Prognostic value of perfusion-weighted imaging in brain glioma: a prospective study

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

Perfusion-Weighted Imaging: The Use of a Novel Perfusion Scoring Criteria to Improve the Assessment of Brain Tumor Recurrence versus Treatment Effects

INTRODUCTION

Imaging surveillance of contrast-enhancing lesions after the treatment of malignant brain tumors with radiation is plagued by an inability to reliably distinguish between tumor recurrence and treatment effects. Magnetic resonance perfusion-weighted imaging (PWI)-among other advanced brain tumor imaging modalities-is a useful adjunctive tool for distinguishing between these two entities but can be clinically unreliable, leading to the need for tissue sampling to confirm diagnosis. This may be partially because clinical PWI interpretation is non-standardized and no grading criteria are used for assessment, leading to interpretation discrepancies. This variance in the interpretation of PWI and its subsequent effect on the predictive value has not been studied. Our objective is to propose structured perfusion scoring criteria and determine their effect on the clinical value of PWI.

METHODS

Patients treated at a single institution between 2012 and 2022 who had prior irradiated malignant brain tumors and subsequent progression of contrast-enhancing lesions determined by PWI were retrospectively studied from CTORE (CNS Tumor Outcomes Registry at Emory). PWI was given two separate qualitative scores (high, intermediate, or low perfusion). The first (control) was assigned by a neuroradiologist in the radiology report in the course of interpretation with no additional instruction. The second (experimental) was assigned by a neuroradiologist with additional experience in brain tumor interpretation using a novel perfusion scoring rubric. The perfusion assessments were divided into three categories, each directly corresponding to the pathology-reported classification of residual tumor content. The interpretation accuracy in predicting the true tumor percentage, our primary outcome, was assessed through Chi-squared analysis, and inter-rater reliability was assessed using Cohen's Kappa.

RESULTS

Our 55-patient cohort had a mean age of 53.5 ± 12.2 years. The percentage agreement between the two scores was 57.4% (κ: 0.271). Upon conducting the Chi-squared analysis, we found an association with the experimental group reads (p-value: 0.014) but no association with the control group reads (p-value: 0.734) in predicting tumor recurrence versus treatment effects.

CONCLUSIONS

With our study, we showed that having an objective perfusion scoring rubric aids in improved PWI interpretation. Although PWI is a powerful tool for CNS lesion diagnosis, methodological radiology evaluation greatly improves the accurate assessment and characterization of tumor recurrence versus treatment effects by all neuroradiologists. Further work should focus on standardizing and validating scoring rubrics for PWI evaluation in tumor patients to improve diagnostic accuracy.

Dual-layer detector spectral CT-a new supplementary method for preoperative evaluation of glioma

PURPOSE

To investigate the value of the iodine concentration (IC) measured by dual-layer detector spectral CT (DLDSCT) in evaluating the factors related to the treatment scheme and survival prognosis of patients with glioma.

METHODS

From 2018 to 2019, we prospectively collected the data of 99 patients with glioma. The degree of CT enhancement and the IC of low grade gliomas (LGGs, II), high grade gliomas (HGGs, III and IV), grade II and III gliomas, were compared. The predictive performance of the degree of CT enhancement and IC was examined via receiver operating characteristic (ROC) analysis. The correlations between IC and Ki-67 labeling index, isocitrate dehydrogenase (IDH) mutation, chromosome 1p/19q deletion status of the tumor were examined.

RESULTS

Both IC and the degree of CT enhancement of patients with HGG were significantly higher than those of patients with LGG (p < 0.001; χ² =41.707, p <  0.001); IC had large area under the ROC curve for diagnostic HGG (0.931; 95 % CI: 0.882-0.979; p <  0.001). The IC in the grade III gliomas was significantly higher than that in grade II gliomas (p < 0.001); IC had a large area under the ROC curve for diagnostic grade III gliomas (0.865; 95 % CI: 0.779-0.952; p <  0.001). There was a significant positive correlation between IC and Ki-67 LI (r = 0.679; p < 0.001).

CONCLUSIONS

The DLDSCT technology can be used as a supplementary method to provide more information for preoperative grading of the gliomas and the prognosis assessment of the patients.

The Practical Application of Emerging Technologies Influencing the Diagnosis and Care of Patients With Primary Brain Tumors

Over the past decade, a variety of new and innovative technologies has led to important advances in the diagnosis and management of patients with primary malignant brain tumors. New approaches to surgical navigation and tumor localization, advanced imaging to define tumor biology and treatment response, and the widespread adoption of a molecularly defined integrated diagnostic paradigm that complements traditional histopathologic diagnosis continue to impact the day-to-day care of these patients. In the neuro-oncology clinic, discussions with patients about the role of tumor treating fields (TTFields) and the incorporation of next-generation sequencing (NGS) data into therapeutic decision-making are now a standard practice. This article summarizes newer applications of technology influencing the pathologic, neuroimaging, neurosurgical, and medical management of patients with malignant primary brain tumors.

The biological and clinical basis for early referral of low grade glioma patients to a surgical neuro-oncologist

The discovery of IDH1/2 (isocitrate dehydrogenase) mutation in large scale, genomewide mutational analyses of gliomas has led to profound developments in understanding tumourigenesis, and restructuring of the classification of both high and low grade gliomas. Owing to this progress made in the recognition of molecular markers which predict tumour behavior and treatment response, the increasing importance of adjuvant treatments such as chemo- and radiotherapy, and the tremendous advances in surgical technique and intraoperative monitoring which have facilitated superior extents of resection whilst preserving neurological functioning and quality of life, contemporary management of low grade glioma (LGG) has switched from a passive, observant approach to a more active, interventional one. Furthermore, this has implications for the manner in which patients with incidentally discovered and/or asymptomatic LGG are managed, and this review of the biological behaviour of LGG, as well as its clinical investigation and management, should act as a timely reminder to all clinicians of the importance of referring LGG patients early to a surgical neuro-oncologist who is not only familiar and acquainted with the vagaries of this disease process, but who, in addition, is devoted to delivering care to these patients with the support of a multi-disciplinary clinical decision-making unit, comprising medical neuro-oncologists, radiation oncologists and allied health professionals.

