Maximum-likelihood estimation for indicator dilution analysis.
Indicator-dilution methods are widely used by many medical imaging techniques and by dye-, lithium-, and thermodilution measurements. The measured indicator dilution curves are typically fitted by a mathematical model to estimate the hemodynamic parameters of interest. This paper presents a new maximum-likelihood algorithm for parameter estimation, where indicator dilution curves are considered as the histogram of underlying transit-time distribution. Apart from a general description of the algorithm, semianalytical solutions are provided for three well-known indicator dilution models. An adaptation of the algorithm is also introduced to cope with indicator recirculation. In simulations as well as in experimental data obtained by dynamic contrast-enhanced ultrasound imaging, the proposed algorithm shows a superior parameter estimation accuracy over nonlinear least-squares regression. The feasibility of the algorithm for use in vivo is evaluated using dynamic contrast-enhanced ultrasound recordings obtained with the purpose of prostate cancer detection. The proposed algorithm shows an improved ability (increase in receiver-operating characteristic curve area of up to 0.13) with respect to existing methods to differentiate between healthy tissue and cancer.
Maarten P J
MP
Kuenen
Ingeborg H F
IH
Herold
Hendrikus H M
HH
Korsten
Jean J M C H
JJ
de la Rosette
Hessel
H
Wijkstra
Massimo
M
Mischi
D000465:Algorithms; D003287:Contrast Media; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007201:Indicator Dilution Techniques; D016013:Likelihood Functions; D008297:Male; D008954:Models, Biological; D011467:Prostate / Q000000981:diagnostic imaging / Q000502:physiology; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000503:physiopathology; D012372:ROC Curve; D015203:Reproducibility of Results; D014463:Ultrasonography / Q000379:methods
D003287:Contrast Media