(60 days)
The device is a diagnostic imaging system that combines Positron Emission Tomography (PET) and X-ray Computed Tomography (CT) systems. The CT component produces cross-sectional images of the body by computer reconstruction of X-ray transmission data. The PET component images the distribution of PET radiopharmaceuticals in the patient body. The PET component utilizes CT images for attenuation correction and anatomical reference in the fused PET and CT images.
This device is to be used by a trained health care professional to gather metabolic and functional information from the distribution of the radiopharmaceutical in the body for the assessment of metabolic and physiologic functions. This information can assist in the evaluation, detection, diagnosis, therapeutic planning and therapeutic outcome assessment of (but not limited to) cancer, cardiovascular disease and brain dysfunction. Additionally, this device can be operated independently as a whole body multi-slice CT scanner.
Cartesion Prime, PCD-1000A, system combines a high-end CT and a high-throughput PET designed to acquire CT, PET and fusion images. The high-end CT system is a multi-slice helical CT scanner with a gantry aperture of 780 mm and a maximum scanning field of 700 mm. The high-throughput PET system has a digital PET detector utilizing SiPM sensors with temporal resolution of 280 ps. Cartesion Prime, PCD-1000A is intended to acquire PET images of any desired region of the whole body and CT images of the same region (to be used for attenuation correction or image fusion), to detect the location of positron emitting radiopharmaceuticals in the obtained images. This device is used to gather the metabolic and functional information from the distribution of radiopharmaceuticals in the body for the assessment of metabolic and physiologic functions. This information can assist research, diagnosis, therapeutic planning, and therapeutic outcome assessment. This device can also function independently as a whole body multi-slice CT scanner.
The provided text does not contain acceptance criteria or a study proving that an AI/algorithm-based device meets specific acceptance criteria.
The document is a 510(k) summary for a PET/CT imaging system (Cartesion Prime, PCD-1000A). It describes the device, its intended use, and argues for its substantial equivalence to previously cleared predicate devices. While it mentions "testing" and "risk analysis and verification/validation testing," this largely refers to standard engineering and performance testing of the imaging hardware and software, rather than a clinical study evaluating an AI/algorithm's diagnostic performance against established criteria and ground truth.
Specifically, the document focuses on:
- Device Description: The physical and functional characteristics of the PET/CT scanner.
- Indications for Use: What the device is intended for (diagnostic imaging, assessment of metabolic/physiologic functions, aiding in evaluation, diagnosis, therapeutic planning, outcome assessment for various diseases).
- Substantial Equivalence: A comparison of the subject device's technical specifications (PET sensitivity, timing resolution, CT detector, etc.) with predicate devices to demonstrate it performs similarly.
- Safety and Standards Compliance: Adherence to quality systems regulations (ISO 13485, 21 CFR 820) and various IEC/NEMA standards, as well as general statements about software documentation and cybersecurity.
- Testing (General): "Risk analysis and verification/validation testing conducted through bench testing" and that "PET image quality metrics were performed which validated that the subject device met established specifications for spatial resolution, sensitivity, NECR, energy/timing resolution and PET/CT alignment." This is about the scanner's image quality and technical performance, not an AI's diagnostic accuracy.
There is no mention of:
- An AI/algorithm component requiring specific performance evaluation.
- Diagnostic performance metrics (e.g., sensitivity, specificity, AUC) for an AI.
- Human readers, MRMC studies, or human-in-the-loop performance.
- Ground truth establishment methods for a diagnostic algorithm.
- Training or test sets for an AI.
Therefore, I cannot fulfill the request to describe the acceptance criteria and the study that proves an AI/algorithm device meets those criteria based on the provided text. The document is about a medical imaging device (a PET/CT scanner), not an AI/algorithm that performs diagnostic tasks.
§ 892.1200 Emission computed tomography system.
(a)
Identification. An emission computed tomography system is a device intended to detect the location and distribution of gamma ray- and positron-emitting radionuclides in the body and produce cross-sectional images through computer reconstruction of the data. This generic type of device may include signal analysis and display equipment, patient and equipment supports, radionuclide anatomical markers, component parts, and accessories.(b)
Classification. Class II.