Imaging of intratumoral heterogeneity in high-grade glioma

High-grade glioma (HGG), and particularly Glioblastoma (GBM), can exhibit pronounced intratumoral heterogeneity that confounds clinical diagnosis and management. While conventional contrast-enhanced MRI lacks the capability to resolve this heterogeneity, advanced MRI techniques and PET imaging offer a spectrum of physiologic and biophysical image features to improve the specificity of imaging diagnoses. Published studies have shown how integrating these advanced techniques can help better define histologically distinct targets for surgical and radiation treatment planning, and help evaluate the regional heterogeneity of tumor recurrence and response assessment following standard adjuvant therapy. Application of texture analysis and machine learning (ML) algorithms has also enabled the emerging field of radiogenomics, which can spatially resolve the regional and genetically distinct subpopulations that coexist within a single GBM tumor. This review focuses on the latest advances in neuro-oncologic imaging and their clinical applications for the assessment of intratumoral heterogeneity.

Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO)

Relative cerebral blood volume (rCBV) cannot be used as a response metric in clinical trials, in part, because of variations in biomarker consistency and associated interpretation across sites, stemming from differences in image acquisition and postprocessing methods (PMs). This study leveraged a dynamic susceptibility contrast magnetic resonance imaging digital reference object to characterize rCBV consistency across 12 sites participating in the Quantitative Imaging Network (QIN), specifically focusing on differences in site-specific imaging protocols (IPs; n = 17), and PMs (n = 19) and differences due to site-specific IPs and PMs (n = 25). Thus, high agreement across sites occurs when 1 managing center processes rCBV despite slight variations in the IP. This result is most likely supported by current initiatives to standardize IPs. However, marked intersite disagreement was observed when site-specific software was applied for rCBV measurements. This study's results have important implications for comparing rCBV values across sites and trials, where variability in PMs could confound the comparison of therapeutic effectiveness and/or any attempts to establish thresholds for categorical response to therapy. To overcome these challenges and ensure the successful use of rCBV as a clinical trial biomarker, we recommend the establishment of qualifying and validating site- and trial-specific criteria for scanners and acquisition methods (eg, using a validated phantom) and the software tools used for dynamic susceptibility contrast magnetic resonance imaging analysis (eg, using a digital reference object where the ground truth is known).

Machine-learning in grading of gliomas based on multi-parametric magnetic resonance imaging at 3T

OBJECTIVE

The objective of this study was to assess the contribution of multi-parametric (mp) magnetic resonance imaging (MRI) quantitative features in the machine learning-based grading of gliomas with a multi-region-of-interests approach.

MATERIALS AND METHODS

Forty-three patients who were newly diagnosed as having a glioma were included in this study. The patients were scanned prior to any therapy using a standard brain tumor magnetic resonance (MR) imaging protocol that included T1 and T2-weighted, diffusion-weighted, diffusion tensor, MR perfusion and MR spectroscopic imaging. Three different regions-of-interest were drawn for each subject to encompass tumor, immediate tumor periphery, and distant peritumoral edema/normal. The normalized mp-MRI features were used to build machine-learning models for differentiating low-grade gliomas (WHO grades I and II) from high grades (WHO grades III and IV). In order to assess the contribution of regional mp-MRI quantitative features to the classification models, a support vector machine-based recursive feature elimination method was applied prior to classification.

RESULTS

A machine-learning model based on support vector machine algorithm with linear kernel achieved an accuracy of 93.0%, a specificity of 86.7%, and a sensitivity of 96.4% for the grading of gliomas using ten-fold cross validation based on the proposed subset of the mp-MRI features.

CONCLUSION

In this study, machine-learning based on multiregional and multi-parametric MRI data has proven to be an important tool in grading glial tumors accurately even in this limited patient population. Future studies are needed to investigate the use of machine learning algorithms for brain tumor classification in a larger patient cohort.

Optimization of DSC MRI Echo Times for CBV Measurements Using Error Analysis in a Pilot Study of High-Grade Gliomas

BACKGROUND AND PURPOSE

The optimal TE must be calculated to minimize the variance in CBV measurements made with DSC MR imaging. Simulations can be used to determine the influence of the TE on CBV, but they may not adequately recapitulate the in vivo heterogeneity of precontrast T2*, contrast agent kinetics, and the biophysical basis of contrast agent-induced T2* changes. The purpose of this study was to combine quantitative multiecho DSC MRI T2* time curves with error analysis in order to compute the optimal TE for a traditional single-echo acquisition.

MATERIALS AND METHODS

Eleven subjects with high-grade gliomas were scanned at 3T with a dual-echo DSC MR imaging sequence to quantify contrast agent-induced T2* changes in this retrospective study. Optimized TEs were calculated with propagation of error analysis for high-grade glial tumors, normal-appearing white matter, and arterial input function estimation.

RESULTS

The optimal TE is a weighted average of the T2* values that occur as a contrast agent bolus transverses a voxel. The mean optimal TEs were 30.0 ± 7.4 ms for high-grade glial tumors, 36.3 ± 4.6 ms for normal-appearing white matter, and 11.8 ± 1.4 ms for arterial input function estimation (repeated-measures ANOVA, P < .001).

CONCLUSIONS

Greater heterogeneity was observed in the optimal TE values for high-grade gliomas, and mean values of all 3 ROIs were statistically significant. The optimal TE for the arterial input function estimation is much shorter; this finding implies that quantitative DSC MR imaging acquisitions would benefit from multiecho acquisitions. In the case of a single-echo acquisition, the optimal TE prescribed should be 30-35 ms (without a preload) and 20-30 ms (with a standard full-dose preload).

