Multiattribute probabilistic prostate elastic registration (MAPPER): application to fusion of ultrasound and magnetic resonance imaging.
OBJECTIVE
Transrectal ultrasound (TRUS)-guided needle biopsy is the current gold standard for prostate cancer diagnosis. However, up to 40% of prostate cancer lesions appears isoechoic on TRUS. Hence, TRUS-guided biopsy has a high false negative rate for prostate cancer diagnosis. Magnetic resonance imaging (MRI) is better able to distinguish prostate cancer from benign tissue. However, MRI-guided biopsy requires special equipment and training and a longer procedure time. MRI-TRUS fusion, where MRI is acquired preoperatively and then aligned to TRUS, allows for advantages of both modalities to be leveraged during biopsy. MRI-TRUS-guided biopsy increases the yield of cancer positive biopsies. In this work, the authors present multiattribute probabilistic postate elastic registration (MAPPER) to align prostate MRI and TRUS imagery.


METHODS
MAPPER involves (1) segmenting the prostate on MRI, (2) calculating a multiattribute probabilistic map of prostate location on TRUS, and (3) maximizing overlap between the prostate segmentation on MRI and the multiattribute probabilistic map on TRUS, thereby driving registration of MRI onto TRUS. MAPPER represents a significant advancement over the current state-of-the-art as it requires no user interaction during the biopsy procedure by leveraging texture and spatial information to determine the prostate location on TRUS. Although MAPPER requires manual interaction to segment the prostate on MRI, this step is performed prior to biopsy and will not substantially increase biopsy procedure time.


RESULTS
MAPPER was evaluated on 13 patient studies from two independent datasets—Dataset 1 has 6 studies acquired with a side-firing TRUS probe and a 1.5 T pelvic phased-array coil MRI; Dataset 2 has 7 studies acquired with a volumetric end-firing TRUS probe and a 3.0 T endorectal coil MRI. MAPPER has a root-mean-square error (RMSE) for expert selected fiducials of 3.36 ± 1.10 mm for Dataset 1 and 3.14 ± 0.75 mm for Dataset 2. State-of-the-art MRI-TRUS fusion methods report RMSE of 3.06-2.07 mm.


CONCLUSIONS
MAPPER aligns MRI and TRUS imagery without manual intervention ensuring efficient, reproducible registration. MAPPER has a similar RMSE to state-of-the-art methods that require manual intervention.
Centre for Medical Image Computing, University College London, London WC1E 6BT, United Kingdom.
Rachel
R
Sparks
Department of Radiology, Boston Medical Center and Boston University, Boston, Massachusetts 02118.
B Nicolas
BN
Bloch
Lizzi Center for Biomedical Engineering, Riverside Research Institute, New York, New York 10038.
Ernest
E
Feleppa
Centre for Medical Image Computing, University College London, London WC1E 6BT, United Kingdom.
Dean
D
Barratt
South Western Sydney Clinical School, University of New South Wales, Sydney NSW 2052, Australia.
Daniel
D
Moses
Department of Urology, University Hospitals Case Medical Center, Cleveland, Ohio 44106.
Lee
L
Ponsky
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106.
Anant
A
Madabhushi
D004548:Elasticity; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D061705:Image-Guided Biopsy; D008279:Magnetic Resonance Imaging; D008297:Male; D011336:Probability; D011467:Prostate / Q000000981:diagnostic imaging* / Q000473:pathology; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D014463:Ultrasonography