Synopsis

Keywords: Image acquisition: Quantification, Image acquisition: Sequences, Image acquisition: Multiparametric

This lecture highlights the clinical needs and challenges of neuro and body MRI, with a focus on Alzheimer's, Parkinson's, epilepsy, cancer, and liver disease. Although MR imaging is a powerful tool, standard techniques may not provide the necessary information for accurate diagnosis and treatment monitoring. Advanced MRI and quantitative approaches offer promising results but have yet to fully penetrate clinical practice due to their limitations. The lecture emphasizes the need for interdisciplinary collaboration to advance the field and meet clinical demands. The potential of emerging technologies such as AI-driven image reconstruction and quantitative MRI is discussed as future directions.

Introduction

Magnetic resonance imaging (MRI) is an integral tool in clinical neuro and body imaging, allowing for diagnosis, disease progression evaluation, and treatment monitoring. However, standard MR imaging may not always provide the necessary information for differential diagnosis, staging, disease progression, or treatment response evaluation. Advanced MRI and quantitative approaches offer promising results and have the potential to shed light on disease pathophysiology. As new discoveries in disease pathology and treatments arise, there is a need to develop new imaging protocols and approaches to evaluate them. Furthermore, advanced MRI technology itself may generate new hypotheses about disease pathogenesis. Despite these advancements, quantitative and advanced MR imaging have yet to fully penetrate clinical practice due to their current limitations. This lecture will address the clinical needs and challenges for neuro and body MR imaging.

Clinical Needs in Neuroimaging

Three neurological diseases that have unmet needs in neuroimaging are Alzheimer’s disease, Parkinson's disease, and epilepsy.
Alzheimer’s disease
Alzheimer's disease is now characterized by a combination of three biomarkers, namely amyloid accumulation (A), tau accumulation (T), and neurodegeneration (N). Amyloid and tau pathology can be evaluated through amyloid/tau-PET or cerebrospinal fluid (CSF) biomarkers, while neurodegeneration (hippocampal atrophy) is usually evaluated through MRI. Quantifying the extent of brain atrophy, particularly in regions such as the hippocampus, entorhinal cortex, and medial temporal lobe, can help determine the stage of Alzheimer's disease and inform clinical management strategies. MR imaging can also provide valuable information on the patterns of brain atrophy and other characteristics specific to each type of dementia, helping to differentiate Alzheimer's disease from other types of dementia such as frontotemporal dementia, vascular dementia, or Lewy body dementia. Advanced MRI techniques, such as diffusion tensor imaging (DTI), resting-state functional MRI (rs-fMRI), and arterial spin labeling (ASL), can provide insights into the underlying microstructural, functional, and perfusion alterations associated with Alzheimer's disease. Alzheimer's disease is often accompanied by other age-related changes, such as cerebrovascular disease or brain lesions (white matter hyperintensity and microbleeds). MR imaging can help identify and assess the impact of these comorbidities on the clinical presentation and management of Alzheimer's disease. With the advancement of new anti-amyloid antibody drugs, the role of imaging is becoming more important. Quantitative and advanced imaging approaches are necessary to evaluate treatment efficacy and disease progression. Additionally, new imaging approaches to explore uncovered pathophysiologies, such as blood-brain barrier permeability and neuro-fluid clearance, are increasing and need to be optimized and standardized. Furthermore, new MR imaging approaches to visualize key Alzheimer's disease pathology (i.e. amyloid and tau) have the potential to be game-changing.
Parkinson’s disease
Parkinson's disease is a chronic and progressive neurological disorder that affects movement and coordination and is characterized by the loss of dopaminergic cells (neuromelanin-containing) in the substantia nigra, resulting in movement symptoms such as resting tremor, rigidity, and bradykinesia. Differential diagnosis of idiopathic Parkinson's disease and Parkinson plus syndrome (including multiple system atrophy and progressive supranuclear palsy) is crucial due to differences in drug response. Nigrosome imaging based on SWI and neuromelanin imaging based on T1-weighted imaging with MTC pulse has shown promising results in diagnosing Parkinson's disease. However, these two imaging sequences are usually limited to visual assessment, and quantitative approaches would be needed to improve their accuracy. In addition, quantitative susceptibility mapping (QSM) can provide valuable information by quantifying iron in deep gray matter areas in these patients. Advanced MRI techniques, such as connectivity MRI or diffusion kurtosis imaging, may offer better diagnostic accuracy and earlier detection of Parkinson's disease. These techniques can reveal microstructural changes and functional alterations in the brain associated with the disease, potentially aiding in earlier diagnosis and monitoring of disease progression. Overall, there is a need for further research to optimize and standardize these advanced imaging techniques for Parkinson's disease, in order to improve diagnosis, differentiate from other movement disorders, and monitor treatment response.
Epilepsy
Epilepsy is a neurological disorder that is characterized by recurrent seizures, which can be caused by various factors such as brain injury, infection, or genetic factors. It is a common neurologic disorder that affects 1.2% of the overall US population. While MR imaging is a standard diagnostic tool for epilepsy, current techniques may not always detect all cases or accurately identify the location and extent of the seizure focus. This is where new MR technology, such as MR spectroscopy or quantitative susceptibility mapping, may prove useful in providing a better characterization of epileptic lesions and improving the accuracy of diagnosis. Additionally, super-high resolution structural MRI may also be necessary for more precise identification of the seizure focus. Advanced imaging techniques, such as arterial spin labeling (ASL) and glutamate chemical exchange saturation transfer (gluCEST), have been studied for identifying the seizure focus, while diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) have been extensively studied for structural connectivity derangement following epilepsy. However, the limitations of spatial resolution may hinder their use in clinical practice.

