MRI apparent diffusion coefficient reflects histopathologic subtype, axonal disruption, and tumor fraction in diffuse-type grade II gliomas

Correlation Between Apparent Diffusion Coefficient and the Ki-67 Proliferation Index in Grading Pediatric Glioma

OBJECTIVE

This study aimed to investigate the correlation between apparent diffusion coefficient (ADC) and the Ki-67 proliferation index with the pathologic grades of pediatric glioma and to compare their diagnostic performance in differentiating grades of pediatric glioma.

PATIENTS AND METHODS

Magnetic resonance imaging examinations and histopathologies of 121 surgically treated pediatric gliomas (87 low-grade gliomas [LGGs; grades 1 and 2] and 34 high-grade gliomas [HGGs; grades 3 and 4]) were retrospectively reviewed. The mean tumor ADC (ADCmean), minimum tumor ADC (ADCmin), tumor/normal brain ADC ratio (ADC ratio), and value of the Ki-67 proliferation index of LGGs and HGGs were compared. Correlation coefficients were calculated for ADC parameters and Ki-67 values. The receiver operating characteristic curve was used to determine the diagnostic value of ADCmean, ADCmin, ADC ratio, and Ki-67 proliferation index for differentiating LGGs and HGGs.

RESULTS

The ADC values were significantly negatively correlated with glioma grade, and the Ki-67 proliferation index had a significant positive correlation with glioma grade. A significant negative correlation was observed between ADCmean and Ki-67 proliferation index, between ADCmin and Ki-67 proliferation index, and between ADC ratio and Ki-67 proliferation index. The receiver operating characteristic analysis demonstrated moderate to good accuracy for ADCmean in discriminating LGGs from HGGs (area under the curve [AUC], 0.875; sensitivity, 79.3%; specificity, 82.4%; accuracy, 80.2%; positive predictive value [PPV], 92.0%; and negative predictive value [NPV], 60.9% [cutoff value, 1.187] [×10-3 mm2/s]). Minimum tumor ADC showed very good to excellent accuracy with AUC of 0.946, sensitivity of 86.2%, specificity of 94.1%, accuracy of 88.4%, PPV of 97.4%, and NPV of 72.7% (cutoff value, 0.970) (×10-3 mm2/s). The ADC ratio showed moderate to good accuracy with AUC of 0.854, sensitivity of 72.4%, specificity of 88.2%, accuracy of 76.9%, PPV of 94.0%, and NPV of 55.6% (cutoff value, 1.426). For the parameter of the Ki-67 proliferation index, in discriminating LGGs from HGGs, very good to excellent diagnostic accuracy was observed (AUC, 0.962; sensitivity, 94.1%; specificity, 89.7%; accuracy, 90.9%; PPV, 97.5%; and NPV, 78.0% [cutoff value, 7]).

CONCLUSIONS

Apparent diffusion coefficient parameters and the Ki-67 proliferation index were significantly correlated with histological grade in pediatric gliomas. Apparent diffusion coefficient was closely correlated with the proliferative potential of pediatric gliomas. In addition, ADCmin showed superior performance compared with ADCmean and ADC ratio in differentiating pediatric glioma grade, with a close diagnostic efficacy to the Ki-67 proliferation index.

Hypovascular Cellular Tumor in Primary Central Nervous System Lymphoma is Associated with Treatment Resistance: Tumor Habitat Analysis Using Physiologic MRI

BACKGROUND AND PURPOSE

The microenvironment of lymphomas is known to be highly variable and closely associated with treatment resistance and survival. We tried to develop a physiologic MR imaging-based spatial habitat analysis to identify regions associated with treatment resistance to facilitate the prediction of tumor response after initial chemotherapy in patients with primary central nervous system lymphoma.

MATERIALS AND METHODS

Eighty-one patients with pathologically confirmed primary central nervous system lymphoma were enrolled. Pretreatment physiologic MR imaging was performed, and K-means clustering was used to separate voxels into 3 spatial habitats according to ADC and CBV values. Associations of spatial habitats and clinical and conventional imaging predictors with time to progression were analyzed using Cox proportional hazards modeling. The performance of statistically significant predictors for time to progression was assessed using the concordance probability index.

RESULTS

The 3 spatial habitats of hypervascular cellular tumor, hypovascular cellular tumor, and hypovascular hypocellular tumor were identified. A large hypovascular cellular habitat was most significantly associated with short time to progression (hazard ratio, 2.83; P = . 017). The presence of an atypical finding (hazard ratio, 4.41; P = . 016), high performance score (hazard ratio, 5.82; P = . 04), and high serum lactate dehydrogenase level (hazard ratio, 1.01; P = .013) was significantly associated with time to progression. A predictive model constructed using the habitat score and other imaging parameters showed a concordance probability index for prediction of time to progression of 0.70 (95% CI, 0.54-0.87).

