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AccuCheck is a quality assurance software to the quality assurance of general offline planning, online adaptive planning and various radiotherapy technology such as photon and proton. It is used for data transfer integrity check, secondary dose calculation with Monte Carlo algorithm, and treatment plan verification in radiotherapy. AccuCheck also provides independent dose verification based on Accelerator delivery log after radiotherapy plan execution.

AccuCheck is not a treatment planning system or a radiation delivery device. It is to be used only by trained radiation oncology personnel for quality assurance purposes.

AccuCheck, defined as a radiotherapy plan quality assurance system, aims to improve the clinical efficiency of offline and online quality control. AccuCheck supports Monte Carlo dose calculation engine, and is applicable to the quality assurance of general offline planning, online adaptive planning and various radiotherapy technology such as photon and proton.

AccuCheck is to be used for the quality assurance of offline plans and online adaptive radiotherapy plans, where the TPS Check module is used to check whether the parameters related to treatment plan are within the executable range of the machine; the Dose Check module is designed to use an independent dose calculation engine to re-calculate the original plan before the treatment, and is compared with the dose of the original plan; the Transfer Check module could verify whether errors are occurred during transferring from the TPS system to the accelerator; the Log Check module is used to obtain execution log of each execution of the accelerator, calculate dose through an independent dose calculation engine, and compare it with the dose of original plan; Treatment Summary supports physical dose accumulation of doses executed multiple times for a single plan, which reflect the stability of the accelerator operating, it could at the same time support the reconstruction of log to the fractional images so as to evaluate the daily exposure dose of the patient. AccuCheck provides abundant auxiliary analysis tools, including DVH Graph, Gamma Analysis, Target Coverage, Gamma Pass Rate of each ROI, Dose Statistics, and Clinical Goals Evaluation.

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The MOSkin radiation measurement system intended use is a dosimeter to measure radiation dose delivered by a radiation source to the location of an Radiation Dosimeter (RD) sensor on the patient in a clinical use environment. The system is intended for the verification of the output of radiation producing devices.

The output of the system is not used to directly adjust the radiation dose to the patient.

The Electrogenics Laboratories Ltd MOSkin Radiation Measurement System consists of the following components to provide secondary verification of dose from various radiotherapy and diagnostic imaging devices:

• MOSFET (Si-based metal-oxide-semiconductor field-effect transistor) Dosimeter (RD) to record radiation during radiation exposure.
• Reading device (HUB) for reading the radiation dose recorded by the dosimeter.
• MOSkin Software Application, a simple software tool that the user interacts with for radiation dose calculation, dose reporting, managing and storing data.

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syngo.CT Dual Energy is designed to operate with CT images based on two different X-ray spectra.

The various materials of an anatomical region of interest have different attenuation coefficients, which depend on the used energy. These differences provide information on the chemical composition of the scanned body materials. syngo.CT Dual Energy combines images acquired with low and high energy spectra to visualize this information. Depending on the region of interest, contrast agents may be used.

The general functionality of the syngo.CT Dual Energy application is as follows:

• Bone Marrow ²⁾
• Bone Removal ¹⁾
• Brain Hemorrhage ¹⁾
• Gout Evaluation ¹⁾
• Hard Plaques ¹⁾
• Heart PBV
• Kidney Stones ¹⁾ ²⁾ ³⁾
• Liver VNC ¹⁾
• Lung Mono ¹⁾
• Lung Perfusion ¹⁾
• Lung Vessels ¹⁾
• Monoenergetic ¹⁾ ²⁾
• Monoenergetic Plus ¹⁾ ²⁾
• Optimum Contrast ¹⁾ ²⁾
• Rho/Z ¹⁾ ²⁾
• SPP (Spectral Post-Processing Format) ¹⁾ ²⁾
• SPR (Stopping Power Ratio) ¹⁾ ²⁾
• Virtual Non-Calcium (VNCa) ¹⁾ ²⁾
• Virtual Unenhanced ¹⁾

The availability of each feature depends on the Dual Energy scan mode.

¹⁾ This functionality supports data from Siemens Healthineers Photon-Counting CT scanners acquired in QuantumPlus modes.

²⁾ This functionality supports data from Siemens Healthineers Photon-Counting CT scanners acquired in QuantumPeak modes.

