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The SpotLight / SpotLight Duo is intended to produce cross-sectional images of the body by computer reconstruction of X-ray transmission projection data taken at different angles. The system has the capability to image cardiovascular and thoracic anatomies, including the heart, in a single rotation. The system may acquire data using Axial, Cine and Cardiac scan techniques from patients of all ages (DLIR is limited for patient use above the age of 2 years). These images may be obtained either with or without contrast. This device may include signal analysis and display equipment, patient and equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes. The system is indicated for x-ray Computed Tomography imaging of cardiovascular and thoracic anatomies that fit in the scan field-of-view.

The Low Dose CT Lung Cancer Screening Option for SpotLight / SpotLight Duo is indicated for using low dose CT for lung cancer screening. The screening must be conducted with the established program criteria and protocols that have been approved and published by a governmental body or a professional medical society. Information from professional societies related to lung cancer screening can be found but is not limited to: American College of Radiology® (ACR) – resources and technical specification; accreditation American Association of Physicists in Medicine (AAPM) – Lung Cancer Screening Protocols; radiation management. 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. The DLIR and ASIR-CV algorithms are not compatible with the Low Dose Lung Cancer Screening option.

The device output is useful for diagnosis of disease or abnormality and for planning of therapy procedures.

The Low Dose Lung Cancer Screening (LD LCS) option indication for Arineta's SpotLight and SpotLight Duo scanners is being expanded to include small patients, as defined by AAPM (American Association of Physicists in Medicine). This expansion ensures comprehensive coverage of the intended lung cancer screening population, following the previous clearance of the LD LCS option for medium and large patients under K241200.

The proposed LD LCS option for the SpotLight and SpotLight Duo includes scan protocols with CTDI that comply with AAPM's requirements for the whole LD LCS population patient size groups, as detailed in the following table:

There are not any functional, performance, feature, or design changes required for the CT systems to which the option is applied.

The proposed full LD LCS protocols option, as the cleared K241200, will be activated by service or production personnel, with no additional installation required (option activation only).

This FDA 510(k) clearance letter describes the acceptance criteria and study proving the SpotLight / SpotLight Duo with Low Dose Lung Cancer Screening Option (specifically for small patients) meets these criteria.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the device are largely based on image quality and nodule detectability being maintained at low dose levels, specifically for small patients (50-70 kg) within the AAPM guidelines for CTDI. The reported performance confirms these criteria are met.

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The SpotLight / SpotLight Duo is intended to produce cross-sectional images of the body by computer reconstruction of X-ray transmission projection data taken at different angles. The system has the capability to image cardiovascular and thoracic anatomies, including the heart, in a single rotation. The system may acquire data using Axial, Cine and Cardiac scan techniques from patients of all ages (DLR is limited for patient use of 2 years). These images may be obtained either with or without contrast. This device may include signal analysis and display equipment, patient and equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes. The system is indicated for x-ray Computed Tomography imaging of cardiovascular and thoracic anatomies that fit in the scan field-of-view.

The Low Dose CT Lung Cancer Screening Option for SpotLight / SpotLight Duo is indicated for using low dose CT for lung cancer screening. The screening must be conducted with the established program criteria and protocols (for medium and large patients) that have been approved and published by a governmental body or a professional medical society. Information from professional societies related to lung cancer screening can be found but is not limited to: American College of Radiology® (ACR) - resources and technical specification American Association of Physicists in Medicine (AAPM) - Lung Cancer Screening Protocols; radiation management. 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. The DLIR and ASIR-CV algorithms are not compatible with the Low Dose Lung Cancer Screening option.

The device output is useful for diagnosis of disease or abnormality and for planning of therapy procedures.

The Low Dose Lung Cancer Screening (LD LCS) option is an indication being added to the existing Arineta scanners for SpotLight and SpotLight Duo, previously cleared by the FDA (K230370, K213465).

There are not any functional, performance, feature, or design changes required for the CT systems to which the option is applied.