Characterizing the Influence of Preload Dosing on Percent Signal Recovery (PSR) and Cerebral Blood Volume (CBV) Measurements in a Patient Population With High-Grade Glioma Using Dynamic Susceptibility Contrast MRI

With DSC-MRI, contrast agent leakage effects in brain tumors can either be leveraged for percent signal recovery (PSR) measurements or be adequately resolved for accurate relative cerebral blood volume (rCBV) measurements. Leakage effects can be dimished by administration of a preload dose before imaging and/or specific postprocessing steps. This study compares the consistency of both PSR and rCBV measurements as a function of varying preload doses in a retrospective analysis of 14 subjects with high-grade gliomas. The scans consisted of 6 DSC-MRI scans during 6 sequential bolus injections (0.05 mmol/kg). Mean PSR was calculated for tumor and normal-appearing white matter regions of interest. DSC-MRI data were corrected for leakage effects before computing mean tumor rCBV. Statistical differences were seen across varying preloads for tumor PSR (P value = 4.57E-24). Tumor rCBV values did not exhibit statistically significant differences across preloads (P value = .14) and were found to be highly consistent for clinically relevant preloads (intraclass correlation coefficient = 0.93). For a 0.05 mmol/kg injection bolus and pulse sequence parameters used, the highest PSR contrast between normal-appearing white matter and tumor occurs when no preload is used. This suggests that studies using PSR as a biomarker should acquire DSC-MRI data without preload. The finding that leakage-corrected rCBV values do not depend on the presence or dose of preload contradicts that of previous studies with dissimilar acquisition protocols. This further confirms the sensitivity of rCBV to preload dosing schemes and pulse sequence parameters and highlights the importance of standardization efforts for achieving multisite rCBV consistency.

Sodium Fluorescein Facilitates Guided Sampling of Diagnostic Tumor Tissue in Nonenhancing Gliomas

BACKGROUND

Accurate tissue sampling in nonenhancing (NE) gliomas is a unique surgical challenge due to their intratumoral histological heterogeneity and absence of contrast enhancement as a guide for intraoperative stereotactic guidance. Instead, T2/fluid-attenuated inversion-recovery (FLAIR) hyperintensity on MRI is commonly used as an imaging surrogate for pathological tissue, but sampling from this region can yield nondiagnostic or underdiagnostic brain tissue. Sodium fluorescein is an intraoperative fluorescent dye that has a high predictive value for tumor identification in areas of contrast enhancement and NE in glioblastomas. However, the underlying histopathological alterations in fluorescent regions of NE gliomas remain undefined.

OBJECTIVE

To evaluate whether fluorescein can identify diagnostic tissue and differentiate regions with higher malignant potential during surgery for NE gliomas, thus improving sampling accuracy.

METHODS

Thirteen patients who presented with NE, T2/FLAIR hyperintense lesions suspicious for glioma received fluorescein (10%, 3 mg/kg intravenously) during surgical resection.

RESULTS

Patchy fluorescence was identified within the T2/FLAIR hyperintense area in 10 of 13 (77%) patients. Samples taken from fluorescent regions were more likely to demonstrate diagnostic glioma tissue and cytologic atypia (P &lt; .05). Fluorescein demonstrated a 95% positive predictive value for the presence of diagnostic tissue. Samples from areas of fluorescence also demonstrated greater total cell density and higher Ki-67 labeling than nonfluorescent biopsies (P &lt; .05).

CONCLUSION

Fluorescence in NE gliomas is highly predictive of diagnostic tumor tissue and regions of higher cell density and proliferative activity.

Biopsy targeting with dynamic contrast-enhanced versus standard neuronavigation MRI in glioma: a prospective double-blinded evaluation of selection benefits

Current biopsy planning based on contrast-enhanced T1W (CET1W) or FLAIR sequences frequently delivers biopsy samples that are not in concordance with the gross tumor diagnosis. This study investigates whether the quantitative information of transfer constant K^trans maps derived from T1W dynamic contrast-enhanced MRI (DCE-MRI) can help enhance the quality of biopsy target selection in glioma. 28 patients with suspected glioma received MRI including DCE-MRI and a standard neuronavigation protocol of 3D FLAIR- and CET1W data sets (0.1 mmol/kg gadobutrol) at 3.0 T. After exclusion of five cases with no K^trans-elevation, 2-6 biopsy targets were independently selected by a neurosurgeon (samples based on standard imaging) and a neuroradiologist (samples based on kinetic parameter K^trans) per case and tissue samples corresponding to these targets were collected by a separate independent neurosurgeon. Standard technique and K^trans-based samples were rated for diagnostic concordance with the gross tumor resection reference diagnosis (67 WHO IV; 24 WHO III and II) by a neuropathologist blinded for selection mode. K^trans-based sample targets differed from standard technique sample targets in 90/91 cases. More K^trans-based than standard imaging-based samples could be extracted. Diagnoses from K^trans-based samples were more frequently concordant with the reference gross tumor diagnoses than those from standard imaging-based samples (WHO IV: 30/39 vs. 11/20; p = 0.08; WHO III/II: 12/13 vs. 6/11; p = 0.06). In 4/5 non-contrast-enhancing gliomas, K^trans-based selection revealed significantly more accurate samples than standard technique sample-selection (10/12 vs. 2/8 samples; p = 0.02). If K^trans elevation is present, K^trans-based biopsy targeting provides significantly more diagnostic tissue samples in non-contrast-enhancing glioma than selection based on CET1W and FLAIR-weighted images alone.

Advanced MRI may complement histological diagnosis of lower grade gliomas and help in predicting survival

MRI grading of grade II and III gliomas may have an important impact on treatment decisions. Occasionally,both conventional MRI (cMRI) and histology fail to clearly establish the tumour grade. Three cMRI features(no necrosis; no relevant oedema; absent or faint contrast enhancement) previously validated in 196 patients with supratentorial gliomas directed our selection of 68 suspected low-grade gliomas (LGG) that were also investigated by advanced MRI (aMRI), including perfusion weighted imaging (PWI), diffusion weighted imaging(DWI) and spectroscopy. All the gliomas had histopathological diagnoses. Sensitivity and specificity of cMRI preoperative diagnosis were 78.5 and 38.5 %, respectively, and 85.7 and 53.8 % when a MRI was included, respectively. ROC analysis showed that cut-off values of 1.29 for maximum rCBV, 1.69 for minimum rADC, 2.1 for rCho/Cr ratio could differentiate between LGG and HGG with a sensitivity of 61.5, 53.8, and 53.8 % and a specificity of 54.7, 43 and 64.3 %, respectively. A significantly longer OS was observed in patients with a maximum rCBV<1.46 and minimum rADC>1.69 (80 vs 55 months, p = 0.01; 80 vs 51 months, p = 0.002, respectively). This result was also confirmed when cases were stratified according to pathology (LGG vs HGG). The ability of a MRI to differentiate between LGG and HGG and to predict survival improved as the number of a MRI techniques considered increased. In a selected population of suspected LGG,classification by cMRI underestimated the actual fraction of HGG. aMRI slightly increased the diagnostic accuracy compared to histopathology. However, DWI and PWI were prognostic markers independent of histological grade.

