Search Results

VitalBeam is intended to provide stereotactic radiosurgery and precision radiotherapy for lesions, tumors, and conditions anywhere in the body where radiation therapy is indicated for adults and pediatric patients.

VitalBeam may be used in the delivery of radiation for treatment that includes: brain and spine tumors (such as glioma, meningioma, craniopharyngioma, pituitary tumors, spinal cord tumors, hemangioblastoma, orbital tumors, optic nerve tumors, and skull based tumors), head and neck tumors (such as unknown primary of the head and neck, oral cavity, hypopharynx, larynx, oropharynx, sinonasal, salivary gland, and thyroid cancer), thoracic tumors (such as lung cancer, esophageal cancer, thymic tumors, and mesothelioma), gynecologic tumors (such as ovarian, cervical, endometrial, vulvar, and vaginal), gastrointestinal tumors (such as gastric, pancreatic, hepatobiliary, colon, rectal, and anal carcinoma), genitourinary tumors (such as prostate, bladder, testicular, and kidney), breast tumors, sarcomas, lymphoid tumors (such as Hodgkin's and non-Hodgkin's lymphoma), skin cancers (such as squamous cell, basal cell, and melanoma), benign diseases (such as schwannoma, arteriovenous malformation, trigeminal neuralgia, chordoma, glomus tumors, and hemangiomas), metastasis (including all parts of the body such as brain, bone, liver, lung, kidney, and skin) and pediatric tumors (such as glioma, ependymoma, pituitary tumors, hemangioblastoma, craniopharyngioma, metastasis, medulloblastoma, nasopharyngeal tumors, arteriovenous malformation, cavernous malformation and skull base tumors).

VitalBeam is a medical linear accelerator.

The system consists of two major components, a photon, electron, and diagnostic kV X-ray radiation beam-producing component that is installed in a radiation-shielded vault and a control console area located outside the treatment room.

The VitalBeam device is a medical linear accelerator for radiation therapy. The provided document is a 510(k) summary, which typically focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed study results for acceptance criteria in the way a clinical trial for a new drug or diagnostic might.

Based on the provided information, the acceptance criteria and performance are related to engineering and safety standards, as well as verification and validation (V&V) testing. There is no information about clinical performance or studies involving human readers, training sets, or ground truth established by experts in the context of AI or diagnostic performance metrics like sensitivity/specificity.

Here's an analysis of the provided text in relation to your request:

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

The document does not explicitly present a table of clinical acceptance criteria (e.g., sensitivity, specificity, accuracy) and corresponding device performance values. Instead, it focuses on adherence to engineering and safety standards.

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

The document describes "Hardware and software verification and validation bench testing." This implies internal engineering tests, rather than a clinical study with patients or patient data. Specific sample sizes for these bench tests are not provided, nor is information about the provenance of any "data" in the context of clinical images or patient data (as this is an equipment submission, not an AI diagnostic algorithm).

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 applicable to the type of safety and engineering testing described in the 510(k) summary for a linear accelerator. The "ground truth" here refers to whether the device meets its engineering specifications, not a medical diagnosis.

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

Not applicable. This is not a study assessing diagnostic performance requiring adjudication of labels.

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 applicable. The VitalBeam is a radiation therapy delivery system, not an AI diagnostic or assistive tool for human readers. The document highlights new features like 'Hyperarc™ new automated treatment type' and 'CBCT changes' which involve advanced imaging and treatment delivery techniques. While these are technological advancements, their evaluation in this 510(k) does not involve MRMC studies in the typical sense of AI diagnostics.

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

The document describes "Software verification and validation testing" for a "major" level of concern software. This testing demonstrates the software's ability to function correctly according to its specifications. While this is testing the "algorithm only" in a sense, it's about the performance of the machine control software, not a diagnostic algorithm where "standalone" performance typically refers to metrics like AUC, sensitivity, or specificity.

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

The "ground truth" for the verification and validation (V&V) testing involved adherence to engineering specifications and safety standards. For example, ensuring that radiation doses are delivered accurately, safety interlocks function as designed, and imaging systems perform within established parameters. This is verified against engineering and physics principles, not medical diagnostic ground truths like pathology.

8. The sample size for the training set

Not applicable. This is a V&V summary for a medical device (linear accelerator), not an AI algorithm development where a specific training set size would be relevant.

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

Not applicable, as there is no mention of a training set for an AI algorithm.

Ask a specific question about this device

The VitalBeam System is intended to provide stereotactic radiotherapy for lesions, tumors, and conditions anywhere in the body where radiation therapy is indicated for adults and pediatric patients.