This option includes scan protocols with CTDI that comply with AAPM's requirements for Low Dose Lung Cancer Screening.

No Hardware modifications and minor Software modifications (for compatibility with the Low-Dose Lung Cancer Screening protocols) are required for the subject device, which includes the following LD LCS protocol characteristics:

• Lung Cancer Screening protocols for medium and large patients according to AAPM's definitions.

· Lung Cancer Screening protocols option will be activated by service or production personnel (no need for additional installation, option activation only).

Here's a breakdown of the acceptance criteria and the study proving the device's performance, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size:
  • Bench Testing: Not explicitly stated as a number of phantom scans, but described as "extensive bench testing" using "standard phantoms" and a "semi-anthropomorphic clinical simulation lung phantom."
  • Clinical Image Quality Assessment: Fourteen (14) cases.
• Data Provenance:
  • Bench Testing: Internal laboratory testing ("extensive bench testing").
  • Clinical Image Quality Assessment: Collected from two (2) U.S. sites. The text doesn't specify if it was retrospective or prospective, but the phrasing "were collected" often implies retrospective.

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

• Number of Experts: Two (2) U.S. board-certified radiologists.
• Qualifications: U.S. board-certified radiologists. No specific years of experience are mentioned.

4. Adjudication Method for the Test Set

The provided text only states "a clinical image quality assessment was performed by two U.S. board-certified radiologists." It does not specify an adjudication method (e.g., 2+1, 3+1, none). It implies both radiologists performed the assessment, but not how disagreements (if any) were resolved or if their readings were merged.

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

No MRMC comparative effectiveness study was mentioned. The study described focuses on whether the device's low-dose protocols produce diagnostic-quality images and maintain image quality compared to the predicate device, not on human reader performance with or without AI assistance.

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

The "device" in this context is the CT scanner itself with an added low-dose lung cancer screening option, which includes specific scan protocols and minor software modifications for compatibility. The "acceptance criteria" and "study" described are for the performance of the CT system under these low-dose conditions, as an image acquisition and reconstruction device. It is not an AI algorithm that provides diagnostic readings independently. Therefore, the concept of a "standalone" AI performance study is not directly applicable here. The performance evaluated is the image quality produced by the system.

7. The Type of Ground Truth Used

• Bench Testing: Phantom specifications or known values within the phantoms (e.g., specific nodule sizes, CT number values of materials). Comparison was also made against a "reference device" (GE Revolution CT).
• Clinical Image Quality Assessment: The "ground truth" for the clinical evaluation was the qualitative assessment by the two board-certified radiologists that the images were "diagnostic for the indications for use" and "enable the detection of findings relevant to LD LCS," including 2mm nodules. This is essentially expert consensus on clinical diagnostic utility. It does not refer to histopathological ground truth for nodules, for example.

8. The Sample Size for the Training Set

The document does not mention any training set size. This is because the submission describes an option for an existing CT system (SpotLight/SpotLight Duo) to perform Low Dose Lung Cancer Screening. It does not describe a new AI algorithm that requires a separate training set. The changes are primarily in scan protocols and minor software adjustments for compatibility. The core image reconstruction algorithms (Modified FDK, MBAF, MBAF2) are pre-existing.

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

As no training set is mentioned (since it's not a new AI algorithm being trained), this information is not applicable.

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SpotLight /SpotLight Duo (with DLIR option) is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission projection data taken at different angles. The system has the capability to image cardiovascular and thoracic anatomies, in a single rotation. The system may acquire data using Axial, Cine, and Cardiac scan techniques from patients of all ages (DLR is limited for patient use above the age of 2 years). These images may be obtained either with or without contrast. This device may include signal analysis and display equipment, patient and equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes.

The system is indicated for X-ray Computed Tomography imaging of cardiovascular and thoracic anatomies that fit in the scan field of view. The device output is useful for diagnosis of disease or abnormality and for planning of therapy procedures.

