Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis

Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response

Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis

Imaging; Multiple sclerosis; Quantitative MRIImatges; Esclerosi múltiple; Ressonància magnètica quantitativaImágenes; Esclerosis múltiple; Resonancia magnética cuantitativaQuantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.C.G. is supported by the Swiss National Science Foundation (SNSF) grant PP00P3_176984, the Stiftung zur Förderung der gastroenterologischen und allgemeinen klinischen Forschung and the EUROSTAR E! 113682 HORIZON2020. F.B. is supported by the National Institute for Health Research biomedical research center at University College London Hospitals. J.W. is supported by the EU Horizon2020 research and innovation grant (FORCE, 668039). D.S.R. is supported by the Intramural Research Program of National Institute of Neurological Disorders and Stroke, National Institutes of Health. A.T.T. is supported by an Medical Research Council grant (MR/S026088/1). S.R. is supported by the Austrian Science Foundation (FWF) grant I-3001. P.S. is supported by the Intramural Research Program of National Institute of Neurological Disorders and Stroke, National Institutes of Health. H.V. is supported by the Dutch multiple sclerosis Research Foundation, ZonMW and HealthHolland

Multiparametric Imaging and MR Image Texture Analysis in Brain Tumors

Discrimination of tumor from radiation injured (RI) tissues and differentiation of tumor types using noninvasive imaging is essential for guiding surgical and radiotherapy treatments are some of the challenges that clinicians face in the course of treatment of brain tumors. The first objective in this thesis was to develop a method to discriminate between glioblastoma tumor recurrences and radiation injury using multiparametric characterization of the tissue incorporating conventional magnetic resonance imaging signal intensities and diffusion tensor imaging parameters. Our results show significant correlations in the RI that was missing in the tumor regions. These correlations may aid in differentiating between tumor recurrence and RI. The second objective of was to investigate whether texture based image analysis of routine MR images would provide quantitative information that could be used to differentiate between glioblastoma and metastasis. Our results demonstrate that first-order texture feature of standard deviation and second-order texture features of entropy, inertia, homogeneity, and energy show significant differences between the two groups. The third objective was to investigate whether quantitative measurements of tumor size and appearance on MRI scans acquired prior to helical tomotherapy (HT) type whole brain radiotherapy with simultaneous infield boost treatment could be used to differentiate responder and non-responder patient groups. Our results demonstrated that smaller size lesions may respond better to this type of radiation therapy. Measures of appearance provided limited added value over measures of size for response prediction. Quantitative measurements of rim enhancement and core necrosis performed separately did not provide additional predictive value

Optimized non-invasive MRI protocols for characterizing tissue microstructures: applications in humans to prostate cancer and fetal brain development

