Doctor of Philosophy

dissertationIn Chapter 1, an introduction to basic principles or MRI is given, including the physical principles, basic pulse sequences, and basic hardware. Following the introduction, five different published and yet unpublished papers for improving the utility of MRI are shown. Chapter 2 discusses a small rodent imaging system that was developed for a clinical 3 T MRI scanner. The system integrated specialized radiofrequency (RF) coils with an insertable gradient, enabling 100 'm isotropic resolution imaging of the guinea pig cochlea in vivo, doubling the body gradient strength, slew rate, and contrast-to-noise ratio, and resulting in twice the signal-to-noise (SNR) when compared to the smallest conforming birdcage. Chapter 3 discusses a system using BOLD MRI to measure T2* and invasive fiberoptic probes to measure renal oxygenation (pO2). The significance of this experiment is that it demonstrated previously unknown physiological effects on pO2, such as breath-holds that had an immediate (<1 sec) pO2 decrease (~6 mmHg), and bladder pressure that had pO2 increases (~6 mmHg). Chapter 4 determined the correlation between indicators of renal health and renal fat content. The R2 correlation between renal fat content and eGFR, serum cystatin C, urine protein, and BMI was less than 0.03, with a sample size of ~100 subjects, suggesting that renal fat content will not be a useful indicator of renal health. Chapter 5 is a hardware and pulse sequence technique for acquiring multinuclear 1H and 23Na data within the same pulse sequence. Our system demonstrated a very simple, inexpensive solution to SMI and acquired both nuclei on two 23Na channels using external modifications, and is the first demonstration of radially acquired SMI. Chapter 6 discusses a composite sodium and proton breast array that demonstrated a 2-5x improvement in sodium SNR and similar proton SNR when compared to a large coil with a linear sodium and linear proton channel. This coil is unique in that sodium receive loops are typically built with at least twice the diameter so that they do not have similar SNR increases. The final chapter summarizes the previous chapters

Editorial for "Diffusion Tensor Imaging for Quantitative Assessment of Anterior Cruciate Ligament Injury Grades and Graft".

Tears to the anterior cruciate ligament (ACL) are common and serious knee injuries which tend to occur in young, active individuals. They result in functional impairment and require a period of relative immobilisation followed by rehabilitation, often leading to surgery. Individuals suffering from an ACL injury also have a higher risk of developing osteoarthritis as a long-term consequence(1, 2). ACL reconstructive surgery using a tendon graft remains the clinical standard of care to provide stability to the knee joint and allow patients to return to sport quicker. However, the question of when to allow patients to return to high-level sport remains hotly debated, as the risk of sustaining a second ACL rupture following reconstructive surgery is highest within the subsequent two years(3). While conventional MRI methods continue to provide high diagnostic structural information for ACL injuries, they are unable to deliver advanced quantitative measures required for biological tissue characterisation and longitudinal observation of graft maturation. Promising techniques such as diffusion tensor imaging (DTI), are used for research purposes only and have not yet made the translation into routine clinical application.University of Cambridg

Quantitative analysis of the ACL and PCL using T1rho and T2 relaxation time mapping: an exploratory, cross-sectional comparison between OA and healthy control knees.