Advanced MR imaging in hemispheric low-grade gliomas before surgery; the indications and limits in the pediatric age

INTRODUCTION

Advanced magnetic resonance imaging (MRI) techniques is an umbrella term that includes diffusion (DWI) and diffusion tensor (DTI), perfusion (PWI), spectroscopy (MRS), and functional (fMRI) imaging. These advanced modalities have improved the imaging of brain tumors and provided valuable additional information for treatment planning. Despite abundant literature on advanced MRI techniques in adult brain tumors, few reports exist for pediatric brain ones, potentially because of technical challenges.

REVIEW OF THE LITERATURE

The authors review techniques and clinical applications of DWI, PWI, MRS, and fMRI, in the setting of pediatric hemispheric low-grade gliomas.

PERSONAL EXPERIENCE

The authors propose their personal experience to highlight benefits and limits of advanced MR imaging in diagnosis, grading, and presurgical planning of pediatric hemispheric low-grade gliomas.

DISCUSSION

Advanced techniques should be used as complementary tools to conventional MRI, and in theory, the combined use of the three techniques should ensure achieving the best results in the diagnosis of hemispheric low-grade glioma and in presurgical planning to maximize tumor resection and preserve brain function.

FUTURE PERSPECTIVES

In the setting of pediatric neurooncology, these techniques can be used to distinguish low-grade from high-grade tumor. However, these methods have to be applied on a large scale to understand their real potential and clinical relapse, and further technical development is required to reduce the excessive scan times and other technical limitations.

The role of imaging in the management of adults with diffuse low grade glioma: A systematic review and evidence-based clinical practice guideline

QUESTION

What is the optimal imaging technique to be used in the diagnosis of a suspected low grade glioma, specifically: which anatomic imaging sequences are critical for most accurately identifying or diagnosing a low grade glioma (LGG) and do non-anatomic imaging methods and/or sequences add to the diagnostic specificity of suspected low grade gliomas?

TARGET POPULATION

These recommendations apply to adults with a newly diagnosed lesion with a suspected or histopathologically proven LGG.

RECOMMENDATION

LEVEL II

In patients with a suspected brain tumor, the minimum magnetic resonance imaging (MRI) exam should be an anatomic exam with both T2 weighted and pre- and post-gadolinium contrast enhanced T1 weighted imaging. CRITICAL IMAGING FOR THE IDENTIFICATION AND DIAGNOSIS OF LOW GRADE GLIOMA:

LEVEL II

In patients with a suspected brain tumor, anatomic imaging sequences should include T1 and T2 weighted and Fluid Attenuation Inversion Recovery (FLAIR) MR sequences and will include T1 weighted imaging after the administration of gadolinium based contrast. Computed tomography (CT) can provide additional information regarding calcification or hemorrhage, which may narrow the differential diagnosis. At a minimum, these anatomic sequences can help identify a lesion as well as its location, and potential for surgical intervention. IMPROVEMENT OF DIAGNOSTIC SPECIFICITY WITH THE ADDITION OF NON-ANATOMIC (PHYSIOLOGIC AND ADVANCED IMAGING) TO ANATOMIC IMAGING:

LEVEL II

Class II evidence from multiple studies and a significant number of Class III series support the addition of diffusion and perfusion weighted MR imaging in the assessment of suspected LGGs, for the purposes of discriminating the potential for tumor subtypes and identification of suspicion of higher grade diagnoses.

LEVEL III

Multiple series offer Class III evidence to support the potential for magnetic resonance spectroscopy (MRS) and nuclear medicine methods including positron emission tomography and single-photon emission computed tomography imaging to offer additional diagnostic specificity although these are less well defined and their roles in clinical practice are still being defined.

QUESTION

Which imaging sequences or parameters best predict the biological behavior or prognosis for patients with LGG?

TARGET POPULATION

These recommendations apply to adults with a newly diagnosed lesion with a suspected or histopathologically proven LGG.

RECOMMENDATION

Anatomic and advanced imaging methods and prognostic stratification

LEVEL III

Multiple series suggest a role for anatomic and advanced sequences to suggest prognostic stratification among low grade gliomas. Perfusion weighted imaging, particularly when obtained as a part of diagnostic evaluation (as recommended above) can play a role in consideration of prognosis. Other imaging sequences remain investigational in terms of their role in consideration of tumor prognosis as there is insufficient evidence to support more formal recommendations as to their use at this time.

QUESTION

What is the optimal imaging technique to be used in the follow-up of a suspected (or biopsy proven) LGG?

TARGET POPULATION

This recommendation applies to adults with a newly diagnosed low grade glioma.

RECOMMENDATIONS

LEVEL II

In patients with a diagnosis of LGG, anatomic imaging sequences should include T2/FLAIR MR sequences and T1 weighted imaging before and after the administration of gadolinium based contrast. Serial imaging should be performed to identify new areas of contrast enhancement or significant change in tumor size, which may signify transformation to a higher grade.

LEVEL III

Advanced imaging utility may depend on tumor subtype. Multicenter clinical trials with larger cohorts are needed. For astrocytic tumors, baseline and longitudinal elevations in tumor perfusion as assessed by dynamic susceptibility contrast perfusion MRI are associated with shorter time to tumor progression, but can be difficult to standardize in clinical practice. For oligodendrogliomas and mixed gliomas, MRS may be helpful for identification of progression.

