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The SIGMA Spectrum Infusion Pump with Master Drug Library is intended to be used for the controlled administration of fluids. These may include pharmaceutical drugs, blood, blood products and mixtures of required patient therapy. The intended routes of administration consist of the following clinically accepted routes: intravenous, arterial, subcutaneous, or epidural. The SIGMA Spectrum Infusion Pump with Master Drug Library is intended to be used in conjunction with legally marketed and compatible intravenous administration sets and medications provided by the user.

The SIGMA Spectrum Infusion Pump with Master Drug Library is suitable for a variety of patient care environments such as, but not limited to, hospitals and outpatient care areas.

The SIGMA Spectrum Infusion Pump with Master Drug Library is intended to reduce operator interaction through guided programming, thereby helping to reduce errors. The SIGMA Spectrum Infusion Pump with Master Drug Library is intended to be used by trained healthcare professionals.

SIGMA Spectrum is a large volume pump within the SIGMA Spectrum infusion system used by clinicians at the patient bedside to control the delivery of medications from a bag. The pump moves fluid from the bag to the patient via specified administration sets using a peristaltic pumping action. The pump offers various programmable delivery modes to address specific patient care needs. The delivery modes available to support the patient are determined by how the pump and its associated drug library are configured.

The pump provides delivery of fluids into a patient in a controlled manner, as identified in 21 CFR 880.5725. The system includes a software controlled, electromechanical pump used for the controlled administration of fluids including pharmaceutical drugs, blood, blood products, and mixtures of required patient therapy through administration sets at clinician's selectable rates and volumes.

The pump is intended for the controlled administration of fluids through the following clinically accepted routes of administration: intravenous, arterial, subcutaneous, and epidural. The pump is intended to be used in conjunction with legally marketed and compatible administration sets, as indicated in the device labeling, and medications provided by the user. The subject device is suitable for patient care in hospitals and outpatient health care facilities.

The Master Drug Library (MDL) is a stand-alone (not embedded in the pump) software application installed on a hospital-provided computing platform and used to create a drug library file. MDL facilitates the generation, configuration, and management of a facility-specific drug library file for dedicated infusion pumps. The drug library file is intended to be distributed to all compatible infusion pumps in the hospital.

This submission includes software design and labeling changes to address the issues leading to recalls Z-0530-2022 and Z-2103-2023.

This FDA 510(k) clearance letter pertains to an infusion pump, not an AI/ML powered medical device. Therefore, many of the requested categories in your prompt (such as "Number of experts used to establish the ground truth," "Adjudication method," "MRMC study," "Standalone performance," "Type of ground truth," and "Training set sample size/ground truth establishment") are not applicable to this type of medical device submission.

The document primarily focuses on demonstrating substantial equivalence to a predicate device through a comparison of technical characteristics and verification of performance against established requirements.

Here's an analysis based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" for the overall device in a quantifiable manner that would typically be found in an AI/ML context (e.g., specific sensitivity, specificity, or AUC targets). Instead, it demonstrates compliance with a range of technical specifications, which inherently act as acceptance criteria for the design and performance. The "Reported Device Performance" is implied by the statement that "Non-clinical testing met all acceptance criteria."

Below is a table summarizing key technical characteristics that function as performance criteria for the infusion pump. Since the subject device is deemed "substantially equivalent" to the predicate, and no new performance claims are made that deviate from the predicate, their performance characteristics are identical as presented.

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Mini-X is intended for use by qualified/trained medical professionals who fully understand the safety information, emergency procedures, and the device's capabilities and function. The device provides fluoroscopic imaging and is used for guidance and visualization during diagnostic radiography and surgical procedures of the extremities. The device will be used in healthcare facilities inside and outside the hospital, using various methods for the extremities on all patients except neonates (birth to one month) within the limits of the device. Applications can be performed with the patient sitting, standing, or lying in a prone or supine position. The system is not intended for mammography applications. (Rx Only)

The Mini-X system, a unique mobile imaging system, can acquire, process, and display fluoroscopic images. Its portability allows for easy positioning within a room and movement from room to room within a facility, facilitating on-demand fluoroscopic examinations. The system's innovative design incorporates a low-powered mono-block generator and a dynamic flat-panel detector, enabling it to be powered through a single-phase 120VAC power outlet.

The Insight Enhanced™ DRF Digital Imaging System, a cutting-edge tool for healthcare professionals, offers full control over the imaging chain. It empowers the operator to view and enhance high-definition fluoroscopy images up to 30 fps, bringing out diagnostic details that are challenging or impossible to see using conventional imaging techniques. The system's versatility is demonstrated by its ability to store images locally for short-term storage, produce hardcopy images with a laser printer, or send images over a network for longer-term storage. Its primary components, including a dynamic flat panel detector, monitors, and an image processor PC, underscore its comprehensive and advanced capabilities.

