Imaging of brain tumors: functional magnetic resonance imaging and diffusion tensor imaging

Extracellular vesicles in the breast cancer brain metastasis: physiological functions and clinical applications

Breast cancer, which exhibits an increasing incidence and high mortality rate among cancers, is predominantly attributed to metastatic malignancies. Brain metastasis, in particular, significantly contributes to the elevated mortality in breast cancer patients. Extracellular vesicles (EVs) are small lipid bilayer vesicles secreted by various cells that contain biomolecules such as nucleic acids and proteins. They deliver these bioactive molecules to recipient cells, thereby regulating signal transduction and protein expression levels. The relationship between breast cancer metastasis and EVs has been extensively investigated. In this review, we focus on the molecular mechanisms by which EVs promote brain metastasis in breast cancer. Additionally, we discuss the potential of EV-associated molecules as therapeutic targets and their relevance as early diagnostic markers for breast cancer brain metastasis.

Detection and Mitigation of Neurovascular Uncoupling in Brain Gliomas

Functional magnetic resonance imaging (fMRI) with blood oxygen level-dependent (BOLD) technique is useful for preoperative mapping of brain functional networks in tumor patients, providing reliable in vivo detection of eloquent cortex to help reduce the risk of postsurgical morbidity. BOLD task-based fMRI (tb-fMRI) is the most often used noninvasive method that can reliably map cortical networks, including those associated with sensorimotor, language, and visual functions. BOLD resting-state fMRI (rs-fMRI) is emerging as a promising ancillary tool for visualization of diverse functional networks. Although fMRI is a powerful tool that can be used as an adjunct for brain tumor surgery planning, it has some constraints that should be taken into consideration for proper clinical interpretation. BOLD fMRI interpretation may be limited by neurovascular uncoupling (NVU) induced by brain tumors. Cerebrovascular reactivity (CVR) mapping obtained using breath-hold methods is an effective method for evaluating NVU potential.

Functional MRI in Neuro-Oncology: State of the Art and Future Directions

Since its discovery in the early 1990s, functional MRI (fMRI) has been used to study human brain function. One well-established application of fMRI in the clinical setting is the neurosurgical planning of patients with brain tumors near eloquent cortical areas. Clinical fMRI aims to preoperatively identify eloquent cortices that serve essential functions in daily life, such as hand movement and language. The primary goal of neurosurgery is to maximize tumor resection while sparing eloquent cortices adjacent to the tumor. When a lesion presents in the vicinity of an eloquent cortex, surgeons may use fMRI to plan their best surgical approach by determining the proximity of the lesion to regions of activation, providing guidance for awake brain surgery and intraoperative brain mapping. The acquisition of fMRI requires patient preparation prior to imaging, determination of functional paradigms, monitoring of patient performance, and both processing and analysis of images. Interpretation of fMRI maps requires a strong understanding of functional neuroanatomy and familiarity with the technical limitations frequently present in brain tumor imaging, including neurovascular uncoupling, patient compliance, and data analysis. This review discusses clinical fMRI in neuro-oncology, relevant ongoing research topics, and prospective future developments in this exciting discipline.

Power spectral analysis can determine language laterality from resting-state functional MRI data in healthy controls

BACKGROUND AND PURPOSE

Resting-state functional magnetic resonance imaging (rsfMRI) has been proposed as an alternative to task-based fMRI including clinical situations such as preoperative brain tumor planning, due to advantages including ease of performance and time savings. However, one of its drawbacks is the limited ability to accurately lateralize language function.

METHODS

Using the rsfMRI data of healthy controls, we carried out a power spectra analysis on three regions of interest (ROIs): Broca's area (BA) in the frontal cortex for language, hand motor (HM) area in the primary motor cortex, and the primary visual cortex (V1). Spike removal, motion correction, linear trend removal, and spatial smoothing were applied. Spontaneous low-frequency fluctuations (0.01-0.1 Hz) were filtered to enable functional integration.

RESULTS

BA showed greater power on the left hemisphere relative to the right (p = .0055), while HM (p = .1563) and V1 (p = .4681) were not statistically significant. A novel index, termed the power laterality index (PLI), computed to estimate the degree of power lateralization for each brain region, revealed a statistically significant difference between BA and V1 (p < .00001), where V1 was used as a control since the primary visual cortex does not lateralize. Validation studies used to compare PLI to a laterality index computed using phonemic fluency, a task-based, language fMRI paradigm, demonstrated good correlation.

CONCLUSIONS

The power spectra for BA revealed left language lateralization, which was not replicated in HM or V1. This work demonstrates the feasibility and validity of an ROI-based power spectra analysis on rsfMRI data for language lateralization.

