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Dive into the research topics where Edward M. Lawrence is active.

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Featured researches published by Edward M. Lawrence.


BJUI | 2013

Definitions of terms, processes and a minimum dataset for transperineal prostate biopsies: a standardization approach of the Ginsburg Study Group for Enhanced Prostate Diagnostics.

Timur H. Kuru; Karan Wadhwa; Richard T.M. Chang; Lina Maria Carmona Echeverria; Matthias Roethke; Alexander Polson; Giles Rottenberg; Brendan Koo; Edward M. Lawrence; Jonas Seidenader; Vincent Gnanapragasam; Richard G. Axell; Wilfried Roth; Anne Warren; Andrew Doble; Gordon Muir; Rick Popert; Heinz Peter Schlemmer; Boris Hadaschik; Christof Kastner

To define terms and processes and agree on a minimum dataset in relation to transperineal prostate biopsy procedures and enhanced prostate diagnostics. To identify the need for further evaluation and establish a collaborative research practice.


Nature Reviews Urology | 2012

The emerging role of diffusion-weighted MRI in prostate cancer management

Edward M. Lawrence; Vincent Gnanapragasam; Andrew N. Priest; Evis Sala

A significant amount of research has focused on the role of diffusion-weighted MRI (DW-MRI) in the management of patients with prostate cancer. Although uncertainties remain, a clearer picture of where this technique fits into clinical practice is now available. A combination of DW-MRI and T2-weighted MRI (T2W-MRI) demonstrates improved accuracy for lesion detection and localization compared with T2W-MRI alone, and has been suggested as a tool to guide tissue biopsy. DW-MRI could also have roles in active surveillance, evaluating treatment efficacy, and predicting disease recurrence. Furthermore, DW-MRI offers the exciting possibility of gathering information about tumor characteristics and aggressiveness in a noninvasive manner. Validation in large prospective multicenter trials is critical if this technique is to be integrated into current management algorithms for prostate cancer.


American Journal of Roentgenology | 2015

Ratio of Tumor to Normal Prostate Tissue Apparent Diffusion Coefficient as a Method for Quantifying DWI of the Prostate

Tristan Barrett; Andrew N. Priest; Edward M. Lawrence; Debra A. Goldman; Anne Warren; Vincent Gnanapragasam; Evis Sala; Ferdia A. Gallagher

OBJECTIVE The purpose of this study was to investigate the ability of the apparent diffusion coefficient (ADC) ratio of tumor to normal prostate tissue to overcome inherent variability based on choice of b values, with whole-mount histopathologic analysis as the reference standard for tumor identification. MATERIALS AND METHODS Thirty-nine patients with prostate cancer underwent 3-T MRI, including DWI with b values of 0, 150, 750, and 1000 s/mm(2). ADC maps were derived from four b value combinations. Histologically derived ROIs were defined for prostate tumor and benign prostate tissue to generate a ratio. The concordance correlation coefficient was used to evaluate agreement and reproducibility at different b values. Bland-Altman plots were used to evaluate the pattern of relative measurement difference between b value combinations. The relationship between ADC values and Gleason score was tested by Spearman rank correlation. RESULTS ADC values varied depending on the b value combination selected. The concordance correlation coefficient was higher for ADC ratios (0.883; 95% CI, 0.816-0.927) compared with absolute ADC values for normal tissue (0.873; 95% CI, 0.799-0.921) and tumor (0.792; 95% CI, 0.688-0.864). The ADC ratio concordance correlation coefficient for transition zone tumors was considerably higher than that for the peripheral zone in all cases. Bland-Altman analysis showed higher variation for ADC maps incorporating a b value of zero for both ratio and absolute values. There was a stronger inverse relationship to Gleason score for ADC ratios (rho, -0.354 to -0.456) compared with absolute ADC values (rho, -0.117 to -0.379). CONCLUSION The use of a simple ratio of prostate tumor ADC to normal tissue ADC improved the concordance between different b value combinations and could provide a more robust means of assessing restricted diffusion in the prostate.


PLOS ONE | 2016

Evaluating Prostate Cancer Using Fractional Tissue Composition of Radical Prostatectomy Specimens and Pre-Operative Diffusional Kurtosis Magnetic Resonance Imaging.

Edward M. Lawrence; Anne Warren; Andrew N. Priest; Tristan Barrett; Debra A. Goldman; Andrew Brian Gill; Vincent Gnanapragasam; Evis Sala; Ferdia A. Gallagher

Background Evaluating tissue heterogeneity using non-invasive imaging could potentially improve prostate cancer assessment and treatment. Methods 20 patients with intermediate/high-risk prostate cancer underwent diffusion kurtosis imaging, including calculation of apparent diffusion (Dapp) and kurtosis (Kapp), prior to radical prostatectomy. Whole-mount tissue composition was quantified into: cellularity, luminal space, and fibromuscular stroma. Peripheral zone tumors were subdivided according to Gleason score. Results Peripheral zone tumors had increased cellularity (p<0.0001), decreased fibromuscular stroma (p<0.05) and decreased luminal space (p<0.0001). Gleason score ≥4+3 tumors had significantly increased cellularity and decreased fibromuscular stroma compared to Gleason score ≤3+4 (p<0.05). In tumors, there was a significant positive correlation between median Kapp and cellularity (ρ = 0.50; p<0.05), and a negative correlation with fibromuscular stroma (ρ = -0.45; p<0.05). In normal tissue, median Dapp had a significant positive correlation with luminal space (ρ = 0.65; p<0.05) and a negative correlation with cellularity (ρ = -0.49; p<0.05). Median Kapp and Dapp varied significantly between tumor and normal tissue (p<0.0001), but only median Kapp was significantly different between Gleason score ≥4+3 and ≤3+4 (p<0.05). Conclusions Peripheral zone tumors have increased cellular heterogeneity which is reflected in mean Kapp, while normal prostate has a more homogeneous luminal space and cellularity better represented by Dapp.


