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510(k) Data Aggregation
(70 days)
Clinical or mass-chest radiography
ThoraScan provides the radiologists or pneumologists the ability to acquire chest x-ray images by filmless radiography (digital radiography), based on a Csl/CCD slot scan detector produced by Thomson TE.
The x-ray transmission profile of the chest is converted into an electronic, digital image in real-time. Chest images become available for preview by the x-ray technician on the operator's workstation only seconds after the x-ray exposure.
operator o wonecation one by the tech, digital (DICOM) images can be stored on electronic media, as e.g. CD-ROM, magnetic disk, or be exported to a (DICOM/PACS) network, c.q. clinical review station or to a film printer.
Note: PACS, networks, clinical review stations and (laser-) film printers are not considered part of the Digidelca system for which this application is filed, only external interfaces tot this type of equipment are defined.
The Nucletron Oldelft ThoraScan is intended to be used for medical procedures on patients to be prescribed and performed by a suitably trained and certified medical professional.
ThoraScan is a digital X-ray chest camera based on slot-scan technology and is designed to perform radiographic chest examinations. The detector is comprised of CCD's directly coupled to a cesium iodide scintillator. The digital image is sent through a DICOM network. The ThoraScan consists of a camera stand with detector, tube stand, control unit, x-ray tube, collimator, generator and the OWS (Operators workstation).
The provided 510(k) summary for the Nucletron Oldelft ThoraScan describes non-clinical and clinical tests, but it does not provide specific, quantifiable acceptance criteria or detailed results in the format requested. The document primarily focuses on demonstrating substantial equivalence to a predicate device (Digidelca) and highlighting improvements.
Here's an analysis based on the information provided and what is missing:
Description of Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria
The Nucletron Oldelft ThoraScan is a digital X-ray chest camera based on slot-scan technology, designed for radiographic chest examinations. The study presented is a comparison to a predicate device, the Nucletron Digidelca, aiming to demonstrate substantial equivalence and improved performance. However, there are no explicitly stated, quantifiable acceptance criteria for either non-clinical or clinical performance, nor is there a detailed study report with metrics to prove these criteria were met.
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria (Quantitative) | Reported Device Performance (Quantitative) |
---|---|
Not explicitly stated in the document. The document generally states "superior results" and "better image quality" compared to the predicate device. | Not explicitly stated in the document. |
Example of what might be expected: Modulation Transfer Function (MTF) at certain spatial frequencies > X | Reported for ThoraScan: Superior results compared to Digidelca-C (for resolution and contrast) |
Example of what might be expected: Signal-to-Noise Ratio (SNR) > Y | Reported for ThoraScan: Superior results compared to Digidelca-C (for resolution and contrast) |
Example of what might be expected: Radiologist agreement on diagnostic quality improvement > Z% | Reported for ThoraScan: Digital images had "better image quality than the Digidelca-C" as judged by radiologists. |
Missing Information: The document states "resolution and contrast measurements which are reported in Tab 10 of this application," but "Tab 10" is not included in the provided text. Without this table, specific numerical acceptance criteria and performance data are unavailable.
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: Not specified. The document only mentions "PA and lateral radiograms were judged."
- Data Provenance: Not specified. The country of origin for the clinical data is not mentioned, nor is it stated whether the study was retrospective or prospective.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
- Number of Experts: "several radiologist" - the exact number is not specified.
- Qualifications of Experts: Not specified (e.g., years of experience, subspecialty).
4. Adjudication Method
- Adjudication Method: Not specified. The document only states that radiograms "were judged by several radiologist." It does not detail how disagreements were resolved or if a consensus method (e.g., 2+1, 3+1) was used.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- The document describes a comparative evaluation where "PA and lateral radiograms were judged by several radiologist and found the digital images had better image quality than the Digidelca-C." This suggests a comparative reading, but it's not explicitly framed as a formal MRMC comparative effectiveness study in the way modern AI clearance studies are.
- Effect Size of Human Readers Improve with AI vs without AI: Not applicable, as this device itself is an imaging system, not an AI algorithm assisting human readers. The comparison is between two imaging systems (ThoraScan vs. Digidelca-C) with human readers evaluating image quality. The "better image quality" implies a positive effect, but no quantifiable effect size is provided.
6. Standalone (Algorithm Only) Performance
- This question is not applicable in the context of the Oldelft ThoraScan. The device is a digital X-ray system, not an AI algorithm. Its performance is inherent in the image acquisition and output, which is then interpreted by human readers. The non-clinical tests (resolution, contrast) could be considered standalone performance metrics of the imaging system.
7. Type of Ground Truth Used
- Ground Truth Type: Expert consensus on "image quality." This is subjective judgment by radiologists, rather than objective pathology or outcomes data.
8. Sample Size for the Training Set
- Training Set Sample Size: Not applicable. As an imaging device (hardware/firmware), the ThoraScan does not utilize a "training set" in the machine learning sense. Its design and calibration are based on engineering principles and prototype testing.
9. How the Ground Truth for the Training Set was Established
- Ground Truth Establishment for Training Set: Not applicable, as a training set is not relevant to this type of device.
Summary of Limitations in the Provided Text for a Modern AI/Medical Device Study Perspective:
The provided 510(k) summary is typical for medical device submissions from 2001, focusing on establishing substantial equivalence to a predicate device. It lacks the quantitative detail, rigorous study design, and specific metrics that would be expected for a modern AI-powered diagnostic device, particularly regarding acceptance criteria, sample sizes, and detailed expert adjudication methods. The "clinical tests" described are more akin to a usability or preference study regarding image quality than a definitive diagnostic accuracy trial.
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