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

BACKGROUND

MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB).

METHODS

One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients.

RESULTS

Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy.

CONCLUSIONS

By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood-brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients.

Automatic brain tumour detection and neovasculature assessment with multiseries MRI analysis

In this paper a novel multi-stage automatic method for brain tumour detection and neovasculature assessment is presented. First, the brain symmetry is exploited to register the magnetic resonance (MR) series analysed. Then, the intracranial structures are found and the region of interest (ROI) is constrained within them to tumour and peritumoural areas using the Fluid Light Attenuation Inversion Recovery (FLAIR) series. Next, the contrast-enhanced lesions are detected on the basis of T1-weighted (T1W) differential images before and after contrast medium administration. Finally, their vascularisation is assessed based on the Regional Cerebral Blood Volume (RCBV) perfusion maps. The relative RCBV (rRCBV) map is calculated in relation to a healthy white matter, also found automatically, and visualised on the analysed series. Three main types of brain tumours, i.e. HG gliomas, metastases and meningiomas have been subjected to the analysis. The results of contrast enhanced lesions detection have been compared with manual delineations performed independently by two experts, yielding 64.84% sensitivity, 99.89% specificity and 71.83% Dice Similarity Coefficient (DSC) for twenty analysed studies of subjects with brain tumours diagnosed.

Dynamic susceptibility contrast MRI measures of relative cerebral blood volume as a prognostic marker for overall survival in recurrent glioblastoma: results from the ACRIN 6677/RTOG 0625 multicenter trial

BACKGROUND

The study goal was to determine whether changes in relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) MRI are predictive of overall survival (OS) in patients with recurrent glioblastoma multiforme (GBM) when measured 2, 8, and 16 weeks after treatment initiation.

METHODS

Patients with recurrent GBM (37/123) enrolled in ACRIN 6677/RTOG 0625, a multicenter, randomized, phase II trial of bevacizumab with irinotecan or temozolomide, consented to DSC-MRI plus conventional MRI, 21 with DSC-MRI at baseline and at least 1 postbaseline scan. Contrast-enhancing regions of interest were determined semi-automatically using pre- and postcontrast T1-weighted images. Mean tumor rCBV normalized to white matter (nRCBV) and standardized rCBV (sRCBV) were determined for these regions of interest. The OS rates for patients with positive versus negative changes from baseline in nRCBV and sRCBV were compared using Wilcoxon rank-sum and Kaplan-Meier survival estimates with log-rank tests.

RESULTS

Patients surviving at least 1 year (OS-1) had significantly larger decreases in nRCBV at week 2 (P = .0451) and sRCBV at week 16 (P = .014). Receiver operating characteristic analysis found the percent changes of nRCBV and sRCBV at week 2 and sRCBV at week 16, but not rCBV data at week 8, to be good prognostic markers for OS-1. Patients with positive change from baseline rCBV had significantly shorter OS than those with negative change at both week 2 and week 16 (P = .0015 and P = .0067 for nRCBV and P = .0251 and P = .0004 for sRCBV, respectively).

CONCLUSIONS

Early decreases in rCBV are predictive of improved survival in patients with recurrent GBM treated with bevacizumab.

Survival analysis in patients with newly diagnosed primary glioblastoma multiforme using pre- and post-treatment peritumoral perfusion imaging parameters

The objective of this study was to evaluate if peritumoral (PT) perfusion parameters obtained from dynamic susceptibility weighted contrast enhanced perfusion MRI can predict overall survival (OS) and progression free survival (PFS) in patients with newly diagnosed glioblastoma multiforme (GBM). Twenty-eight newly diagnosed GBM patients, who were treated with resection followed by concurrent chemoradiation and adjuvant chemotherapy, were included in this study. Evaluated perfusion parameters were pre- and post-treatment PT relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF). Proportional hazard analysis was used to assess the relationship OS, PFS and perfusion parameters. Kaplan-Meier survival estimates and log-rank test were used to characterize and compare the patient groups with high and low perfusion parameter values in terms of OS and PFS. Pretreatment PT rCBV and rCBF were not associated with OS and PFS whereas there was statistically significant association of both posttreatment PT rCBV and rCBF with OS and posttreatment rCBV with PFS (association of PFS and posttreatment rCBF was not statistically significant). Neither the Kaplan-Meier survival estimates nor the log-rank test demonstrated any differences in OS between high and low pretreatment PT rCBV values and rCBF values; however, high and low post-treatment PT rCBV and rCBF values did demonstrate statistically significant difference in OS and PFS. Our study found posttreatment, not pretreatment, PT perfusion parameters can be used to predict OS and PFS in patients with newly diagnosed GBM.

Correlation between cerebral blood volume measurements by perfusion-weighted magnetic resonance imaging and two-year progression-free survival in gliomas

Our goal was to determine whether relative cerebral blood volume (rCBV) can serve as an adjunct to histopathologic grading in the assessment of gliomas, with the hypothesis that rCBV can predict two-year survival. We evaluated 29 newly diagnosed gliomas (13 WHO grade II, seven grade III, nine grade IV; 17 astrocytomas, 12 oligodendroglial tumors). Dynamic susceptibility-weighted contrast-enhanced perfusion MR images and CBV maps were obtained. rCBVmax measurements (maximum tumor CBV/contralateral normal tissue CBV) and progression-free survival (PFS) were recorded. Receiver operating characteristic curves and Kaplan-Meier survival curves were calculated for rCBVmax and histologic grade. rCBVmax measurements differed between gliomas without (2.38 +/- 1.22) and with progression (5.57 +/- 2.84) over two years. The optimal rCBVmax cut-off value to predict progression was 2.95. rCBVmax < 2.95 was a significant predictor of two-year PFS, almost as accurate as WHO grade II. In the pure astrocytoma subgroup, the optimal rCBVmax cut-off value to predict progression was 2.85. In this group rCBVmax < 2.85 was a significant predictor of two-year PFS, an even better predictor of two-year PFS than WHO grade II. rCBVmax can be used to predict two-year PFS in patients with gliomas, independent of pathologic findings, especially in tumors without oligodendroglial components.