It seems there's a misunderstanding of the provided text. The document is an FDA 510(k) Clearance Letter for a mobile digital imaging system. It describes the device, its intended use, and its substantial equivalence to predicate devices based on technological similarities and differences, and outlines general testing performed (bench testing, compliance with IEC standards).

**Crucially, this document does not describe:

• An AI/ML device or its performance characteristics.
• Acceptance criteria related to AI/ML performance metrics (e.g., sensitivity, specificity, AUC).
• A study proving an AI device meets acceptance criteria.**

The document discusses imaging quality and radiation dose comparisons, and compliance with general medical device standards. It briefly mentions "software" and "cybersecurity" in generic terms, but not in the context of an AI algorithm or its performance.

Therefore, I cannot fulfill the request to describe the acceptance criteria and a study proving an AI device meets those criteria based on the provided text, as the text describes a standard imaging system, not an AI-powered one.

To answer your request, I would need a 510(k) submission document or a scientific paper that specifically details the clinical validation of an AI/ML medical device, including the elements you listed.

Hypothetical Example (if the document were about an AI device):

If this document were to refer to an AI device for, say, detecting fractures on Mini-X images, the relevant sections would typically be under "Non-Clinical and/or Clinical Tests Summary & Conclusions" (Page 7) or a dedicated "Performance Benchmarks" section, which are absent here for AI.

To illustrate what you're asking for, here's an example of how I would answer if the provided text contained the necessary information about an AI device:

(This is a hypothetical response, as the provided text doesn't contain this information.)

Based on the provided (hypothetical) information regarding an AI-powered diagnostic device, here's a description of the acceptance criteria and the study proving the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance (Hypothetical)

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

• Test Set Sample Size: 1500 unique imaging studies.
• Data Provenance: Retrospective and prospective data collected from multiple hospitals across the United States (70% retrospective, 30% prospective). The retrospective data covered a period of 5 years (2018-2023).

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

• Number of Experts: A panel of 3 independent radiologists.
• Qualifications: All radiologists were board-certified with a minimum of 10 years of experience in diagnostic radiography, specializing in musculoskeletal imaging. One radiologist had subspecialty fellowship training in advanced imaging.

4. Adjudication Method for the Test Set (Hypothetical)

• Adjudication Method: 2+1 adjudication method was employed.
  • Initially, two radiologists independently reviewed each case.
  • If their interpretations agreed, that consensus was taken as the preliminary ground truth.
  • If their interpretations disagreed, a third, senior radiologist served as an adjudicator and made the final decision to establish the ground truth.

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

• MRMC Study Done: Yes, an MRMC study was conducted to evaluate the impact of AI assistance on human reader performance.
• Effect Size: The study demonstrated a significant improvement in reader performance. Human readers, when assisted by the AI device, showed an average 15% increase in sensitivity for detecting [condition A] and a 5% reduction in reading time per case, compared to reading without AI assistance, while maintaining specificity. The estimated Area Under the Free-Response Receiver Operating Characteristic (FROC) curve, a common metric in MRMC studies, improved from 0.78 (unaided) to 0.86 (AI-aided).

6. Standalone (Algorithm Only) Performance Study (Hypothetical)

• Standalone Study Done: Yes, a standalone performance evaluation was conducted on the full test set (1500 cases) against the established ground truth.
• Standalone Performance Metrics:
  • Sensitivity: 92.5%
  • Specificity: 85.1%
  • F1-score: 0.88
  • AUC: 0.93

7. Type of Ground Truth Used (Hypothetical)

• Type of Ground Truth: Expert consensus, established through the 2+1 adjudication process involving three qualified radiologists. In cases where available and relevant, this was supplemented or confirmed by pathology reports or follow-up outcomes data (e.g., surgical confirmation or clinical progression documented over 6 months).

8. Sample Size for the Training Set (Hypothetical)

• Training Set Sample Size: 50,000 imaging studies, collected from a diverse patient population.

9. How Ground Truth for the Training Set Was Established (Hypothetical)

• Ground Truth Establishment for Training Set: The ground truth for the training set was primarily established through a combination of:
  • Radiologist Consensus: A larger team of 10 radiologists (separate from the test set readers) annotated the training data. Each image was reviewed by at least two radiologists, with disagreements resolved by an internal consensus committee.
  • Clinical Records & Reports: For a subset of cases, ground truth was derived from detailed clinical reports, electronic health records, and existing radiology reports.
  • Automated Labeling (with verification): For a large portion of the normal or clearly pathological cases, a pre-existing, highly accurate internal model was used for initial labeling, which was then systematically reviewed and corrected by human annotators to ensure high fidelity. All ambiguous or complex cases were subjected to full manual review by multiple radiologists.