The SpotLight / SpotLight Duo (with DLIR option) is a multi-slice (192 detector rows), dual tube CT scanner consisting of a gantry, patient table, operator console, power distribution unit (PDU) and interconnecting cables. The system includes image acquisition hardware, image acquisition and reconstruction software and software for operator interface and image handling. The Deep Learning Image Reconstruction (DLIR) algorithm is a deep learning technology-based software sub-system that is integrated into the image reconstruction software. As in other CT scanners, a scanned subject is irradiated by X rays and a detector array measures attenuation data of X rays that have been attenuated by the subject from multiple view angles. This is achieved by rotation of the radiation source and the detector about the subject while acquiring the attenuation data. A computer is used to reconstruct cross sectional images of the subject from the attenuation data.

Here's a summary of the acceptance criteria and the study details for the SpotLight/SpotLight Duo (with DLIR option) CT system, based on the provided FDA 510(k) summary:

1. Acceptance Criteria and Reported Device Performance

The document doesn't explicitly list specific quantitative acceptance criteria in a table format. However, it indicates that the DLIR (Deep Learning Image Reconstruction) algorithm was evaluated to demonstrate non-inferiority to the predicate device's ASiR-CV noise reduction algorithm in terms of image quality. The performance tests focused on several image quality parameters:

2. Sample Size and Data Provenance for the Test Set

• Sample Size (Test Set): Not explicitly stated as a number of cases, but implied to be a collection of "clinical cases of different anatomies, using different types of scans, from patients with a wide range of BMIs and clinical features."
• Data Provenance: Retrospective clinical data acquired by SpotLight / CardioGraphe scanners. Collected from "multiple clinical sites with at least 50% of the cases performed in the US."

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Five (5) certified CT readers.
• Qualifications of Experts: 3 radiologists and 2 cardiologists. "4 out 5 are US board certified." Specific years of experience are not mentioned.

4. Adjudication Method

• Adjudication Method: The study was a "retrospective blinded image evaluation." Each exam was reviewed using both standard (ASiR-CV) and alternative (DLIR) methods. The data was "coded to avoid readers' bias." This suggests a comparative reading where readers likely assessed both image sets for the same patient without knowing which was which, and potentially without direct consensus discussions as a formal adjudication step, but rather an independent assessment that collectively informed the non-inferiority conclusion. No explicit "2+1" or "3+1" adjudication method is described.

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

• Was an MRMC study done? Yes, a form of multi-reader evaluation was performed, comparing DLIR to ASiR-CV on clinical cases by five expert readers.
• Effect Size (human readers improve with AI vs. without AI assistance): The document states that "DLIR was found to provide diagnostic image quality that is not inferior to ASiR." It does not provide a specific quantitative effect size or a measure of improvement for human readers with AI (DLIR) vs. without AI (ASiR-CV, which is also an algorithm, a noise reduction one). The focus was on non-inferiority rather than an enhancement measurement for the readers themselves.

6. Standalone Performance Study

• Was a standalone study done? Yes, "DLIR bench tests were performed by applying DLIR and ASIR on phantoms." This represents a standalone evaluation of the algorithm's performance on objective image quality metrics using phantoms.

7. Type of Ground Truth Used

• For Bench Tests: Physical phantoms (water phantoms, CATPHAN, QA phantom) with known properties were used.
• For Clinical Evaluation: "Diagnostic image quality that is not inferior to ASiR" as determined by the expert readers serves as the ground truth/comparison metric. This is effectively expert consensus/opinion on diagnostic quality. There's no mention of pathology or outcomes data being used to establish ground truth for the clinical cases.

8. Sample Size for the Training Set

• The document does not specify the sample size used for training the Deep Learning Image Reconstruction (DLIR) algorithm.

9. How Ground Truth for the Training Set Was Established

• The document does not explicitly describe how ground truth for the training set was established. It only mentions that DLIR is a "deep learning technology-based software sub-system." For deep learning reconstruction, training typically involves pairs of noisy (or lower-dose) input images and corresponding high-quality (or higher-dose/reference standard) images, often reconstructed with a traditional full-dose, high-quality algorithm (not explicitly stated here, but common practice).