³⁾ Kidney Stones is designed to support the visualization of the chemical composition of kidney stones and especially the differentiation between uric acid and non-uric acid stones. For full identification of the kidney stone, additional clinical information should be considered such as patient history and urine testing. Only a well-trained radiologist can make the final diagnosis upon consideration of all available information. The accuracy of identification is decreased in obese patients.

Dual energy offers functions for qualitative and quantitative post-processing evaluations. syngo.CT Dual Energy is a post-processing application consisting of several post-processing application classes that can be used to improve the visualization of the chemical composition of various energy dependent materials in the human body when compared to single energy CT. Depending on the organ of interest, the user can select and modify different application classes or parameters and algorithms.

Different body regions require specific tools that allow the correct evaluation of data sets. syngo.CT Dual Energy provides a range of application classes that meet the requirements of each evaluation type. The different application classes for the subject device can be combined into one workflow.

The product is intended to be used for at least 21-year-old humans.

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The TrueBeam™, TrueBeam STx and Edge™ Systems are 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. The TrueBeam radiotherapy system can produce CBCT images that can be used in image guided radiation therapy, and the simulation and planning for adaptive radiation therapy.

The TrueBeam, TrueBeam STx and Edge Systems 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, 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, 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, cavernous malformation, trigeminal neuralgia, chordoma, glomus tumors, hemangiomas, and medically refractory essential tremor (indicated for adults only)), metastasis (including all parts of the body such as brain, bone, liver, lung, kidney, and skin), pediatric tumors (such as glioma, ependymoma, pituitary tumors, hemangioblastoma, craniopharyngioma, meningioma, metastasis, medulloblastoma, nasopharyngeal tumors, arteriovenous malformation, cavernous malformation, and skull base tumors), and low-dose radiotherapy for adults with medically refractory osteoarthritis.

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, 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, 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, cavernous malformation, trigeminal neuralgia, chordoma, glomus tumors, and hemangiomas), metastasis (including all parts of the body such as brain, bone, liver, lung, kidney, and skin), pediatric tumors (such as glioma, ependymoma, pituitary tumors, hemangioblastoma, craniopharyngioma, meningioma, metastasis, medulloblastoma, nasopharyngeal tumors, arteriovenous malformation, cavernous malformation, and skull base tumors), and low-dose radiotherapy for adults with medically refractory osteoarthritis.

The TrueBeam and VitalBeam Radiotherapy System is a medical linear accelerator that delivered therapeutic radiation to patient in accordance with the physician's prescription.

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.

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The PRO-DOSE System is intended to provide dosimetry or detect in real-time the dose delivered to a patient during therapeutic radiation procedures. The system is intended for the verification of the output of HDR brachytherapy after-loaders involving Iridium-192 sources.

The PRO-DOSE System is intended to provide dosimetry or detect in real-time the dose delivered to a patient during therapeutic radiation procedures. The system is intended for the verification of the output of HDR brachytherapy after-loaders involving Iridium-192 sources.

It is designed to measure the total dose and dose rate administered to patients during radiation therapy treatments. It enables real-time, in vivo monitoring throughout the treatment and generates a Dosimetry Report upon completion.

The Reading Device allows simultaneous dosimetry measurements in up to three independent positions by using three probes.

The System can be operated via an Software Graphical User Interface (GUI) that runs on the MiniPC, which functions in kiosk mode to ensure secure and exclusive use. The Software is pivotal in controlling the Reading Device, processing the signal and displaying measurements. As treatment progresses, real-time dose and dose rate measurements are provided. It also allows for the export of a Dosimetry Report as PDF files for documentation and review. The Probes allow instant detection and quantification of radiation dose. These probes are strategically placed at predefined locations by the user to ensure optimal monitoring throughout the treatment. The probes are single-use and pre-calibrated. Due to their small size and water equivalence, these probes can be inserted into the patient body using the same techniques through needles used in the HDR brachytherapy treatments.

The real-time radiation dose data is intended for use by qualified and trained personnel who recognize radiation hazards associated with the use of radiation therapy and radiology equipment. The system does not interact with the radiation source and is solely designed to monitor and report the accuracy of the treatment delivery. It does not deliver, plan, simulate, or control the radiation delivery. The trained and qualified user is responsible for the interpretation of the information.

