ABSTRACT
The effects of nerve sparing on the risk of positive surgical margins (PSMs) and biochemical recurrence after radical prostatectomy (RP) remain controversial. We examined data from 1018 men treated by RP between 1988 and 2006 at five centers in the Shared Equal Access Regional Cancer Hospital database. Neither bilateral nor unilateral nerve-sparing techniques were associated with a higher risk of PSM; on multivariate analysis of individual sides, the risk of PSM on either side was not increased by nerve sparing on either side. The risk for biochemical recurrence was not affected by bilateral or unilateral nerve sparing. When used on appropriately selected patients, nerve sparing does not increase the probability of PSM or biochemical recurrence after RP.
Subject(s)
Adenocarcinoma/surgery , Neoplasm Recurrence, Local/epidemiology , Prostatectomy/methods , Prostatic Neoplasms/surgery , Adenocarcinoma/mortality , Adenocarcinoma/pathology , Databases as Topic , Humans , Kaplan-Meier Estimate , Male , Middle Aged , Neoplasm Recurrence, Local/mortality , Neoplasm Staging , Prostate/innervation , Prostate-Specific Antigen/blood , Prostatic Neoplasms/mortality , Prostatic Neoplasms/pathologyABSTRACT
For functional magnetic resonance imaging studies of the neural substrates of language, the ability to have subjects performing overt verbal responses while in the scanner environment is important for several reasons. Most directly, overt responses allow the investigator to measure the accuracy and reaction time of the behavior. One problem, however, is that magnetic resonance gradient noise obscures the audio recordings made of voice responses, making it difficult to discern subject responses and to calculate reaction times. ASSERT (Adaptive Spectral Subtraction for Extracting Response Times), an algorithm for removing MR gradient noise from audio recordings of subject responses, is described here. The signal processing improves intelligibility of the responses and also allows automated extraction of reaction times. The ASSERT-derived response times were comparable to manually measured times with a mean difference of -8.75 ms (standard deviation of difference = 26.2 ms). These results support the use of ASSERT for the purpose of extracting response latencies and scoring overt verbal responses.