This PhD project was aimed to optimize MRI protocols for pelvis imaging, in particular for the diagnosis of prostate cancer (PCa) and for the fetal brain development. Different non-invasive MRI techniques were employed to investigate biological tissues, with the purpose to obtain information on microstructures and potentially metabolism. Prostate cancer is the second most common malignancy and the fifth leading cause of death in men worldwide. Due to the high incidence of PCa and the limitations of current diagnostic methods, the primary goal of this work was to develop an MRI protocol able to improve the sensitivity of the diagnostic. The investigation of prostate cancer started with ex-vivo experiments conducted on specimens of human prostate gland, obtained after radical prostatectomy, with the 9.4T scanner at the NMR and Medical Physics Laboratory of CNR-ISC (Sapienza). Diffusion Tensor Imaging (DTI) and Diffusion Kurtosis Imaging (DKI) were performed at high-resolution (70x70 micrometers in plane) to evaluate diffusion metrics in the different prostate compartment and directly compare measurements with the histopathology results. This study proceeded with in-vivo experiments with a 3T clinical MR scanner (Philips Achieva at Policlinico Tor Vergata) on subjects with diagnosed PCa. DTI was performed with the purpose to assess its diagnostic ability in individuating and classifying PCa with different ranges of diffusion weightings, i.e. b-values. Our results showing that the diagnostic accuracy of DTI is improved with high diffusion weightings motivated our interest in performing DKI, a technique that captures water diffusion features when high b-values are employed, providing additional information on tissue microstructures, inaccessible to DTI technique. The second part of this PhD project was conducted at the Center for Magnetic Resonance Research (CMRR) in Minneapolis and was funded by the European Union's Horizon 2020 research and innovation program under the Marie Curie grant agreement No 691110 (MICROBRADAM). The study was dedicated to perform prostate cancer imaging with new contrast mechanisms, based on T1rho and T2rho relaxation times. T1rho and T2rho characterize the relaxation of the nuclear magnetization in the rotating frame and they are sensitive to molecular dynamics occurring at frequencies in the range of kHz, characteristic of several in-vivo processes, enabling the access to important information on tissue microenvironment. T1rho and T2rho imaging is limited by the intensive energy deposited by the acquisition sequence, which it is usually overcome by increasing the acquisition time, preventing the possibility of diagnostic applications. Therefore the aim of this work was to develop a new approach to perform imaging in the rotating frame with a three-dimensional acquisition method, recently developed at the CMRR, in order to address the aforementioned shortcomings. Given the incidence of PCa, this research has international interest and potentially contributes to improve not only the sensitivity of PCa diagnostic but also the knowledge of the tissue micro-changing caused by the tumor development. A part of this project was dedicated to Diffusion MRI application in woman pelvis to image fetuses during gestation. The aim of this work was to develop a fast and reliable protocol for fetal imaging to minimize mother-fetal motion artifact and perfusion effects. The protocol designed for acquisition and post-processing was employed to successfully study fetal brain development during the second and third trimester of gestation, in normal cases and in fetuses affected by ventriculomegaly disease. These preliminary data can contribute to delineate a reference standard to assess the normal progress of sulcation and myelination as well as the normative biometry of the fetal brain, improving the knowledge of brain maturation. Globally, the impact of this research lies in having demonstrated that the sensitivity of DMRI for microstructural changes in body tissue caused by cancer, brain disease or normal condition like brain maturation can be fruitfully utilized in combination with artifact correction methods. Moreover, new strategy of image reconstruction, such as 3D gradient echo, can be successfully employed to perform abdominal imaging, enriching the investigation of in-vivo systems with information on tissue microenvironment and metabolism

