivalence to the predicate device (K213438) and are considered as evidence of the overall safety and effectiveness of the device. |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample size: The document states "worst-case geometrical test samples and real-patient final devices" were used for Verification and Validation activities. It does not provide a specific number for the sample size.
- Data provenance: Not specified.
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)
This information is not provided in the document. The general indication statement mentions that "the device is designed by the radiation therapy professional using patient imaging data as input and must be verified and approved by the trained radiation therapy professional prior to use." This refers to the clinical use process, not the establishment of ground truth for device testing.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not provided in the document.
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
This document describes a medical device (TrueFit Bolus, TrueFlex Bolus) which is a 3D-printed accessory for radiation therapy, applied to the patient's skin. It is not an AI-powered diagnostic or decision support software. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not applicable to this device type.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The device itself is a physical bolus. Its design process involves software (3D Bolus Software Application - K213438), which generates a digital design, and then a physical product is manufactured. The software component, by its nature, is "standalone" in generating the STL file, but the overall product (the bolus) is applied by a human and is a physical accessory designed to interact with external beam radiation. The document focuses on the physical and radiological properties of the manufactured bolus rather than the performance of an algorithm in isolation for diagnostic or interpretive tasks.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The document focuses on "acceptable spatial fidelity" and "acceptable physical and radiological properties." Ground truth for these aspects would typically involve:
- Precise measurements of the 3D printed objects against the digital design for spatial fidelity.
- Laboratory measurements of material density, Hounsfield units (for radiological properties), and physical characteristics (e.g., flexibility, rigidity) for physical/radiological properties.
The document does not detail the specific ground truth methods or references.
8. The sample size for the training set
This information is not applicable and is not provided. This is a medical device clearance document for a manufactured product, not an AI/machine learning model where a training set size would be relevant. The "design" of the bolus is based on patient imaging data as input to software, but the software itself (K213438) has been previously developed, and details of its training (if applicable, as it's not explicitly stated to be an AI/ML product) are not covered here.
9. How the ground truth for the training set was established
Not applicable, as it's not an AI/ML model for which a training set and its ground truth would be described in this context.
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(112 days)
Adaptiiv Medical Technologies, Inc.
Nova Surface Applicator is indicated for and intended to be placed on the patient's skin to navigate an HDR radiation source during the treatment of various types of cancer using brachytherapy.
The device is for a single patient's use only and can be reused throughout the entirety of the treatment plan.
The device is designed by radiation therapy professionals using patient imaging data as input and must be verified and approved by the trained radiation therapy professional prior to use.
The device is restricted to sale by or on the order of a physician and is by prescription only.
Adaptiv's Nova Surface applicator is a 3D printed patient-matched radiation therapy accessory that expands the application of brachytherapy by providing a patient-specific fit and catheter trajectory design.
Patient imaging data from the treatment planning system (TPS) are used as inputs to generate digital design of the surface brachytherapy applicator by 3D Brachy Software Application (K213438), previously developed by Adaptiv. The resulting output Stereolithography (STL) file is compatible with the third-party 3D printers.
Nova Surface applicator navigates a radiation source toward tumors located closely to or on the surface of the body (e.g. skin cancers). It fits the patient's anatomy by means of a patient-specific contact surface ensuring that optimal dose is delivered to a target surface of the body. It accommodates catheter tunnels which guide the HDR brachytherapy radiation source according to the patient-specific design input chosen by users.
A surface brachytherapy applicator device is 3D printed by Stereolithography (SLA) technology using methacrylic resin.
It appears there might be a misunderstanding. The provided text is a 510(k) clearance letter and its associated summary for a medical device (Nova Surface Applicator). This document does not describe a study involving an AI algorithm or a multi-reader, multi-case (MRMC) comparative effectiveness study.
The device in question, the Nova Surface Applicator, is a 3D-printed accessory for brachytherapy that navigates a radiation source. The performance testing described is focused on the physical characteristics and accuracy of this manufactured device, not on the performance of a diagnostic AI algorithm.
Therefore, I cannot provide information on:
- Table of acceptance criteria and reported device performance for an AI algorithm: The criteria listed are for physical properties and fit, not for diagnostic accuracy (e.g., sensitivity, specificity).
- Sample size for test set and data provenance for an AI algorithm: There's no mention of a test set for an AI. The "worst-case samples" and "real patient datasets" refer to the physical testing of the applicator itself.
- Number of experts and their qualifications for ground truth establishment for an AI algorithm.
- Adjudication method for an AI algorithm test set.