Small extracellular vesicles in breast cancer brain metastasis and the prospect of clinical application

Extracellular vesicles (EVs) are nanoscale extracellular particles that have received widespread scientific attention for carrying a variety of biomolecules such as nucleic acids and proteins and participating in the process of intercellular information exchange, making them become a research hotspot due to their potential diagnostic value. Breast cancer is the leading cause of cancer-related death in women, approximately 90% of patient deaths are due to metastasis complications. Brain metastasis is an important cause of mortality in breast cancer patients, about 10-15% of breast cancer patients will develop brain metastasis. Therefore, early prevention of brain metastasis and the development of new treatments are crucial. Small EVs have been discovered to be involved in the entire process of breast cancer brain metastasis (BCBM), playing an important role in driving organ-specific metastasis, forming pre-metastatic niches, disrupting the blood-brain barrier, and promoting metastatic tumor cell proliferation. We summarize the mechanisms of small EVs in the aforementioned pathological processes at the cellular and molecular levels, and anticipate their potential applications in the treatment of breast cancer brain metastasis, with the hope of providing new ideas for the precise treatment of breast cancer brain metastasis.

Intracranial hemorrhages associated with meningiomas: Own experience and literature review

Intracranial hemorrhage associated with meningioma is rare. Relatively, few such cases are described in the source literature, and it is estimated that intracranial meningiomas presenting with hemorrhage account for about one percent of all meningiomas. Hemorrhage can occur in both meningioma tissue and on the tumor surface. It can lead to intracerebral, subdural and subarachnoid hematoma. This can in turn cause high intracranial pressure with rapid neurological deterioration. Urgent neurosurgical intervention is often necessary. In our department, three patients with meningioma-related hemorrhage were treated surgically from 2006 to 2020. One patient was operated on as an emergency, due to the patient's poor neurological condition, while the two others underwent surgery following supplementary diagnosis several days following their admission. The outcomes of the three patients were good. The three meningiomas associated with hemorrhage described in the present manuscript constitute 2.2% of all 136 meningiomas treated surgically from 2006 to 2020 at our department. All three hemorrhages described in this study were associated with WHO I convexity meningiomas. Similar data can be found in some sources also describing meningioma WHO I-related hemorrhages; nevertheless, other literature references indicate a higher risk of bleeding into meningiomas of a higher degree of malignancy. The hemorrhage mechanism remains unclear; however, the proposed mechanism is rupture of defective intratumoral blood vessels and stretching of the superficial veins including bridge veins by the growing tumor, leading to their rupture. Our observations regarding the incidence of meningioma hemorrhage and tumor location are consistent with the source literature data.

Understanding Language Reorganization With Neuroimaging: How Language Adapts to Different Focal Lesions and Insights Into Clinical Applications

When the language-dominant hemisphere is damaged by a focal lesion, the brain may reorganize the language network through functional and structural changes known as adaptive plasticity. Adaptive plasticity is documented for triggers including ischemic, tumoral, and epileptic focal lesions, with effects in clinical practice. Many questions remain regarding language plasticity. Different lesions may induce different patterns of reorganization depending on pathologic features, location in the brain, and timing of onset. Neuroimaging provides insights into language plasticity due to its non-invasiveness, ability to image the whole brain, and large-scale implementation. This review provides an overview of language plasticity on MRI with insights for patient care. First, we describe the structural and functional language network as depicted by neuroimaging. Second, we explore language reorganization triggered by stroke, brain tumors, and epileptic lesions and analyze applications in clinical diagnosis and treatment planning. By comparing different focal lesions, we investigate determinants of language plasticity including lesion location and timing of onset, longitudinal evolution of reorganization, and the relationship between structural and functional changes.

Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities

Differentiating between glioblastomas and solitary brain metastases proves to be a challenging diagnosis for neuroradiologists, as both present with imaging patterns consisting of peritumoral hyperintensities with similar intratumoral texture on traditional magnetic resonance imaging sequences. Early diagnosis is paramount, as each pathology has completely different methods of clinical assessment. In the past decade, recent developments in advanced imaging modalities enabled providers to acquire a more accurate diagnosis earlier in the patient's clinical assessment, thus optimizing clinical outcome. Dynamic susceptibility contrast has been optimized for detecting relative cerebral blood flow and relative cerebral blood volume. Diffusion tensor imaging can be used to detect changes in mean diffusivity. Neurite orientation dispersion and density imaging is an innovative modality detecting changes in intracellular volume fraction, isotropic volume fraction, and extracellular volume fraction. Magnetic resonance spectroscopy is able to assist by providing a metabolic descriptor while detecting variable ratios of choline/N-acetylaspartate, choline/creatine, and N-acetylaspartate/creatine. Finally, radiomics and machine learning algorithms have been devised to assist in improving diagnostic accuracy while often utilizing more than one advanced imaging protocol per patient. In this review, we provide an update on all the current evidence regarding the identification and differentiation of glioblastomas from solitary brain metastases.

