How does performance of ultrasound tissue typing affect design of prostate IMRT dose-painting protocols?
OBJECTIVE
To investigate how the performance characteristics of ultrasound tissue typing (UTT) affect the design of a population-based prostate dose-painting protocol.


METHODS
The performance of UTT is evaluated using the receiver operating characteristic curve. As the imager's sensitivity increases, more tumors are detected, but the specificity worsens, causing more false-positive results. The UTT tumor map, obtained with a specific sensitivity and specificity setup, was used with the patient's CT image to guide intensity-modulated radiotherapy (IMRT) planning. The optimal escalation dose to the UTT positive region, as well as the safe dose to the negative background, was obtained by maximizing the uncomplicated control (i.e., a combination of tumor control probability and weighted normal tissue complication probability). For high- and low-risk tumors, IMRT plans guided by conventional ultrasound or UTT with a one-dimensional or two-dimensional spectrum analysis technique were compared with an IMRT plan in which the whole prostate was dose escalated.


RESULTS
For all imaging modalities, the specificity of 0.9 was chosen to reduce complications resulting from high false-positive results. If the primary tumors were low risk, the IMRT plans guided by all imaging modalities achieved high tumor control probability and reduced the normal tissue complication probability significantly compared with the plan with whole gland dose escalation. However, if the primary tumors were high risk, the accuracy of the imaging modality was critical to maintain the tumor control probability and normal tissue complication probability at acceptable levels.


CONCLUSIONS
The performance characteristics of an imager have important implications in dose painting and should be considered in the design of dose-painting protocols.
Zhang
Pengpeng
P
Department of Radiation Oncology, Columbia University Medical Center, New York, NY 10032-3784, USA. pz2010@columbia.edu
Osterman
K Sunshine
KS
Liu
Tian
T
Li
Xiang
X
Kessel
Jack
J
Wu
Leester
L
Schiff
Peter
P
Kutcher
Gerald J
GJ
D000465:Algorithms; D005189:False Positive Reactions; D006801:Humans; D008297:Male; D011336:Probability; D011467:Prostate / Q000000981:diagnostic imaging*; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D012372:ROC Curve; D011880:Radiotherapy Planning, Computer-Assisted; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed; D014463:Ultrasonography