The current version of PRO-DOSE System is specifically suitable for monitoring High Dose Rate (HDR) Brachytherapy treatments involving Iridium-192 sources.

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The MEVION S250-FIT Proton Beam Radiation Therapy Device is intended to deliver proton radiation treatment to patients with localized tumors or any other conditions susceptible to treatment by radiation. When the patient is in the fully seated position, the MEVION S250-FIT is indicated for treatment of patients with localized tumors and other conditions susceptible to treatment by radiation in the sites above the mid-chest or carina.

The MEVION S250-FIT Proton Beam Radiation Therapy Device is a proton beam radiation therapy system that provides a therapeutic proton beam for clinical treatment. It is designed to deliver a proton beam with the prescribed dose and three-dimensional dose distribution to the prescribed patient treatment site. The MEVION S250-FIT delivers radiation via a pencil beam (spot) scanning modality. In order to reach a target depth of 32cm in the patient, the accelerator is designed to produce a 230MeV beam.

The S250-FIT is comprised of 6 subsystems:

• Beam Generation System – generates the beam and directs it to the beam delivery system.
• Beam Delivery System – ensures that the therapeutic prescription parameters are properly delivered.
• Hardwired Safety System (HSS) – provides for system and beam delivery interlocking without the use of software
• Patient Positioning System – The Marie Device from Leo Cancer Care (K250970) allows for accurate and efficient positioning of the patient in a seated or perched position for treatment using an Upright Patient Positioner and 3D CT Scanner for Treatment Planning and Patient Registration.
• Structural Support/Alignment System – supports the beam generation and delivery systems and allows the fixed beam delivery to the single point in space (i.e., the Isocenter)
• System Software – controls the above subsystems (except the HSS) and provides interfaces to the system for the end-user.

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Dose+ is a software-only medical device intended for use by qualified, trained radiation therapy professionals (including but not limited to medical physicists, radiation oncologists, and medical dosimetrists). The device is intended for male patients with localized prostate cancer or prostate cancer with pelvic lymph node involvement who are undergoing external beam radiation therapy treatment. The software uses machine learning-based algorithms to automatically produce 3D dose distributions from patient-specific anatomical geometry and target dose prescription.

The predicted dose distribution output is required to be transferred to a radiotherapy treatment planning system (TPS) or reviewed by any DICOM-RT compliant software prior to further use in clinical workflows. Dose+ is intended to provide additional information during the treatment planning process facilitating the creation and review of a treatment plan.

Dose+ is not intended to be used for disease diagnosis and treatment decision purposes in clinical workflows.

Dose+ is a software-only medical device that assists radiation oncologists, medical dosimetrists and medical physicists during external beam radiotherapy treatment planning. The software utilizes pre-trained machine learning models that are not modifiable or editable by the end-user. The product provides information during the radiotherapy plan creation but does not replace a treatment planning system (TPS).

The central value proposition of Dose+ is to provide personalized organ-at-risk (OAR) dose optimization goals based on individual patient anatomy, rather than relying solely on population-based protocol templates. The software analyzes patient-specific anatomical geometry to determine achievable dose levels for each OAR relative to target volumes. This helps to ensure:

• Initial optimization objectives are more achievable, reducing the number of iterations needed during plan optimization
• Opportunities for further OAR dose reduction are not missed when standard fixed templates suggest a higher dose
• Inappropriately aggressive goals for one OAR do not compromise target coverage or dose reduction to other OARs

The device operates in two deployment modes:

• Cloud-based service with secure HTTPS data transfer
• Local installation in healthcare provider's IT network

Key features include:

• Automated dose prediction using locked machine learning models
• Generation of DICOM RT Dose objects
• Integration with existing treatment planning workflows
• Support for multiple fractionation schemes
• Compatibility with major treatment planning systems

The first release includes two models for male pelvis patients:

• "Prostate" model: For localized prostate treatments
• "PelvisLN" model: Designed for cancers involving lymph nodes

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided FDA 510(k) Clearance Letter for Dose+:

1. Acceptance Criteria and Reported Device Performance

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

The description distinguishes between a "Performance Verification Dataset" and a "Clinical Validation Dataset", both of which function as test sets for different aspects of performance.