BACKGROUND: Quantitative magnetic resonance imaging (MRI) methods such as T1rho and T2 mapping are sensitive to changes in tissue composition, however their use in cruciate ligament assessment has been limited to studies of asymptomatic populations or patients with posterior cruciate ligament tears only. The aim of this preliminary study was to compare T1rho and T2 relaxation times of the anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) between subjects with mild-to-moderate knee osteoarthritis (OA) and healthy controls. METHODS: A single knee of 15 patients with mild-to-moderate knee OA (Kellgren-Lawrence grades 2-3) and of 6 age-matched controls was imaged using a 3.0 T MRI. Three-dimensional (3D) fat-saturated spoiled gradient recalled-echo images were acquired for morphological assessment and T1ρ- and T2-prepared pseudo-steady-state 3D fast spin echo images for compositional assessment of the cruciate ligaments. Manual segmentation of whole ACL and PCL, as well as proximal / middle / distal thirds of both ligaments was carried out by two readers using ITK-SNAP and mean relaxation times were recorded. Variation between thirds of the ligament were assessed using repeated measures ANOVAs and differences in these variations between groups using a Kruskal-Wallis test. Inter- and intra-rater reliability were assessed using intraclass correlation coefficients (ICCs). RESULTS: In OA knees, both T1rho and T2 values were significantly higher in the distal ACL when compared to the rest of the ligament with the greatest differences in T1rho (e.g. distal mean = 54.5 ms, proximal = 47.0 ms, p < 0.001). The variation of T2 values within the PCL was lower in OA knees (OA: distal vs middle vs proximal mean = 28.5 ms vs 29.1 ms vs 28.7 ms, p = 0.748; Control: distal vs middle vs proximal mean = 26.4 ms vs 32.7 ms vs 33.3 ms, p = 0.009). ICCs were excellent for the majority of variables. CONCLUSION: T1rho and T2 mapping of the cruciate ligaments is feasible and reliable. Changes within ligaments associated with OA may not be homogeneous. This study is an important step forward in developing a non-invasive, radiological biomarker to assess the ligaments in diseased human populations in-vivo.Declarations Ethics approval and consent to participate This study was approved by the East of England Cambridge Central Research Ethics Committee and written informed consent was given by all subjects included in the study. All methods were carried out in accordance with relevant guidelines and regulations. Consent for publication Not Applicable Availability of data and materials The datasets generated and analysed during the current study are not publicly available due to unattained permission from participants and research ethics committee but could be made available from JWM (email: [email protected]). Competing interests JWM, DAK and JDK acknowledge funding support from GlaxoSmithKline for their studentships and fellowships, respectively. JWM is an employee of AstraZeneca. CDSR, VAC and SMM have no competing interests to declare. Acknowledgements The Addenbrooke's Hospital Magnetic Resonance Imaging and Spectroscopy (MRIS) staff are thanked for their help with arranging and conducting the study MRI examinations. We also acknowledge the support of the Addenbrooke's Charitable Trust and the National Institute for Health Research Cambridge Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Funding The study was funded by an Experimental Medicine Initiative PhD studentship from the University of Cambridge [grant number RG81329] and by GlaxoSmithKline [grant number RG87552]. Authors' contributions Writing of original draft manuscript: CDSR. Study design and coordination: CDSR, JWM, JDK and SMM. Data acquisition: JWM and JDK. Data curation, analysis and interpretation: CDSR, JWM, VAC, JDK, DAK and SMM. Statistical analysis: CDSR and JWM. Review and editing of manuscript: JWM, VAC, JDK, DAK and SMM. All authors read and approved the final manuscript

Reproducibility of magnetic resonance fingerprinting-based T 1 mapping of the healthy prostate at 1.5 and 3.0 T: A proof-of-concept study

Funder: Cancer Research UK; funder-id: http://dx.doi.org/10.13039/501100000289Funder: National Institute of Health Research Cambridge Biomedical Research CentreFunder: Cancer Research UK and the Engineering and Physical Sciences Research Council Imaging Centre in Cambridge and ManchesterFunder: Cambridge Experimental Cancer Medicine CentreFacilitating clinical translation of quantitative imaging techniques has been suggested as means of improving interobserver agreement and diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI) of the prostate. One such technique, magnetic resonance fingerprinting (MRF), has significant competitive advantages over conventional mapping techniques in terms of its multi-site reproducibility, short scanning time and inherent robustness to motion. It has also been shown to improve the detection of clinically significant prostate cancer when added to standard mpMRI sequences, however, the existing studies have all been conducted on 3.0 T MRI systems, limiting the technique’s use on 1.5 T MRI scanners that are still more widely used for prostate imaging across the globe. The aim of this proof-of-concept study was, therefore, to evaluate the cross-system reproducibility of prostate MRF T1 in healthy volunteers (HVs) using 1.5 and 3.0 T MRI systems. The initial validation of MRF T1 against gold standard inversion recovery fast spin echo (IR-FSE) T1 in the ISMRM/NIST MRI system revealed a strong linear correlation between phantom-derived MRF and IR-FSE T1 values was observed at both field strengths (R2 = 0.998 at 1.5T and R2 = 0.993 at 3T; p = < 0.0001 for both). In young HVs, inter-scanner CVs demonstrated marginal differences across all tissues with the highest difference of 3% observed in fat (2% at 1.5T vs 5% at 3T). At both field strengths, MRF T1 could confidently differentiate prostate peripheral zone from transition zone, which highlights the high quantitative potential of the technique given the known difficulty of tissue differentiation in this age group. The high cross-system reproducibility of MRF T1 relaxometry of the healthy prostate observed in this preliminary study, therefore, supports the technique’s prospective clinical validation as part of larger trials employing 1.5 T MRI systems, which are still widely used clinically for routine mpMRI of the prostate

The optimisation of deep neural networks for segmenting multiple knee joint tissues from MRIs.