CONCLUSIONS

A hypovascular cellular tumor habitat is associated with treatment resistance in primary central nervous system lymphoma, and its assessment may refine prechemotherapy imaging-based response prediction for patients with primary central nervous system lymphoma.

Molecular characteristics of diffuse lower grade gliomas: what neurosurgeons need to know

The importance of genomic information in intrinsic brain tumors is highlighted in the World Health Organization (WHO) 2016 classification of gliomas, which now incorporates both phenotype and genotype data to assign a diagnosis. By using genetic markers to both categorize tumors and advise patients on prognosis, this classification system has minimized the risk of tissue sampling error, improved diagnostic accuracy, and reduced inter-rater variability. In the neurosurgical community, it is critical to understand the role genetics plays in tumor biology, what certain mutations mean for the patient's prognosis and adjuvant treatment, and how to interpret the results of sequencing data that are generated following tumor resection. In this review, we examine the critical role of genetics for diagnosis and prognosis and highlight the importance of tumor genetics for neurosurgeons caring for patients with diffuse lower grade gliomas.

Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review

OBJECTIVE:

The diversity of tumour characteristics among glioma patients, even within same tumour grade, is a big challenge for disease outcome prediction. A possible approach for improved radiological imaging could come from combining information obtained at the molecular level. This review assembles recent evidence highlighting the value of using radiogenomic biomarkers to infer the underlying biology of gliomas and its correlation with imaging features.

METHODS:

A literature search was done for articles published between 2002 and 2017 on Medline electronic databases. Of 249 titles identified, 38 fulfilled the inclusion criteria, with 14 articles related to quantifiable imaging parameters (heterogeneity, vascularity, diffusion, cell density, infiltrations, perfusion, and metabolite changes) and 24 articles relevant to molecular biomarkers linked to imaging.

RESULTS:

Genes found to correlate with various imaging phenotypes were EGFR, MGMT, IDH1, VEGF, PDGF, TP53, and Ki-67. EGFR is the most studied gene related to imaging characteristics in the studies reviewed (41.7%), followed by MGMT (20.8%) and IDH1 (16.7%). A summary of the relationship amongst glioma morphology, gene expressions, imaging characteristics, prognosis and therapeutic response are presented.

CONCLUSION:

The use of radiogenomics can provide insights to understanding tumour biology and the underlying molecular pathways. Certain MRI characteristics that show strong correlations with EGFR, MGMT and IDH1 could be used as imaging biomarkers. Knowing the pathways involved in tumour progression and their associated imaging patterns may assist in diagnosis, prognosis and treatment management, while facilitating personalised medicine.

ADVANCES IN KNOWLEDGE:

Radiogenomics can offer clinicians better insight into diagnosis, prognosis, and prediction of therapeutic responses of glioma.

Predicting Genotype and Survival in Glioma Using Standard Clinical MR Imaging Apparent Diffusion Coefficient Images: A Pilot Study from The Cancer Genome Atlas

BACKGROUND AND PURPOSE

Few studies have shown MR imaging features and ADC correlating with molecular markers and survival in patients with glioma. Our purpose was to correlate MR imaging features and ADC with molecular subtyping and survival in adult diffuse gliomas.

MATERIALS AND METHODS

Presurgical MRIs and ADC maps of 131 patients with diffuse gliomas and available molecular and survival data from The Cancer Genome Atlas were reviewed. MR imaging features, ADC (obtained by ROIs within the lowest ADC area), and mean relative ADC values were evaluated to predict isocitrate dehydrogenase (IDH) mutation, 1p/19q codeletion status, MGMT promoter methylation, and overall survival.

RESULTS

IDH wild-type gliomas tended to exhibit enhancement, necrosis, and edema; >50% enhancing area (P < .001); absence of a cystic area (P = .013); and lower mean relative ADC (median, 1.1 versus 1.6; P < .001) than IDH-mutant gliomas. By means of a cutoff value of 1.08 for mean relative ADC, IDH-mutant and IDH wild-type gliomas with lower mean relative ADC (<1.08) had poorer survival than those with higher mean relative ADC (median survival time, 24.2 months; 95% CI, 0.0-54.9 months versus 62.0 months; P = .003; and median survival time, 10.4 months; 95% CI, 4.4-16.4 months versus 17.7 months; 95% CI, 11.6-23.7 months; P = .041, respectively), regardless of World Health Organization grade. Median survival of those with IDH-mutant glioma with low mean relative ADC was not significantly different from that in those with IDH wild-type glioma. Other MR imaging features were not statistically significant predictors of survival.