• Performance Verification Dataset: This dataset was used for demonstrating non-inferiority in OAR mean dose predictions and target coverage against manual planning.

  • Prostate Model: 25 cases
  • PelvisLN Model: 27 cases
  • Data Provenance:
    • Prostate Model: 100% US dataset, collected from 7 U.S. institutions across 6 US states.
    • PelvisLN Model: 96.3% US dataset, collected from 6 institutions from 6 US states.
    • Retrospective/Prospective: Not explicitly stated, but the description of "independent dataset" and "multiple US institutions" suggests retrospective collection for this phase.

• Clinical Validation Dataset: This dataset was used for a comparative effectiveness study involving human readers.

  • Sample Size: Not explicitly stated as a number of cases, but mentions "prospective patient enrollment" at 4 US institutions and "within-subject comparison". Given the context of a "validation study", it implies a separate cohort from the Verification Dataset.
  • Data Provenance: 100% US dataset, conducted at 4 geographically diverse US institutions across 3 states. Patients aged 60 years and older, with demographic representativeness matching the US national median age for prostate cancer diagnosis.
  • Retrospective/Prospective: Prospective patient enrollment.

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

• Performance Verification: The ground truth for OAR mean dose predictions and target coverage was established against "manual planning." It's implied that these manual plans, considered the ground truth, were created by qualified radiation therapy professionals (medical physicists, radiation oncologists, and medical dosimetrists), but the specific number and qualifications of experts involved in creating this specific ground truth dataset are not detailed. It refers to the ground truth as "ground truth dose distributions," which would typically be the outcome of expert-created and approved treatment plans.
• Clinical Validation: The study involved "Independent validators (ABR-certified medical physicists)" for assessing plan quality, optimization iterations, and user acceptance. The exact number of these physicists is not specified.

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method (such as 2+1 or 3+1 consensus) for establishing the ground truth or evaluating disagreements between readers or with the AI.

• For Performance Verification, the ground truth appears to be established from existing "manual planning" dose distributions.
• For Clinical Validation, "Independent validators (ABR-certified medical physicists)" were used, but the process for reconciling differences in their assessments or how their assessments contributed to a final ground truth is not detailed.

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

Yes, a multi-reader multi-case (MRMC) comparative effectiveness study was done as part of the Performance Validation.

• Effect Size of Human Readers' Improvement:
  • The study demonstrated a "statistically significant reduction in optimization iterations (≥20% mean reduction)" when using Dose+ compared to conventional planning.
  • It also showed "non-inferior OAR mean doses (≤10 Gy difference)" and "non-inferior target coverage (no statistically significant differences)" compared to conventional planning, suggesting that AI assistance helps achieve comparable or better plan quality with less effort from human readers.
  • Validators also "reported potential time savings in treatment planning."

6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study

Yes, a standalone performance study was conducted. This is referred to as "Performance Verification."

• The Dose+ models were evaluated on their ability to predict OAR mean doses and target coverage against "ground truth dose distributions" (presumably from expert-generated manual plans) on an independent dataset. This evaluation focuses solely on the algorithm's output without direct human interaction in the generation or real-time review of the predicted dose distributions for the verification metrics themselves.

7. Type of Ground Truth Used

• Performance Verification: The ground truth used was "ground truth dose distributions" and "manual planning," implying expert-approved treatment plans generated through conventional clinical practice.
• Clinical Validation: The ground truth for comparison was "conventional planning" and subjective assessments from "ABR-certified medical physicists" regarding plan quality, optimization iterations, and user acceptance.

8. Sample Size for the Training Set

The document mentions a "Model Development Dataset" (with internal splits for training, validation, and testing during model development). However, the specific sample size for the training set itself is not provided. It only states that samples in all datasets are from distinct and individual patients, so the number of cases is the same as the number of patients.

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

The ground truth for the training set (part of the Model Development Dataset) was established by using "patient-specific anatomical geometry and target dose prescription" and training the machine learning models. It's implied that these models learned from a dataset of existing, clinically accepted treatment plans. The document states, "The software analyzes patient-specific anatomical geometry to determine achievable dose levels for each OAR relative to target volumes," indicating that it was trained on examples where optimal dose levels for OARs were determined by human experts. The description "processes input using locked machine learning (ML) models trained on patient-specific anatomical geometry to generate the predicted 3D dose distribution" further supports that the ground truth for training would have been expert-generated or clinical gold-standard dose distributions and associated patient data.

