Automatic localization of the prostate for on-line or off-line image-guided radiotherapy.
OBJECTIVE
With higher radiation dose, higher cure rates have been reported in prostate cancer patients. The extra margin needed to account for prostate motion, however, limits the level of dose escalation, because of the presence of surrounding organs at risk. Knowledge of the precise position of the prostate would allow significant reduction of the treatment field. Better localization of the prostate at the time of treatment is therefore needed, e.g. using a cone-beam computed tomography (CT) system integrated with the linear accelerator. Localization of the prostate relies upon manual delineation of contours in successive axial CT slices or interactive alignment and is fairly time-consuming. A faster method is required for on-line or off-line image-guided radiotherapy, because of prostate motion, for patient throughput and efficiency. Therefore, we developed an automatic method to localize the prostate, based on 3D gray value registration.


METHODS
A study was performed on conventional repeat CT scans of 19 prostate cancer patients to develop the methodology to localize the prostate. For each patient, 8-13 repeat CT scans were made during the course of treatment. First, the planning CT scan and the repeat CT scan were registered onto the rigid bony structures. Then, the delineated prostate in the planning CT scan was enlarged by an optimum margin of 5 mm to define a region of interest in the planning CT scan that contained enough gray value information for registration. Subsequently, this region was automatically registered to a repeat CT scan using 3D gray value registration to localize the prostate. The performance of automatic prostate localization was compared to prostate localization using contours. Therefore, a reference set was generated by registering the delineated contours of the prostates in all scans of all patients. Gray value registrations that showed large differences with respect to contour registrations were detected with a chi(2) analysis and were removed from the data set before further analysis.


RESULTS
Comparing gray value registration to contour registration, we found a success rate of 91%. The accuracy for rotations around the left-right, cranial-caudal, and anterior-posterior axis was 2.4 degrees, 1.6 degrees, and 1.3 degrees (1 SD), respectively, and for translations along these axes 0.7, 1.3, and 1.2 mm (1 SD), respectively. A large part of the error is attributed to uncertainty in the reference contour set. Automatic prostate localization takes about 45 seconds on a 1.7 GHz Pentium IV personal computer.


CONCLUSIONS
This newly developed method localizes the prostate quickly, accurately, and with a good success rate, although visual inspection is still needed to detect outliers. With this approach, it will be possible to correct on-line or off-line for prostate movement. Combined with the conformity of intensity-modulated dose distributions, this method might permit dose escalation beyond that of current conformal approaches, because margins can be safely reduced.
Smitsmans
Monique H P
MH
Department of Radiotherapy, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital (NKI-AVL), Amsterdam, The Netherlands.
Wolthaus
Jochem W H
JW
Artignan
Xavier
X
de Bois
Josien
J
Jaffray
David A
DA
Lebesque
Joos V
JV
van Herk
Marcel
M
D000465:Algorithms; D006801:Humans; D008297:Male; D011467:Prostate / Q000000981:diagnostic imaging*; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D011881:Radiotherapy, Computer-Assisted; D020266:Radiotherapy, Conformal; D012669:Seminal Vesicles / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*