Combined diffusion and perfusion MR imaging as biomarkers of prognosis in immunocompetent patients with primary central nervous system lymphoma

BACKGROUND AND PURPOSE

ADC derived from DWI has been shown to correlate with PFS and OS in immunocompetent patients with PCNSL. The purpose of our study was to confirm the validity of ADC measurements as a prognostic biomarker and to determine whether rCBV measurements derived from DSC perfusion MR imaging provide prognostic information.

MATERIALS AND METHODS

Pretherapy baseline DWI and DSC perfusion MR imaging in 25 patients with PCNSL was analyzed before methotrexate-based induction chemotherapy. Contrast-enhancing tumor was segmented and coregistered with ADC and rCBV maps, and mean and minimum values were measured. Patients were separated into high or low ADC groups on the basis of previously published threshold values of ADC(min) < 384 × 10(-6) mm(2)/s. High and low rCBV groups were defined on the basis of receiver operating curve analysis. High and low ADC and rCBV groups were analyzed independently and in combination. Multivariate Cox survival analysis was performed.

RESULTS

Patients with ADC(min) values < 384 × 10(-6) mm(2)/s or rCBV(mean) values < 1.43 had worse PFS and OS. The patient cohort with combined low ADC(min)-low rCBV(mean) had the worst prognosis. No other variables besides ADC and rCBV significantly affected survival.

CONCLUSIONS

Our study reinforces the validity of ADC values as a prognostic biomarker and provides the first evidence of low tumor rCBV as a novel risk factor for adverse prognosis in immunocompetent patients with PCNSL.

Perfusion MRI as a neurosurgical tool for improved targeting in stereotactic tumor biopsies

OBJECTIVE

Stereotactic biopsies are subject to sampling errors (essentially due to target selection). The presence of contrast enhancement is not a reliable marker of malignancy. The goal of the present study was to determine whether perfusion-weighted imaging can improve target selection in stereotactic biopsies.

METHODS

We studied 21 consecutive stereotactic biopsies between June 2009 and March 2010. Perfusion-weighted magnetic resonance imaging (MRI) was integrated into our neuronavigator. Perfusion-weighted imaging was used as an adjunct to conventional MRI data for target determination. Conventional MRI alone was used to determine the trajectory.

RESULTS

We found a linear correlation between regional cerebral blood volume (rCBV) and vessel density (number of vessels per mm(2); R = 0.64; p < 0.001). Perfusion-weighted imaging facilitated target determination in 11 cases (52.4%), all of which were histopathologically diagnosed as glial tumors. For glial tumors, which presented with contrast enhancement, perfusion-weighted imaging identified a more precisely delimited target in 9 cases, a different target in 1 case, and exactly the same target in 1 other case. In all cases, perfusion-selected sampling provided information on cellular features and tumor grading. rCBV was significantly associated with grading (p < 0.01), endothelial proliferation (p < 0.01), and vessel density (p < 0.01). For lesions with rCBV values ≤1, perfusion-weighted MRI did not help to determine the target but was useful for surgical management.

CONCLUSIONS

For stereotactic biopsies, targeting based on perfusion-weighted imaging is a feasible method for reducing the sampling error and improving target selection in the histopathological diagnosis of tumors with high rCBVs.

Imaging characteristics of oligodendrogliomas that predict grade

BACKGROUND AND PURPOSE

Oligodendrogliomas are tumors that have variable WHO grades depending on anaplasia and astrocytic components and their treatment may differ accordingly. Our aim was to retrospectively evaluate imaging features of oligodendrogliomas that predict tumor grade.

MATERIALS AND METHODS

The imaging studies of 75 patients with oligodendrogliomas were retrospectively reviewed and compared with the histologic grade. The presence and degree of enhancement and calcification were evaluated subjectively. rCBV and ADC maps were measured. Logistic linear regression models were used to determine the relationship between imaging factors and tumor grade.

RESULTS

Thirty of 75 (40%) tumors enhanced, including 9 of 46 (19.6%) grade II and 21 of 29 (72.4%) grade III tumors (P < .001). Grade III tumors showed lower ADC values compared with grade II tumors (odds ratio of a tumor being grade III rather than grade II = 0.07; 95% CI, 0.02-0.25; P = .001). An optimal ADC cutoff of 925 10(-6) mm(2)/s was established, which yielded a specificity of 89.1%, sensitivity of 62.1%, and accuracy of 78.7%. There was no statistically significant association between tumor grade and the presence of calcification and perfusion values. Multivariable prediction rules were applied for ADC < 925 10(-6) mm(2)/s, the presence of enhancement, and the presence of calcification. If either ADC < 925 10(-6) mm(2)/s or enhancement was present, it yielded 93.1% sensitivity, 73.9% specificity, and 81.3% accuracy. The most accurate (82.2%) predictive rule was seen when either ADC < 925 10(-6) mm(2)/s or enhancement and calcification were present.

CONCLUSIONS

Models based on contrast enhancement, calcification, and ADC values can assist in predicting the grade of oligodendrogliomas and help direct biopsy sites, raise suspicion of sampling error, and predict prognosis.

Quantitative diffusion-weighted and dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging analysis of T2 hypointense lesion components in pediatric diffuse intrinsic pontine glioma

BACKGROUND AND PURPOSE

Focal anaplasia characterized by T2 hypointensity, signal-intensity enhancement on postcontrast T1-weighted MR imaging and restricted water diffusion has been reported in a patient with juvenile pilocytic astrocytoma. We identified T2(HOF) with these MR imaging characteristics in children with DIPG and hypothesized that these represent areas of focal anaplasia; and may, therefore, have increased perfusion properties and should be characterized by increased perfusion. Thus, we used DSC to investigate our hypothesis.

MATERIALS AND METHODS

We retrospectively reviewed the baseline MR imaging scans of 86 patients (49 girls, 37 boys; median age, 6.1 years; range, 1.1-17.6 years) treated for DIPG at our hospital (2004-2009). T2(HOF) with the described MR imaging characteristics was identified in 10 patients. We used a region of interest-based approach to compare the ADC, FA, rCBV, rCBF, and rMTT of T2(HOF) with those of the typical T2(HRT).