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AquaCast Mask is a device used for the positioning and immobilization of patient's head undergoing or receiving a course of external beam radiation therapy for the treatment of cancer. Thermoplastic Mask is intended as a single-patient reusable device only and are not sterile.

AquaCast Mask is used for the positioning and immobilization of patient's head undergoing or receiving a course of external beam radiation therapy for the treatment of cancer. The low temperature thermoplastic mask is made of AquaCast polycaprolactone sheet for patient immobilization. Heat at a temperature of 150°F ~ 158°F is applied to the sheet to soften it and mold it to the shape of the patient anatomy. The perforated thermoplastic is pre-mounted to a non-patient contacting frame to interface with the user's existing support hardware and hold the patient's head in a fixed position for radiation therapy treatments

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The EmpNia eMotus system is used to measure and record the patient's respiratory waveform to aid with respiratory-synchronized image acquisition or reconstruction during CT diagnostic imaging or radiation treatment planning procedures, where there is a risk of respiratory motion compromising the resulting image.

The EmpNia eMotus system is used to derive and communicate a Gate signal to aid with organ position verification for radiation therapy treatment using CT or Xray imaging by monitoring the patient's respiratory waveform during the image acquisition, where there is a risk of respiratory motion compromising the resulting image.

The EmpNia eMotus system is used to derive and communicate a Gate signal to aid with radiation therapy treatment, where there is a risk of respiratory motion compromising the resulting treatment accuracy.

The eMotus Respiratory Motion Management System ("eMotus system") is designed to monitor patient respiratory motion and to provide information about this respiratory motion to an external medical device system, such as a radiation therapy delivery device (TDD) or a diagnostic imaging device (DX). The main components of the eMotus system include:

• Sensor pad with optical fiber sensors,
• Optical fiber cables,
• Optical transceiver,
• Data acquisition computer with eMotus software application,
• Communication modules for compatible external systems, and
• Cables to allow data transmission between the components.

The sensor pad is a single-use, disposable component with an adhesive backing that is placed directly on the patient's thorax or abdomen. The sensor pad is attached to optical fiber cables that connect to the optical transceiver, which collects optical signal data based on deflection of the sensors in response to respiratory motion. The transceiver digitizes the data and transmits it to the eMotus computer, which visualizes the data as a waveform that can be highlighted when the waveform amplitude reaches a user-specified threshold or the patient's respiratory cycle reaches a user-specified phase. The user can utilize the respiratory threshold and phase information to manually control an external TDD or DX system.

When connected to an external TDD or DX, the eMotus system supports the following functions (as applicable given the functions of the external system):

• Threshold-gated therapy delivery: Automatic gating (turning on / off) of the radiation treatment beam based on user-set parameters for the amplitude of the respiratory waveform.
• Phase-gated therapy delivery: Automatic gating (turning on / off) of the radiation treatment beam based on user-set parameters for the phase of the respiratory waveform cycle.
• Retrospective four-dimensional planning scan: Delivery of the respiratory waveform to an imaging device to synchronize the waveform data with the scan data, enabling retrospective four-dimensional reconstruction of the imaging session for use in treatment planning.
• Prospective four-dimensional planning scan: Automatic patient's respiratory waveform are within preset limits, which is used to disable the radiation beam automatically.

The eMotus device is an ancillary device and does not provide stand-alone therapy or diagnostic information.

Unfortunately, the provided text does not contain the detailed study information required to answer many of your questions. The 510(k) summary focuses on demonstrating "substantial equivalence" to a predicate device, and while it mentions "bench performance," it lacks the specific methodology, sample sizes, and expert involvement that would typically be present in a comprehensive clinical or standalone performance study report.

Here's a breakdown of what can and cannot be answered based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document mentions "Bench performance" testing but does not explicitly state formal acceptance criteria in a quantitative sense, nor does it provide specific numerical performance metrics beyond "nearly identical signals" and "stable dynamics."

