https://novaprd-lb.newcastle.edu.au/vital/access/manager/Index ${session.getAttribute("locale")} 5 https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:36699 Wed 24 Jun 2020 18:21:42 AEST ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:53604 75% (AUC = 0.79, SE = 0.014). Discrimination between ISO lesions and cNAWM was accomplished with an accuracy of >69% (AUC = 0.74, SE = 0.018), while discrimination between BH lesions and cNAWM was achieved at an accuracy of >80% (AUC = 0.87, SE = 0.021). Conclusions: Our results highlight the potential of APTw imaging for use as a non-invasive technique that is able to provide essential molecular information to clinicians and researchers so that the stages of inflammation and degeneration in MS lesions can be better characterized.]]> Wed 07 Feb 2024 14:34:19 AEDT ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:53309 .05). Compared to HCs, both RRMS cohorts showed volume changes in white matter (−13%), gray matter (−16%), and cerebral spinal fluid (CSF) (+17-23%), as well as reduced NAA (−17%, p =.001, hippocampus), (−7%, p =.001, PCG), and (−9%, p =.001, PFC). MRI/S metrics in three regions were moderately correlated with cognition and fatigue functions. Conclusion: While both treatment arms showed overall similar volumetric and neurometabolic profiles, longitudinal studies are warranted to clarify neurometabolic changes and associations with treatment efficacy.]]> Tue 21 Nov 2023 12:02:21 AEDT ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:36572 Tue 09 Jun 2020 11:40:47 AEST ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:54037 Mon 24 Jun 2024 15:39:11 AEST ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:42377 Mon 22 Aug 2022 14:29:24 AEST ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:48497 1H MR spectroscopic imaging (3D ¹H MRSI) with a semi-localized adiabatic selective refocusing (sLASER) sequence and gradient-modulated offset-independent adiabatic (GOIA) pulses for detection of central gland prostate cancer. Additionally four risk models were developed to differentiate 1) normal vs. cancer, 2) low- vs. high-risk cancer, 3) low- vs. intermediate-risk cancer, and 4) intermediate- vs. high-risk cancer voxels. Study Type: Prospective. Subjects: Thirty-six patients with biopsy-proven central gland prostate cancer. Field Strength/Sequence: 3T MRI / 3D ¹H MRSI using GOIA-sLASER. Assessment: Cancer and normal regions of interest (ROIs) were selected by an experienced radiologist and ¹H MRSI voxels were placed within the ROIs to calculate seven metabolite signal ratios. Voxels were split into two subsets, 80% for model training and 20% for testing. Statistical Tests: Four support vector machine (SVM) models were built using the training dataset. The accuracy, sensitivity, and specificity for each model were calculated for the testing dataset. Results: High-quality MR spectra were obtained for the whole central gland of the prostate. The normal vs. cancer diagnostic model achieved the highest predictive performance with an accuracy, sensitivity, and specificity of 96.2%, 95.8%, and 93.1%, respectively. The accuracy, sensitivity, and specificity of the low- vs. high-risk cancer and low- vs. intermediate-risk cancer models were 82.5%, 89.2%, 70.2%, and 73.0%, 84.7%, 60.8%, respectively. The intermediate- vs. high-risk cancer model yielded an accuracy, sensitivity, and specificity lower than 55%. Data Conclusion: The GOIA-sLASER sequence with an external phased-array coil allows for fast assessment of central gland prostate cancer. The classification offers a promising diagnostic tool for discriminating normal vs. cancer, low- vs. high-risk cancer, and low- vs. intermediate-risk cancer. Level of Evidence: 2. Technical Efficacy: Stage 2.]]> Mon 20 Mar 2023 14:05:29 AEDT ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:43429 P ≤ .05). Only GPC showed positive correlation with all fatigue domains (r = .537, P ≤ .05). On the other hand, Glx-upper, NAA-2, GSH+Hca, and fucose-3 showed negative correlations with all fatigue domains (r = –.345 to –.580, P ≤ .05). While tyrosine showed positive correlation with MFIS (r = .499, P ≤ .05), cognitive fatigue was negatively correlated with total GSH (r = –.530, P ≤ .05). No correlations were found between lesion load or brain volumes with fatigue score. CONCLUSIONS: Our results suggest that fatigue in MS is strongly correlated with an imbalance in neurometabolites but not structural brain measurements.]]> Mon 19 Sep 2022 09:29:20 AEST ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:54737 90 % accuracy in this cohort (AUC=0.92, SE=0.86 - 0.94). Conclusion: Multi-modal MRI signatures can predict cognitive decline in a cohort of pwMS over 5 years with high accuracy. Future studies will benefit from the inclusion of even more MR modalities e.g., functional MRI, quantitative susceptibility mapping, magnetisation transfer imaging, as well as other potential predictors e.g., genetic and environmental factors. With further validation, this signature could be used in future trials with high-risk patients to personalise the management of cognitive decline in pwMS, even in the absence of relapses.]]> Mon 11 Mar 2024 14:19:33 AEDT ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:30630 1H-MRS) and localization techniques principles, different fast MRSI techniques will be discussed from their initial development to the recent innovations with particular emphasis on their capacity to record neurochemical changes in the brain in a variety of pathologies. The clinical applications of whole brain fast spectroscopic techniques, can assist in the assessment of neurochemical changes in the human brain and help in understanding the roles they play in disease. To give a good example of the utilities of these techniques in clinical context, MRSI application in multiple sclerosis was chosen. The available up to date and relevant literature is discussed and an outline of future research is presented.]]> Mon 11 Mar 2019 12:08:59 AEDT ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:36797 Mon 06 Jul 2020 16:25:41 AEST ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:40208 Mon 01 Aug 2022 09:10:25 AEST ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:51918 Fri 22 Sep 2023 10:40:32 AEST ]]> https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:47224 Fri 16 Dec 2022 10:37:25 AEDT ]]>