- MRMC comparative effectiveness study or effect size of AI assistance.
- Standalone AI algorithm performance.
- Ground truth type for an AI algorithm.
- Sample size for the training set for an AI algorithm.
- How ground truth for the training set for an AI algorithm was established.
The document describes non-clinical performance testing for a physical medical device. Here's what can be extracted about the device's acceptance criteria and testing:
Device: Nova Surface Applicator (ADPT-ONDEM-3DPRT-BRA) - a 3D printed patient-matched radiation therapy accessory.
Purpose: To be placed on the patient's skin to navigate an HDR radiation source during the treatment of various types of cancer using brachytherapy.
Acceptance Criteria & Reported Device Performance (Based on Non-Clinical Tests):
| Acceptance Criteria Category | Specific Criteria/Test Description | Reported Device Performance/Conclusion |
|---|---|---|
| Post-production verification (Physical Inspection & Functional Tests) | - Look, feel, surface quality: Ensure acceptable physical appearance and tactile properties. | Demonstrated conformance to requirements. |
| - Inner structure consistency (mass consistency and dimensional fidelity): Verify that the internal structure of the 3D printed device is uniform and accurately reproduces the designed dimensions. | Demonstrated high printing accuracy of key functional features and functional key property (density of the material after printing) in conformance with performance requirements. | |
| - Functionality of catheter tunnel accessibility, orientation, inter-tunnel, and source-to-surface distances: Ensure that the tunnels for guiding the radiation source are correctly formed, accessible, oriented as designed, and maintain specified distances. | Demonstrated high printing accuracy of key functional features. | |
| - Labels legibility: Verify that all labels on the device are clear and readable. | Results not explicitly detailed for this point, but implied by overall positive conclusion. | |
| - Additional features functionality (dosimetry pockets and alignment guides): Ensure any other designed features perform as intended. | Results not explicitly detailed for this point, but implied by overall positive conclusion. | |
| Simulated performance testing (Spatial Fidelity & Fit) | - Evaluation of spatial fidelity and fit of patient-specific devices: Virtuallý positioning a CT scan of the device with respect to a DICOM-RT structure representing the patient's anatomy to ensure accurate fit and spatial relationship. This ensures the "patient-specific contact surface" provides enough accuracy to fit the patient's anatomy. | Demonstrated high accuracy in terms of spatial fidelity, providing a precise fit of the device on the patient's anatomy and successful delivery of radiation to the treatment target tissues. The technological and validation methods used are considered applicable to ensure product quality during the production process. Performance testing results demonstrate substantial equivalence to the predicate device and are considered evidence of overall safety and effectiveness. |
| Material & Manufacturing Process | - SLA technology and material compatibility: Ensure that Stereolithography (SLA) technology and methacrylic resin are suitable for manufacturing and do not negatively impact safety and effectiveness. | All tests verified that the chosen manufacturing technology performed as intended and did not affect the overall safety and effectiveness of the device, and are beneficial compared to the previously used technology (FDM and PLA for predicate). SLA offers high accuracy/tolerance, smoother surface finish, and transparency. |
Other Available Information from the Provided Text (NOT related to AI):
- Sample size used for the test set: The document states "The batch of the tests has been performed on worst-case samples as well as on the final device real patient datasets." No specific number for "worst-case samples" or "real patient datasets" is provided.
- Data provenance: Not explicitly stated for the "real patient datasets" (e.g., country of origin). The testing is described as non-clinical.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable as this is a physical device test, not a diagnostic accuracy study. The device design process mentions it's "designed by radiation therapy professionals using patient imaging data as input and must be verified and approved by the trained radiation therapy professional prior to use." This refers to clinical use and design, not the test itself.
- Adjudication method for the test set: Not applicable.
- Multi-reader multi-case (MRMC) comparative effectiveness study: Not conducted, as this is not an AI diagnostic device.
- Standalone (i.e. algorithm only without human-in-the-loop performance): Not applicable, as this is a physical medical device, not an algorithm.
- The type of ground truth used: For the physical device testing, the "ground truth" seems to be the designed specifications and the expected physical and functional performance of the applicator. For the simulated performance, the "ground truth" is the patient's anatomy as represented by the DICOM-RT structure.
- The sample size for the training set: Not applicable; this device is manufactured from a design based on patient imaging data, not trained like a machine learning model.
- How the ground truth for the training set was established: Not applicable. The device is designed based on patient-specific imaging data as input into the Adaptiv's 3D Brachy Software Application.
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