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

• Sample Size for Test Set: Not specified. The text mentions "infant and adult phantoms" and "multiple sensors" but does not give specific numbers.
• Data Provenance: The study described as "bench performance" clearly implies a laboratory/simulated environment rather than clinical data from human patients. Therefore, information about country of origin, retrospective or prospective data, is not applicable or 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 specified. Given it was "bench performance" with phantoms and a comparison to a predicate device, it's unlikely human experts were establishing ground truth in the traditional sense. The "ground truth" was likely derived from the known simulated respiratory patterns and the output of the predicate device.

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

Not applicable/Not specified. Adjudication methods are typically used when human reviewers are involved in assessing complex outputs. This was a bench performance study comparing waveforms and functionality.

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, an MRMC comparative effectiveness study was not explicitly done or described. The device is a "Respiratory Motion Management System," which aids in synchronizing image acquisition or radiation treatment – it's not an AI diagnostic tool that human readers would directly interpret to improve diagnostic accuracy in the way an MRMC study typically assesses. Therefore, the effect size for human reader improvement is not applicable to the information provided.

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

Yes, the "bench performance" described primarily represents a standalone evaluation of the eMotus system's technical capabilities in a controlled environment, comparing its output directly to known inputs and the predicate device's output. The "human factors" testing mentioned separately focuses on usability, but the core performance data is standalone.

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

The "ground truth" for the bench performance testing appears to be based on:

• Known simulated respiratory patterns (for assessing stable dynamics, peak frequency, irregular breathing alerts).
• Output of the predicate device (for comparing respiratory waveforms).

8. The sample size for the training set

The document does not mention any training set size, which suggests that the device, being a physiological signal monitoring and gating system, likely does not involve machine learning or AI that requires a labeled training set in the conventional sense for its core functionality. Its "software functions" are verified and validated, indicating traditional software engineering practices.

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

Not applicable/Not specified, as no training set is mentioned in the provided text.

In summary, the provided FDA 510(k) clearance letter and summary are designed to demonstrate substantial equivalence, not to provide a detailed clinical or standalone performance study report with the specific metrics you've requested beyond what's inferable from the "bench performance" section.

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Cranial 4Pi is intended for patient immobilization in radiotherapy and radiosurgery procedures.

Cranial 4Pi is indicated for any medical condition in which the use of radiotherapy or radiosurgery may be appropriate for cranial and head & neck treatments.

Cranial 4Pi is an assembly of the following medical device/ accessory groups:

• CRANIAL 4PI OVERLAYS (CRANIAL 4PI CT OVERLAY, CRANIAL 4PI TREATMENT OVERLAY)
• CRANIAL 4PI HEADRESTS (CRANIAL 4PI HEADREST STANDARD, CRANIAL 4PI HEADREST LOW-NECK, CRANIAL 4PI HEADREST PLATFORM)
• CRANIAL 4PI HEADREST INLAYS (CRANIAL 4PI HEADREST INLAY STANDARD, CRANIAL 4PI HEADREST INLAY OPEN FACE, CRANIAL 4PI HEADREST INLAY H&N, CRANIAL 4PI HEAD SUPPORT STANDARD, CRANIAL 4PI HEAD SUPPORT WIDE)
• CRANIAL 4PI MASKS (CRANIAL 4PI BASIC MASK, CRANIAL 4PI OPEN FACE MASK, CRANIAL 4PI EXTENDED MASK, CRANIAL 4PI STEREOTACTIC MASK, CRANIAL 4PI STEREOTACTIC MASK 3.2MM)
• CRANIAL 4PI WEDGES AND SPACERS (CRANIAL 4PI WEDGE 5 DEG., CRANIAL 4PI WEDGE 10 DEG., CRANIAL 4PI SPACER 20MM, CRANIAL 4PI INDEXING PLATE)

The Cranial 4Pi Overlays are medical devices used for fixation of the patient in a CT- resp. linear accelerator - environment.

The Cranial 4Pi Headrests and the Cranial 4Pi Headrest Inlays are accessories to the Cranial 4Pi Overlays to allow an indication specific positioning of the patient's head and neck. The Cranial 4Pi Wedges and Spacers are accessories to the Cranial 4Pi Headrest Platform to adapt the inclination of the head support to the patients necks.