Role of Functional Magnetic Resonance Imaging in the Presurgical Mapping of Brain Tumors

When planning for brain tumor resection, a balance between maximizing resection and minimizing injury to eloquent brain parenchyma is paramount. The advent of blood oxygenation level-dependent functional magnetic resonance (fMR) imaging has allowed researchers and clinicians to reliably measure physiologic fluctuations in brain oxygenation related to neuronal activity with good spatial resolution. fMR imaging can offer a unique insight into preoperative planning for brain tumors by identifying eloquent areas of the brain affected or spared by the neoplasm. This article discusses the fMR imaging techniques and their applications in neurosurgical planning.

Diffusion Tensor Imaging Color-Coded Maps: An Alternative to Tractography

INTRODUCTION

White matter tracts can be observed using tractograms generated from diffusion tensor imaging (DTI). However, the dependence of these white matter tract images on subjective variables, including how seed points are placed and the preferred level of fractional anisotropy, introduces interobserver inconsistency and potential lack of reliability. We propose that color-coded maps (CCM) generated from DTI can be a preferred method for the visualization of important white matter tracts, circumventing bias in preoperative brain tumor resection planning.

METHODS

DTI was acquired retrospectively in 25 patients with brain tumors. Lesions included 15 tumors of glial origin, 9 metastatic tumors, 2 meningiomas, and 1 cavernous angioma. Tractograms of the pyramidal tract and/or optic radiations, based on tumor location, were created by marking seed regions of interest using known anatomical locations. We compared the degree of tract involvement and white matter alteration between CCMs and tractograms. Neurological outcomes were obtained from chart reviews.

RESULTS

The pyramidal tract was evaluated in 20/25 patients, the visual tracts were evaluated in 10/25, and both tracts were evaluated in 5/25. In 19/25 studies, the same patterns of white matter alternations were found between the CCMs and tractograms. In the 6 patients where patterns differed, 2 tractograms were not useful in determining pattern alteration; in the remaining 4/6, no practical difference was seen in comparing the studies. Two patients were lost to follow-up. Thirteen patients were neurologically improved or remained intact after intervention. In these, 10 of the 13 patients showed tumor-induced white matter tract displacement on CCM. Twelve patients had no improvement of their preoperative deficit. In 9 of these 12 patients, CCM showed white matter disruption.

CONCLUSION

CCMs provide a convenient, practical, and objective method of visualizing white matter tracts, obviating the need for potentially subjective and time-consuming tractography. CCMs are at least as reliable as tractograms in predicting neurological outcomes after neurosurgical intervention.

Functional Brain Anatomy

Knowledge of functional neuroanatomy is essential to design the most appropriate clinical functional MR imaging (fMR imaging) paradigms and to properly interpret fMR imaging study results. The correlation between neuroanatomy and brain function is also useful in general radiologic practice, as it improves the radiologist's ability to read routine brain examinations. Functional MR imaging is used primarily to determine the areas involved in functioning of movements, speech, and vision. Preoperative fMR imaging findings also play a key role in the neurosurgeon's decision to perform a biopsy, a subtotal resection, or a maximal resection using awake craniotomy.

Patient Preparation and Paradigm Design in fMRI

Functional magnetic resonance imaging (fMRI) is useful for localizing eloquent cortex in the brain prior to neurosurgery. Language and motor paradigms offer a wide range of tasks to test brain regions within the language and motor networks. With the help of fMRI, hemispheric language dominance can be determined. It also is possible to localize specific motor and sensory areas within the motor and sensory gyri. These findings are critical for presurgical planning. The most important factor in presurgical fMRI is patient performance. Patient interview and instruction time are crucial to ensure that patients understand and comply with the fMRI paradigm.

Methods of Analysis: Functional MRI for Presurgical Planning

There are many technical and nontechnical steps involved in a successful clinical functional MRI (fMRI) scan. The output from scanning and analysis can only be as good as the input, so task instruction and rehearsal are the most important steps during an clinical fMRI procedure. Properly pre-processed data significantly affects statistical analysis, which has a great impact on image interpretation. Even though there is general agreement on how to process clinical fMRI data, such as algorithms for head motion detection and correction, the theory and practicalities associated with data processing remain complex and constantly evolving.

The Problem of Neurovascular Uncoupling

Neurovascular uncoupling (NVU) is one of the most important confounds of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMR imaging) in the setting of focal brain lesions such as brain tumors. This article reviews the assessment of NVU related to focal brain lesions with emphasis on the use of cerebrovascular reactivity mapping measurement methods and resting state BOLD fMR imaging metrics in the detection of NVU, as well as the use of amplitude of low-frequency fluctuation metrics to mitigate the effects of NVU on clinical fMR imaging activation.