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TEMP MASTER, PMMA-based dental resin developed by Taiwan Dental Materials CO., LTD. is a self-cured resin indicated for the fabrication of short-term restorations including temporary inlays, crowns, and bridges, which can protect or restore damaged teeth while permanent restorations are being prepared. It is a traditional auto-cured PMMA-based resin composed of powder and liquid. Polymerization occurs when the powder and liquid are mixed at room temperature.

TEMP MASTER, PMMA-based dental resin, is a self-curing (cold-cure) material designed to fabricate temporary crowns and bridges. It consists of two components: powder and liquid. Polymerization occurs when the powder and liquid are mixed at room temperature. Classified as a Type 1 (autopolymerizable) acrylic resin according to ISO 10477 standards, TEMP MASTER, PMMA-based dental resin provides reliable performance for temporary restorations.

This document describes a 510(k) premarket notification for a dental material, not an AI/ML powered device. Therefore, much of the requested information regarding AI/ML device studies (such as sample sizes for test and training sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, and ground truth types) is not applicable.

However, I can extract the acceptance criteria and reported device performance based on the provided bench testing information for the TEMP MASTER, PMMA-based dental resin.

Here's the information as it relates to the provided document:

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

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: The document does not specify the exact sample sizes used for the bench tests. It only states that "the nonclinical tests conducted in accordance with ISO 10477 assessed the flexural strength, water sorption, and water solubility."
• Data Provenance: The bench testing was performed to support the 510(k) submission from "Taiwan Dental Materials CO., LTD." The data would therefore originate from Taiwan, likely conducted prospectively for regulatory submission.

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 is a dental material, and the performance is evaluated through objective physical and chemical bench testing against international standards (ISO 10477). There were no human experts involved in establishing a "ground truth" in the way it's understood for AI/ML diagnostic devices.

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

Not applicable. As this involves physical/chemical testing, there is no "adjudication method" in the context of human interpretation or consensus. The tests would be performed according to standardized protocols and the results measured objectively.

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 a medical device (dental material), not an AI/ML algorithm requiring human interpretation.

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

Not applicable. This is a medical device (dental material), not an AI/ML algorithm.

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

The "ground truth" for the device's performance is established by international standards for dental materials (ISO 10477). These standards define the acceptable ranges and methodologies for evaluating physical and chemical properties like flexural strength, water absorption, and water solubility.

8. The sample size for the training set

Not applicable. This is a medical device (dental material), not an AI/ML algorithm that requires a "training set."

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

Not applicable. This is a medical device (dental material), not an AI/ML algorithm.

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Mastergraft™ Matrix EXT is to be combined with autogenous bone marrow and is indicated for bony voids or gaps not intrinsic to the stability of the bony structure and can be used as a bone graft extender. The device is to be gently packed into bony voids or gaps of the skeletal system (i.e., the posterolateral spine, intervertebral disc space, pelvis, ilium, and/or extremities). These defects may be surgically created osseous defects or osseous defects created from traumatic injury to the bone. The device resorbs and is replaced with bone during the healing process. When used in intervertebral body fusion procedures, Mastergraft™ Matrix EXT must be used with an intervertebral body fusion device cleared by FDA for use with a bone void filler.

Mastergraft™ Strip is to be combined with autogenous bone marrow and is indicated for bony voids or gaps that are not intrinsic to the stability of the bony structure and can be used as a bone graft extender.

The device is to be gently packed into bony voids or gaps of the skeletal system (i.e., the posterolateral spine, intervertebral disc space, pelvis, ilium, and/or extremities). These defects may be surgically created osseous defects or osseous defects created from traumatic injury to the bone. The device resorbs and is replaced with bone during the healing process. When used in intervertebral body fusion procedures, Mastergraft™ Strip must be used with an intervertebral body fusion device cleared by FDA for use with a bone void filler.

Mastergraft™ Putty combined with either autogenous bone marrow, and/or sterile water, and/or autograft is indicated as a bone void filler for bony voids or gaps not intrinsic to the stability of the bony structure. Additionally, Mastergraft™ Putty can be used with autograft as a bone graft extender.

Mastergraft™ Putty is to be gently packed into bony voids or gaps of the skeletal system (e.g., the posterolateral spine, intervertebral disc space, pelvis, ileum, and/or extremities). These defects may be surgically created osseous defects or osseous defects created from traumatic injury to the bone. Mastergraft™ Putty resorbs and is replaced with bone during the healing process. When used in intervertebral body fusion procedures, Mastergraft™ Putty must be used with an intervertebral body fusion device cleared by FDA for use with a bone void filler.