Clinical Needs in Body Imaging: Cancer and Liver Disease

Cancer
MR imaging is commonly used in cancer diagnosis and monitoring, but new MR technologies such as diffusion-weighted imaging and dynamic contrast-enhanced MRI can provide additional information about tumor microstructure and vascularization, which can aid in tumor grading and treatment planning. Quantitative MR techniques such as T1 and T2 mapping, magnetization transfer imaging, and chemical exchange saturation transfer imaging can provide more detailed information about tumor metabolism and tissue composition.
Cardiovascular disease
MR imaging is an important tool for diagnosing and monitoring cardiovascular disease, but new MR technologies such as 4D flow imaging and vessel wall imaging can provide more detailed information about blood flow dynamics, vessel structure, and plaque composition. Quantitative MR techniques such as T1 and T2 mapping, T2* mapping, and T2-weighted imaging can provide a more accurate characterization of tissue damage and fibrosis.
Liver disease
MR imaging is increasingly used in liver disease diagnosis and monitoring, but new MR technologies such as diffusion-weighted imaging and MR elastography can provide more accurate detection and staging of liver fibrosis and cirrhosis. Quantitative MR techniques such as T1 and T2 mapping, chemical shift imaging, and relaxometry can provide more detailed information about liver tissue composition and function

Limitations of Advanced MRI Techniques in Clinical Practice

Arterial Spin Labeling (ASL)
ASL has a low signal-to-noise ratio (SNR) due to its reliance on endogenous blood water as a tracer. This can make it challenging to detect subtle changes in cerebral blood flow (CBF) and may require longer acquisition times to improve SNR. ASL measurements can be influenced by factors such as patient age, sex, and physiological conditions, which can lead to variability in CBF measurements. Standardization of acquisition protocols and post-processing techniques is essential to minimize variability. In ASL, the time it takes for the labeled blood to reach the imaging slice can affect the accuracy of CBF quantification. This can be particularly problematic in patients with altered blood flow, such as those with cerebrovascular disease. However, one major clinical limitation of ASL is low spatial resolution. For instance, while CT perfusion can achieve submillimeter resolution, MR perfusion (DSC) typically has a resolution of 2x2x5mm, and ASL is even worse with 3-5mm in-plane resolution x 5-7mm slice thickness (although some advanced ASL techniques provide 2mm in-plane resolution). Therefore, achieving adequately high spatial resolution should be a priority
Diffusion imaging
There are several advanced diffusion imaging techniques including diffusion kurtosis imaging, HARDI, multi-shell diffusion imaging, and diffusion basis spectrum imaging (DBSI). Nevertheless, The interpretation of diffusion imaging results can be challenging, as diffusion measures are sensitive to different aspects of tissue microstructure, such as axonal integrity, myelination, and neurite density. The relationships between these measures and tissue microstructure are complex and may vary across different brain regions and disease states. Diffusion imaging can be affected by variations in MR hardware, software, and acquisition protocols, which can lead to inconsistencies and variability in the data across different imaging sites and vendors. This can make it difficult to compare data across studies or establish standardized protocols for clinical use.
Susceptibility-weighted imaging (SWI)
