(133 days)
The Philips Multislice CT Systems are Computed Tomography X-Ray Systems intended to produce cross-sectional images of the body by computer reconstruction of X-ray transmission data taken at different angles and planes. These devices may include signal analysis and display equipment supports, components and accessories. The scanners are intended to be used for diagnostic imaging and for low dose CT lung cancer screening for the early detection of lung nodules that may represent cancer*.
The screening must be performed within the established inclusion criteria of protocols that have been approved and published by either a governmental body or professional medical society.
*Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.
Philips Low Dose CT Lung Cancer Screening option can be used with Philips whole body multi-slice CT X-Ray Systems installed in a healthcare facility (clinic / hospital). These systems provide a continuously rotating X-ray tube and detector array with multi-slice capability. The acquired x-ray transmission data is reconstructed by computer into cross-sectional images of the body taken at different angles and planes. Reconstruction algorithms available are standard reconstruction (filtered back projection), iDose 4 and IMR iterative reconstruction. These systems also include signal analysis and display equipment, patient and equipment supports, components and accessories.
There are no functional, performance, feature, or design changes required for the qualified CT systems onto which the LDCT LCS Option is applied. Because none of the CTs will require hardware or software modifications, the Philips Low Dose CT Lung Cancer Screening option and the currently marketed and predicate Philips Multislice CT System for qualified CT systems in the installed base consists of:
- A set of up to three reference LDCT LCS protocols: standard reconstruction, standard reconstruction with iDose 4, and with IMR iterative reconstruction (where applicable), for each qualified CT System on a per CT platform basis;
- Detailed instructions on how to create the protocols on the corresponding CT System; and
- A dedicated Instructions for Use for LDCT LCS that covers all qualified systems.
This document is a 510(k) premarket notification for the Philips Multislice CT System with Low Dose CT Lung Cancer Screening. It primarily focuses on demonstrating substantial equivalence to existing predicate devices, rather than presenting a standalone study proving the device meats specific acceptance criteria in a clinical setting with human readers.
However, based on the provided text, I can infer the acceptance criteria relate to maintaining image quality parameters for Low Dose CT Lung Cancer Screening (LDCT LCS) that are equivalent to or better than standard CT performance, especially given the reduced radiation dose. The "study" proving this largely relies on non-clinical bench testing and references to external clinical literature and trials.
Here's a breakdown of the information you requested:
1. Table of Acceptance Criteria and Reported Device Performance
The document doesn't explicitly state "acceptance criteria" in a quantitative, measurable sense for a clinical study with patients. Instead, it focuses on demonstrating that the LDCT LCS option does not degrade image quality compared to existing CT systems and that existing clinical evidence supports the efficacy of LDCT LCS itself.
Here's a table based on the image quality parameters evaluated in non-clinical testing and the reported outcome of that testing:
| Acceptance Criteria (Inferred from Image Quality Parameters Evaluated) | Reported Device Performance (Non-Clinical Bench Testing Outcomes) |
|---|---|
| Spatial Resolution (MTF): Ability to visualize fine anatomical details, preserved at lower dose. | "MTF is a measure of the high contrast spatial resolution performance of the system. Nodules in the lung are high contrast objects and therefore, MTF should be preserved at lower dose conditions." "Demontrates that the image quality metrics including MTF... are substantially equivalent among different family of scanners (Brilliance 16, Brilliance Big Bore, Brilliance 64/Ingenuity, Brilliance iCT and IQon)." |
| Contrast Resolution (CNR): Ability to differentiate tissues with subtle differences in attenuation, sufficient for nodule detection. | "Sufficient Contrast-to-Noise is needed to detect solid and non-solid nodules in the lung. This parameter accounts for the contrast between an object and the background. This could also be a parameter that could influence nodule detectability." "The CNR scans were completed using the LDCT LCS scan protocols for all scanners in the comparison." "The results of non-clinical bench testing demonstrate that the image quality metrics including... Contrast to Noise Ratio are substantially equivalent among different family of scanners." "The contrast of the lung nodules it high relative to this increased noise, demonstrated by the CNR results (section 18) and NLST study." |
| Image Noise (Standard Deviation): Acceptable background noise levels at reduced dose, not compromising nodule detectability/sizing. | "As dose is reduced, background noise in the image increases. If this noise becomes too large, nodule detectability and sizing measurement may be compromised." "The results of non-clinical bench testing demonstrate that the image quality metrics including... Image noise... are substantially equivalent among different family of scanners." "Noise goes up by the square root of the mAs. The contrast of the lung nodules it high relative to this increased noise, demonstrated by the CNR results (section 18) and NLST study." |
| Noise Power Spectrum (NPS): Acceptable noise texture, not influencing nodule detection capabilities. | "Similar to the noise, changes in texture of the noise may have an influence on the nodule detection capabilities." "The NPS scans were completed using the LDCT LCS scan protocol." "The results of non-clinical bench testing also demonstrate the image quality parameters for iDose4 and IMR reconstructions are equivalent to, or better than standard FBP reconstruction." |