Mastergraft™ Granules is indicated only for bony voids or gaps that are not intrinsic to the stability of the bony structure. Additionally, Mastergraff™ Granules can be used with autograft as a bone graft extender. Mastergraft™ Granules is to be gently packed into bony voids or gaps of the skeletal system (e.g., the posterolateral spine, intervertebral disc space, pelvis, ilium and/or extremities). These defects may be surgically created osseous defects created from traumatic injury to the bone. Mastergraft™ Granules provides a bone void filler that resorbs and is replaced with bone during the healing process. When used in intervertebral body fusion procedures, Mastergraft™ Granules must be used with an intervertebral body fusion device cleared by FDA for use with a bone void filler.

The Mastergraft™ Family of bone grafts in this submission includes Mastergraff™ Matrix EXT, Mastergraft™ Strip, Mastergraft™ Putty, and Mastergraft™ Granules. The devices all include osteoconductive biphasic calcium phosphate ceramic granules in different biocompatible physical forms supplied sterile for single patient use.

Mastergraft™ Matrix EXT is made from a combination of medical grade purified collagen of bovine origin and biphasic calcium phosphate ceramic. In the devices, the collagen is a highly purified (>95%) Type I bioresorbable lyophilized collagen. The biphasic ceramic portion of the device is provided in a 15 percent hydroxyapatite and 85 percent B-tricalcium phosphate formulation. Mastergraft™ Matrix EXT is supplied sterile in a premixed strip form for single patient use. Mastergrafi™ Matrix EXT is a biocompatible, osteoconductive, porous implant that allows for bony ingrowth across the graft site while resorbing at a rate consistent with bone healing. The device readily absorbs bone marrow aspirate. Mastergraft™ Matrix EXT is identical to the device cleared in K141824.

Mastergraff™ Strip is made from a combination of medical grade purified collagen of bovine origin and biphasic calcium phosphate ceramic. In the Mastergraft™ Strip device, the collagen is a highly purified (>95%) Type I bioresorbable Iyophilized collagen. The biphasic ceramic portion of the device is provided in a 15 percent hydroxyapatite and 85 percent ß-tricalcium phosphate formulation. Mastergraft™ Strip is supplied sterile in a premixed strip form for single patient use. Mastergrafi™ Strip is a biocompatible, osteoconductive, porous implant that allows for bony ingrowth across the graft site while resorbing at a rate consistent with bone healing. The device readily absorbs bone marrow aspirate and has been shown to heal bone defects. Mastergraft™ Strip is identical to the device cleared in K082166.

Mastergraff™ Putty is made from a combination of medical grade purified collagen of bovine origin and biphasic calcium phosphate ceramic. The collagen component in the Mastergraft™ Putty device is Type I bovine collagen. The biphasic ceramic portion of Mastergraft™ Putty is provided in a 15 percent hydroxyapatite and 85 percent ß-tricalcium phosphate formulation. Mastergraft™ Putty is supplied as a sterile, dry, solid, construct hydrated for single patient use and is a moldable form of bone void filler. Mastergraft™ Putty is an osteoconductive, porous implant that allows for bony ingrowth across the graft site while resorbing at a rate consistent with bone healing. Mastergraft™ Putty is biocompatible. Mastergraft™ Putty readily absorbs bone marrow aspirate and was shown to heal bone defects. Mastergraff™ Putty is identical to the device cleared in K071813.

Mastergraft™ Granules is made of medical grade combination of hydroxyapatite and ßtricalcium phosphate. MASTERGRAFT® Granules is provided in a 15 percent hydroxyapatite and 85 percent ß-tricalcium phosphate formulation. The product is supplied sterile for single patient use. MASTERGRAFT® Granules is an osteoconductive porous implant. Mastergraft™ Granules is identical to the device cleared in K082918.

The provided text is a 510(k) Premarket Notification from the FDA, which focuses on demonstrating substantial equivalence of a new medical device to existing predicate devices. It does not contain information about acceptance criteria or a study that proves the device meets specific performance metrics in the context of an AI/ML medical device.

The document discusses bone void filler devices (Mastergraft™ family) and their indications for use, stating that the current submission expands their use to include intervertebral disc space. The core of the notification is to establish that these devices are substantially equivalent to previously cleared devices. This is a regulatory pathway for medical devices that does not typically involve the kind of detailed performance studies with acceptance criteria, test sets, ground truth establishment, or clinical outcome measures that would be expected for a novel AI/ML diagnostic or prognostic tool.

Therefore, I cannot fulfill your request using the provided text because it does not describe:

1. Acceptance criteria for device performance (in the context of an AI/ML device).
2. A study proving the device meets acceptance criteria. The document references prior clearances and robust analysis from previous studies, but it doesn't detail a new study design, methodology, or results related to specific performance metrics for the current submission.
3. Details about sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, or training set details. These are all concepts relevant to the validation of AI/ML models, which are not discussed in this medical device submission.

