Publications
16 results found
Reynolds HM, Tadimalla S, Wang Y-F, et al., 2022, Semi-quantitative and quantitative dynamic contrast-enhanced (DCE) MRI parameters as prostate cancer imaging biomarkers for biologically targeted radiation therapy, Cancer Imaging, Vol: 22, Pages: 1-14, ISSN: 1470-7330
BackgroundBiologically targeted radiation therapy treatment planning requires voxel-wise characterisation of tumours. Dynamic contrast enhanced (DCE) DCE MRI has shown promise in defining voxel-level biological characteristics. In this study we consider the relative value of qualitative, semi-quantitative and quantitative assessment of DCE MRI compared with diffusion weighted imaging (DWI) and T2-weighted (T2w) imaging to detect prostate cancer at the voxel level.MethodsSeventy prostate cancer patients had multiparametric MRI prior to radical prostatectomy, including T2w, DWI and DCE MRI. Apparent Diffusion Coefficient (ADC) maps were computed from DWI, and semi-quantitative and quantitative parameters computed from DCE MRI. Tumour location and grade were validated with co-registered whole mount histology. Kolmogorov–Smirnov tests were applied to determine whether MRI parameters in tumour and benign voxels were significantly different. Cohen’s d was computed to quantify the most promising biomarkers. The Parker and Weinmann Arterial Input Functions (AIF) were compared for their ability to best discriminate between tumour and benign tissue. Classifier models were used to determine whether DCE MRI parameters improved tumour detection versus ADC and T2w alone.ResultsAll MRI parameters had significantly different data distributions in tumour and benign voxels. For low grade tumours, semi-quantitative DCE MRI parameter time-to-peak (TTP) was the most discriminating and outperformed ADC. For high grade tumours, ADC was the most discriminating followed by DCE MRI parameters Ktrans, the initial rate of enhancement (IRE), then TTP. Quantitative parameters utilising the Parker AIF better distinguished tumour and benign voxel values than the Weinmann AIF. Classifier models including DCE parameters versus T2w and ADC alone, gave detection accuracies of 78% versus 58% for low grade tumours and 85% versus 72% for high grade tumours.ConclusionsIncorporating DCE MRI par
Statton BK, Smith J, Finnegan ME, et al., 2022, Temperature dependence, accuracy, and repeatability of T-1 and T-2 relaxation times for the ISMRM/NIST system phantom measured using MR fingerprinting, Magnetic Resonance in Medicine, Vol: 87, Pages: 1446-1460, ISSN: 0740-3194
PurposeBefore MR fingerprinting (MRF) can be adopted clinically, the derived quantitative values must be proven accurate and repeatable over a range of T1 and T2 values and temperatures. Correct assessment of accuracy and precision as well as comparison between measurements can only be performed when temperature is either controlled or corrected for. The purpose of this study was to investigate the temperature dependence of T1 and T2 MRF values and evaluate the accuracy and repeatability of temperature-corrected relaxation values derived from a B1-corrected MRF–fast imaging with steady-state precession implementation using 2 different dictionary sizes.MethodsThe International Society of MR in Medicine/National Institute of Standards and Technology phantom was scanned using an MRF sequence of 2 different lengths, a variable flip angle T1, and a multi-echo spin echo T2 at 14 temperatures ranging from 15°C to 28°C and investigated with a linear regression model. Temperature-corrected accuracy was evaluated by correlating T1 and T2 times from each MRF dictionary with reference values. Repeatability was assessed using the coefficient of variation, with measurements taken over 30 separate sessions.ResultsThere was a statistically significant fit of the model for MRF-derived T1 and T2 and temperature (p < 0.05) for all the spheres with a T1 > 500 ms. Both MRF methods showed a strong linear correlation with reference values for T1 (R2 = 0.996) and T2 (R2 = 0.982). MRF repeatability for T1 values was ≤1.4% and for T2 values was ≤3.4%.ConclusionMRF demonstrated relaxation times with a temperature dependence similar to that of conventional mapping methods. Temperature-corrected T1 and T2 values from both dictionaries showed adequate accuracy and excellent repeatability in this phantom study.