Automated semantic segmentation of multiple knee joint tissues is desirable to allow faster and more reliable analysis of large datasets and to enable further downstream processing e.g. automated diagnosis. In this work, we evaluate the use of conditional Generative Adversarial Networks (cGANs) as a robust and potentially improved method for semantic segmentation compared to other extensively used convolutional neural network, such as the U-Net. As cGANs have not yet been widely explored for semantic medical image segmentation, we analysed the effect of training with different objective functions and discriminator receptive field sizes on the segmentation performance of the cGAN. Additionally, we evaluated the possibility of using transfer learning to improve the segmentation accuracy. The networks were trained on i) the SKI10 dataset which comes from the MICCAI grand challenge "Segmentation of Knee Images 2010″, ii) the OAI ZIB dataset containing femoral and tibial bone and cartilage segmentations of the Osteoarthritis Initiative cohort and iii) a small locally acquired dataset (Advanced MRI of Osteoarthritis (AMROA) study) consisting of 3D fat-saturated spoiled gradient recalled-echo knee MRIs with manual segmentations of the femoral, tibial and patellar bone and cartilage, as well as the cruciate ligaments and selected peri-articular muscles. The Sørensen-Dice Similarity Coefficient (DSC), volumetric overlap error (VOE) and average surface distance (ASD) were calculated for segmentation performance evaluation. DSC ≥ 0.95 were achieved for all segmented bone structures, DSC ≥ 0.83 for cartilage and muscle tissues and DSC of ≈0.66 were achieved for cruciate ligament segmentations with both cGAN and U-Net on the in-house AMROA dataset. Reducing the receptive field size of the cGAN discriminator network improved the networks segmentation performance and resulted in segmentation accuracies equivalent to those of the U-Net. Pretraining not only increased segmentation accuracy of a few knee joint tissues of the fine-tuned dataset, but also increased the network's capacity to preserve segmentation capabilities for the pretrained dataset. cGAN machine learning can generate automated semantic maps of multiple tissues within the knee joint which could increase the accuracy and efficiency for evaluating joint health.European Union's Horizon 2020 Framework Programme [grant number 761214] Addenbrooke’s Charitable Trust (ACT) National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre University of Cambridge Cambridge University Hospitals NHS Foundation Trust GSK VARSITY: PHD STUDENTSHIP Funder reference: 300003198

Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T1 and T2 Mapping in a PET/MR Setting.

Multiparametric magnetic resonance imaging (MRI) can be used to characterize many cancer subtypes including ovarian cancer. Quantitative mapping of MRI relaxation values, such as T 1 and T 2 mapping, is promising for improving tumor assessment beyond conventional qualitative T 1- and T 2-weighted images. However, quantitative MRI relaxation mapping methods often involve long scan times due to sequentially measuring many parameters. Magnetic resonance fingerprinting (MRF) is a new method that enables fast quantitative MRI by exploiting the transient signals caused by the variation of pseudorandom sequence parameters. These transient signals are then matched to a simulated dictionary of T 1 and T 2 values to create quantitative maps. The ability of MRF to simultaneously measure multiple parameters, could represent a new approach to characterizing cancer and assessing treatment response. This feasibility study investigates MRF for simultaneous T 1, T 2, and relative proton density (rPD) mapping using ovarian cancer as a model system

The effect of gadolinium-based contrast agent administration on magnetic resonance fingerprinting-based T 1 relaxometry in patients with prostate cancer

Abstract: Magnetic resonance fingerprinting (MRF) is a rapidly developing fast quantitative mapping technique able to produce multiple property maps with reduced sensitivity to motion. MRF has shown promise in improving the diagnosis of clinically significant prostate cancer but requires further validation as part of a prostate multiparametric (mp) MRI protocol. mpMRI protocol mandates the inclusion of dynamic contrast enhanced (DCE) imaging, known for its significant T1 shortening effect. MRF could be used to measure both pre- and post-contrast T1 values, but its utility must be assessed. In this proof-of-concept study, we sought to evaluate the variation in MRF T1 measurements post gadolinium-based contrast agent (GBCA) injection and the utility of such T1 measurements to differentiate peripheral and transition zone tumours from normal prostatic tissue. We found that the T1 variation in all tissues increased considerably post-GBCA following the expected significant T1 shortening effect, compromising the ability of MRF T1 to identify transition zone lesions. We, therefore, recommend performing MRF T1 prior to DCE imaging to maintain its benefit for improving detection of both peripheral and transition zone lesions while reducing additional scanning time. Demonstrating the effect of GBCA on MRF T1 relaxometry in patients also paves the way for future clinical studies investigating the added value of post-GBCA MRF in PCa, including its dynamic analysis as in DCE-MRF