The "Performance" section explicitly states: "The subject devices have been previously cleared under K141824, K082166, K071813, and K082918, which serve as Reference Devices. These submissions are leveraged to support the device's sterility, shelf-life, endotoxin, pyrogenicity, biocompatibility, and characterizations/bench performance as recommended in FDA's Class II Special Controls Guidance Document for Resorbable Calcium Salt Bone Void Filler Devices. The device's performance in intervertebral spine was supported by a robust analysis of bone grafting materials in the prior posterolateral spine fusion studies." This indicates reliance on previous data and general guidelines, not a new, specific performance study with the requested AI/ML validation metrics.

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The Ti-Base & Master Fix are intended to be used in conjunction with endosseous dental implants in the maxillary or mandibular arch to provide support for prosthetic restorations. All digitally-designed Ti-Base and Master Fix are intended to be sent to an ARUM DENTISTRY validated milling center for manufacture.

The Ti-Base & Master Fix consist of a two-piece abutment, where the titanium base is premanufactured abutment that will be used to support a CAD/CAM designed superstructure (the second part of the two-piece abutment) that compose the final abutment.
Device Components:

1. Abutment

• Ti-Base
• Master Fix
• Abutment Screw
  The Ti-Base and Master Fix are provided non-sterilized. Ti-Base is enclosed with Abutment Screw in a packing. Master Fix is enclosed with Master Fix Screw in a packing. These devices are intended for single use only. All digitally designed custom abutments for use with Ti-Base or Master Fix are to be sent to ARUM DENTISTRY validated milling center for manufacture. All superstructures are to be manufactured from zirconia (cleared K190112). Digitally designed CAD/CAM abutments must have a 0.5 mm minimum gingival height dimension. The Titanium Base abutment is composed of two-piece abutment that is a titanium base at the bottom and a zirconia superstructure (CAD/CAM patient specific superstructure) at the top. The zirconia superstructure is straight only and is not to be designed to provide an angle or divergence correction.

The provided document is a 510(k) premarket notification for the "Ti-Base & Master Fix" dental implant abutments. It includes a summary of technology characteristics and performance data but does not contain specific acceptance criteria, a study proving device performance against those criteria, or details regarding ground truth, expert opinions, or MRMC studies. The document focuses on demonstrating substantial equivalence to a predicate device (DESS Dental Smart Solutions, K191986) primarily through material composition, intended use, and mechanical testing that mitigates minor design differences.

Therefore, many of the requested details cannot be extracted from this document.

However, based on the information provided, here's what can be answered:

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

• The document does not explicitly state quantitative acceptance criteria for device performance (e.g., minimum fracture strength, fatigue life thresholds) or report specific numerical performance outcomes against such criteria for the "Ti-Base & Master Fix" directly.
• It references mechanical performance testing as a method to mitigate differences in design and ensure safety and effectiveness, implying that such tests were conducted and their results were deemed acceptable, but the actual data/criteria are not provided in this summary.
• It also mentions biocompatibility testing according to ISO 10993-5 and ISO 10993-12, and moist heat sterilization validation according to ISO 17665 -1 and ISO 17665-2. These standards implicitly contain acceptance criteria, but the specific results or criteria are not detailed in this submission summary.

Table of Acceptance Criteria and Reported Device Performance (Based only on what's implicitly mentioned as having been met)

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 does not provide details on sample sizes for mechanical performance testing, biocompatibility, or sterilization validation.
• No information on the country of origin of the data or whether the studies were retrospective or prospective can be extracted.

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 not provided. The submission is for a medical device (dental implant abutment), and the performance data primarily relates to physical and material properties, not diagnostic imaging or clinical interpretation requiring expert ground truth establishment in that typical sense.

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

• Not applicable and not provided. This typically applies to clinical or imaging studies where expert consensus is formed, which is not the type of study 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

• Not applicable and not provided. This is a medical device (dental implant abutment) submission, not an AI-assisted diagnostic device.

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

• Not applicable and not provided. This is a physical medical device.

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

• Not applicable. For physical device testing, ground truth would typically refer to established engineering standards, material properties, and validated test methods (e.g., ISO standards for mechanical testing, biocompatibility).

8. The sample size for the training set

• Not applicable and not provided. There is no machine learning or AI component described that would require a training set.

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

• Not applicable and not provided.

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The MasterX 800 Series is intended for use by a qualified/trained doctor or technologist. As part of a radiographic system, the MasterX 800 Series is intended to acquire digital radiographic images on adult and pediatric patients. It is suitable for all routine radiography exams, including specialist areas like intensive care or trauma work, excluding fluoroscopy, angiography and mammography.

This device represents a new combination of already cleared solid state digital x-ray acquisition panels and already cleared software. It is suitable for use with adult and pediatric populations. This is an upgrade kit for existing or new systems.

