MRI has been an essential diagnostic tool in healthcare for several decades. It offers unique insights into most tissues without the need for ionising radiation. Historically, MRI has been predominantly used qualitatively, images are formed to allow visual discrimination of tissues types and pathologies, rather than providing quantitative measurements. Increasingly, quantitative MRI (qMRI) is also finding clinical application, where images provide the basis for physical measurements of, e.g. tissue volume measures and represent aspects of tissue composition and microstructure. This article reviews some common current research and clinical applications of qMRI from the perspective of measurement science. qMRI not only offers additional information for radiologists, but also the opportunity for improved harmonisation and calibration between scanners and as such it is well-suited to large-scale investigations such as clinical trials and longitudinal studies. Realising these benefits, however, presents a new kind of technical challenge to MRI practioners. When measuring a parameter quantitatively, it is crucial that the reliability and reproducibility of the technique are well understood. Strictly speaking, a numerical result of a measurement is meaningless unless it is accompanied by a description of the associated measurement uncertainty. It is therefore necessary to produce not just estimates of physical properties in a quantitative image, but also their associated uncertainties. As the process of determining a physical property from the raw MR signal is complicated and multistep, estimation of uncertainty is challenging and there are many aspects of the MRI process that require validation. With the clinical implementation of qMRI techniques and its continued expansion, there is a clear and urgent need for metrology in this field.

Impaired FMD (flow-mediated dilatation) has traditionally been recognized as an indirect marker of NO bioactivity, occurring in disease states such as DM (diabetes mellitus). Endothelium-dependent FMD is a homoeostatic response to short-term increases in local shear stress. Microvascular dysfunction in DM influences blood flow velocity patterns. We explored the determinants of the FMD response in relation to evoked DSS (diastolic shear stress) and forearm microcirculation haemodynamics by quantifying changes in Doppler flow velocity waveforms between groups. Forty patients with uncomplicated Type 1 DM and 32 controls underwent B-mode and Doppler ultrasound scanning to interrogate the brachial artery. Postischaemic Doppler velocity spectral envelopes were recorded and a wavelet-based time-frequency spectral analysis method was employed to track change in distal microcirculatory haemodynamics. No difference in baseline brachial artery diameter was evident between the groups (4.15 compared with 3.94 mm, P=0.23). FMD was significantly impaired in patients with Type 1 DM (3.95 compared with 7.75%, P<0.001). Endothelium-independent dilatation in response to GTN (glyceryl trinitrate) was also significantly impaired (12.07 compared with 18.77%, P<0.001). DSS (dyn/cm2) was significantly reduced in the patient group (mean 20.19 compared with 29.5, P=0.001). Wavelet interrogation of postischaemic flow velocity waveforms identified significant differences between groups. In conclusion, DSS, microcirculatory function and endothelium-independent vasodilatation in response to GTN are important determinants that impact on the magnitude of FMD response and are impaired in patients with Type 1 DM. Impaired FMD response is multifactorial in origin and cannot be attributed solely to a diminished NO bioavailability.

The earliest signs of cardiovascular disease occur in microcirculations. Changes to mechanical and structural properties of these small resistive vessels alter the impedance to flow, subsequent reflected waves, and consequently, flow waveform morphology. In this paper, we compare two frequency analysis techniques: 1) rootMUSIC and 2) the discrete wavelet transform (DWT) to extract features of flow velocity waveform morphology captured using Doppler ultrasound from the ophthalmic artery (OA) in 30 controls and 38 age and sex matched Type I diabetics. Conventional techniques for characterizing Doppler velocity waveforms, such as mean velocity, resistive index, and pulsatility index, revealed no significant differences between the groups. However, rootMUSIC and the DWT provided highly correlated results with the spectral content in bands 2-7 (30-0.8 Hz) significantly elevated in the diabetic group (p < 0.05). The spectral distinction between the groups may be attributable to manifestations of underlying pathophysiological processes in vascular impedance and consequent wave reflections, with bands 5 and 7 related to age. Spectral descriptors of OA blood velocity waveforms are better indicators of preclinical microvascular abnormalities in Type I diabetes than conventional measures. Although highly correlated DWT proved slightly more discriminatory than rootMUSIC and has the advantage of extending to subheart rate frequencies, which may be of interest.

A novel method is proposed for the measurement of signal-to-noise ratio (SNR) for the purpose of quality assurance (QA) in MRI. A boxcar filtering technique is applied which allows estimation of signal and noise from a single image. The method has been used to estimate SNR in a large set of images acquired in a consistent manner using various scanner models, coils and phantoms. Performance is evaluated by comparison with the double-image subtraction technique incorporating temporal instability correction. The limits of agreement between the techniques are comparable to typical variability in daily SNR, and significantly superior to the performance of other single-image methods published to date. Single-image methods are preferable as they halve the image acquisition time of the recommended double-image approach. Major inaccuracies are identified in methods of SNR measurement currently used for QA in MRI.