https://nova.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:45220 Wed 26 Oct 2022 19:56:49 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:42282 Wed 16 Aug 2023 14:37:30 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:15470 Wed 11 Apr 2018 12:20:10 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:44516 95% of fractions were successfully delivered. The secondary outcomes were (1) the improvement in beam-target geometric alignment, (2) the improvement in dosimetric coverage of the prostate and avoidance of critical structures, and (3) no acute grade ≥3 genitourinary or gastrointestinal toxicity. Results: All 858 planned fractions were successfully delivered with MLC tracking, demonstrating the primary outcome of feasibility (P < .001). MLC tracking improved the beam-target geometric alignment from 1.4 to 0.90 mm (root-mean-square error). MLC tracking improved the dosimetric coverage of the prostate and reduced the daily variation in dose to critical structures. No acute grade ≥3 genitourinary or gastrointestinal toxicity was observed. Conclusions: Electromagnetic-guided MLC tracking radiation therapy for prostate cancer is feasible. The patients received improved geometric targeting and delivered dose distributions that were closer to those planned than they would have received without electromagnetic-guided MLC tracking. No significant acute toxicity was observed.]]> Wed 09 Nov 2022 10:02:12 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:45588 Wed 02 Nov 2022 10:40:43 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:20181 Sat 24 Mar 2018 07:51:40 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:26357 Sat 24 Mar 2018 07:35:51 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:38429 p = 0.04, ROC AUC 0.90) and standard deviation (SD) (p = 0.02, ROC AUC 0.90), week 2 skewness (p = 0.02, ROC AUC 0.91) and SD (p = 0.01, ROC AUC 0.94), week 4 kurtosis (p = 0.01, AUC 0.92) and SD (p = 0.01, ROC AUC 0.96). Changes in minimum ADC between baseline and week 2 (p = 0.02, ROC AUC 0.94) and baseline and week 4 (p = 0.02, ROC AUC 0.94) were prognostic for local recurrence. For prediction of any recurrence, ADC minimum (p = 0.02, ROC AUC 0.87) and SD (p = 0.01, ROC AUC 0.85) at baseline, and ADC maximum (p = 0.03, ROC AUC 0.77) and SD (p = 0.02, ROC AUC 0.81) at week 4 were significant. On LASSO logistic regression, ADC minimum and SD at baseline were retained for any recurrence. The only significant finding for DCE-MRI was a correlation of k-trans min at the second follow-up with local recurrence (p = 0.05, AUC 0.84). Conclusion: Several ADC parameters at various time points correlate with recurrence suggesting DW-MRI is a potential biomarker for SCCAC.]]> Fri 10 Sep 2021 12:16:47 AEST ]]>