Patient-specific pharmacokinetic parameter estimation on dynamic contrast-enhanced MRI of prostate: Preliminary evaluation of a novel AIF-free estimation method.
To develop and evaluate a prostate-based method (PBM) for estimating pharmacokinetic parameters on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) by leveraging inherent differences in pharmacokinetic characteristics between the peripheral zone (PZ) and transition zone (TZ).



This retrospective study, approved by the Institutional Review Board, included 40 patients who underwent a multiparametric 3T MRI examination and subsequent radical prostatectomy. A two-step PBM for estimating pharmacokinetic parameters exploited the inherent differences in pharmacokinetic characteristics associated with the TZ and PZ. First, the reference region model was implemented to estimate ratios of Ktransbetween normal TZ and PZ. Subsequently, the reference region model was leveraged again to estimate values for Ktransand vefor every prostate voxel. The parameters of PBM were compared with those estimated using an arterial input function (AIF) derived from the femoral arteries. The ability of the parameters to differentiate prostate cancer (PCa) from benign tissue was evaluated on a voxel and lesion level. Additionally, the effect of temporal downsampling of the DCE MRI data was assessed.



Significant differences (P < 0.05) in PBM Ktransbetween PCa lesions and benign tissue were found in 26/27 patients with TZ lesions and in 33/38 patients with PZ lesions; significant differences in AIF-based Ktransoccurred in 26/27 and 30/38 patients, respectively. The 75thand 100thpercentiles of Ktransand veestimated using PBM positively correlated with lesion size (P < 0.05).



Pharmacokinetic parameters estimated via PBM outperformed AIF-based parameters in PCa detection. J. Magn. Reson. Imaging 2016;44:1405-1414.
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Shoshana B
0000-0002-5764-8524
SB
Ginsburg
Department of Pathology, University of Turku and Turku University Hospital, Turku, Finland.
Pekka
P
Taimen
Department of Diagnostic Radiology, University of Turku, Turku, Finland.|Turku PET Centre, University of Turku, Turku, Finland.|Department of Information Technology, University of Turku, Turku, Finland.
Harri
H
Merisaari
Department of Pathology, University of Turku and Turku University Hospital, Turku, Finland.
Paula
P
Vainio
Department of Urology, Turku University Hospital, Turku, Finland.
Peter J
PJ
Boström
Department of Diagnostic Radiology, University of Turku, Turku, Finland.|Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland.
Hannu J
HJ
Aronen
Department of Diagnostic Radiology, University of Turku, Turku, Finland.|Turku PET Centre, University of Turku, Turku, Finland.|Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland.
Ivan
I
Jambor
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Anant
A
Madabhushi
D000328:Adult; D000465:Algorithms; D003198:Computer Simulation; D003287:Contrast Media / Q000493:pharmacokinetics; D003937:Diagnosis, Differential; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008536:Meglumine / Q000493:pharmacokinetics*; D008657:Metabolic Clearance Rate; D008875:Middle Aged; D008954:Models, Biological; D009942:Organometallic Compounds / Q000493:pharmacokinetics*; D010865:Pilot Projects; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000378:metabolism*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D014018:Tissue Distribution
D003287:Contrast Media; D009942:Organometallic Compounds; D008536:Meglumine; C072417:gadoterate meglumine
DCE MRI; pharmacokinetic modeling; prostate cancer