Introduction to Functional MR Imaging

During the past decade, functional MR imaging has rapidly moved from the research environment into clinical practice. Preoperative functional MR imaging is now standard clinical practice not only in major academic institutions, but also in community neurosurgical and neuroradiologic practices. The clinical use of functional MR imaging will only increase in the years to come. Application of functional MR imaging (including resting-state functional MR imaging) to the context of neuropsychiatric diseases is likely to continue to advance.

Comparisons among MRI signs, apparent diffusion coefficient, and fractional anisotropy in dogs with a solitary intracranial meningioma or histiocytic sarcoma

Although MRI has become widely used in small animal practice, little is known about the validity of advanced MRI techniques such as diffusion-weighted imaging and diffusion tensor imaging. The aim of this retrospective analytical observational study was to investigate the characteristics of diffusion parameters, that is the apparent diffusion coefficient and fractional anisotropy, in dogs with a solitary intracranial meningioma or histiocytic sarcoma. Dogs were included based on the performance of diffusion MRI and histological confirmation. Statistical analyses were performed to compare apparent diffusion coefficient and fractional anisotropy for the two types of tumor in the intra- and peritumoral regions. Eleven cases with meningioma and six with histiocytic sarcoma satisfied the inclusion criteria. Significant differences in apparent diffusion coefficient value (× 10^-3 mm² /s) between meningioma vs. histiocytic sarcoma were recognized in intratumoral small (1.07 vs. 0.76) and large (1.04 vs. 0.77) regions of interest, in the peritumoral margin (0.93 vs. 1.08), and in the T2 high region (1.21 vs. 1.41). Significant differences in fractional anisotropy values were found in the peritumoral margin (0.29 vs. 0.24) and the T2 high region (0.24 vs. 0.17). The current study identified differences in measurements of apparent diffusion coefficient and fractional anisotropy for meningioma and histiocytic sarcoma in a small sample of dogs. In addition, we observed that all cases of intracranial histiocytic sarcoma showed leptomeningeal enhancement and/or mass formation invading into the sulci in the contrast study. Future studies are needed to determine the sensitivity of these imaging characteristics for differentiating between these tumor types.

Thermal injury to corticospinal tracts and postoperative motor deficits after laser interstitial thermal therapy

OBJECTIVE Laser interstitial thermal therapy (LITT) has been increasingly used to treat deep-seated tumors. Despite its being minimally invasive, there is a risk of LITT damaging adjacent critical structures, including corticospinal tracts (CSTs). In this study, the authors investigated the predictive value of overlap between the hyperthermic field and CSTs in determining postoperative motor deficit (PMDs). METHODS More than 140 patients underwent an LITT procedure in our institution between April 2011 and June 2015. Because of the tumor's proximity to critical structures, 80 of them underwent preoperative diffusion tensor imaging and were included in this study. Extent of the hyperthermic field was delineated by the software as thermal-damage-threshold (TDT) lines (yellow [43°C for 2 minutes], blue [43°C for 10 minutes], and white [43°C for 60 minutes]). The maximum volume and the surface area of overlaps between motor fibers and the TDT lines were calculated and compared with the PMDs. RESULTS High-grade glioma (n = 46) was the most common indication for LITT. Postoperative motor deficits (partial or complete) were seen in 14 patients (11 with permanent and 3 with temporary PMDs). The median overlap volumes between CSTs with yellow, blue, and white TDT lines in patients with any PMD (temporary or permanent) were 1.15, 0.68, and 0.41 cm³, respectively. The overlap volumes and surface areas revealed significant differences in those with PMDs and those with no deficits (p = 0.0019 and 0.003, 0.012 and 0.0012, and 0.001 and 0.005 for the yellow, blue, and white TDT lines, respectively). The receiver operating characteristic was used to select the optimal cutoff point of the overlapped volumes and areas. Cutoff points for overlap volumes and areas based on optimal sensitivity (92%-100%) and specificity (80%-90%) were 0.103, 0.068, and 0.046 cm³ and 0.15, 0.07, and 0.11 mm² for the yellow, blue, and white TDT lines, respectively. CONCLUSIONS Even a minimal overlap between the TDT lines and CSTs can cause a PMD after LITT. Precise planning and avoidance of critical structures and important white matter fibers should be considered when treating deep-seated tumors.

The utility of diffusion MRI with quantitative ADC measurements for differentiating high-grade from low-grade cerebral gliomas: Evidence from a meta-analysis

OBJECTIVE

The aim of this meta-analysis was to predict the grades of cerebral gliomas using quantitative apparent diffusion coefficient (ADC) values.