Advanced perfusion quantification methods for dynamic PET and MRI data modelling

The functionality of tissues is guaranteed by the capillaries, which supply the microvascular network providing a considerable surface area for exchanges between blood and tissues. Microcirculation is affected by any pathological condition and any change in the blood supply can be used as a biomarker for the diagnosis of lesions and the optimization of the treatment. Nowadays, a number of techniques for the study of perfusion in vivo and in vitro are available. Among the several imaging modalities developed for the study of microcirculation, the analysis of the tissue kinetics of intravenously injected contrast agents or tracers is the most widely used technique. Tissue kinetics can be studied using different modalities: the positive enhancement of the signal in the computed tomography and in the ultrasound dynamic contrast enhancement imaging; T1-weighted MRI or the negative enhancement of T2* weighted MRI signal for the dynamic susceptibility contrast imaging or, finally, the uptake of radiolabelled tracers in dynamic PET imaging. Here we will focus on the perfusion quantification of dynamic PET and MRI data. The kinetics of the contrast agent (or the tracer) can be analysed visually, to define qualitative criteria but, traditionally, quantitative physiological parameters are extracted with the implementation of mathematical models. Serial measurements of the concentration of the tracer (or of the contrast agent) in the tissue of interest, together with the knowledge of an arterial input function, are necessary for the calculation of blood flow or perfusion rates from the wash-in and/or wash-out kinetic rate constants. The results depend on the acquisition conditions (type of imaging device, imaging mode, frequency and total duration of the acquisition), the type of contrast agent or tracer used, the data pre-processing (motion correction, attenuation correction, correction of the signal into concentration) and the data analysis method. As for the MRI, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a non-invasive imaging technique that can be used to measure properties of tissue microvasculature. It is sensitive to differences in blood volume and vascular permeability that can be associated with tumour angiogenesis. DCE-MRI has been investigated for a range of clinical oncologic applications (breast, prostate, cervix, liver, lung, and rectum) including cancer detection, diagnosis, staging, and assessment of treatment response. Tumour microvascular measurements by DCE-MRI have been found to correlate with prognostic factors (such as tumour grade, microvessel density, and vascular endothelial growth factor expression) and with recurrence and survival outcomes. Furthermore, DCE-MRI changes measured during treatment have been shown to correlate with outcome, suggesting a role as a predictive marker. The accuracy of DCE-MRI relies on the ability to model the pharmacokinetics of an injected contrast agent using the signal intensity changes on sequential magnetic resonance images. DCE-MRI data are usually quantified with the application of the pharmacokinetic two-compartment Tofts model (also known as the standard model), which represents the system with the plasma and tissue (extravascular extracellular space) compartments and with the contrast reagent exchange rates between them. This model assumes a negligible contribution from the vascular space and considers the system in, what-is-known as, the fast exchange limit, assuming infinitely fast transcytolemmal water exchange kinetics. In general, the number, as well as any assumption about the compartments, depends on the properties of the contrast agent used (mainly gadolinium) together with the tissue physiology or pathology studied. For this reason, the choice of the model is crucial in the analysis of DCE-MRI data. The value of PET in clinical oncology has been demonstrated with studies in a variety of cancers including colorectal carcinomas, lung tumours, head and neck tumours, primary and metastatic brain tumours, breast carcinoma, lymphoma, melanoma, bone cancers, and other soft-tissue cancers. PET studies of tumours can be performed for several reasons including the quantification of tumour perfusion, the evaluation of tumour metabolism, the tracing of radiolabelled cytostatic agents. In particular, the kinetic analysis of PET imaging has showed, in the past few years, an increasing value in tumour diagnosis, as well as in tumour therapy, through providing additional indicative parameters. Many authors have showed the benefit of kinetic analysis of anticancer drugs after labelling with radionuclide in measuring the specific therapeutic effect bringing to light the feasibility of applying the kinetic analysis to the dynamic acquisition. Quantification methods can involve visual analysis together with compartmental modelling and can be applied to a wide range of different tracers. The increased glycolysis in the most malignancies makes 18F-FDG-PET the most common diagnostic method used in tumour imaging. But, PET metabolic alteration in the target tissue can depend by many other factors. For example, most types of cancer are characterized by increased choline transport and by the overexpression of choline kinase in highly proliferating cells in response to enhanced demand of phosphatidylcholine (prostate, breast, lung, ovarian and colon cancers). This effect can be diagnosed with choline-based tracers as the 18Ffluoromethylcholine (18F-FCH), or the even more stable 18F-D4-Choline. Cellular proliferation is also imaged with 18F-fluorothymidine (FLT), which is trapped within the cytosol after being mono phosphorylated by thymidine kinase-1 (TK1), a principal enzyme in the salvage pathway of DNA synthesis. 18F-FLT has been found to be useful for noninvasive assessment of the proliferation rate of several types of cancer and showed high reproducibility and accuracy in breast and lung cancer tumours. The aim of this thesis is the perfusion quantification of dynamic PET and MRI data of patients with lung, brain, liver, prostate and breast lesions with the application of advanced models. This study covers a wide range of imaging methods and applications, presenting a novel combination of MRI-based perfusion measures with PET kinetic modelling parameters in oncology. It assesses the applicability and stability of perfusion quantification methods, which are not currently used in the routine clinical practice. The main achievements of this work include: 1) the assessment of the stability of perfusion quantification of D4-Choline and 18F-FLT dynamic PET data in lung and liver lesions, respectively (first applications in the literature); 2) the development of a model selection in the analysis of DCE-MRI data of primary brain tumours (first application of the extended shutter speed model); 3) the multiparametric analysis of PET and MRI derived perfusion measurements of primary brain tumour and breast cancer together with the integration of immuohistochemical markers in the prediction of breast cancer subtype (analysis of data acquired on the hybrid PET/MRI scanner). The thesis is structured as follows: - Chapter 1 is an introductive chapter on cancer biology. Basic concepts, including the causes of cancer, cancer hallmarks, available cancer treatments, are described in this first chapter. Furthermore, there are basic concepts of brain, breast, prostate and lung cancers (which are the lesions that have been analysed in this work). - Chapter 2 is about Positron Emission Tomography. After a brief introduction on the basics of PET imaging, together with data acquisition and reconstruction methods, the chapter focuses on PET in the clinical settings. In particular, it shows the quantification techniques of static and dynamic PET data and my results of the application of graphical methods, spectral analysis and compartmental models on dynamic 18F-FDG, 18F-FLT and 18F-D4- Choline PET data of patients with breast, lung cancer and hepatocellular carcinoma. - Chapter 3 is about Magnetic Resonance Imaging. After a brief introduction on the basics of MRI, the chapter focuses on the quantification of perfusion weighted MRI data. In particular, it shows the pharmacokinetic models for the quantification of dynamic contrast enhanced MRI data and my results of the application of the Tofts, the extended Tofts, the shutter speed and the extended shutter speed models on a dataset of patients with brain glioma. - Chapter 4 introduces the multiparametric imaging techniques, in particular the combined PET/CT and the hybrid PET/MRI systems. The last part of the chapter shows the applications of perfusion quantification techniques on a multiparametric study of breast tumour patients, who simultaneously underwent DCE-MRI and 18F-FDG PET on a hybrid PET/MRI scanner. Then the results of a predictive study on the same dataset of breast tumour patients integrated with immunohistochemical markers. Furthermore, the results of a multiparametric study on DCE-MRI and 18F-FCM brain data acquired both on a PET/CT scanner and on an MR scanner, separately. Finally, it will show the application of kinetic analysis in a radiomic study of patients with prostate cancer