Effectively Measuring Exercise-Related Variations in T1ρ and T2 Relaxation Times of Healthy Articular Cartilage.

BACKGROUND: Determining the compositional response of articular cartilage to dynamic joint-loading using MRI may be a more sensitive assessment of cartilage status than conventional static imaging. However, distinguishing the effects of joint-loading vs. inherent measurement variability remains difficult, as the repeatability of these quantitative methods is often not assessed or reported. PURPOSE: To assess exercise-induced changes in femoral, tibial, and patellar articular cartilage composition and compare these against measurement repeatability. STUDY TYPE: Prospective observational study. POPULATION: Phantom and 19 healthy participants. FIELD STRENGTH/SEQUENCE: 3T; 3D fat-saturated spoiled gradient recalled-echo; T1ρ - and T2 -prepared pseudosteady-state 3D fast spin echo. ASSESSMENT: The intrasessional repeatability of T1ρ and T2 relaxation mapping, with and without knee repositioning between two successive measurements, was determined in 10 knees. T1ρ and T2 relaxation mapping of nine knees was performed before and at multiple timepoints after a 5-minute repeated, joint-loading stepping activity. 3D surface models were created from patellar, femoral, and tibial articular cartilage. STATISTICAL TESTS: Repeatability was assessed using root-mean-squared-CV (RMS-CV). Using Bland-Altman analysis, thresholds defined as the smallest detectable difference (SDD) were determined from the repeatability data with knee repositioning. RESULTS: Without knee repositioning, both surface-averaged T1ρ and T2 were very repeatable on all cartilage surfaces, with RMS-CV SDD) average exercise-induced in T1ρ and T2 of femoral (-8.0% and -5.3%), lateral tibial (-6.9% and -5.9%), medial tibial (+5.8% and +2.9%), and patellar (-7.9% and +2.8%) cartilage were observed. DATA CONCLUSION: Joint-loading with a stepping activity resulted in T1ρ and T2 changes above background measurement error. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1 J. MAGN. RESON. IMAGING 2020;52:1753-1764.GlaxoSmithKline National Institute of Health Research (NIHR) Cambridge Biomedical Research Centr

Improving the quantitative classification of Erlenmeyer flask deformities

Abstract: The Erlenmeyer flask deformity is a common skeletal modeling deformity, but current classification systems are binary and may restrict its utility as a predictor of associated skeletal conditions. A quantifiable 3-point system of severity classification could improve its predictive potential in disease. Ratios were derived from volumes of regions of interests drawn in 50 Gaucher’s disease patients. ROIs were drawn from the distal physis to 2 cm proximal, 2 cm to 4 cm, and 4 cm to 6 cm. Width was also measured at each of these boundaries. Two readers rated these 100 femurs using a 3-point scale of severity classification. Weighted kappa indicated reliability and one-way analysis of variance characterized ratio differences across the severity scale. Accuracy analyses allowed determination of clinical cutoffs for each ratio. Pearson’s correlations assessed the associations of volume and width with a shape-based concavity metric of the femur. The volume ratio incorporating the metaphyseal region from 0 to 2 cm and the diametaphyseal region at 4–6 cm was most accurate at distinguishing femurs on the 3-point scale. Receiver operating characteristic curves for this ratio indicated areas of 0.95 to distinguish normal and mild femurs and 0.93 to distinguish mild and severe femurs. Volume was moderately associated with the degree of femur concavity. The proposed volume ratio method is an objective, proficient method at distinguishing severities of the Erlenmeyer flask deformity with the potential for automation. This may have application across diseases associated with the deformity and deficient osteoclast-mediated modeling of growing bone

Author Correction: Ultra Short Echo Time MRI of Iron-Labelled Mesenchymal Stem Cells in an Ovine Osteochondral Defect Model.

An amendment to this paper has been published and can be accessed via a link at the top of the paper