MATERIALS AND METHODS

A comprehensive search of the PubMed, EMBASE, Web of Science, and Cochrane Library databases was performed up to 8, 2016. The quality assessment of diagnostic accuracy studies (QUADAS 2) was used to evaluate the quality of studies. Statistical analyses included pooling of sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ratio' (NLR), diagnostic odds ratio (DOR), and diagnostic accuracy values of the included studies using the summary receiver operating characteristic (SROC). All analyses were conducted using STATA (version 12.0), RevMan (version 5.3), and Meta-Disc 1.4 software programs.

RESULTS

Fifteen studies were analyzed and included a total of 821 patients and 821 lesions. In regards to the diagnostic accuracy of ADC maps, the pooled SEN, SPE, PLR, NLR, and DOR with 95%CIs were 0.82 [95%CI: 0.76, 0.87] and 0.75 [95%CI: 0.67, 0.81], 3.24 [95%CI: 2.48, 4.24], 0.24 [95%CI: 0.17, 0.33], and 13.60 [95%CI: 8.37, 22.07], respectively. The SROC curve showed an AUC of 0.85. Deeks testing confirmed no significant publication bias in all studies.

CONCLUSION

Our findings indicate that quantitative ADC values have high accuracy in separating high-grade from low-grade cerebral gliomas. Further studies using a standardized methodology may help guide the use of ADC values for clinical decision-making.

Functional Imaging in Radiotherapy in the Netherlands: Availability and Impact on Clinical Practice

AIMS

Functional imaging with positron emission tomography/computed tomography (PET/CT) and multiparametric magnetic resonance (mpMR) is increasingly applied for radiotherapy purposes. However, evidence and experience are still limited, and this may lead to clinically relevant differences in accessibility, interpretation and decision making. We investigated the current patterns of care in functional imaging for radiotherapy in the Netherlands in a care evaluation study.

MATERIALS AND METHODS

The availability of functional imaging in radiotherapy centres in the Netherlands was evaluated; features available in >80% of academic and >80% of non-academic centres were considered standard of care. The impact of functional imaging on clinical decision making was evaluated using case questionnaires on lung, head/neck, breast and prostate cancer, with multiple-choice questions on primary tumour delineation, nodal involvement, distant metastasis and incidental findings. Radiation oncologists were allowed to discuss cases in a multidisciplinary approach. Ordinal answers were evaluated by median and interquartile range (IQR) to identify the extent and variability of clinical impact; additional patterns were evaluated descriptively.

RESULTS

Information was collected from 18 radiotherapy centres in the Netherlands (all except two). PET/CT was available for radiotherapy purposes to 94% of centres; 67% in the treatment position and 61% with integrated planning CT. mpMR was available to all centres; 61% in the treatment position. Technologists collaborated between departments to acquire PET/CT or mpMR for radiotherapy in 89%. All sites could carry out image registration for target definition. Functional imaging generally showed a high clinical impact (average median 4.3, scale 1-6) and good observer agreement (average IQR 1.1, scale 0-6). However, several issues resulted in ignoring functional imaging (e.g. positional discrepancies, central necrosis) or poor observer agreement (atelectasis, diagnostic discrepancies, conformation strategies).

CONCLUSIONS

Access to functional imaging with PET/CT and mpMR for radiotherapy purposes, with collaborating technologists and multimodal delineation, can be considered standard of care in the Netherlands. For several specific clinical situations, the interpretation of images may benefit from further standardisation.

Assessment of diffusion tensor imaging metrics in differentiating low-grade from high-grade gliomas

AIM

The aim of this article is to assess diffusion tensor imaging (DTI) metrics in differentiating low-grade from high-grade gliomas.

PATIENTS AND METHODS

A prospective study was conducted on 35 patients with gliomas who underwent DTI. Gliomas were classified into low-grade and high-grade gliomas. The fractional anisotropy (FA), mean diffusivity (MD), linear coefficient (CL), planar coefficient (CP) and spherical coefficient (CS) of the solid tumoral part and peri-tumoral regions were calculated.