RESULTS

The ADC of T2(HOF) with the specified MR imaging characteristics was significantly lower than that of T2(HRT) (range, 0.71-1.95 μm(2)/ms versus 1.36-2.13 μm(2)/ms; P < .01); and the FA (range, 0.12-0.34 versus 0.07-0.24; P = .03) and rCBV (range, 0.4-2.62 versus 0.23-1.57; P = .01) values of T2(HOF)s were significantly higher.

CONCLUSIONS

Our data suggest that T2(HOF) in DIPG may represent areas of focal anaplasia and underline the importance of regional, rather than global, tumor-field analysis. T2(HOF) may be the ideal target when stereotactic biopsy of tumors that present with an inhomogeneous T2 signal intensity is considered.

Clinical impact of integrated physiologic brain tumor imaging

The development of new MRI techniques in the last two decades has provided neuroradiologists and neurosurgeons with additional noninvasive imaging tools for management and treatment of brain tumors. When coupled with standard structural MR sequences in imaging brain tumors, Blood Oxygenation Level Dependent (BOLD) functional MRI (fMRI), Perfusion Weighted Imaging (PWI) and Diffusion Tensor Imaging (DTI) provide additional physiologic information that is very useful for differential diagnosis, presurgical planning and prognosis. In this review after a brief technical description of BOLD fMRI, PWI and DTI, studies are described from the literature that have extensively validated these imaging techniques in comparison with invasive "gold standard" techniques such as intraoperative electrical cortical and subcortical stimulation mapping or biopsy. Additional studies are mentioned that demonstrate the positive impact of BOLD fMRI, PWI and DTI on brain tumor treatment and clinical outcome. In the final section an interesting clinical case treated at our institution is presented that highlights the clinical utility of this integrated physiologic brain tumor imaging approach.

Intraprocedural diffusion-weighted PROPELLER MRI to guide percutaneous biopsy needle placement within rabbit VX2 liver tumors

PURPOSE

To test the hypothesis that diffusion-weighted (DW)-PROPELLER (periodically rotated overlapping parallel lines with enhanced reconstruction) magnetic resonance imaging (MRI) can be used to guide biopsy needle placement during percutaneous interventional procedures to selectively target viable and necrotic tissues within VX2 rabbit liver tumors.

MATERIALS AND METHODS

Our institutional Animal Care and Use Committee approved all experiments. In six rabbits implanted with 15 VX2 liver tumors, baseline DW-PROPELLER images acquired prior to the interventional procedure were used for apparent diffusion coefficient (ADC) measurements. Next, intraprocedural DW-PROPELLER scans were performed with needle position iteratively adjusted to target viable, necrotic, or intermediate border tissue regions. DW-PROPELLER ADC measurements at the selected needle tip locations were compared with the percentage of tumor necrosis qualitatively assessed at histopathology.

RESULTS

DW-PROPELLER images demonstrated intratumoral tissue heterogeneity and clearly depicted the needle tip position within viable and necrotic tumor tissues. Mean ADC measurements within the region-of-interest encompassing the needle tip were highly correlated with histopathologic tumor necrotic tissue assessments.

CONCLUSION

DW-PROPELLER is an effective method to selectively position the biopsy needle tip within viable and necrotic tumor tissues. The DW-PROPELLER method may offer an important complementary tool for functional guidance during MR-guided percutaneous procedures.

Cerebral blood volume measurements by perfusion-weighted MR imaging in gliomas: ready for prime time in predicting short-term outcome and recurrent disease?

BACKGROUND AND PURPOSE

Current classification and grading of primary brain tumors has significant limitations. Our aim was to determine whether the relative cerebral volume (rCBV) measurements in gliomas may serve as an adjunct to histopathologic grading, with a hypothesis that rCBV values are more accurate in predicting 1-year survival and recurrence.

MATERIALS AND METHODS

Thirty-four patients with gliomas (WHO grade I-IV, 27 astrocytomas, 7 tumors with oligodendroglial components) underwent contrast-enhanced MR rCBV measurements before treatment. The region of interest and the single pixel with the maximum CBV value within the tumors were normalized relative to the contralateral normal tissue (rCBV(mean) and rCBV(max), respectively). Karnofsky performance score and progression-free survival (PFS) were recorded. Receiver operating characteristic curves and Kaplan-Meier survival analysis were conducted for CBV and histologic grade (WHO grade).

RESULTS

Significant correlations were detected only when patients with oligodendrogliomas and oligoastrocytomas were excluded. The rCBV(mean) and rCBV(max) in the astrocytomas were 3.5 +/- 2.9 and 3.7 +/- 2.7. PFS correlated with rCBV parameters (r = -0.54 to -0.56, P < or = .009). WHO grade correlated with rCBV values (r = 0.65, P < or = .0002). rCBV(max) > 4.2 was found to be a significant cutoff value for recurrence prediction with 77.8% sensitivity and 94.4% specificity (P = .0001). rCBV(max) < or = 3.8 was a significant predictor for 1-year survival (93.7% sensitivity, 72.7% specificity, P = .0002). The relative risk for shorter PFS was 11.1 times higher for rCBV(max) > 4.2 (P = .0006) and 6.7 times higher for WHO grade > II (P = .05). The combined CBV-WHO grade classification enhanced the predictive value for recurrence/progression (P < .0001).

CONCLUSIONS

rCBV values in astrocytomas but not tumors with oligodendroglial components are predictive for recurrence and 1-year survival and may be more accurate than histopathologic grading.

