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The ATLAS™ Plating System is intended to stabilize and aid in the repair of fractures, fusions, and osteotomies of small bones and bone fragments in adult and pediatric patients.

The ATLAS™ Plating System is a metallic plate and screw system for treatment and fixation of fractures, fusions and osteotomies of bones in the Foot, Ankle, Hand, and Wrist of children (2-12 years), adolescents (12-21 years), and adults. The screws are available in different diameters from Ø2.7mm to Ø5.5mm, non-locking configurations with lengths ranging from 8mm to 60mm. All screws are manufactured from Titanium alloy (Ti-6Al-4V ELI per ASTM F136-13). The plates are available in different geometries to accommodate different patient and bone anatomies. The plates are manufactured from MoRe® alloy (Molybdenum-47.5Rhenium Alloy per ASTM F3273-17).

The provided text is a 510(k) summary for the ATLAS™ Plating System. This document focuses on demonstrating substantial equivalence to predicate devices for regulatory clearance, primarily through mechanical testing of the device itself rather than studies involving human or animal subjects or complex algorithms. Therefore, much of the requested information regarding "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of AI/ML or diagnostic device performance is not present in this type of submission.

Here's a breakdown of the available information:

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

The document does not specify quantified acceptance criteria (e.g., specific tensile strength values, fatigue limits with minimum requirement numbers) or explicit reported device performance in a table format. Instead, it states that "Mechanical testing for screws (ASTM F543-17)" and "Mechanical testing for plates (ASTM F382-17)" were performed. The conclusion is that "Performance data demonstrate that the ATLAS™ Plating System is substantially equivalent legally marketed predicate devices." This implies that the device met the performance characteristics demonstrated by the predicate devices through these standard tests, which is the basis for substantial equivalence.

If this were an AI/ML device, this section would typically include metrics like Sensitivity, Specificity, AUC, F1-score, accuracy, etc., with associated thresholds.

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

This information is not applicable to this type of device submission. The "test set" in this context refers to the physical devices (screws and plates) subjected to mechanical testing, not a dataset of patient information. No patient data provenance is relevant here.

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 is not applicable. The "ground truth" for mechanical testing is established by engineering standards (ASTM F543-17 and ASTM F382-17) and the physical properties of the materials and device design, not by expert human interpretation.

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

This is not applicable to mechanical testing.

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 is not applicable. This is a medical device (plating system) submission, not an AI/ML diagnostic or assistive device.

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

This is not applicable.

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

The "ground truth" for this submission is implicitly the established performance characteristics dictated by the referenced ASTM standards (ASTM F543-17 for screws and ASTM F382-17 for plates), which define the methods and expected results for mechanical properties. The device's performance is compared against the performance of predicate devices tested under similar standards to establish substantial equivalence.

8. The sample size for the training set

This is not applicable. There is no "training set" in the context of mechanical device testing for a 510(k) submission of this nature.

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

This is not applicable.

Summary regarding the provided document:

The provided 510(k) summary for the ATLAS™ Plating System represents a traditional medical device submission focused on mechanical performance and material compatibility. The "study" proving acceptance criteria is a series of mechanical tests conducted according to recognized ASTM standards (ASTM F543-17 and ASTM F382-17). The "acceptance criteria" are not explicitly quantified in the document but are understood to be the successful demonstration of mechanical properties comparable to predicate devices, thus establishing substantial equivalence.

This type of submission does not involve clinical studies with patient data, AI/ML algorithms, or human reader performance evaluations, which are typically found in submissions for diagnostic software or AI-enabled devices.

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The KrystalRad 1100 and KrystalRad 3000 Digital Stationary Radiographic Systems are intended for use by a qualified/ trained doctor or technician on both adult and pediatic subjects for taking diagnostic radiographic exposures of the skull, spinal column, chest. abdomen, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. Not for mammography.

This device represents a new combination of already cleared solid state digital x-ray acquisition panels and software with the diagnostic x-ray compnents required to make a complete system. The purchaser may select their digital panel from this list:

• Toshiba wireless flat panel detector (FDX-3543RP, FDX-3543RPW, 14 in. x 17 in.) or Toshiba wired flat panel detector (FDX-4343R, 17 in x 17in). (K130883)
• Vieworks all series: (FXRD-1717SA/SB, or FXRD-1417SA/SB or FXRD-1417WA/WB. (K130337, Medicatech "New Series.")
• PerkinElmer XRpad™ 4336 MED, (K140551).
  The purchaser can select either a "C" arm configuration (KrystalRad 1100) or an overhead tube crane configuration (KrystalRad 3000). The x-ray generator is a CPI CMP 200DR. The x-ray tubes are supplied by Toshiba (E7252X Series), and the collimator is the Ralco R302A. An IBA kerma meter model 120-131 is supplied.

The provided text describes the KrystalRad 1100 and KrystalRad 3000 Digital Stationary Radiographic Systems. However, it does not contain detailed information regarding the acceptance criteria, specific performance metrics, sample sizes for test/training sets, expert qualifications, or adjudication methods typically found in a clinical study report for AI-powered devices.

This document is a 510(k) premarket notification for a traditional medical device (an X-ray system), not an AI/ML-powered device that requires extensive clinical performance evaluation against specific acceptance criteria. The approval is based on substantial equivalence to a predicate device, meaning it has the same intended use and similar technological characteristics, and that its components have been previously cleared.

Here's a breakdown of the available information based on your request, highlighting what is present and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Missing: Specific quantitative performance metrics (e.g., sensitivity, specificity, AUC) or defined acceptance thresholds for diagnostic accuracy that would be typical for an AI device.

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

• Test Set Sample Size: Not specified. The document states "Clinical images were acquired from each panel".
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).

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

• Number of Experts: One
• Qualifications of Experts: "a board certified radiologist."

4. Adjudication Method for the Test Set

• Adjudication Method: Implicitly "none," as only one radiologist reviewed the images. There was no consensus or arbitration process mentioned.

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

• Was an MRMC study done? No. This type of study is more common for assessing the impact of AI on human reader performance.
• Effect size of improvement with AI vs. without AI: Not applicable, as this is not an AI-powered device.

6. Standalone Performance Study (Algorithm Only)

• Was a standalone study done? No. This device is a radiographic system, and its performance is evaluated as an integrated system producing images for human interpretation.

7. Type of Ground Truth Used

• Ground Truth Type: Expert opinion/review ("clinical images... reviewed by a board certified radiologist").

8. Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device is a traditional X-ray system, not an AI/ML model that requires a training set.

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

• How Ground Truth Was Established: Not applicable, as there is no training set for an AI/ML model.

Summary of Device and Study Context:

The KrystalRad 1100 and KrystalRad 3000 Digital Stationary Radiographic Systems are conventional X-ray machines. Their FDA clearance (K143257) is based on demonstrating substantial equivalence to an existing legally marketed device (Sedecal Nova FA DR System, K133782). The "study" described is a non-clinical bench testing and review of clinical images to ensure the system functions correctly and produces diagnostically acceptable images. It is not a clinical trial designed to establish specific performance metrics against a medical condition, nor does it involve an AI algorithm with training and test sets. The focus is on the safety and effectiveness of the hardware and integrated software for image acquisition, primarily through demonstrating that its components (cleared digital panels, generator, collimator) work together to produce images of "excellent diagnostic quality" as judged by a single radiologist.

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