RESULTS

There was significant difference (p = 0.001) in MD of the solid tumoral part of low-grade (1.78 ± 0.33 × 10(-3 )mm(2)/s) and high-grade (1.16 ± 0.22 × 10(-3 )mm(2)/s) gliomas. The selection of 1.42 × 10(-3 )mm(2)/s as a cutoff value of MD of the tumoral part was used to differentiate low-grade and high-grade gliomas; the best results were obtained with area under the curve (AUC) of 0.957 and accuracy of 91.4%. There was a significant difference in FA, MD, CP and CS of peri-tumoral regions of both groups with p values of 0.006, 0.042, 0.030 and 0.037, respectively. The cutoff values of MD, FA, CS and CP of the peri-tumoral region used to differentiate low-grade from high-grade gliomas were 1.24, 0.315, 0.726 and 0.321 with AUC of 0.694, 0.773, 0.734 and 0.724 and accuracy of 68.6%, 80.0%, 74.3% and 74.3%, respectively. The combined MD of the solid tumoral part and FA of the peri-tumoral region used to differentiate low-grade from high-grade gliomas revealed AUC of 0.974 and accuracy of 88.6%.

CONCLUSION

We conclude that the combination of MD of the solid tumoral part and FA of the peri-tumoral region is a noninvasive method to differentiate low-grade from high-grade gliomas.

Differentiation of high-grade-astrocytomas from solitary-brain-metastases: Comparing diffusion kurtosis imaging and diffusion tensor imaging

OBJECTIVE

To compare the value of MRI diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in differentiating high-grade-astrocytomas from solitary-brain-metastases.

METHODS

Thirty-one high-grade-astrocytomas and twenty solitary-brain-metastases were retrospectively identified. DKI parameters [mean kurtosis (MK), radial kurtosis (Kr), and axial kurtosis (Ka)] and DTI parameters [fractional anisotropy (FA) and mean diffusivity (MD)] values with and without correction by contralateral normal-appearing white matter (NAWM) in the tumoral solid part and peritumoral edema, were compared using the t-test. Receiver operating characteristic (ROC) curves were used to test for the best parameters.

RESULTS

The DKI values (MK, Kr, and Ka) and DTI values (FA and MD) in tumoral solid parts did not show significant differences between the two groups. Corrected and uncorrected MK, Kr, and Ka values in peritumoral edema were significantly higher in high-grade-astrocytomas than solitary-brain-metastases, and MD values without correction were lower in high-grade astrocytomas than solitary-brain-metastases. The areas under curve (AUC) of corrected Ka (1.000), MK (0.889), and Kr (0.880) values were significantly higher than those of MD (0.793) and FA (0.472) values. The optimal thresholds for corrected MK, Kr, Ka, and MD were 0.369, 0.405, 0.483, and 2.067, respectively.

CONCLUSION

DKI and directional analysis could lead to improved differentiation with better sensitivity and directional specificity than DTI.

Neuromorphometry of primary brain tumors by magnetic resonance imaging

Magnetic resonance imaging is a technique for the diagnosis and classification of brain tumors. Discrete compactness is a morphological feature of two-dimensional and three-dimensional objects. This measure determines the compactness of a discretized object depending on the sum of the areas of the connected voxels and has been used for understanding the morphology of nonbrain tumors. We hypothesized that regarding brain tumors, we may improve the malignancy grade classification. We analyzed the values in 20 patients with different subtypes of primary brain tumors: astrocytoma, oligodendroglioma, and glioblastoma multiforme subdivided into the contrast-enhanced and the necrotic tumor regions. The preliminary results show an inverse relationship between the compactness value and the malignancy grade of gliomas. Astrocytomas exhibit a mean of [Formula: see text], whereas oligodendrogliomas exhibit a mean of [Formula: see text]. In contrast, the contrast-enhanced region of the glioblastoma presented a mean of [Formula: see text], and the necrotic region presented a mean of [Formula: see text]. However, the volume and area of the enclosing surface did not show a relationship with the malignancy grade of the gliomas. Discrete compactness appears to be a stable characteristic between primary brain tumors of different malignancy grades, because similar values were obtained from different patients with the same type of tumor.

White matter tracts of speech and language

Diffusion tensor imaging (DTI) has been used to investigate the white matter (WM) tracts underlying the perisylvian cortical regions known to be associated with language function. The arcuate fasciculus is composed of 3 segments (1 long and 2 short) whose separate functions correlate with traditional models of conductive and transcortical motor or sensory aphasia, respectively. DTI mapping of language fibers is useful in presurgical planning for patients with dominant hemisphere tumors, particularly when combined with functional magnetic resonance imaging. DTI has found damage to language networks in stroke patients and has the potential to influence poststroke rehabilitation and treatment. Assessment of the WM tracts involved in the default mode network has been found to correlate with mild cognitive impairment, potentially explaining language deficits in patients with apparently mild small vessel ischemic disease. Different patterns of involvement of language-related WM structures appear to correlate with different clinical subtypes of primary progressive aphasias.