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The SpotLight Duo is intended to produce cross-sectional images of the body by computer reconstruction of X-ray transmission projection data taken at different angles. The system has the capability to image whole organs, including the heart, in a single rotation. The system may acquire data using Axial, Cine and Cardiac scan techniques from patients of all ages. These images may be obtained either with or without contrast. This device may include signal analysis and display equipment, patient and equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes.

The system is indicated for X-ray Computed Tomography imaging of organs that fit in the scan field of view, including cardiac and vascular CT imaging. The device output is useful for diagnosis of disease or abnormality and for planning of therapy procedures.

The SpotLight Duo is a multi-slice (192 detector rows), dual tube CT scanner consisting of a gantry, patient table, operator console, power distribution unit (PDU) and interconnecting cables. The system includes image acquisition hardware, image acquisition and reconstruction software for operator interface and image handling. As in other CT scanned subject is irradiated by X rays and a detector array measures attenuation data of X rays that have been attenuated by the subject from multiple view angles. This is achieved by rotation source and the detector about the subject while acquiring the attenuation data. A computer is used to reconstruct cross sectional images of the subject from the attenuation data.

The provided text describes the regulatory clearance of a medical device, the "SpotLight Duo," and its substantial equivalence to predicate devices based on non-clinical performance testing. However, it does not include detailed acceptance criteria or the specific results of a study designed to prove the device meets these criteria in the format requested.

Here's a breakdown of the missing information and what can be inferred:

1. A table of acceptance criteria and the reported device performance: This information is not explicitly provided in a table format with specific quantitative criteria and corresponding performance metrics. The document mentions "performance specifications are met" but does not detail what these specifications are.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective): No information about sample size or data provenance is provided. The testing described is non-clinical performance testing using phantoms, not clinical data from patients.

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): Not applicable, as the testing described is non-clinical performance testing using phantoms. No human expert review for establishing ground truth is mentioned.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable, as the testing described is non-clinical performance testing using phantoms.

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: An MRMC comparative effectiveness study was not done. The device is a CT scanner, not an AI-assisted diagnostic tool.

6. If a standalone (i.e., algorithm-only without human-in-the-loop performance) was done: The document describes non-clinical performance testing of the CT scanner hardware and software. It's essentially a standalone performance evaluation of the imaging system itself, independent of human interpretation for the purpose of demonstrating technical specifications.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the non-clinical performance testing, the ground truth would be established by the known physical properties and configurations of the phantoms used, as well as established metrology and physics principles for evaluating CT image quality and dose.

8. The sample size for the training set: Not applicable. The device is a CT scanner, and the "training set" concept is typically associated with machine learning or AI models, which is not the primary focus of this submission. The software adaptations mentioned are for supporting new detector configurations, reconstruction at larger FOV, and scan modes based on engineering modifications, not machine learning model training.

9. How the ground truth for the training set was established: Not applicable for the reasons stated above.

In summary, the provided text describes a 510(k) premarket notification for a Computed Tomography X-ray System (SpotLight Duo). The "study" proving it meets acceptance criteria refers to a series of non-clinical performance tests using phantoms to demonstrate that the device's technical specifications - regarding image quality (spatial resolution, low contrast detectability, noise, uniformity, CT number accuracy) and dose performance - are met, and that it complies with relevant electrical safety and radiation protection standards.

The document does not contain information about clinical studies with human participants, expert review of images, or AI-specific performance metrics. It focuses on the physical and technical performance of the imaging device itself.

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The SpotLight CT Computed Tomography X-ray is intended to produce cross-sectional images of the body by computer reconstruction of X-ray transmission data taken at different angles. The system has the capability to image whole organs, including the heart, in a single rotation. The system may acquire data using Axial, Cine and Cardiac CT scan techniques from patients of all ages. These images may be obtained either with or without contrast. This device may include signal analysis and display equipment, patient and equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes.