| Slice Thickness: Accurate slice thickness for clear edges and boundaries of nodules. | "The ability to produce slice thicknesses (FWHM of the slice sensitivity profile) that are close to the nominal slice thickness is important in defining clear edges and boundaries of the nodule." "The results of non-clinical bench testing demonstrate that the image quality metrics including... Slice Thickness... are substantially equivalent among different family of scanners." |
| CT Number Uniformity: Sufficient uniformity in the lung for robust nodule detectability. | "In a low dose scanning protocols such as with lung cancer screening, maintaining sufficient CT number uniformity throughout the lung and its various structures is important for more robust detectability of the nodules." "The results of non-clinical bench testing demonstrate that the image quality metrics including... CT number linearity, CT number accuracy... are substantially equivalent among different family of scanners." |
| CT Number Linearity: Measured CT number in a nodule not significantly affected by low dose scanning. | "In a low dose scanning protocols such as with lung cancer screening, the CT number measured in a nodule may be affected and therefore measuring CT number linearity is important." "The results of non-clinical bench testing demonstrate that the image quality metrics including... CT number linearity... are substantially equivalent among different family of scanners." |
| Image Artifacts: No new or increased artifacts obscuring anatomical details or mimicking pathology. | (Implicit in overall image quality assessment, not explicitly detailed as a separate quantified metric but mentioned as an important image quality parameter). "Image artifacts can obscure anatomical details and mimic pathology." |
| Geometric Distortion: Accuracy of measurements and image correlation with other modalities. | (Implicit in overall image quality assessment, not explicitly detailed as a separate quantified metric but mentioned as an important image quality parameter). "Geometric distortion can affect the accuracy of measurements and the ability to correlate images with other modalities." |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Test Set Sample Size: Not applicable in the context of a clinical patient test set for this specific submission. The "test set" for demonstrating substantial equivalence related to image quality was composed of various CT scanner models and reconstruction algorithms.
- Data Provenance: The primary data used to support the efficacy of LDCT LCS itself comes from externally referenced clinical literature, specifically the National Lung Screening Trial (NLST) (N Engl J Med 2011; 365:395-409) and the International Early Lung Cancer Action Program (I-ELCAP), along with "subsequent literature." These were large-scale prospective clinical trials, likely conducted across multiple centers, including within the US (NLST).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Number of Experts: Not applicable for this specific submission's non-clinical testing. The non-clinical image quality phantom measurements do not involve expert interpretation for ground truth.
- Qualifications of Experts: For the external clinical trials (NLST, I-ELCAP) referenced, radiologists and other medical professionals were involved in establishing diagnoses and outcomes, but their specific numbers and qualifications are not detailed in this 510(k) document.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Adjudication Method: Not applicable for this specific submission's non-clinical testing. No human adjudication was performed for the image quality metrics tested.
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
- MRMC Comparative Effectiveness Study: No, a multi-reader, multi-case comparative effectiveness study with human readers (with vs. without AI assistance) was not conducted or presented in this 510(k) submission. This submission is for the CT system itself with a low-dose protocol option, not for an AI-powered CAD (Computer-Aided Detection) or CADx (Computer-Aided Diagnosis) device. The device does not incorporate AI for interpretation.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone Performance Study: No, a standalone algorithm-only performance study was not conducted or presented in this 510(k) submission. The device is a CT scanner, not an independent algorithm for diagnosis or detection.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Type of Ground Truth:
- For the image quality bench testing: Ground truth was established by the physical phantoms used for measurements (e.g., wire phantom for MTF, ramp/disk phantom for slice thickness, water/density phantoms for CT numbers).
- For the clinical efficacy of LDCT LCS (referenced externally): The ground truth for the NLST and I-ELCAP studies would have included pathology reports (for confirmed cancers), clinical follow-up/outcomes data (for stable or resolving nodules), and potentially expert consensus reviews of indeterminate findings.
8. The sample size for the training set
- Training Set Sample Size: Not applicable. This submission describes a CT scanner with a new protocol, not a machine learning algorithm that requires a training set. The reconstruction algorithms (iDose4, IMR) themselves would have been developed using various data, but details are not provided here.
9. How the ground truth for the training set was established
- Ground Truth for Training Set: Not applicable, as this is not an AI/ML device requiring a training set with ground truth established through labeled data in the context of this submission.
§ 892.1750 Computed tomography x-ray system.
(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.