The role of diffusion and perfusion weighted imaging in the differential diagnosis of cerebral tumors: a review and future perspectives

The role of conventional Magnetic Resonance Imaging (MRI) in the detection of cerebral tumors has been well established. However its excellent soft tissue visualization and variety of imaging sequences are in many cases non-specific for the assessment of brain tumor grading. Hence, advanced MRI techniques, like Diffusion-Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI) and Dynamic-Susceptibility Contrast Imaging (DSCI), which are based on different contrast principles, have been used in the clinical routine to improve diagnostic accuracy. The variety of quantitative information derived from these techniques provides significant structural and functional information in a cellular level, highlighting aspects of the underlying brain pathophysiology. The present work, reviews physical principles and recent results obtained using DWI/DTI and DSCI, in tumor characterization and grading of the most common cerebral neoplasms, and discusses how the available MR quantitative data can be utilized through advanced methods of analysis, in order to optimize clinical decision making.

Use of diffusion tensor imaging in glioma resection

Diffusion tensor imaging (DTI) is increasingly used in the resection of both high- and low-grade gliomas. Whereas conventional MRI techniques provide only anatomical information, DTI offers data on CNS connectivity by enabling visualization of important white matter tracts in the brain. Importantly, DTI allows neurosurgeons to better guide their surgical approach and resection. Here, the authors review basic scientific principles of DTI, include a primer on the technology and image acquisition, and outline the modality's evolution as a frequently used tool for glioma resection. Current literature supporting its use is summarized, highlighting important clinical studies on the application of DTI in preoperative planning for glioma resection, preoperative diagnosis, and postoperative outcomes. The authors conclude with a review of future directions for this technology.

Analysis of diffusion tensor imaging metrics for gliomas grading at 3 T

OBJECTIVES

To assess the diagnostic accuracy of axial diffusivity (AD), radial diffusivity (RD), apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values derived from DTI for grading of glial tumors, and to estimate the correlation between DTI parameters and tumor grades.

METHODS

Seventy-eight patients with glial tumors underwent DTI. AD, RD, ADC and FA values of tumor, peritumoral edema and contralateral normal-appearing white matter (NAWM) and AD, RD, ADC and FA ratios: lowest average AD, RD, ADC and FA values in tumor or peritumoral edema to AD, RD, ADC and FA of NAWM were calculated. DTI parameters and tumor grades were analyzed statistically and with Pearson correlation. Receiver operating characteristic (ROC) curve analysis was also performed.

RESULTS

The differences in ADC, AD and RD tumor values, and ADC and RD tumor ratios were statistically significant between grades II and III, grades II and IV, and between grades II and III-IV. The AD tumor ratio differed significantly among all tumor grades. Tumor ADC, AD, RD and glial tumor grades were strongly correlated. In the ROC curve analysis, the area under the curve (AUC) of the parameter tumor ADC was the largest for distinguishing grade II from grades III to IV (98.5%), grade II from grade IV (98.9%) and grade II from grade III (97.0%).

CONCLUSION

ADC, RD and AD are useful DTI parameters for differentiation between low- and high-grade gliomas with a diagnostic accuracy of more than 90%. Our study revealed a good inverse correlation between ADC, RD, AD and WHO grades II-IV astrocytic tumors.

Probabilistic fiber tracking of the language and motor white matter pathways of the supplementary motor area (SMA) in patients with brain tumors

BACKGROUND AND PURPOSE

Accurate localization of anatomically and functionally separate SMA tracts is important to improve planning prior to neurosurgery. Using fMRI and probabilistic DTI techniques, we assessed the connectivity between the frontal language area (Broca's area) and the rostral pre-SMA (language SMA) and caudal SMA proper (motor SMA).

MATERIALS AND METHODS

Twenty brain tumor patients completed motor and language fMRI paradigms and DTI. Peaks of functional activity in the language SMA, motor SMA and Broca's area were used to define seed regions for probabilistic tractography.

RESULTS

fMRI and probabilistic tractography identified separate and unique pathways connecting the SMA to Broca's area - the language SMA pathway and the motor SMA pathway. For all subjects, the language SMA pathway had a larger number of voxels (P<0.0001) and higher connectivity (P<0.0001) to Broca's area than did the motor SMA pathway. In each patient, the number of voxels was greater in the language and motor SMA pathways than in background pathways (P<0.0001). No differences were found between patients with ipsilateral and those with contralateral tumors for either the language SMA pathway (degree of connectivity: P<0.36; number of voxels: 0.35) or the motor SMA pathway (degree of connectivity, P<0.28; number of voxels, P<0.74).

CONCLUSION

Probabilistic tractography can identify unique white matter tracts that connect language SMA and motor SMA to Broca's area. The language SMA is more significantly connected to Broca's area than is the motor subdivision of the SMA proper.

