Search Results

The BSD4343R Digital Flat Panel X-ray Detector (Model: BT-DA24-IA) is indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to replace film or screen based radiographic system in all general-purpose diagnostic procedures. It is not to be used for mammography.

Not Found

This document is a 510(k) clearance letter from the FDA for a digital flat panel X-ray detector. It is not a study proving the device meets acceptance criteria for an AI/ML medical device. Therefore, I cannot extract the information required to populate the fields you specified.

The provided text discusses:

• Device: BSD4343R Digital Flat Panel X-ray Detector
• Manufacturer: Bontech Inc.
• Regulatory Classification: Class II, Product Code MOB, Regulation Number 21 CFR 892.1680 (Stationary x-ray system)
• Approval Date: June 21, 2017
• Indications for Use: Digital imaging solution for general radiographic systems for human anatomy, intended to replace film or screen-based systems in general-purpose diagnostic procedures (not for mammography).

The letter confirms substantial equivalence to a predicate device, meaning it's cleared because it's as safe and effective as a device already on the market, not because it's an AI/ML device that has met specific performance criteria through a clinical study.

Therefore, I cannot provide the requested information for acceptance criteria and study details because this document does not contain that information, nor does it describe an AI/ML device or its performance study.

Ask a specific question about this device

The BSD3543(BT-DA22-IA) detector is indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to replace film or screen based radiographic system in all general-purpose diagnostic procedures. It is not to be used for mammography.

BSD3543(BT-DA22-IA/BT-DB22-IA) is a digital X-ray flat panel detector which intercepts x-ray photons and the scintillator (BT-DB22-IA(Gdos) / BT-DA22-IA(CsI)) emits visible spectrum photons that illuminate an array of photo (a-SI)-detector that creates electrical signals. After the electrical signals are generated, it is converted to digital values, and the images will be displayed on the monitor. This device should be integrated with an operating PC and an X-Ray generator. It can digitalize x-ray images and transfer them for radiography diagnostics. Advanced digital image processing allows considerably efficient diagnosis, all kinds of information management, and sharing of image information on network.

Based on the provided text, the device in question is the BSD3543 Digital Flat Panel X-ray Detector. The information describes non-clinical performance testing to demonstrate substantial equivalence to a predicate device (BONTECH BSD4343, K160204), rather than a study proving the device meets specific clinical acceptance criteria for diagnostic accuracy.

Here's a breakdown of the requested information based on the provided text. Please note that several items (like clinical study details, expert qualifications, adjudication methods, and training set information) are explicitly not available because the submission relies on non-clinical testing for substantial equivalence, not clinical studies for efficacy.

Acceptance Criteria and Device Performance for BSD3543 Digital Flat Panel X-ray Detector

The acceptance criteria for the BSD3543 Digital Flat Panel X-ray Detector are based on demonstrating substantial equivalence to its predicate device, BONTECH BSD4343 (K160204), through non-clinical performance testing. The key performance metrics compared are related to image quality and technical specifications.

1. Table of Acceptance Criteria and Reported Device Performance

The document states that the non-clinical performance testing concluded that "BSD3543(BT-DA22-IA/BT-DB22-IA) offer similar or better resolution performance than BSD4343 at 0 ~ 3.5lp/mm spatial frequencies. Moreover, the ability of BSD3543(BT-DA22-IA/BT-DB22-IA) to utilize the input image signal are more efficient than BSD4343 at same patient exposure as shown in the detective quantum efficiency graph." While the tables provide numerical differences, the overall conclusion is that performance is similar or better. Note that direct comparison of GDOS to CsI is done, and both are offered for the proposed device, suggesting the specific scintillator type impacts the exact values. The table for predicate only lists CsI for MTF/DQE, while proposed lists GDOS.