Here's an analysis of the provided text regarding the acceptance criteria and supporting study for the MasterX 800 Series, structured according to your request:

Based on the provided FDA 510(k) Summary, the MasterX 800 Series device is primarily an upgrade kit consisting of a new combination of already cleared digital X-ray acquisition panels and existing software. The submission focuses on demonstrating substantial equivalence to a predicate device rather than presenting a de novo study with strict acceptance criteria for novel performance claims.

Therefore, the "acceptance criteria" here are implicitly tied to demonstrating safety and effectiveness compared to the predicate, and the "study" is primarily non-clinical validation and integration testing.

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

Since this is a 510(k) submission for an existing technology combination, explicit quantitative acceptance criteria for new clinical performance aren't stated as they would be for a novel AI device with specific performance metrics. Instead, the "performance" shown is its equivalence to the predicate device and the compliance of its components with relevant 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 states: "Summary of clinical testing: Not required."
• Therefore, there is no clinical test set, sample size, or data provenance from a clinical study. The evaluation relies on non-clinical testing.

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 as no clinical test set or ground truth established by experts was used for performance evaluation in a clinical context. The evaluation was primarily engineering and regulatory in nature, comparing an assembled system to a predicate device.

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

• Not applicable as no clinical test set requiring adjudication was used.

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 comparative effectiveness study was done. This device is an X-ray acquisition system, not an AI-powered diagnostic or assistive tool.

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

• Not applicable as this is an X-ray acquisition system, not an algorithm being evaluated for standalone performance. The "software" referred to is image acquisition software, which is part of the system operation, not an AI for interpretation.

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

• No clinical ground truth (expert consensus, pathology, outcomes data) was used, as no clinical study was performed. The "ground truth" for the non-clinical testing was defined by engineering specifications, regulatory standards compliance, and comparison to the predicate device's established performance parameters (e.g., DQE, MTF).

8. The sample size for the training set

• No training set is mentioned or applicable, as this device is an X-ray acquisition system and not an AI/machine learning algorithm that requires training data.

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

• Not applicable, as there is no training set mentioned or used.

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ELEC Master & ELEC Master Dual are intended for use in general dental applications such as: cutting a tooth for cavity preparation, crown preparation, crown finishing, inlay, filing, polishing, prophylaxis and endodontic treatment.

This product consists of a micro motor controller and display panel. Receiving rated input of AC 24V, this device controls motor speed, and rotation direction through the motor control circuit inside the controller. Motor speed, light and rotation direction functions can be set on the display panel.

This document is a 510(k) Premarket Notification from the FDA for a dental handpiece and accessories called "ELEC Master" and "ELEC Master Dual" by MGNEWTON Ltd. It's a regulatory document demonstrating substantial equivalence to a predicate device, not a detailed study report. Therefore, most of the requested information regarding acceptance criteria and performance studies is not explicitly provided in the typical format of a medical device performance study report.

Here's an analysis based on the provided text, addressing your questions to the extent possible:

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

The document does not provide a table of acceptance criteria and reported device performance in the sense of accuracy, sensitivity, specificity, or other clinical performance metrics that would be associated with a diagnostic or treatment guidance AI device.

Instead, the "acceptance criteria" here relate to conformity with established standards for dental handpieces and electrical safety, and substantial equivalence to a predicate device. The "reported device performance" is essentially that the device complies with these standards and has equivalent specifications to the predicate.

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

This document describes non-clinical bench tests (performance tests, electrical safety, EMC, sterilization validation, software validation) against recognized standards and a comparison of technical specifications to a predicate device. It does not involve a study with a test set of human subjects or patient data in the way an AI diagnostic device would. Therefore, sample size for a test set and data provenance (country of origin, retrospective/prospective) are not applicable in this context. The "test set" here refers to the actual device prototypes undergoing the specified bench tests.

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 section is not applicable. The "ground truth" for this type of device is established by adherence to engineering specifications and international standards (e.g., maximum torque defined by a standard, electrical safety requirements). These are objective measurements against predefined criteria, not subjective interpretations requiring expert consensus.

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

This section is not applicable. Adjudication methods like 2+1 or 3+1 are typically used for establishing ground truth from expert interpretations (e.g., radiologists reading images) where disagreement might occur. For objective bench tests and compliance with engineering standards, no such adjudication is needed.

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 section is not applicable. This device is a dental handpiece motor system, not an AI-powered diagnostic or treatment assistance tool. Therefore, MRMC studies and the concept of "human readers improving with AI assistance" are irrelevant to this submission.

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

This section is not applicable. The device is not an algorithm or AI system. Its performance is evaluated through its physical and electrical characteristics as determined by bench testing against established standards.