The system is indicated for X-ray Computed Tomography imaging of organs that fit in a 25cm field of view, including cardiac and vascular CT imaging. The device output is useful for diagnosis of disease or abnormality and for planning of therapy procedures.

The SpotLight CT is a third generation rotate-rotate CT scanner, designed and built based on technologies and principles of operation of the predicate device and other legally marketed CT scanners. The SpotLight CT is a multi-slice (192 detector rows), dual tube CT scanner consisting of a gantry, patient table, operator console, power distribution unit (PDU) and interconnecting cables. The system includes image acquisition hardware, image acquisition and reconstruction software for operator interface and image handling.

The provided document describes the Arineta Ltd. SpotLight CT device and its substantial equivalence to a predicate device. Here's a breakdown of the acceptance criteria and the study details:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a tabular format with corresponding "reported device performance." Instead, it describes various performance specifications and how the device performed against them. I've re-framed the reported performance metrics as if they were acceptance criteria.

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

• Test Set (Clinical Testing): 38 subjects
• Data Provenance: Not explicitly stated, but the study was conducted at "one site," and the readers were "US certified." This suggests the data was collected in the US.
• Retrospective or Prospective: The clinical testing describes "data were collected," which could mean either. However, the phrase "The study protocol was designed to test the scanner across different patient populations, clinical scenarios and scan techniques" implies a prospective study design for collecting new data specifically for this evaluation.

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

• Number of Experts: Four (4)
• Qualifications: "US certified readers who are qualified radiologists or cardiologists." Specific years of experience are not mentioned.

4. Adjudication Method for the Test Set

The document states, "The images were evaluated and rated by four US certified readers." It does not specify an adjudication method like 2+1 or 3+1 for resolving discrepancies. It implies independent evaluation by each reader.

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

• Was an MRMC study done? No, a multi-reader multi-case (MRMC) comparative effectiveness study (comparing human readers with and without AI assistance) was not done. The clinical testing focused on evaluating the device's diagnostic image quality for standalone performance.
• Effect size of human readers with AI vs without AI assistance: Not applicable, as no such study was conducted or reported.

6. Standalone (Algorithm Only) Performance

• Was a standalone study done? Yes, the described "Non-clinical Performance Testing" and "Clinical Testing" primarily focus on the standalone performance of the SpotLight CT system. The image quality, temporal resolution, dose performance, and diagnostic quality evaluations are all measures of the device's inherent capabilities without human intervention during the image generation or initial analysis phase. The "clinical diagnostic value and image quality" evaluated by the readers are also assessing the output of the device itself.

7. Type of Ground Truth Used

• Non-clinical/Phantom Testing: The ground truth for these tests would be objective physical measurements and known parameters of the phantoms used to evaluate image quality metrics (e.g., spatial resolution targets, known low contrast objects, CT number uniformity).
• Animal Testing: The "diagnostic quality" evaluation in animal models likely used established veterinary diagnostic criteria and potentially post-mortem examination or other correlative imaging as ground truth.
• Clinical Testing: The "clinical diagnostic value and image quality" in human subjects were evaluated by "qualified radiologists or cardiologists" against established clinical diagnostic criteria. While not explicitly stated as "expert consensus ground truth," the assessment by multiple, qualified experts serves as the de-facto ground truth for evaluating diagnostic utility. It does not mention pathology or long-term outcomes data for ground truth.

8. Sample Size for the Training Set

The document does not provide any information about a training set since this is a hardware device (CT scanner) with associated imaging software, not typically an AI/ML algorithm that requires a distinct "training set" in the common sense. The image reconstruction algorithm is described as "Stereo CT reconstruction algorithm based on common algorithms used in single source scanners that are modified to combine the data acquired from the two sources." This implies an engineered algorithm, not one trained on a dataset.

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

Not applicable, as there is no mention of an AI/ML algorithm requiring a training set in the document. The device uses an engineered image reconstruction algorithm.

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