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WE‐C‐103‐11: Impact of Patient Parameters On the Repeatability of DCE‐CT Kinetic Analysis
Author(s) -
Fontaine M La,
McDaniel L,
Kubicek L,
Chappell R,
Forrest L,
Jeraj R
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4815560
Subject(s) - repeatability , reproducibility , nuclear medicine , blood flow , medicine , biomedical engineering , materials science , mathematics , radiology , statistics
Purpose: A mixed‐effects model can separate and quantify effects according to randomness and measurable patient parameters such as weight or blood pressure. Using data acquired with a high signal‐to‐noise ratio (SNR) and limited patient motion in test‐retest‐retest scanning, we investigated the impact of various patient parameters on the repeatability of dynamic contrast enhanced CT (DCE‐CT) kinetic analysis. Methods: Eleven canine patients with sinonasal tumors received three pre‐treatment DCE‐CT scans on consecutive days. To ensure sub‐millimeter reproducibility, patients were anesthetized and immobilized with a patient‐specific bite‐block, dental mold, and vacuum mattress. Kinetic analysis was performed using the distributed parameter model to compute values for blood flow (F), blood volume ratio (BVR), transit time, and permeability (PER). The repeatability of each parameter was evaluated by the Bland‐Altman repeatability coefficient. The impact of patient parameters was determined by a hierarchical mixed‐effects model. Results: The repeatability coefficients were calculated for F (45%), BVR (39%), transit time (29%), and PER (37%). Between patients, the patient parameters with significant influence on the kinetic parameters were patient weight, area underneath the curve (AUC) of the artery, and AUC of the vein (p<0.05). However, within a patient, patient weight did not have a prominent bearing on the repeatability as it was found stable with a standard error of measurement (SEM) of 2%. As the AUC of the artery increased by one SEM, F decreased by 24% and BVR by 40%. In addition, PS decreased by 14% when the AUC of the vein increased by one SEM. Conclusion: Despite high SNR and limited patient motion, the AUCs of the artery and vein had a notable impact on the repeatability within patients for F, BVR, and PER. This indicates the need for reliable vessel selection in order to minimize kinetic analysis uncertainty.

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