The VitalBeam System may be used in the delivery of radiation for treatment that includes: brain and spine tumors (such as glioma, meningioma, craniopharyngioma, pituitary tumors, hemangioblastoma, orbital tumors, ocular tumors, optic nerve tumors, and skull based tumors), head and neck tumors (such as unknown primary of the head and neck, oral cavity, hypopharynx, larynx, oropharynx, nasopharynx, sinonasal, salivary gland, and thyroid cancer), thoracic tumors (such as lung cancer, esophageal cancer, thymic tumors, and mesothelioma), gynecologic tumors (such as ovarian, cervical, endometrial), gastrontestinal tumors (such as gastric, hepatobiliary, colon, rectal, and anal carcinoma), genitourinary tumors (such as prostate, bladder, testicular, and kidney), breast tumors, sarcomas, lymphoid turnors (such as Hodgkin's lymphoma), skin cancers (such as squamous cell, and melanoma), benign diseases (such as schwannoma, arteriovenous malformation, cavemous malformation, trigeninal neuralgia, chordoma, glomus tumors, and hemangiomas), metastasis (including all parts of the body such as brain, bone, liver, lung, kidney, and skin) and pediatric tumors (such as glioma, pitutary tumors, hemangioblastoma, craniopharyngioma, metastasis, medulloblastoma, nasopharyngeal tumors, arteriovenous malformation, cavernous malformation and skull base tumors).

The VitalBeam™ Radiotherapy Delivery System is a medical linear accelerator based on the previously cleared TrueBeam Radiotherapy system and associated accessories.

The system consists of two major components: a beam-producing component that is installed in a radiation-shielded vault (hereafter referred to as the treatment room) and a control console located outside the treatment room.

The provided text describes the VitalBeam Radiotherapy Delivery System, a medical linear accelerator system. It is a 510(k) premarket notification, indicating that the device aims to demonstrate substantial equivalence to a legally marketed predicate device. This type of submission focuses on comparing the new device's safety and effectiveness to a predicate, rather than providing a detailed study proving the device meets specific acceptance criteria in the manner of a diagnostic AI device.

Therefore, much of the requested information (acceptance criteria for performance metrics, sample sizes for test/training sets, ground truth establishment, expert qualifications, MRMC studies, standalone performance for AI, etc.) is not present in this document because it pertains to the performance evaluation of a diagnostic or algorithmic device, not a therapeutic hardware device like a linear accelerator.

The document mostly discusses the device's technical specifications, intended use, indications for use, and a comparison to a predicate device based on features and adherence to recognized standards.

Here's an attempt to answer the questions based on the provided text, highlighting what is available and what is not:

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

The document does not explicitly present a table of acceptance criteria for specific performance metrics (e.g., sensitivity, specificity, accuracy) paired with reported performance results as would be typical for a diagnostic algorithm. Instead, the "acceptance criteria" for a radiotherapy delivery system in a 510(k) context largely revolve around demonstrating substantial equivalence to a predicate device and conformance to applicable safety and performance standards.

The document states:

• Acceptance Criteria (Implicit): Conformance to applicable requirements specifications, assurance of hazard safeguards functioning properly, and compliance with recognized consensus standards (listed below). The ultimate "acceptance criterion" for 510(k) clearance is demonstrating that the device is as safe and effective as a legally marketed predicate.
• Reported Device Performance: "Results of verification and validation testing showed conformance to applicable requirements specifications and assured hazard safeguards functioned properly."

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

This information is not provided. The document describes a medical device (linear accelerator) for delivering radiation, not a diagnostic algorithm that would typically use test data sets of patient images or clinical records. The "testing" mentioned is likely engineering verification and validation testing of the hardware and software components, not clinical data analysis in the sense of AI performance evaluation.

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 applicable and is not provided. The device described is a radiotherapy delivery system, not a diagnostic tool requiring expert-established ground truth for a test set.

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

This information is not applicable and is not provided for the same reasons as above.

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 information is not applicable and is not provided, as the VitalBeam Radiotherapy Delivery System is not a diagnostic AI device that would assist human readers.

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

This information is not applicable and is not provided. The VitalBeam is a hardware system for delivering radiation therapy, not a standalone algorithm.

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

This information is not applicable and is not provided. "Ground truth" in the context of diagnostic performance is not relevant for this type of device submission.

8. The sample size for the training set

This information is not applicable and is not provided. The device is a hardware system, not an AI model that would have a "training set."

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

This information is not applicable and is not provided for the same reasons as above.

Ask a specific question about this device