Investigating Tissue Heterogeneity using MRI in Prostate Cancer

Multi-parametric MRI, a promising new technique for grading prostate cancer using MRI, classifies a high number of regions as indeterminate. This is a symptom of the wider problem that clinical usage of MRI in prostate cancer only includes basic techniques and does not directly categorise tissue microstructure. This work provides insight into the microstructure of the prostate using a combination of new tissue models and acquisition schemes. Each is tested with the aim of producing a method that is better at detecting and grading prostate cancer. The first section utilises microstructural diffusion models to better quantify tissue heterogeneity in the prostate. The two models investigated provided more information about the heterogeneous nature of the prostate that ADC and showed significant difference between lesions and normal tissue. The next section looks into combining multi-echo T2 (ME-T2) sequences with quantitative tissue modelling called Luminal Water Imaging (LWI). This work produced an optimal LWI fitting technique and acquisition. Then the ability of LWI to detect the PI-RADS v2.0 score of regions of interest was examined, showing that it was able to differentiate between scores better than ADC. This work also showed that LWI can differentiate between tumour and normal tissue with an AUC of 0.81 (p<0.05) when compared to ADC with an AUC of 0.75 (p<0.05) in this dataset. The next section further improves the acquisitions using larger datasets. It showed that correcting for imperfect pulse refocusing could improve on the performance of LWI in detecting PCa. This work also showed that fewer echoes could be used in the acquisition. Neural networks were then used to detect and grade prostate cancer using the data points from both multiple b-value diffusion and ME-T2 decay curves. The neural network’s ability to distinguish between different PIRADS scores was shown to have an AUC of 0.87 (p<0.05) using 32-echo data

Assessing Optic Neuritis in a Mouse Model of Multiple Sclerosis with Diffusion MR Imaging