CONCLUSIONS

IDH wild-type glioma showed lower ADC values, which also correlated with poor survival in both IDH-mutant and IDH wild-type gliomas, irrespective of histologic grade. A subgroup with IDH-mutant gliomas with lower ADC had dismal survival similar to that of those with IDH wild-type gliomas.

Relationship of In Vivo MR Parameters to Histopathological and Molecular Characteristics of Newly Diagnosed, Nonenhancing Lower-Grade Gliomas

The goal of this research was to elucidate the relationship between WHO 2016 molecular classifications of newly diagnosed, nonenhancing lower grade gliomas (LrGG), tissue sample histopathology, and magnetic resonance (MR) parameters derived from diffusion, perfusion, and ¹H spectroscopic imaging from the tissue sample locations and the entire tumor. A total of 135 patients were scanned prior to initial surgery, with tumor cellularity scores obtained from 88 image-guided tissue samples. MR parameters were obtained from corresponding sample locations, and histograms of normalized MR parameters within the T2 fluid-attenuated inversion recovery lesion were analyzed in order to evaluate differences between subgroups. For tissue samples, higher tumor scores were related to increased normalized apparent diffusion coefficient (nADC), lower fractional anisotropy (nFA), lower cerebral blood volume (nCBV), higher choline (nCho), and lower N-acetylaspartate (nNAA). Within the T2 lesion, higher tumor grade was associated with higher nADC, lower nFA, and higher Cho to NAA index. Pathological analysis confirmed that diffusion and metabolic parameters increased and perfusion decreased with tumor cellularity. This information can be used to select targets for tissue sampling and to aid in making decisions about treating residual disease.

Apparent diffusion coefficient for molecular subtyping of non-gadolinium-enhancing WHO grade II/III glioma: volumetric segmentation versus two-dimensional region of interest analysis

Objectives

To investigate if quantitative apparent diffusion coefficient (ADC) measurements can predict genetic subtypes of non-gadolinium-enhancing gliomas, comparing whole tumour against single slice analysis.

Methods

Volumetric T2-derived masks of 44 gliomas were co-registered to ADC maps with ADC mean (ADC_mean) calculated. For the slice analysis, two observers placed regions of interest in the largest tumour cross-section. The ratio (ADC_ratio) between ADC_mean in the tumour and normal appearing white matter was calculated for both methods.

Results

Isocitrate dehydrogenase (IDH) wild-type gliomas showed the lowest ADC values throughout (p < 0.001). ADC_mean in the IDH-mutant 1p19q intact group was significantly higher than in the IDH-mutant 1p19q co-deleted group (p < 0.01). A volumetric ADC_mean threshold of 1201 × 10⁻⁶ mm²/s identified IDH wild-type with a sensitivity of 83% and a specificity of 86%; a volumetric ADC_ratio cut-off value of 1.65 provided a sensitivity of 80% and a specificity of 92% (area under the curve (AUC) 0.9–0.94). A slice ADC_ratio threshold for observer 1 (observer 2) of 1.76 (1.83) provided a sensitivity of 80% (86%), specificity of 91% (100%) and AUC of 0.95 (0.96). The intraclass correlation coefficient was excellent (0.98).

Conclusions

ADC measurements can support the distinction of glioma subtypes. Volumetric and two-dimensional measurements yielded similar results in this study.

Key Points

• Diffusion-weighted MRI aids the identification of non-gadolinium-enhancing malignant gliomas

• ADC measurements may permit non-gadolinium-enhancing glioma molecular subtyping

• IDH wild-type gliomas have lower ADC values than IDH-mutant tumours

• Single cross-section and volumetric ADC measurements yielded comparable results in this study

Whole-Tumor Histogram and Texture Analyses of DTI for Evaluation of IDH1-Mutation and 1p/19q-Codeletion Status in World Health Organization Grade II Gliomas

BACKGROUND AND PURPOSE

Prediction of the isocitrate dehydrogenase 1 (IDH1)-mutation and 1p/19q-codeletion status of World Health Organization grade ll gliomas preoperatively may assist in predicting prognosis and planning treatment strategies. Our aim was to characterize the histogram and texture analyses of apparent diffusion coefficient and fractional anisotropy maps to determine IDH1-mutation and 1p/19q-codeletion status in World Health Organization grade II gliomas.

