Computer aided analysis of breast MRI enhancement kinetics using mean shift clustering and multifeature iterative region of interest selection.
OBJECTIVE
To evaluate automatic characterization of a breast MR lesion by its spatially coherent region of interest (ROI).


METHODS
The method delineated 247 enhancing lesions using Otsu thresholding after manually placing a sphere. Mean Shift Clustering subdivided each volume, based on features including pharmacokinetic parameters. An iteratively trained classifier to predict the most suspicious ROI (IsR) was used, to predict the malignancy likelihood of each lesion. Performance was evaluated using receiver operator characteristic (ROC) analysis, and compared with a previous prototype. IsR was compared with noniterative training. The effect of adding BI-RADS™ morphology (from a radiologist) to the classifier was investigated.


RESULTS
The area under the ROC curve (AUC) was 0.83 (95% confidence interval [CI] of 0.77-0.88), and was 0.75 (95%CI = 0.68-0.81; P = 0.029) without pharmacokinetic features. IsR performed better than conventional selection, based on one feature (AUC 0.75, 95%CI = 0.68-0.81; P = 0.035). With morphology, the AUC was 0.84 (95%CI = 0.78-0.88) versus 0.82 without (P = 0.40).


CONCLUSIONS
Breast lesions can be characterized by their most suspicious, contiguous ROI using multi-feature clustering and iterative training. Characterization was improved by including pharmacokinetic modeling, while in our experiments, including morphology did not improve characterization.
Ikazia Hospital Radiology, Rotterdam, The Netherlands. m.stoutjesdijk@ikazia.nl
Mark J
MJ
Stoutjesdijk
Miranda
M
Zijp
Carla
C
Boetes
Nico
N
Karssemeijer
Jelle O
JO
Barentsz
Henkjan
H
Huisman
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001943:Breast Neoplasms / Q000378:metabolism* / Q000473:pathology*; D003198:Computer Simulation; D003287:Contrast Media / Q000493:pharmacokinetics; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007700:Kinetics; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008536:Meglumine / Q000493:pharmacokinetics*; D008657:Metabolic Clearance Rate; D008875:Middle Aged; D008954:Models, Biological; D009942:Organometallic Compounds / Q000493:pharmacokinetics*; D010363:Pattern Recognition, Automated / Q000379:methods; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult
D003287:Contrast Media; D009942:Organometallic Compounds; D008536:Meglumine; C072417:gadoterate meglumine