The overarching objective of the project is to develop a new C-arm interventional x-ray imaging platform that integrates both a photon counting detector and a flat panel detector to provide high image quality and quantitative spectral computed tomography (CT) image guidance will be developed to enable more accurate and safe interventional procedures for patients.
The objective of this pilot study is to assess the feasibility of acquiring high-quality images using new imaging concepts and methods. All imaging will be performed in addition to standard-of-care procedures and will not influence clinical decisions or patient management. The endpoint of this project includes: 1) PCD-CBCT data will be processed to generate virtual non-iodine images for evaluating contrast extravasation, as well as virtual monoenergetic (VME) images. 2) Images will be analyzed retrospectively to evaluate image quality and explore potential clinical benefits of PCD-CBCT compared to flat panel detector cone beam CT (FPD-CBCT) and multidetector computed tomography (MDCT).
Study Type
OBSERVATIONAL
Enrollment
20
A single research PCD-CBCT scan will be performed directly after the participant's SOC scan.
UW Hospital and Clinics
Madison, Wisconsin, United States
Mean Confidence Score for Calcifications
MDCT, PCD-CBCT, and FPD-CBCT images will be co-registered and displayed on a clinical monitor using a customized software that allows the users to toggle between energy bin images. At least 4 readers with a broad spectrum of clinical experiences (radiology residents, interventional radiology and neurosurgery fellows, and experienced physician co-investigators) will independently identify calcifications and extravasated iodine contrast (if available) and provide a 1 (low) to 5 (high) confidence score on each image.
Time frame: after participant data collection is complete (up to 1 year)
Mean Confidence Score for Metal Artifacts
MDCT, PCD-CBCT, and FPD-CBCT images will be co-registered and displayed on a clinical monitor using a customized software that allows the users to toggle between energy bin images. At least 4 readers with a broad spectrum of clinical experiences (radiology residents, interventional radiology and neurosurgery fellows, and experienced physician co-investigators) will independently identify metal artifacts (if any) and provide a 1 (low) to 5 (high) confidence score on each image.
Time frame: after participant data collection is complete (up to 1 year)
Area Under the Curve (AUC) for Calcification Detection
For all reading studies, the order of subjects and imaging modality (MDCT, FPD-CBCT, and PCD-CBCT) will be randomized; three separate reading sessions will be implemented with a washout period of at least 3 months between sessions. For calcification and iodine staining detection in the human subjects, the receiver operating characteristic (ROC) curves will be calculated using the maximum-likelihood method with the binormal model. The 95% confidence interval (CI) of each ROC curve will be estimated and the area under the curve (AUC) and its 95% CI will be calculated.
Time frame: image analysis will proceed after participant data collection is complete (up to 2 years)
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