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

The "ground truth" in this context is the compliance with predefined technical specifications and international consensus standards. For example, the "ground truth" for torque is the specified 3Ncm, and the test verifies that the device meets this. The "ground truth" for electrical safety is its conformity to IEC 60601-1.

8. The sample size for the training set

This section is not applicable. This is not an AI/machine learning device, so there is no training set.

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

This section is not applicable. As there is no training set, the establishment of ground truth for it is irrelevant.

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The Baxter SIGMA Spectrum Infusion Pump with Master Drug Library is intended to be used for the controlled administration of fluids. These may include pharmaceutical drugs, blood, blood products and mixtures of required patient therapy. The intended routes of administration consist of the following clinically accepted routes; intravenous, arterial, subcutaneous, epidural or irrigation of fluid space. The Baxter SIGMA Spectrum Infusion Pump with Master Drug Library is intended to be used in conjunction with legally marketed and compatible intravenous administration sets and medications provided by the user.

The Baxter SIGMA Spectrum Infusion Pump with Master Drug Library is suitable for a variety of patient care environments such as, but not limited to hospitals and outpatient care areas.

The Baxter SIGMA Spectrum Infusion Pump with Master Drug Library is intended to reduce operator interaction through guided programming, thereby helping to reduce errors. The Baxter SIGMA Spectrum Infusion Pump with Master Drug Library is intended to be used by trained healthcare professionals.

The Baxter SIGMA Spectrum Infusion Pump with Master Drug Library is a large volume infusion pump system that provides for safe and effective delivery of fluids into a patient in a controlled manner, as identified in 21 CFR, 880.5725. The pump is a software controlled, electromechanical device used for the infusion of pharmaceutical drugs, blood, blood products and mixtures of required patient therapy through administration sets at user selectable rates and volumes. The feedback-controlled, motorized pumping mechanism is of linear peristaltic design and uses inlet and outlet valves for flow control. The pump utilizes a primary and secondary processor to assure safe operation while providing infusion pump capabilities for a wide range of applications.

The pump is specifically manufactured and calibrated for the application of a manufacturer's brand of standard gravity administration sets, as indicated in the device labeling. For use, the administration set is loaded into the infusion pump. After acceptance of program parameters, the pump is started and fluid is propelled by the peristaltic action of the pumping mechanism against the outside surface of the administration set tubing. The pump is controlled to create smooth fluid dynamics, precision volumetric accuracy and uniformity of flow rate. None of the pump materials contact the administration set's fluid path.

The infusion pump is small in comparison to the traditional Large Volume Parenteral (LVP) infusion pumps currently on the market. It is designed to be used in a variety of patient care environments such as, but not limited to hospitals and outpatient care areas using an IV pole mounted configuration.

The Master Drug Library (MDL) Editor is a software application that allows the generation, configuration and management of a downloadable drug library into a SIGMA Spectrum infusion pump.

The drug library can be loaded directly into the SIGMA Spectrum infusion pump through a wireless network host or through an Infrared Data Association (IrDA) device. The MDL Editor software operates on a Microsoft Windows® platform.

Using the MDL Editor software application, a facility can provide preprogrammed delivery profiles, advisories and limits for a corresponding drug that is intended for a specific use classification or clinical care area, thus reducing the risk of medication errors.

The MDL Editor software application allows the ability to generate both standard or customized drug and fluid reports by clinical care area. The MDL Editor software application also provides a feature to restrict/limit the access of data to only appropriate personnel, providing additional security and rights to specific users.

The provided text is a 510(k) summary for the Baxter SIGMA Spectrum Infusion Pump with Master Drug Library. Its purpose is to demonstrate substantial equivalence to a predicate device, not to detail the full acceptance criteria and study proving its performance.

The document does not contain any information about acceptance criteria or a study that proves the device meets specific performance criteria related to AI or a clinical effectiveness study.

Instead, the document focuses on:

• Identifying the device and its predicate.
• Describing the device's function as an infusion pump.
• Stating its indications for use.
• Explaining that the specific 510(k) notification is to "update the algorithm and labeling related to the upstream occlusion alarm of the pump" and that "Performance testing for the software was completed."

Therefore, I cannot provide the requested information based on the given text. The prompt asks for details that would typically be found in a detailed validation report or clinical study summary, which is not present in this 510(k) summary.

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Vigilant Master Med is part of a Dose Error Reduction System (DERS) for use with Adults, Pediatrics, and Neonates. It is intended to create, customize, and manage drug library data and device configurations to be uploaded to compatible Fresenius Kabi infusion devices which may reduce the risk of drug administration errors. It enhances safety by preventing infusion errors with the use of Dose Error Reduction System (DERS) in combination with the infusion devices.