Radiological progression of cerebral metastases after radiosurgery: assessment of perfusion MRI for differentiating between necrosis and recurrence

To assess the capability of perfusion MRI to differentiate between necrosis and tumor recurrence in patients showing radiological progression of cerebral metastases treated with stereotactic radiosurgery (SRS). From 2004 to 2006 dynamic susceptibility-weighted contrast-enhanced perfusion MRI scans were performed on patients with cerebral metastasis showing radiological progression after SRS during follow-up. Several perfusion MRI characteristics were examined: a subjective visual score of the relative cerebral blood volume (rCBV) map and quantitative rCBV measurements of the contrast-enhanced areas of maximal perfusion. For a total of 34 lesions in 31 patients a perfusion MRI was performed. Diagnoses were based on histology, definite radiological decrease or a combination of radiological and clinical follow-up. The diagnosis of tumor recurrence was obtained in 20 of 34 lesions, and tumor necrosis in 14 of 34. Regression analyses for all measures proved statistically significant (χ² = 11.6–21.6, P < 0.001–0.0001). Visual inspection of the rCBV map yielded a sensitivity and specificity of 70.0 respectively 92.9%. The optimal cutoff point for maximal tumor rCBV relative to white matter was 2.00 (improving the sensibility to 85.0%) and 1.85 relative to grey matter (GM), improving the specificity to 100%, with a corresponding sensitivity of 70.0%. Perfusion MRI seems to be a useful tool in the differentiation of necrosis and tumor recurrence after SRS. For the patients displaying a rCBV-GM greater than 1.85, the diagnosis of necrosis was excluded. Salvage treatment can be initiated for these patients in an attempt to prolong survival.

Role of advanced MR imaging modalities in diagnosing cerebral gliomas

The objective of this study was to evaluate the potential role of newly developed, advanced magnetic resonance (MR) imaging techniques (spectroscopy, diffusion and perfusion imaging) in diagnosing brain gliomas, with special reference to histological typing and grading, treatment planning and posttreatment follow-up. Conventional MR imaging enables the detection and localisation of neoplastic lesions, as well as providing, in typical cases, some indication about their nature. However, it has limited sensitivity and specificity in evaluating histological type and grade, delineating margins and differentiating oedema, tumour and treatment side-effects. These limitations can be overcome by supplementing the morphological data obtained with conventional MR imaging with the metabolic, structural and perfusional information provided by new MR techniques that are increasingly becoming an integral part of routine MR studies. Incorporation of such new MR techniques can lead to more comprehensive and precise diagnoses that can better assist surgeons in determining prognosis and planning treatment strategies. In addition, the recent development of new, more effective, treatments for cerebral glioma strongly relies on morphofunctional MR imaging with its ability to provide a biological interpretation of these characteristically heterogeneous tumours.

Magnetic resonance perfusion imaging in neuro-oncology

Recent advances in magnetic resonance imaging (MRI) have seen the development of techniques that allow quantitative imaging of a number of anatomical and physiological descriptors. These techniques have been increasingly applied to cancer imaging where they can provide some insight into tumour microvascular structure and physiology. This review details technical approaches and application of quantitative MRI, focusing particularly on perfusion imaging and its role in neuro-oncology.

[Value of relative cerebral blood volume measurement using perfusion MRI in glioma management]

INTRODUCTION

Neoangiogenesis is a critical feature that can differentiate high-grade from low-grade glioma. Conventional MR imaging does not assess this histological feature accurately. The goal of this study was to evaluate the gain in relative cerebral blood volume measurement using perfusion MRI in the management of cerebral gliomas.

MATERIALS AND METHODS

Between 1998 and 2001, 32 histologically proven glial tumors were assessed by perfusion MRI using echoplanar imaging (EPI) and gradient-echo techniques. Relative cerebral blood volume (rCBV) was measured in all patients and compared to histological data.

RESULTS

rCBV values were significantly correlated to histological grading in all 32 patients (P<0.001). Mean rCBV values were 8.74 (+/-3.79) for glioblastomas, 7.37 (+/-2.83) for anaplastic gliomas and 0.84 (+/-0.61) for low-grade gliomas. Mean rCBV values were significantly different between low- and high-grade gliomas, making it possible to determine a threshold (2.5-3) that can separate these two types of lesion. In determining the histological grading, rCBV was shown to be significantly more accurate than conventional MRI (P<0.005).

CONCLUSION

Perfusion MRI using the EPI technique reliably assesses tumoral neoangiogenesis in gliomas preoperatively. The specificity and sensitivity of this technique make this radiological modality a valuable tool in the assessment of cerebral gliomas.

Diagnostics of cerebral gliomas with radiolabeled amino acids

INTRODUCTION

Magnetic resonance tomography (MRT) is the investigation of choice for diagnosing cerebral glioma, but its capacity to differentiate tumor tissue from non-specific tissue changes is limited. Positron emission tomography (PET) and single photon emission computerized tomography (SPECT) using radiolabeled amino acids add information which helps increase diagnostic accuracy.

METHODS

Review based on the authors' own research results and a selective literature review.

RESULTS

The use of radiolabeled amino acids allows better delineation of tumor margins and improves targeting of biopsy and radiotherapy, and planning surgery. In addition, amino acid imaging appears useful in distinguishing tumor recurrence from non-specific post-therapeutic scar tissue, in predicting prognosis in low grade gliomas, and in monitoring metabolic response during treatment.

DISCUSSION

The benefits of amino acid imaging in cerebral gliomas support arguments for its introduction into routine clinical practice in defined clinical situations; however, its influence on treatment quality remains to be demonstrated.

Advanced MRI of adult brain tumors

This article is intended to provide clinical neurologists with an overview of the major techniques of advanced MRI of brain tumor: diffusion-weighted imaging, perfusion-weighted imaging, dynamic contrast-enhanced T1 permeability imaging, diffusion-tensor imaging, and magnetic resonance spectroscopy. These techniques represent a significant addition to conventional anatomic MRI T2-weighted images, fluid attenuated inversion recovery (FLAIR) T2-weighted images, and gadolinium-enhanced T1-weighted images for assessing tumor cellularity, white matter invasion, metabolic derangement including hypoxia and necrosis, neovascular capillary blood volume, and permeability. Although a brief introduction and more extensive references to the technical literature is provided, the major focus is to provide a summary of recent clinical experience in application of these major advanced MRI techniques to differential diagnosis, grading, surgical planning, and monitoring of therapeutic response of tumors.