PMID- 23775728
OWN - NLM
STAT- MEDLINE
DCOM- 20140507
LR  - 20151119
IS  - 1099-1492 (Electronic)
IS  - 0952-3480 (Linking)
VI  - 26
IP  - 11
DP  - 2013 Nov
TI  - A comprehensive non-invasive framework for automated evaluation of acute renal 
      transplant rejection using DCE-MRI.
PG  - 1460-70
LID - 10.1002/nbm.2977 [doi]
AB  - The objective was to develop a novel and automated comprehensive framework for 
      the non-invasive identification and classification of kidney non-rejection and 
      acute rejection transplants using 2D dynamic contrast-enhanced magnetic resonance 
      imaging (DCE-MRI). The proposed approach consists of four steps. First, kidney 
      objects are segmented from the surrounding structures with a geometric deformable 
      model. Second, a non-rigid registration approach is employed to account for any 
      local kidney deformation. In the third step, the cortex of the kidney is 
      extracted in order to determine dynamic agent delivery, since it is the cortex 
      that is primarily affected by the perfusion deficits that underlie the 
      pathophysiology of acute rejection. Finally, we use an analytical function-based 
      model to fit the dynamic contrast agent kinetic curves in order to determine 
      possible rejection candidates. Five features that map the data from the original 
      data space to the feature space are chosen with a k-nearest-neighbor (KNN) 
      classifier to distinguish between acute rejection and non-rejection transplants. 
      Our study includes 50 transplant patients divided into two groups: 27 patients 
      with stable kidney function and the remainder with impaired kidney function. All 
      of the patients underwent DCE-MRI, while the patients in the impaired group also 
      underwent ultrasound-guided fine needle biopsy. We extracted the kidney objects 
      and the renal cortex from DCE-MRI for accurate medical evaluation with an 
      accuracy of 0.97 +/- 0.02 and 0.90 +/- 0.03, respectively, using the Dice similarity 
      metric. In a cohort of 50 participants, our framework classified all cases 
      correctly (100%) as rejection or non-rejection transplant candidates, which is 
      comparable to the gold standard of biopsy but without the associated deleterious 
      side-effects. Both the 95% confidence interval (CI) statistic and the receiver 
      operating characteristic (ROC) analysis document the ability to separate 
      rejection and non-rejection groups. The average plateau (AP) signal magnitude and 
      the gamma-variate model functional parameter alpha have the best individual 
      discriminating characteristics.
CI  - Copyright (c) 2013 John Wiley & Sons, Ltd.
FAU - Khalifa, Fahmi
AU  - Khalifa F
AD  - BioImaging Laboratory, Bioengineering Department, University of Louisville, 
      Louisville, KY, USA; Electrical and Computer Engineering Department, University 
      of Louisville, Louisville, KY, USA.
FAU - Abou El-Ghar, Mohamed
AU  - Abou El-Ghar M
FAU - Abdollahi, Behnaz
AU  - Abdollahi B
FAU - Frieboes, Hermann B
AU  - Frieboes HB
FAU - El-Diasty, Tarek
AU  - El-Diasty T
FAU - El-Baz, Ayman
AU  - El-Baz A
LA  - eng
PT  - Journal Article
DEP - 20130618
PL  - England
TA  - NMR Biomed
JT  - NMR in biomedicine
JID - 8915233
RN  - 0 (Contrast Media)
SB  - IM
MH  - Adolescent
MH  - Adult
MH  - *Algorithms
MH  - Automation
MH  - Bayes Theorem
MH  - Child
MH  - Computer-Aided Design
MH  - Confidence Intervals
MH  - *Contrast Media
MH  - Female
MH  - Graft Rejection/*diagnosis
MH  - Humans
MH  - *Image Enhancement
MH  - *Kidney Transplantation
MH  - *Magnetic Resonance Imaging
MH  - Male
MH  - Middle Aged
MH  - Perfusion
MH  - ROC Curve
MH  - Young Adult
OTO - NOTNLM
OT  - Laplace equation
OT  - acute rejection
OT  - dynamic MRI
OT  - kidney transplant
OT  - level set segmentation
OT  - non-rigid registration
EDAT- 2013/06/19 06:00
MHDA- 2014/05/08 06:00
CRDT- 2013/06/19 06:00
PHST- 2012/09/13 00:00 [received]
PHST- 2013/04/29 00:00 [revised]
PHST- 2013/04/30 00:00 [accepted]
PHST- 2013/06/19 06:00 [entrez]
PHST- 2013/06/19 06:00 [pubmed]
PHST- 2014/05/08 06:00 [medline]
AID - 10.1002/nbm.2977 [doi]
PST - ppublish
SO  - NMR Biomed. 2013 Nov;26(11):1460-70. doi: 10.1002/nbm.2977. Epub 2013 Jun 18.