Henson DP, Edgar C, Ding Z, et al., 2021, Understanding lower limb muscle volume adaptations to amputation., Journal of Biomechanics, Vol: 125, Pages: 1-8, ISSN: 0021-9290
Amputation of a major limb, and the subsequent return to movement with a prosthesis, requires the development of compensatory strategies to account for the loss. Such strategies, over time, lead to regional muscle atrophy and hypertrophy through chronic under or overuse of muscles compared to uninjured individuals. The aim of this study was to quantify the lower limb muscle parameters of persons with transtibial and transfemoral amputations using high resolution MRI to ascertain muscle volume and to determine regression equations for predicting muscle volume using femur- and tibia-length, pelvic-width, height, and mass. Twelve persons with limb loss participated in this study and their data were compared to six matched control subjects. Subjects with unilateral transtibial amputation showed whole-limb muscle volume loss in the residual-limb, whereas minor volume changes in the intact limb were found, providing evidence for a compensation strategy that is dominated by the intact-limb. Subjects with bilateral-transfemoral amputations showed significant muscle volume increases in the short adductor muscles with an insertion not affected by the amputation, the hip flexors, and the gluteus medius, and significant volume decreases in the longer adductor muscles, rectus femoris, and hamstrings. This study presents a benchmark measure of muscle volume discrepancies in persons with limb-loss, and can be used to understand the compensation strategies of persons with limb-loss and the impact on muscle volume, thus enabling the development of optimised intervention protocols, conditioning therapies, surgical techniques, and prosthetic devices that promote and enhance functional capability within the population of persons with limb loss.
Favier C, Finnegan M, Quest R, et al., 2021, An open-source musculoskeletal model of the lumbar spine and lower limbs: a validation for movements of the lumbar spine, Computer Methods in Biomechanics and Biomedical Engineering, Vol: 24, Pages: 1310-1325, ISSN: 1025-5842
Musculoskeletal models of the lumbar spine have been developed with varying level of detail for a wide range of clinical applications. Providing consistency is ensured throughout the modelling approach, these models can be combined with other computational models and be used in predictive modelling studies to investigate bone health deterioration and the associated fracture risk. To provide precise physiological loading conditions for such predictive modelling studies, a new full-body musculoskeletal model including a detailed and consistent representation of the lower limbs and the lumbar spine was developed. The model was assessed against in-vivo measurements from the literature for a range of spine movements representative of daily living activities. Comparison between model estimations and electromyography recordings was also made for a range of lifting tasks. This new musculoskeletal model will provide a comprehensive physiological mechanical environment for future predictive finite element modelling studies on bone structural adaptation. It will be made freely available on https://simtk.org/projects/llsm/.
Sun Y, Reynolds HM, Wraith D, et al., 2019, Automatic stratification of prostate tumour aggressiveness using multiparametric MRI: a horizontal comparison of texture features, ACTA ONCOLOGICA, Vol: 58, Pages: 1118-1126, ISSN: 0284-186X
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- Citations: 13
Finnegan ME, Visanji NP, Romero-Canelon I, et al., 2019, Synchrotron XRF imaging of Alzheimer's disease basal ganglia reveals linear dependence of high-field magnetic resonance microscopy on tissue iron concentration, Journal of Neuroscience Methods, Vol: 319, Pages: 28-39, ISSN: 0165-0270
Background: Chemical imaging of the human brain has great potential for diagnostic and monitoring purposes. The heterogeneity of human brain iron distribution, and alterations to this distribution in Alzheimer's disease, indicate iron as a potential endogenous marker. The influence of iron on certain magnetic resonance imaging (MRI) parameters increases with magnetic field, but is under-explored in human brain tissues above 7 T. New Method: Magnetic resonance microscopy at 9.4 T is used to calculate parametric images of chemically-unfixed post-mortem tissue from Alzheimer's cases (n = 3) and healthy controls (n = 2). Iron-rich regions including caudate nucleus, putamen, globus pallidus and substantia nigra are analysed prior to imaging of total iron distribution with synchrotron X-ray fluorescence mapping. Iron fluorescence calibration is achieved with adjacent tissue blocks, analysed by inductively coupled plasma mass spectrometry or graphite furnace atomic absorption spectroscopy. Results: Correlated MR images and fluorescence maps indicate linear dependence of R 2 , R 2 * and R 2 ’ on iron at 9.4 T, for both disease and control, as follows: [R 2 (s −1 ) = 0.072[Fe] + 20]; [R 2 *(s −1 ) = 0.34[Fe] + 37]; [R 2 ’(s −1 ) = 0.26[Fe] + 16] for Fe in μg/g tissue (wet weight). Comparison with Existing Methods: This method permits simultaneous non-destructive imaging of most bioavailable elements. Iron is the focus of the present study as it offers strong scope for clinical evaluation; the approach may be used more widely to evaluate the impact of chemical elements on clinical imaging parameters. Conclusion: The results at 9.4 T are in excellent quantitative agreement with predictions from experiments performed at lower magnetic fields.