Optic neuritis (ON) is an early manifestation in patients of multiple sclerosis (MS), typically resulting in visual dysfunction. The inflammatory demyelination of the optic nerve in ON closely resembles pathologies of the rest of central nervous system (CNS) white matter in MS. Since accumulated axonal degeneration in MS was considered as the potential cause leading to permanent disability, correlating optic nerve pathology and visual function in ON could be a model system to investigate the relationship between functional outcome and neuropathology. It may also present a new way to reflect the disease progression in MS. Various MR techniques have been used to assess inflammation (inflammatory cell infiltration and vasogenic edema) of ON, but rarely demonstrated the ability to image cellularity changes non-invasively. Diffusion MRI measures the Brownian motion of water molecules in the microstructure of biological tissues. Diffusion tensor imaging (DTI) holds the promise to provide a specific biomarker of axonal injury and demyelination in CNS white matter by axial diffusivity (the diffusion parallel to white matter fibers) and radial diffusivity (the diffusion perpendicular to white matter fibers), respectively. However, DTI assumes a single diffusion tensor model and thus takes an average of varied diffusion components. In contrast, our recently developed diffusion basis spectrum imaging (DBSI) resolves the complex diffusion components and provides relatively accurate directional diffusivities and diffusion component fractions, relating to the detail and accurate pathological picture of the disease or injury. In the current work, in vivo 25-direction DBSI was applied to the optic nerve of mice with experimental autoimmune encephalomyelitis (EAE), an animal model of MS, with visual impairment at onset of ON. Our results demonstrate that inflammation correlated well with visual impairment in acute ON. DBSI successfully detected inflammatory cell infiltration and optic nerve white matter pathology in EAE that was consistent with histology, supporting the capability of DBSI to quantify increased cellularity, axonal injury and myelin damage in the optic nerve of EAE mice

Macroscale imaging: a potential biomarker for post stroke functional outcome?

To determine whether long-term functional outcomes in stroke patients can be predicted by the amount of acutely damaged white matter tracts. We collected acute behavioral and neuroimaging data from a group of first-time stroke patients and add those from the other(s) databases. (n=114 + n) within one week (check with the other DBs) post-stroke. Functional outcome was telephonically evaluated using the Stroke Impact Scale 3.0 at 12 months post-stroke. For each patient, we calculated the absolute number of white matter tracts affected by the ischemic lesion from our anatomical scans. We measured a numerical index that considers white matter tract density (WMTD index). We compared the ability of the WMTD index, considered individually, or within a series of prediction models including demographics and behavioral data), to predict chronic outcomes. Multiple linear regression was used to assess the quality of prediction of the most informative model.To determine whether long-term functional outcomes in stroke patients can be predicted by the amount of acutely damaged white matter tracts. We collected acute behavioral and neuroimaging data from a group of first-time stroke patients and add those from the other(s) databases. (n=114 + n) within one week (check with the other DBs) post-stroke. Functional outcome was telephonically evaluated using the Stroke Impact Scale 3.0 at 12 months post-stroke. For each patient, we calculated the absolute number of white matter tracts affected by the ischemic lesion from our anatomical scans. We measured a numerical index that considers white matter tract density (WMTD index). We compared the ability of the WMTD index, considered individually, or within a series of prediction models including demographics and behavioral data), to predict chronic outcome. Multiple linear regression was used to assess the quality of prediction of the most informative model

New neurophysiological and imaging methods for detection of microstructural changes in mild traumatic brain injury