SWI relies on phase information, which can be influenced by factors such as echo time, field strength, and tissue orientation, making it challenging to standardize across studies or sites. SWI images may be difficult to interpret due to their complex contrast mechanisms. QSM requires multiple processing steps, making it sensitive to errors at each stage, such as phase unwrapping, background field removal, and dipole inversion. QSM is vulnerable to signal-to-noise ratio (SNR) degradation and artifacts from factors like motion, susceptibility effects, and field inhomogeneities. The complex processing pipeline can lead to longer reconstruction times, limiting its applicability in time-sensitive clinical scenarios.
Magnetic Resonance Spectroscopy (MRS)
MRS typically has lower spatial resolution compared to other MRI techniques, which can make it difficult to localize metabolite changes to specific brain regions or lesions. The interpretation of MRS spectra can be challenging due to the overlapping peaks of various metabolites and the presence of baseline artifacts or macromolecular signals. MRS can have lengthy acquisition times, particularly for 2D or 3D acquisitions, which can be a challenge in clinical settings and may result in patient discomfort or motion artifacts.
Chemical Exchange Saturation Transfer (CEST)
CEST imaging is sensitive to changes in molecular exchange rates, pH, and temperature, which can confound the detection of specific metabolites or biomarkers. CEST imaging typically requires long acquisition times to obtain high-resolution images, which can be a challenge in clinical settings. CEST imaging involves complex data processing and analysis, which can be time-consuming and require specialized expertise.
MR Elastography
MR elastography requires specialized equipment, such as mechanical actuators, and complex acquisition and post-processing techniques to generate accurate and reliable elastograms. MR elastography is not widely available in all clinical settings, and access to the technique may be limited. The mechanical vibrations used in MR elastography may cause discomfort for some patients, particularly those with pain or sensitivity in the head or neck region.
Body Imaging
Body MR imaging can be especially susceptible to motion artifacts caused by respiration, cardiac motion, peristalsis, and patient movement. These artifacts can compromise image quality and hinder accurate diagnosis. Various techniques, such as breath-holding, respiratory gating, and advanced motion correction algorithms, can help reduce motion artifacts. Magnetic Field Inhomogeneity can be particularly problematic in body imaging due to the presence of air-tissue interfaces and metallic implants. Techniques such as shimming and advanced image reconstruction algorithms can help minimize the impact of field inhomogeneities. Achieving high spatial resolution in body MR imaging can be challenging due to the need for rapid imaging and large fields of view. The trade-off between spatial resolution, signal-to-noise ratio, and acquisition time can be a limiting factor in body MR imaging.

Conclusion

Although MR imaging is constantly being updated, there are still unmet clinical needs and challenges in both neuro and body imaging, particularly for common diseases. To address these challenges, emerging technologies and future directions may include AI-driven image reconstruction and quantitative MRI. However, to achieve these advancements, extensive interdisciplinary collaboration will be necessary.

Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) and funded by the Korean government (Ministry of Science, ICT and Future Planning) (grant 2020R1A2C1102896).