* Understand the main effects of iron deposition on MR signals

* Become familiar with the major MR-based techniques to quantify liver iron

* Appreciate the challenges associated with quantifying liver iron, and the techniques designed to overcome these challenges

Excess iron accumulation in the body, due to excess intestinal absorption (hemochromatosis) or multiple blood transfusions (hemosiderosis), is toxic and can cause multiple health complications including liver and heart damage, pancreatic dysfunction, and growth failure. Oral chelation treatments are commonly prescribed to reduce body iron content, but they are expensive (~$50,000/year) and have side effects. Assessment of body iron levels is necessary for detection and quantitative staging of iron overload, and monitoring of iron-reducing treatments.

The simplest method to assess body iron content is based on measuring serum ferritin concentration from a blood sample. However, ferritin is confounded by a number of factors (e.g. inflammation) and often does not accurately reflect iron levels(1). In contrast, measurement of liver iron concentration (LIC) is well known to be a reliable indicator of total body iron(2). Liver biopsy can provide accurate measurement of LIC, however it is invasive, suffers from high sampling variability(3), and is contraindicated in many patients due to the risk of uncontrolled bleeding.

MRI is highly sensitive to the presence of iron in tissue. Iron stores, typically in the form of ferritin and hemosiderin, shorten the relaxation times T2, T2* and T1 (ie: increase in the relaxation rates R2, R2* and R1, respectively). The most prominent effect of iron is increasing R2 and R2* relaxation rates(4): R2 (as measured using single spin echo acquisitions with increasing echo times) increases monotonically (although not linearly) in the presence of liver iron deposits. This effect of iron on R2 is not completely understood, but likely due in part to the diffusion of protons in areas of microscopic B0 field inhomogeneities introduced by iron particles (ie: effective diffusion weighting introduced by iron). These microscopic B0 inhomogeneities also cause rapid signal dephasing in gradient echo acquisitions, resulting in increased R2*. The relationship between LIC and R2* has been shown to be linear, although several calibrations have been produced.

A number of techniques have been proposed for liver iron quantification, largely based on one of the following three approaches:

* Signal Intensity Ratio (SIR): In SIR methods, the signal intensity of the liver on spin-echo (SE) or gradient-echo (GRE) sequences is divided by the signal intensity of a reference tissue that does not accumulate iron, such as fat or skeletal muscle, or air outside the body (i.e., image noise) (5-7). Images are acquired using a body coil to avoid sensitivity variations arising from surface coils (8). Large regions-of-interest (ROIs) are placed in the reference object and the liver on the same slice, and the ratio of the mean signals is calculated. The most widely used SIR method is the one described by Gandon and colleagues (8).

* R2 relaxometry: In R2 relaxometry methods, several spin echo images (either single spin echoes or as an echo train) are acquired and the R2 relaxation rate is estimated. The most widely used R2 based method was proposed by St Pierre et al (9). The St Pierre method uses five T2-weighted single spin-echo (SSE) free-breathing sequences with constant repetition time (TR) and increasing TE spaced at 3-ms intervals (TEs=6,9,12,15,18ms). Using this method, a nonlinear relationship between R2 and LIC was calibrated (using biopsy-determined LIC as the reference) in over 100 subjects. The main challenge for spin-echo based R2 techniques is likely the need for relatively long acquisition times.

* R2* relaxometry: R2* relaxometry, based on gradient echo acquisitions, has the potential to overcome some of the limitations of R2-based techniques, due to its ability to provide full liver coverage without motion artifacts within a single breath-hold. R2* relaxometry is typically based on 2D or 3D spoiled gradient echo (SPGR) multi-echo sequences. These sequences can acquire all echoes in each TR using an echo train (either with monopolar or bipolar readout), a single echo per TR, or a combination of the two (ie: multiple interleaved echo trains). Subsequently, R2* is measured from the rate of exponential signal decay of the gradient echo signal.

The liver iron quantification techniques described above are sensitive to a number of confounding factors, which can introduce bias and decreased reproducibility into the LIC estimates. This presentation will provide an overview of the relevant confounders for quantification of LIC, including the following:

* Motion: Motion, particularly due to respiration, can introduce significant image artifacts, which can result in bias in the estimated LIC. Motion is a particular concern in spin echo acquisitions (eg: for R2 mapping) due to the long acquisition times.

* Fat: Hepatic fat accumulation is a very common condition (10). In the presence of water and fat signal components, the signal acquired at a single voxel is not a simple monoexponential decay, but instead contains oscillations as water and fat signals become in and out of phase. These oscillations lead to errors in fat-uncorrected R2* estimation using an exponential signal model, and these errors depend heavily on the choice of TE combination.

* Macroscopic B0 inhomogeneities: The presence of intra-voxel background field variations introduces additional signal decay in R2* mapping acquisitions. This additional signal decay can result in significant bias in R2* measurements, particularly near tissue-air interfaces such as near the dome of the liver.

* High LIC (Noise effects): Liver R2 or R2* relaxometry is challenging in the presence of very high LIC, due to the extremely rapid signal decay. R2* relaxometry is particularly challenging, as R2* relaxation rates can surpass 1000 s^-1 (T2*<1ms) at 1.5T in patients with high LIC. Accurate R2*-based estimation of LIC over a wide range of liver iron levels requires acquisition of short echo times and the use of optimized estimation techniques. Recent efforts for the development of ultra-short TE R2* mapping techniques may enable R2*-based LIC quantification with improved dynamic range.

* Field strength dependence: Relaxation parameters vary with field strength, therefore calibrations between R2 or R2* and LIC are field strength specific. Further, certain LIC quantification challenges (eg: related to high LIC) are increased at 3T relative to 1.5T due to the increased R2 and R2*.