2. Sample Size Used for the Test Set and the Data Provenance
The submission relies on non-clinical bench testing rather than a clinical test set. The data provenance is described as "bench testing performed to compare the subject devices to the predicate." No patient data or country of origin is mentioned for this testing, as it's not a clinical study.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
Not applicable. No experts were used to establish ground truth for a clinical test set, as this was a non-clinical performance evaluation focused on physical properties (MTF, DQE, etc.) of the imaging device.

4. Adjudication Method for the Test Set
Not applicable. No clinical test set or adjudication method 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
Not applicable. This device is an X-ray detector, not an AI-powered diagnostic tool, and no MRMC study was performed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This device is an X-ray detector, not an algorithm, so standalone algorithm performance is not relevant. The performance tested is the inherent image quality of the detector.

7. The Type of Ground Truth Used
The "ground truth" for this non-clinical study were the established scientific and engineering performance metrics (e.g., MTF, DQE values, pixel pitch, resolution) obtained through standardized laboratory measurements. These are objective measurements of the device's physical and technical capabilities.

8. The Sample Size for the Training Set
Not applicable. This is not an AI/machine learning device, so there is no training set in the context of algorithm development.

9. How the Ground Truth for the Training Set Was Established
Not applicable. (See #8).

Ask a specific question about this device

The BSD4343 detector is indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to replace film or screen based radiographic system in all general-purpose diagnostic procedures. It is not to be used for mammography.

BSD4343 is a digital X-ray flat panel detector which intercepts x-ray photons and the scintillator (Gadox:Tb type) emits visible spectrum photons that illuminate an array of photo (a-SI)-detector that creates electrical signals. After the electrical signals are generated, it is converted to digital values, and the images will be displayed on the monitor. This device should be integrated with an operating PC and an X-Ray generator. It can digitalize x-ray images and transfer them for radiography diagnostics. Advanced digital image processing allows considerably efficient diagnosis, all kinds of information management, and sharing of image information on network.

The acceptance criteria and study proving the device meets them are described below for the BSD4343 Digital Flat Panel X-ray Detector.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state quantitative "acceptance criteria" for performance metrics in a pass/fail format. Instead, it demonstrates substantial equivalence to a predicate device (LLX240AB01) by showing similar or better performance in key imaging characteristics and adherence to safety standards. The "Reported Device Performance" below is derived from the comparison table and the "Non-clinical study" section, relative to the predicate.

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

The document does not explicitly mention a "test set" in the context of a clinical study with patient data. The "non-clinical study" section refers to physical values for comparison (DQE, MTF, NPS) with the predicate device. These are typically measured on phantoms or test objects, not human subjects, and therefore do not involve patient-specific sample sizes or data provenance in the clinical sense.

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

Since no clinical "test set" with patient data requiring expert ground truth is described, this information is not applicable. The basis for comparison is the technical specifications and measured performance of the device against a predicate, typically using engineering metrics and standards.

4. Adjudication Method for the Test Set

Not applicable, as no clinical "test set" requiring adjudication or expert consensus for ground truth is described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The submission relies on non-clinical performance data and substantial equivalence to a predicate device.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, the performance testing described is standalone, focusing on the inherent technical capabilities of the device (such as DQE, MTF, NPS) and its compliance with safety and electrical standards. These are measures of the device's technical performance, independent of human interpretation in a clinical setting.

7. The Type of Ground Truth Used

For the non-clinical performance metrics (DQE, MTF, NPS), the "ground truth" would be established through highly controlled measurements using calibrated equipment and phantoms according to industry standards. These are objective physical measurements, not subject to expert consensus, pathology, or outcomes data in the traditional sense of medical image evaluation. For regulatory compliance, the "ground truth" is defined by the requirements of the standards (e.g., IEC 60601-1).

8. The Sample Size for the Training Set

This information is not applicable. This device is a digital X-ray detector, which is hardware, not an AI algorithm that requires a training set of data.

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

This information is not applicable, as the device is not an AI algorithm and therefore does not have a "training set."

Ask a specific question about this device