Mild traumatic brain injury is a very common health problem. Although outcome is generally good, a significant proportion of patients have persistent symptoms or an incomplete functional recovery. The mechanisms of this are incompletely understood, but believed to include microstructural injuries that may be undetectable by presently used diagnostic tests. This thesis aims at exploring new diagnostic methods that could be utilised in examining mild traumatic brain injury. I study tested transcranial magnetic stimulation defined motor thresholds in a sample of chronic phase mild traumatic brain injury patients. Elevated motor thresholds were found compared to healthy controls, associated with altered excitability of the corticospinal tract. II study used transcranial magnetic stimulation combined with electroencephalography to probe responses of frontal brain regions. The employed method is reported to be sensitive to changes in excitability and connectivity of the brain. Differences were found between samples of fully recovered and persistently symptomatic patients with mild traumatic brain injury and healthy controls. On basis of this, transcranial magnetic stimulation and electroencephalography could be used to detect functional changes that are not paralleled by lesions on routine magnetic resonance imaging. III study compared diffusion tensor imaging based deterministic tractography and a newer method, based on constrained spherical deconvolution, automatic, deep learning based segmentation and probabilistic tractography. Participants were patients with symptomatic mild traumatic brain injury and healthy controls. The newer approach was able to find differences between the groups, while diffusion tensor method was not. This suggests the new approach may be more sensitive in detecting microstructural changes related to mild traumatic brain injury. These results show that mild traumatic brain injury can be associated with functional and structural changes in the absence of trauma-related findings on routine MRI. The methods evaluated may provide new ways to detect these changes.Uusia neurofysiologisia ja kuvantamismenetelmiä lievään aivovammaan liittyvien mikrorakenteellisten muutosten toteamisessa Lievä aivovamma on erittäin tavallinen. Toipuminen on yleensä hyvää, mutta osalle potilaista jää pitkäkestoisia oireita tai toimintakyvyn vajavuutta. Näiden syntymekanismia ei täysin ymmärretä, mutta ajatellaan sen voivan liittyä aivojen mikrorakenteellisiin muutoksiin, joiden toteamiseen nykyiset diagnostiset testit voivat olla riittämättömiä. Tämä väitöstutkimus selvittää uusia keinoja, joita voitaisiin hyödyntää lievän aivovamman arvioinnissa. I osatyössä tutkittiin transkraniaalisen magneettistimulaation avulla motorisia kynnyksiä. Tutkimusjoukkona oli lievän aivovamman saaneita, kroonisen vaiheen potilaita. Potilasjoukolla todettiin terveisiin verrokkeihin nähden korkeampia motorisia kynnyksiä, joka liittyy muutoksiin kortikospinaaliradan ärtyvyydessä. II osatyö hyödynsi transkraniaalista magneettistimulaatiota ja elektroenkefalografiaa frontaalisten aivoalueiden vasteiden tutkimisessa. Aiempien julkaisujen perusteella menetelmä on herkkä aivojen ärtyvyyden ja aivoalueiden välisten yhteyksien muutosten toteamisessa. Menetelmällä löydettiin eroja lievästä aivovammasta oireettomiksi toipuneista, pitkäkestoisesti oireilevista ja terveistä verrokeista koostuneiden osallistujajoukkojen välillä. Transkraniaalisen magneettistimulaation ja elektroenkefalografian yhdistelmällä saatetaan siten havaita toimin-nallisia muutoksia, joille ei ole vastinetta tavallisissa magneettikuvissa. III osatyössä verrattiin diffuusiotensorikuvantamista ja determinististä traktografiaa uudempaan menetelmään, joka perustui constrained spherical deconvolution -laskentaan, automaattiseen, syväoppimiseen perustuvaan segmentaatioon ja probabilistiseen traktografiaan. Tutkimusjoukkona oli lievän aivovamman saaneita, oireisia potilaita ja terveitä verrokkeja. Uudella menetelmällä löydettiin eroja ryhmien välillä, mutta vertailumenetelmällä eroja ei havaittu. Tällä perusteella uusi menetelmä vaikuttaa herkemmältä aivovammaan liittyvien mikrorakenteellisten muutosten toteamisessa. Tulokset osoittavat, että lievään aivovammaan voi liittyä toiminnallisia ja rakenteellisia muutoksia, vaikka tavanomaisen magneettikuvauksen löydös olisi normaali. Näiden muutosten toteaminen voi olla mahdollista arvioiduilla menetelmillä