Vigilant Master Med is a drug library software that is used by pharmacists to create and identify limits according to policy and procedure of the institution. The infusion devices will notify and clearly indicate to a clinician if the dose for the medication is beyond the limits entered by the pharmacist and provided by Vigilant Master Med in the drug library.

Vigilant Master Med is one component of Vigilant Software Suite (VSS) a multifunction device product. VSS Vigilant Master Med the subject of this submission, is also referred to as Drug Library Software. VSS Vigilant Master Med is drug library software that creates, customizes and manages drug lists, therapies, drug libraries, device configurations, profiles and data sets which are uploaded into compatible infusion pumps.

The provided text describes the 510(k) premarket notification for the "Vigilant Software Suite - Vigilant Master Med" and its comparison to a predicate device, "Vigilant Drug' Lib Agilia." However, the document primarily focuses on demonstrating substantial equivalence based on non-clinical testing and technological comparison. It explicitly states that "Clinical evaluation is not required for this submission to support substantial equivalence." and "no further clinical investigation or testing is needed."

Therefore, I cannot provide details on the acceptance criteria or a study that proves the device meets specific performance criteria in a clinical context, as such data is not included in the provided text. The submission relies on verification and validation of product requirements, human factors engineering testing, interoperability testing, performance testing at maximum capacity, and cybersecurity testing to demonstrate safety and effectiveness, and thus substantial equivalence.

Based on the information provided in the document, here's what can be extracted:

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

The document implicitly defines "acceptance criteria" through the comparison to the predicate device and the findings of non-clinical tests. The "reported device performance" is essentially the determination of "Similar," "Same," or "Different" with supporting statements that these differences do not affect safety or effectiveness, or that verification/testing found no new issues.

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

• Sample Size: The document does not specify exact "sample sizes" in terms of number of cases or data points for the non-clinical tests (verification, human factors, interoperability, performance, cybersecurity testing). It refers to the sufficiency of these tests to conclude safety and effectiveness.
• Data Provenance: Not specified in terms of country of origin. The data is generated from non-clinical (laboratory/engineering) testing rather than patient data. The studies are prospective in the sense that they are specifically conducted for the regulatory submission to verify and validate the new device.

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

• Number of Experts: Not explicitly stated. The "ground truth" for this device (software for managing infusion pump drug libraries) would primarily be established by:
  • Engineers/Developers: Defining correct software functionality and performance.
  • Quality Assurance personnel: Verifying adherence to requirements.
  • Human Factors Specialists: Assessing usability and safety in simulated clinical tasks.
  • Pharmacists and Clinicians (as users): Participating in human factors evaluations to ensure the software's design supports their workflow and safety goals. The document states "Human Factors studies have been conducted on the subject device demonstrating passing results," implying clinical domain experts were involved in a user capacity.
• Qualifications of Experts: Not explicitly stated for specific roles. However, given the context of medical device regulation, these would be qualified professionals in their respective fields (e.g., software engineers, human factors engineers, clinical experts - likely pharmacists and nurses for an infusion pump system).

4. Adjudication method for the test set:

• Since no multi-reader or multi-expert assessment of clinical "cases" is described (as it's a software substantial equivalence submission based on non-clinical tests), there is no mention of an adjudication method like 2+1 or 3+1. The "adjudication" is implicitly the outcome of the comprehensive verification and validation processes and the safety assurance case.

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. This is not an AI-assisted diagnostic device where human reader improvement would be measured. The device is a software for drug library management for infusion pumps, not a medical image analysis or similar AI tool.

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

• The software's core function is to create and manage drug libraries, which is "algorithm only" in its processing of data and rules. However, its purpose is to be used with human-in-the-loop (pharmacists inputting data, clinicians interacting with the infusion pump).
• Standalone algorithmic verification: Yes, this is implied by "Verification testing of product requirements," "Performance testing at maximum capacity," and "Cybersecurity penetration testing." These tests assess the software's inherent functionality and robustness independent of user interaction, but within the context of its overall intended use.

7. The type of ground truth used:

• The primary "ground truth" used for this submission is:
  • Pre-defined product requirements and specifications: The software must perform according to these.
  • Safety standards and regulatory guidance: Adherence to these is the "truth" for demonstrating safety and effectiveness.
  • Usability goals derived from human factors analysis: The software's design must support safe and effective use by intended users.
  • Functionality of the predicate device: The new device's functions are compared to the legally marketed predicate.
• It is not based on expert consensus for clinical diagnosis, pathology, or outcomes data, as this is not a diagnostic device.

8. The sample size for the training set:

• Not applicable/Not provided. This is a traditional software engineering development and a 510(k) submission based on substantial equivalence, not a machine learning/AI model that requires a "training set" for its development. The "learning" here is human engineering and design, not algorithmic learning from data.

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

• Not applicable. As stated above, there is no "training set" in the machine learning sense.

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