Alexander Daniel

Alexander Daniel
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Alexander verified their affiliation via an institutional email.
Verified
Alexander verified their affiliation via an institutional email.
  • PhD (Physics)
  • Research Fellow at University of Nottingham

About

29
Publications
2,576
Reads
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92
Citations
Current institution
University of Nottingham
Current position
  • Research Fellow
Additional affiliations
April 2021 - December 2021
University of Nottingham
Position
  • Research Associate
Description
  • Physicist working on quantitative renal MRI specialising in computational analysis methods and ex-vivo sample scanning.
Education
September 2016 - June 2021
University of Nottingham
Field of study
  • Physics
September 2011 - June 2015
University of Nottingham
Field of study
  • Physics

Publications

Publications (29)
Conference Paper
Full-text available
Multicentre validation studies are key to the clinical translation of renal MRI and as such, the development of harmonised, cross vendor protocols is crucial. To process data acquired from these protocols, the UK Renal Imaging Network Kidney Analysis Toolbox (UKAT) has been developed. This open-source, vendor agnostic and easy to use Python package...
Article
Full-text available
Purpose Total kidney volume (TKV) is an important measure in renal disease detection and monitoring. We developed a fully automated method to segment the kidneys from T2‐weighted MRI to calculate TKV of healthy control (HC) and chronic kidney disease (CKD) patients. Methods This automated method uses machine learning, specifically a 2D convolution...
Conference Paper
Full-text available
Renal T2 mapping is still in its infancy with little consensus on methodology between studies, this leads to a variation in T¬2 measurements between studies. Here four T2 mapping methods (Spin Echo-Echo Planar Imaging (SE-EPI), Multi-Echo Turbo Spin Echo (ME-TSE), Gradient Spin Echo (GraSE), and Carr-Purcell-Meiboom-Gill T2 preparation (T2 prep)) a...
Conference Paper
Full-text available
T2 Relaxation Under Spin Tagging (TRUST) provides a method to measure oxygenation in venous vessels within the brain. Here, a TRUST scheme is adapted for use within the body, specifically to assess oxygenation in the renal vein, using a respiratory-triggered Flow-sensitive Alternating Inversion Recovery (FAIR) labelling technique. This FAIR-TRUST v...
Presentation
Full-text available
Manual segmentation of the kidneys in renal MRI is a time consuming process in many processing pipelines. Existing automated methods using classical imaging processing are specific to a single pathology. Here we implement a convolutional neural network for rapid and automatic segmentation of the kidneys from both a healthy control and Chronic Kidne...
Conference Paper
Full-text available
Motivation Renal function is driven by cortico-medullary gradients in physiology. Tools to quantitatively study MRI measures of such biological gradients across the whole kidney are highly desirable. Goal To assess/validate cortical-medullary gradient measurements using high-resolution quantitative-MRI (qMRI) of ex-vivo transplant kidneys. Approa...
Conference Paper
Full-text available
Motivation Renal T2-mapping can provide measures of kidney inflammation and oedema, but few studies include T2-mapping due to a lack of consensus on image parameters. Goal To compare the accuracy, sensitivity to B0/B+1, and influence of flow of our four renal T2-mapping sequences; SE-EPI, ME-SE, GraSE and T2-prepared EPI. Approach Each T2-mapping...
Conference Paper
Full-text available
Introduction: Key to the analysis of renal MRI studies is the reporting of quantitative measures in the cortex and medulla. This is often performed using manual regions-of-interest (ROI) which are difficult to define. The Twelve Layer Concentric Object (TLCO) method was proposed by Pruijm et. al 1 as an alternative to ROI analysis when studying blo...
Conference Paper
Full-text available
Motivation: The need for better biomarkers to assess progression of Chronic Kidney Disease (CKD). Goal(s): To determine if multiparametric MRI can detect changes in structure and function in CKD. Approach: In the Application of Functional Renal MRI (AFiRM) study, multiparametric MRI is to be collected on 400 CKD participants at baseline and Year...
Conference Paper
Full-text available
Motivation It is critical that MRI data acquired in multi-site, multi-vendor studies conforms to a standardised acquisition protocol. Goal(s) To develop XNAT tools to highlight scans that do not conform to a specified protocol or are of insufficient quality, enabling rapid correction of errors before future scans. Approach Multi-site DICOM data i...
Conference Paper
Full-text available
Motivation To provide improved methods to estimate cortical-medullary changes in multiparametric MRI measures of the kidney. Goal(s) To develop an analysis method for use with 3D data to generate quantitative-depth-based cortical-medullary layers which can be applied to any multiparametric map. Approach 3DQLayers segments the kidney into layers ba...
Article
Full-text available