Klemt C, Nolte D, Ding Z, et al., 2019, Anthropometric scaling of anatomical datasets for subject-specific musculoskeletal modelling of the shoulder, Annals of Biomedical Engineering, Vol: 47, Pages: 924-936, ISSN: 0090-6964
Linear scaling of generic shoulder models leads to substantial errors in model predictions. Customisation of shoulder modelling through magnetic resonance imaging (MRI) improves modelling outcomes, but model development is time and technology intensive. This study aims to validate 10 MRI-based shoulder models, identify the best combinations of anthropometric parameters for model scaling, and quantify the improvement in model predictions of glenohumeral loading through anthropometric scaling from this anatomical atlas. The shoulder anatomy was modelled using a validated musculoskeletal model (UKNSM). Ten subject-specific models were developed through manual digitisation of model parameters from high-resolution MRI. Kinematic data of 16 functional daily activities were collected using a 10-camera optical motion capture system. Subject-specific model predictions were validated with measured muscle activations. The MRI-based shoulder models show good agreement with measured muscle activations. A tenfold cross-validation using the validated personalised shoulder models demonstrates that linear scaling of anthropometric datasets with the most similar ratio of body height to shoulder width and from the same gender (p < 0.04) yields best modelling outcomes in glenohumeral loading. The improvement in model reliability is significant (p < 0.02) when compared to the linearly scaled-generic UKNSM. This study may facilitate the clinical application of musculoskeletal shoulder modelling to aid surgical decision-making.
Sun Y, Reynolds HM, Parameswaran B, et al., 2019, Multiparametric MRI and radiomics in prostate cancer: a review, AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE, Vol: 42, Pages: 3-25, ISSN: 0158-9938
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- Citations: 70
Sun Y, Reynolds HM, Wraith D, et al., 2018, Voxel-wise prostate cell density prediction using multiparametric magnetic resonance imaging and machine learning, ACTA ONCOLOGICA, Vol: 57, Pages: 1540-1546, ISSN: 0284-186X
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- Citations: 14
Reynolds HM, Parameswaran BK, Finnegan ME, et al., 2018, Diffusion weighted and dynamic contrast enhanced MRI as an imaging biomarker for stereotactic ablative body radiotherapy (SABR) of primary renal cell carcinoma, PLOS ONE, Vol: 13, Pages: e0202387-e0202387
Reynolds HM, Parameswaran B, Roettger D, et al., 2018, Assessing DCE-MRI and DWI as treatment response biomarkers after SABR for primary renal cell carcinoma, JOURNAL OF CLINICAL ONCOLOGY, Vol: 36, ISSN: 0732-183X
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- Citations: 2
Sun Y, Reynolds H, Wraith D, et al., 2017, Predicting prostate tumour location from multiparametric MRI using Gaussian kernel support vector machines: a preliminary study, AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE, Vol: 40, Pages: 39-49, ISSN: 0158-9938
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- Citations: 22
Reynolds HM, Williams S, Zhang A, et al., 2015, Development of a registration framework to validate MRI with histology for prostate focal therapy, Medical Physics, Vol: 42, Pages: 7078-7089, ISSN: 0094-2405
<jats:sec><jats:title>Purpose:</jats:title><jats:p>Focal therapy has been proposed as an alternative method to whole‐gland treatment for prostate cancer when aiming to reduce treatment side effects. The authors recently validated a radiobiological model which takes into account tumor location and tumor characteristics including tumor cell density, Gleason score, and hypoxia in order to plan optimal dose distributions for focal therapy. The authors propose that this model can be informed using multiparametric MRI (mpMRI) and in this study present a registration framework developed to map prostate mpMRI and histology data, where histology will provide the “ground truth” data regarding tumor location and biology. The authors aim to apply this framework to a growing database to develop a prostate biological atlas which will enable MRI based planning for prostate focal therapy treatment.</jats:p></jats:sec><jats:sec><jats:title>Methods:</jats:title><jats:p>Six patients scheduled for routine radical prostatectomy were used in this proof‐of‐concept study. Each patient underwent mpMRI scanning prior to surgery, after which the excised prostate specimen was formalin fixed and mounted in agarose gel in a custom designed sectioning box. T2‐weighted MRI of the specimen in the sectioning box was acquired, after which 5 mm sections of the prostate were cut and histology sections were microtomed. A number of image processing and registration steps were used to register histology images with <jats:italic>ex vivo</jats:italic> MRI and deformable image registration (DIR) was applied to 3D T2w images to align the <jats:italic>in vivo</jats:italic> and <jats:italic>ex vivo</jats:italic> MRI data. Dice coefficient metrics and corresponding feature points from two independent annotators were selected in order to assess the DIR accuracy.</jats:p></jats:sec><jats:sec&g
Gallagher JJ, Finnegan ME, Grehan B, et al., 2012, Modest Amyloid Deposition is Associated with Iron Dysregulation, Microglial Activation, and Oxidative Stress, Journal of Alzheimer's Disease, Vol: 28, Pages: 147-161, ISSN: 1387-2877
Antharam V, Collingwood JF, Bullivant J-P, et al., 2012, High field magnetic resonance microscopy of the human hippocampus in Alzheimer's disease: Quantitative imaging and correlation with iron, NeuroImage, Vol: 59, Pages: 1249-1260, ISSN: 1053-8119
Ugarte M, Grime GW, Lord G, et al., 2012, Concentration of various trace elements in the rat retina and their distribution in different structures, Metallomics, Vol: 4, Pages: 1245-1245, ISSN: 1756-5901
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