The Cranial 4Pi Masks are accessories to the Cranial 4Pi Overlays used for producing individual custom-made masks for patient immobilization to the Cranial 4Pi Overlay.

The provided text is a 510(k) Clearance Letter and 510(k) Summary for a medical device called "Cranial 4Pi Immobilization." This document focuses on demonstrating substantial equivalence to a predicate device, as required for FDA 510(k) clearance.

However, the provided text does not contain the detailed information typically found in a clinical study report or a pre-market approval (PMA) submission regarding acceptance criteria, study methodologies, or specific performance metrics with numerical results (like sensitivity, specificity, or AUC) that would be used to "prove the device meets acceptance criteria" for an AI/ML-driven device. The document primarily describes the device's components, indications for use, and a comparison to a predicate device to establish substantial equivalence.

The "Performance Data" section primarily addresses biocompatibility, mechanical verification, dosimetry, compatibility with another system, and mask stability. It does not describe a study to prove AI model performance against clinical acceptance criteria. The "Usability Evaluation" section describes a formative usability study, which is different from a performance study demonstrating clinical effectiveness or accuracy.

Therefore, many of the requested elements (especially those related to AI/ML model performance, ground truth establishment, expert adjudication, MRMC studies, or standalone algorithm performance) cannot be extracted from the provided text. The Cranial 4Pi Immobilization device appears to be a physical immobilization system, not an AI/ML diagnostic or prognostic tool.

Given the nature of the document (510(k) for an immobilization device), the concept of "acceptance criteria for an AI model" and "study that proves the device meets the acceptance criteria" in the traditional sense of an AI/ML clinical study does not apply here.

I will answer the questions based on the closest relevant information available in the provided text, and explicitly state where the information is not available or not applicable to the type of device described.

Preamble: Nature of the Device and Submission

The Cranial 4Pi Immobilization device is a physical medical device designed for patient immobilization during radiotherapy and radiosurgery. The 510(k) premarket notification for this device seeks to demonstrate substantial equivalence to an existing predicate device (K202050 - Cranial 4Pi Immobilization). This type of submission typically focuses on comparable intended use, technological characteristics, and safety/performance aspects relevant to the physical device's function (e.g., biocompatibility, mechanical stability, dosimetry interaction).

The provided documentation does not describe an AI/ML-driven component that would require acceptance criteria related to AI model performance (e.g., accuracy, sensitivity, specificity, AUC) or a study to prove such performance. Therefore, many of the questions asking about AI-specific validation (like ground truth, expert adjudication, MRMC studies, training/test sets for AI) are not applicable to this type of device and submission.

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

Based on the provided document, specific numerical "acceptance criteria" and "reported device performance" in the context of an AI/ML model are not available and not applicable. The document focuses on demonstrating substantial equivalence of a physical immobilization device.

However, the "Performance Data" section lists several tests and their outcomes, which serve as evidence that the device performs as intended for its physical function. These are not acceptance criteria for an AI model.

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 for Test Set: Not applicable/not stated in the context of an AI/ML test set. The usability evaluation involved "seven participants" in "three different clinics." For biocompatibility, animal studies were performed (guinea pigs for sensitization, rabbits for irritation; specific number of animals not stated but implied to be sufficient for ISO standards).
• Data Provenance: Not applicable for an AI/ML test set. The usability evaluation involved "three different clinics" but the country of origin is 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)

• Not applicable. This device is a physical immobilization system, not an AI/ML diagnostic or prognostic tool that requires expert-established ground truth on medical images.

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

• Not applicable. This information is relevant to validating AI/ML diagnostic performance against ground truth, which is not described for this device.

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. This is an AI/ML-specific study design. The device is a physical immobilization system, not an AI assistance tool for human readers.

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

• Not applicable. This is an AI/ML-specific validation. There is no AI algorithm component described for this physical device.

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

• Not applicable. No ground truth for diagnostic or prognostic purposes is established for this physical device. The "performance data" relies on standards compliance (e.g., ISO, IEC), physical measurements, and usability feedback.

8. The sample size for the training set

• Not applicable. There is no AI model described that would require a training set.

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

• Not applicable. There is no AI model described.

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