Background T2 mapping is valuable to evaluate pathophysiology in kidney disease. However, variations in T2 relaxation time measurements across MR scanners and vendors may occur requiring additional correction. Purpose To harmonize renal T2 measurements between MR vendor platforms, and use an extended‐phase‐graph‐based fitting method (“StimFit”) to...
Presentation
Full-text available
Open source tools for multi-vendor, multi-site studies and vendor agnostic analysis of renal MRI data.
Code
UKAT is a vendor agnostic framework for the analysis of quantitative renal MRI data. The UKRIN-MAPS project aims to standardise the acquisition and analysis of renal MRI data to enable multi-site, multi-vendor studies. Although many MRI vendors produce quantitative maps on the scanner, their methods are closed source and as such, potentially cause...
Conference Paper
Full-text available
Here, we investigate in a porcine model how MR parameters change as donor kidneys are cold stored, by studying the effect of temperature, cold ischaemia time and compare static cold storage (SCS) with hypothermic machine perfusion (HMP). Variation in relaxometry measurements with temperature has been modelled allowing the comparison of in-vivo and...
Conference Paper
Full-text available
Kidney transplantation is the preferred treatment for end-stage kidney disease. Donor kidney viability is currently assessed using donor age, medical history, and serum creatinine, but these have limited predictive power. As part of a study to determine if MRI can be used as an alternative, more accurate, measurement of donor kidney viability, we o...
Conference Paper
Full-text available
Measures of total kidney volume (TKV) help to evaluate disease progression, and masks to define the kidney are important for the automatic assessment of multiparametric images collected in the same data space. For accurate measures in multicentre studies an automated method which is vendor agnostic and robust against image artefacts is needed. Here...
Conference Paper
Full-text available
Manual segmentation of the kidneys is very time consuming and reader dependent, this renders measurements of total kidney volume (TKV) in large multi-site studies impractical. Here we use a convolutional neural network (CNN), trained on data from a single MRI vendor, to segment the kidneys of volunteers scanned with a harmonised FSE image protocol...
Conference Paper
Full-text available
Standardisation and multicentre evaluation of renal MRI measures is crucial for clinical translation. Here we present results of a Travelling kidney study on GE, Philips and Siemens using a harmonised multiparametric renal MRI protocol, and show results of B0 and B1 mapping, T1, and T2* mapping. The mode B0 within the kidneys did not vary across ve...
Poster
Full-text available
A convolutional neural network, trained on single vendor data, is used to segment the kidneys from multi-vendor data as part of a travelling kidney study. Manual segmentations showed a significant difference across vendors which was not seen for the automated method.
Data
A dataset containing 100 T2-weighted abdominal MRI scans and manually defined kidney masks. This MRI sequence is designed to optimise contrast between the kidneys and surrounding tissue to increase the accuracy of segmentation. Half of the acquisitions were acquired of healthy control subjects while the other half were acquired from Chronic Kidney...
Thesis
Full-text available
The kidneys are morphologically and functionally complex organs and as such, lend themselves to complex methodologies of study. One such methodology is quantitative Magnetic Resonance Imaging (MRI). Rather than simply taking a structural image of the kidneys, quantitative MRI aims to measure physical properties such as the rate of blood flow, tissu...
Conference Paper
Full-text available
Manual segmentation of the kidneys in renal MRI is a time consuming process in many processing pipelines. Existing automated methods using classical imaging processing are specific to a single pathology. Here we implement a convolutional neural network for rapid and automatic segmentation of the kidneys from both a healthy control and Chronic Kidne...
Conference Paper
Full-text available
The study of post-mortem brain tissue using MRI has been shown to provide a tool to assess whole organ microstructure and pathology with high spatial resolution. However, few studies have been performed on other organs in the body, here we perform ex-vivo imaging of whole kidneys. T1 and T2* of ex-vivo porcine kidneys are monitored over a ten-week...
Data
Figure S1: The effect of the filter length and adaptability factor (λ) on A: the correlation between the original (gold standard, neuronal) and corrected signals and B: the ratio of the RMS amplitudes of the original and corrected signal. These plots show the average of each metric over all EEG channels using 2 mins 20 secs of neuronal data (from V...
Article
Full-text available
Simultaneous EEG‐fMRI allows multiparametric characterisation of brain function, in principle enabling a more complete understanding of brain responses; unfortunately the hostile MRI environment severely reduces EEG data quality. Simply eliminating data segments containing gross motion artefacts [MAs] (generated by movement of the EEG system and he...

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