World Journal of Radiology | 2015

Updates in advanced diffusion-weighted magnetic resonance imaging techniques in the evaluation of prostate cancer.

Hebert Alberto Vargas; Edward M. Lawrence; Yousef Mazaheri; Evis Sala

Diffusion-weighted magnetic resonance imaging (DW-MRI) is considered part of the standard imaging protocol for the evaluation of patients with prostate cancer. It has been proven valuable as a functional tool for qualitative and quantitative analysis of prostate cancer beyond anatomical MRI sequences such as T2-weighted imaging. This review discusses ongoing controversies in DW-MRI acquisition, including the optimal number of b-values to be used for prostate DWI, and summarizes the current literature on the use of advanced DW-MRI techniques. These include intravoxel incoherent motion imaging, which better accounts for the non-mono-exponential behavior of the apparent diffusion coefficient as a function of b-value and the influence of perfusion at low b-values. Another technique is diffusion kurtosis imaging (DKI). Metrics from DKI reflect excess kurtosis of tissues, representing its deviation from Gaussian diffusion behavior. Preliminary results suggest that DKI findings may have more value than findings from conventional DW-MRI for the assessment of prostate cancer.


BJUI | 2013

Definitions of terms, processes and a minimum dataset for transperineal prostate biopsies: a standardization approach of the Ginsburg Study Group for Enhanced Prostate Diagnostics: A standardization approach for transperineal prostate biopsies

Timur H. Kuru; Karan Wadhwa; Richard T.M. Chang; Lina Maria Carmona Echeverria; Matthias Roethke; Alexander Polson; Giles Rottenberg; Brendan Koo; Edward M. Lawrence; Jonas Seidenader; Vincent Gnanapragasam; Richard G. Axell; Wilfried Roth; Anne Warren; Andrew Doble; Gordon Muir; Rick Popert; Heinz-Peter Schlemmer; Boris Hadaschik; Christof Kastner

To define terms and processes and agree on a minimum dataset in relation to transperineal prostate biopsy procedures and enhanced prostate diagnostics. To identify the need for further evaluation and establish a collaborative research practice.


BJUI | 2013

Definitions of terms, processes and a minimum dataset for transperineal prostate biopsies

Timur H. Kuru; Karan Wadhwa; Richard T.M. Chang; Lina Maria Carmona Echeverria; Matthias Roethke; Alexander Polson; Giles Rottenberg; Brendan Koo; Edward M. Lawrence; Jonas Seidenader; Vincent Gnanapragasam; Richard G. Axell; Wilfried Roth; Anne Warren; Andrew Doble; Gordon Muir; Rick Popert; Heinz-Peter Schlemmer; Boris Hadaschik; Christof Kastner

To define terms and processes and agree on a minimum dataset in relation to transperineal prostate biopsy procedures and enhanced prostate diagnostics. To identify the need for further evaluation and establish a collaborative research practice.


European Radiology | 2014

Prostate cancer: performance characteristics of combined T2W and DW-MRI scoring in the setting of template transperineal re-biopsy using MR-TRUS fusion

Edward M. Lawrence; Sarah Y. W. Tang; Tristan Barrett; Brendan Koo; Debra A. Goldman; Anne Warren; Richard G. Axell; Andrew Doble; Ferdia A. Gallagher; Vincent Gnanapragasam; Christof Kastner; Evis Sala


European Radiology | 2018

Diagnostic evaluation of magnetization transfer and diffusion kurtosis imaging for prostate cancer detection in a re-biopsy population.

Tristan Barrett; Mary A. McLean; Andrew N. Priest; Edward M. Lawrence; Andrew J. Patterson; Brendan Koo; Ilse Patterson; Anne Warren; Andrew Doble; Vincent Jeyaseelan Gnanapragasam; Christof Kastner; Ferdia A. Gallagher


Archive | 2015

The ADC ratio of tumor to normal prostate as a method for quantifying diffusion weighted imaging of the prostate

Tristan Barrett; Andrew N. Priest; Edward M. Lawrence; Debra A. Goldman; Anne Warren; Vincent Gnanapragasam; Evis Sala; Ferdia A. Gallagher

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Anne Warren

Cambridge University Hospitals NHS Foundation Trust

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Andrew Doble

University of Cambridge

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Brendan Koo

University of Cambridge

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Evis Sala

Memorial Sloan Kettering Cancer Center

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Richard G. Axell

Cambridge University Hospitals NHS Foundation Trust

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Karan Wadhwa

University of Cambridge

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