Interrogating Bone Marrow
Timothy Bray1
1University College London, London, United Kingdom

Synopsis

Keywords: Musculoskeletal: Skeletal

This talk will discuss MRI methods for interrogating the bone marrow, building on the previous lectures that introduced the physiology and pathophysiology of the marrow. The discussion will focus on how MRI can be used to measure the size and properties of the key marrow compartments: the cellular and extracellular compartments, the fat compartment, the vascular compartment and trabecular compartment. Particular emphasis will be given to how MRI can be used to disentangle different marrow processes, thus enabling ‘confounder-corrected’ assessments of pathophysiology.

Structure of the lecture

This talk will discuss MRI methods for interrogating the bone marrow, building on the previous lectures that introduced the physiology and pathophysiology of the marrow.

Please note that this is a preliminary syllabus, and that the structure and content may change for the talk itself. Please see the online itself video for the most up-to-date version.

1. What compartments are present in the marrow?

The components of bone marrow and their physiology and pathophysiology have been discussed in the preceding lectures. From an MRI perspective, a useful conceptual simplification is to regard the bone marrow as a combination of blood cells (surrounded by an extracellular space), fat cells, blood vessels and bony trabeculae.

The signal in magnetic resonance imaging (MRI) experiment comes from protons, which reside in either water or fat molecules. In the bone marrow, the majority of water molecules are found in blood cells (red cells, white cells, platelets and precursors), within the extracellular space, within blood vessels (either in the blood itself or in vessel walls), or within bony trabeculae. For clarity of description, the cellular and extracellular spaces have been considered together here as it is often challenging to separate the signal from these spaces. The majority of lipid molecules are found in adipose cells, which are an important component of normal bone marrow and play an active role in physiology and pathophysiology (this has been discussed in more detail in the preceding lectures).

2. How can we measure the size and/or properties of each compartment?

(i) The fat compartment
Fat protons have several physical properties that differ from those of water protons, including relaxation times (particularly T1) and resonant frequency. These differences can be utilized for separating fat and water signals and measuring fat content. Most current methods for fat quantification rely on the difference in the resonant frequency of fat and water protons. This property can be exploited through various methods including chemical shift selective fat suppression (‘fat saturation’) [1], water- or fat-selective imaging [2,3], magnetic resonance spectroscopic imaging (MRSI) [4], magnetic resonance spectroscopy (MRS) [5] and chemical shift-encoded MRI (CSE-MRI) [6–15]. Of these methods, CSE-MRI has become increasingly popular and is now widely used as a clinical imaging tool.

In order to make measures of fat content accurate, and to facilitate comparison across imaging platforms and between sites, it is necessary to measure the true concentration of water and fat in the tissue. However, fat fraction measurements can be confounded by other properties of the tissue and acquisition; these confounding factors include T1 and T2* relaxation, the multipeak nature of the fat spectrum, noise, phase errors and temperature. If we can remove these confounding factors, we can define the proton density fat fraction (PDFF) as the fat signal divided by the combined signal obtained from both water and fat. Specific modifications can be made to the CSE-MRI method to correct for each confounding factor and enable PDFF measurement.


(ii) The cellular and extracellular compartments
Diffusion-weighted imaging (DWI) is ideally suited to capture changes in the movement of water molecules in the intra- and/or extracellular spaces (although it is not always straightforward to clearly differentiate the dominant contribution).

For simplicity, the water-containing marrow compartments can be modelled using a single summary measure of diffusivity: the apparent diffusion coefficient (ADC). ADC values have been shown to provide useful information on malignant infiltration in a variety of cancers, of which multiple myeloma (MM) is a clear example [16,17]. ADC values can also be used to track changes in tumour physiology with treatment.

To better differentiate between the contributions of different compartments, more complex models such as intravoxel incoherent motion (IVIM) imaging can be used. This allows perfusion or perfusion-like (‘pseudodiffusion’) and diffusion effects to be distinguished. However, validation of the individual parameters making up the IVIM model is challenging as reference standards are difficult to obtain.


(iii) The trabecular compartment
Apart from being used as a ‘correction factors’ in fat-water MRI experiments, R2* or R2’ (where R2* = R2 + R2’) measurements may be useful in their own right as markers of trabecular density and structure. There is an approximately linear relationship between R2*/R2’ and bone mineral density (BMD) [18,19]. R2*/R2’ have been shown to parallel apparent bone mineral density measured by dual-energy X-ray absorptiometry (DEXA) or quantitative computed tomography (QCT) [20–24].

This suggests a potential role in the assessment of osteoporosis per se [20] or in alterations of trabecular structure in other diseases. The utility of R2* mapping for BMD measurement can be increased by incorporating ultrashort echo time (UTE) acquisitions, since relaxation times can be extremely short in the bone marrow (particular near trabeculae or when BMD is high). Quantitative susceptibility mapping (QSM) [25–27] has been investigated as an alternative method for quantifying BMD, with promising initial results [28].

This suggests a potential role in the assessment of osteoporosis per se [20] or in alterations of trabecular structure in other diseases. The utility of R2* mapping for BMD measurement can be increased by incorporating ultrashort echo time (UTE) acquisitions, since relaxation times can be extremely short in the bone marrow (particular near trabeculae or when BMD is high). Quantitative susceptibility mapping (QSM) [25–27] has been investigated as an alternative method for quantifying BMD, with promising initial results [28].


(iv) The vascular compartment
The properties of the bone marrow vascular can be measured using dynamic contrast enhancement (DCE) MRI, which relies on rapid acquisition of images after contrast medium injection to assess tissue perfusion and kinetics. DCE MRI can be analysed semiquantitatively, using metrics such as time to peak and area under the curve. The early phase of enhancement reflects tissue micro-vascularisation and the later phases of washout reflect capillary permeability and interstitial space enhancement. Alternatively, pharmacokinetic modelling can be used to explain contrast exchange between the intravascular and extravascular space. Tumour angiogenesis typically leads to increased uptake of contrast medium, and DCE-MRI has been shown to be useful in distinguishing hypercellular haematopoietic marrow from neoplastic marrow. Perfusion changes can also be used to detect response, as they occur early after treatment and correlate with histological necrosis.

3. How can we get multiparametric information from our MRI methods?

The acquisition and signal models used for qMRI can be further extended to allow measurement of multiple tissue properties in a single acquisition.

For example, CSE-MRI can be incorporated into Carr-Purcell-Meiboom-Gill acquisitions to enable measurement of T2 and fat fraction [29]. Similarly, multiecho acquisitions can be repeated with varying flip angles [30] or with pre-saturation pulses [31] to enable simultaneous T1 and fat fraction measurement.

Magnetic resonance fingerprinting (MRF) has the potential to increase the number of contrasts available within a clinically-feasible timeframe. For example, MRF has been used to provide simultaneous T1, T2, T2* and FF maps in the liver [32], heart [33] and skeletal muscle [34]. MRI multitasking can enable acquisition of multiple parameters whilst also accounting for respiratory motion, which can be of value in organs such as the liver where such motion is problematic [35].

Combining qMRI parameters (either acquired together from one method or acquired separately used different methods) can potentially improve diagnostic performance, however, there is little clinical data to support this at present (and proof of this concept requires carefully conducted external validation studies).

Acknowledgements

TJPB is supported by the UCLH NIHR BRC.

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Proc. Intl. Soc. Mag. Reson. Med. 32 (2024)