Intracranial metastases: spectrum of MR imaging findings

Intracranial metastatic lesions arise through a number of routes. Therefore, they can involve any part of the central nervous system and their imaging appearances vary. Magnetic resonance imaging (MRI) plays a key role in lesion detection, lesion delineation, and differentiation of metastases from other intracranial disease processes. This article is a reasoned pictorial review illustrating the many faces of intracranial metastatic lesions based on the location - intra-axial metastases, calvarial metastases, dural metastases, leptomeningeal metastases, secondary invasion of the meninges by metastatic disease involving the calvarium and skull base, direct or perineural intracranial extension of head and neck neoplasm, and other unusual manifestations of intracranial metastases. We also review the role of advanced MRI to distinguish metastases from high-grade gliomas, tumor-mimicking lesions such as brain abscesses, and delayed post-radiation changes in radiosurgically treated patients.

Cardiac magnetic resonance T2 mapping in the monitoring and follow-up of acute cardiac transplant rejection: a pilot study

BACKGROUND

Acute rejection is a major factor impacting survival in the first 12 months after cardiac transplantation. Transplant monitoring requires invasive techniques. Cardiac magnetic resonance (CMR), noninvasive testing, has been used in monitoring heart transplants. Prolonged T2 relaxation has been related to transplant edema and possibly rejection. We hypothesize that prolonged T2 reflects transplant rejection and that quantitative T2 mapping will concur with the pathological and clinical findings of acute rejection.

METHODS AND RESULTS

Patients were recruited within the first year after transplantation. Biopsies were graded according to the International Society for Heart Lung Transplant system for cellular rejection with immunohistochemistry for humoral rejection. Rejection was also considered if patients presented with signs and symptoms of hemodynamic compromise without biopsy evidence of rejection who subsequently improved with treatment. Patients underwent a novel single-shot T2-prepared steady-state free precession 4-chamber and 3 short axis sequences and regions of interest were drawn overlying T2 maps by 2 independent blinded reviewers. A total of 74 (68 analyzable) CMRs T2 maps in 53 patients were performed. There were 4 cellular, 2 humoral, and 2 hemodynamic rejection cases. The average T2 relaxation time for grade 0R (n=46) and grade 1R (n=17) was 52.5±2.2 and 53.1±3.3 ms (mean±SD), respectively. The average T2 relaxation for grade 2R (n=3) was 59.6±3.1 ms and 3R (n=1) was 60.3 ms (all P value <0.05 compared with controls). The T2 average in humoral rejection cases (n=2) was 59.2±3.3 ms and the hemodynamic rejection (n=2) was 61.1±1.8 ms (P<0.05 versus controls). The average T2 relaxation time for all-cause rejection versus no rejection is 60.1±2.1 versus 52.8±2.7 ms (P<0.05). All rejection cases were rescanned 2.5 months after treatment and demonstrated T2 normalization with average of 51.4±1.6 ms. No difference was found in ventricular function between nonrejection and rejection patients, except in ventricular mass 107.8±10.3 versus 127.5±10.4 g (P < 0.05).

CONCLUSIONS

Quantitative T2 mapping offers a novel noninvasive tool for transplant monitoring, and these initial findings suggest potential use in characterizing rejections. Given the limited numbers, a larger multi-institution study may help elucidate the benefits of T2 mapping as an adjunctive tool in routine monitoring of cardiac transplants.

Low-grade gliomas: when and how to treat

Low-grade gliomas are uncommon tumors whose optimal management remains to be determined. Although well-designed clinical trials have been mounted to address certain aspects of postoperative radiotherapeutic management, additional studies are required to refine management based on tumor-specific and patient-specific variables. There is mounting evidence that the relative completeness of surgical resection can improve survival, and the molecular and histopathologic characterization of the glioma requires adequate samples for analysis. Current imaging and operative techniques can direct surgical resection, and the same imaging techniques can help monitor patients postoperatively and predict prognosis.

Targeted imaging and therapy of brain cancer using theranostic nanoparticles

The past decade has seen momentous development in brain cancer research in terms of novel imaging-assisted surgeries, molecularly targeted drug-based treatment regimens or adjuvant therapies and in our understanding of molecular footprints of initiation and progression of malignancy. However, mortality due to brain cancer has essentially remained unchanged in the last three decades. Thus, paradigm-changing diagnostic and therapeutic reagents are urgently needed. Nanotheranostic platforms are powerful tools for imaging and treatment of cancer. Multifunctionality of these nanovehicles offers a number of advantages over conventional agents. These include targeting to a diseased site thereby minimizing systemic toxicity, the ability to solubilize hydrophobic or labile drugs leading to improved pharmacokinetics and their potential to image, treat and predict therapeutic response. In this article, we will discuss the application of newer theranostic nanoparticles in targeted brain cancer imaging and treatment.