Jonathan Goodwin
University of Newcastle
5 Papers
4 Citations
Jonathan Goodwin is an academic researcher from University of Newcastle. The author has contributed to research in topics: Radiation treatment planning & Quantitative susceptibility mapping. The author has an hindex of 1, co-authored 5 publications. Previous affiliations of Jonathan Goodwin include Mater Health Services.
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Papers
QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping.
Ashley Wilton Stewart,Simon Robinson,Kieran O'Brien,Kieran O'Brien,Jin Jin,Jin Jin,Georg Widhalm,Gilbert Hangel,Gilbert Hangel,Angela Walls,Jonathan Goodwin,Jonathan Goodwin,Korbinian Eckstein,Monique C. Tourell,Catherine Morgan,Aswin Narayanan,Markus Barth,Steffen Bollmann +17 more
TL;DR: In this paper, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated quantitative susceptibility mapping (QSM), which is integrated within an open-source software framework: QSMxT.
Diagnosis of transition zone prostate cancer by multiparametric MRI: added value of MR spectroscopic imaging with sLASER volume selection.
Neda Gholizadeh,Peter B. Greer,John Simpson,Jonathan Goodwin,Caixia Fu,Peter Lau,Saabir Siddique,Arend Heerschap,Saadallah Ramadan +8 more
TL;DR: In this article, the authors evaluated the potential diagnostic performance of novel 1H magnetic resonance spectroscopic imaging (MRSI) using a semi-localized adiabatic selective refocusing (sLASER) sequence with gradient offset independent adiability (GOIA) pulses in addition to the routine mp-MRI, including T2-weighted imaging, DWI, DWI and quantitative dynamic contrast enhancement (DCE).
Experimental evaluation of four-dimensional Magnetic Resonance Imaging for radiotherapy planning of lung cancer.
TL;DR: In this article, the authors evaluated 4D-CT and a 4DMRI Radial Volumetric Interpolated Breath-Hold Examination (VIBE) sequence with 13 patient respiratory patterns, simulating tumour motion and found no statistically significant difference in mean motion range.
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QSMxT: Robust Masking and Artefact Reduction for Quantitative Susceptibility Mapping
Ashley Wilton Stewart,Simon Robinson,Simon Robinson,Kieran O'Brien,Kieran O'Brien,Jin Jin,Jin Jin,Georg Widhalm,Gilbert Hangel,Angela Walls,Jonathan Goodwin,Jonathan Goodwin,Korbinian Eckstein,Monique C. Tourell,Catherine Morgan,Aswin Narayanan,Markus Barth,Steffen Bollmann +17 more
TL;DR: In this article, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated Quantitative Susceptibility Mapping (QSM) processing for a wide range of use-cases implemented in an open-source software framework.
Visualising the urethra for prostate radiotherapy planning.
Matthew Richardson,Kate Skehan,Lee Wilton,Joshua Sams,Justin Samuels,Jonathan Goodwin,Peter B. Greer,Swetha Sridharan,Jarad Martin +8 more
Abstract: INTRODUCTION The prostatic urethra is an organ at risk for prostate radiotherapy with genitourinary toxicities a common side effect Many external beam radiation therapy protocols call for urethral sparing, and with modulated radiotherapy techniques, the radiation dose distribution can be controlled so that maximum doses do not fall within the prostatic urethral volume Whilst traditional diagnostic MRI sequences provide excellent delineation of the prostate, uncertainty often remains as to the true path of the urethra within the gland This study aims to assess if a high-resolution isotropic 3D T2 MRI series can reduce inter-observer variability in urethral delineation for radiotherapy planning METHODS Five independent observers contoured the prostatic urethra for ten patients on three data sets; a 2 mm axial CT, a diagnostic 3 mm axial T2 TSE MRI and a 09 mm isotropic 3D T2 SPACE MRI The observers were blinded from each other's contours A Dice Similarity Coefficient (DSC) score was calculated using the intersection and union of the five observer contours vs an expert reference contour for each data set RESULTS The mean DSC of the observer vs reference contours was 047 for CT, 062 for T2 TSE and 078 for T2 SPACE (P < 0001) CONCLUSIONS The introduction of a 09 mm isotropic 3D T2 SPACE MRI for treatment planning provides improved urethral visualisation and can lead to a significant reduction in inter-observer variation in prostatic urethral contouring