MATERIALS AND METHODS

Ninety-three patients with World Health Organization grade II gliomas with known IDH1-mutation and 1p/19q-codeletion status (18 IDH1 wild-type, 45 IDH1 mutant and no 1p/19q codeletion, 30 IDH1-mutant and 1p/19q codeleted tumors) underwent DTI. ROIs were drawn on every section of the T2-weighted images and transferred to the ADC and the fractional anisotropy maps to derive volume-based data of the entire tumor. Histogram and texture analyses were correlated with the IDH1-mutation and 1p/19q-codeletion status. The predictive powers of imaging features for IDH1 wild-type tumors and 1p/19q-codeletion status in IDH1-mutant subgroups were evaluated using the least absolute shrinkage and selection operator.

RESULTS

Various histogram and texture parameters differed significantly according to IDH1-mutation and 1p/19q-codeletion status. The skewness and energy of ADC, 10th and 25th percentiles, and correlation of fractional anisotropy were independent predictors of an IDH1 wild-type in the least absolute shrinkage and selection operator. The area under the receiver operating curve for the prediction model was 0.853. The skewness and cluster shade of ADC, energy, and correlation of fractional anisotropy were independent predictors of a 1p/19q codeletion in IDH1-mutant tumors in the least absolute shrinkage and selection operator. The area under the receiver operating curve was 0.807.

CONCLUSIONS

Whole-tumor histogram and texture features of the ADC and fractional anisotropy maps are useful for predicting the IDH1-mutation and 1p/19q-codeletion status in World Health Organization grade II gliomas.

Prediction of IDH1-Mutation and 1p/19q-Codeletion Status Using Preoperative MR Imaging Phenotypes in Lower Grade Gliomas

BACKGROUND AND PURPOSE

WHO grade II gliomas are divided into three classes: isocitrate dehydrogenase (IDH)-wildtype, IDH-mutant and no 1p/19q codeletion, and IDH-mutant and 1p/19q-codeleted. Different molecular subtypes have been reported to have prognostic differences and different chemosensitivity. Our aim was to evaluate the predictive value of imaging phenotypes assessed with the Visually AcceSAble Rembrandt Images lexicon for molecular classification of lower grade gliomas.

MATERIALS AND METHODS

MR imaging scans of 175 patients with lower grade gliomas with known IDH1 mutation and 1p/19q-codeletion status were included (78 grade II and 97 grade III) in the discovery set. MR imaging features were reviewed by using Visually AcceSAble Rembrandt Images (VASARI); their associations with molecular markers were assessed. The predictive power of imaging features for IDH1-wild type tumors was evaluated using the Least Absolute Shrinkage and Selection Operator. We tested the model in a validation set (40 subjects).

RESULTS

Various imaging features were significantly different according to IDH1 mutation. Nonlobar location, larger proportion of enhancing tumors, multifocal/multicentric distribution, and poor definition of nonenhancing margins were independent predictors of an IDH1 wild type according to the Least Absolute Shrinkage and Selection Operator. The areas under the curve for the prediction model were 0.859 and 0.778 in the discovery and validation sets, respectively. The IDH1-mutant, 1p/19q-codeleted group frequently had mixed/restricted diffusion characteristics and showed more pial invasion compared with the IDH1-mutant, no codeletion group.

CONCLUSIONS

Preoperative MR imaging phenotypes are different according to the molecular markers of lower grade gliomas, and they may be helpful in predicting the IDH1-mutation status.

Biologically aggressive regions within glioblastoma identified by spin-lock contrast T1 relaxation in the rotating frame (T1ρ) MRI

Spin-lattice relaxation in the rotating frame magnetic resonance imaging allows for the quantitative assessment of spin-lock contrast within tissues. We describe the utility of spin-lattice relaxation in the rotating frame metrics in characterizing glioblastoma biological heterogeneity. A 84-year-old man presented to our institution with a right frontal temporal mass. Prior tissue sampling from a peripheral nonenhancing lesion was nondiagnostic. Stereotactic image-guided tissue sampling of the nonenhancing T2-fluid-attenuated inversion recovery hyperintense region involving the anterior cingulate gyrus with elevated spin-lattice relaxation in the rotating frame metrics provided a pathologic diagnosis of glioblastoma. This case illustrates the utility of spin-lattice relaxation in the rotating frame magnetic resonance imaging in identifying biologically aggressive regions within glioblastoma.

Noninvasive Assessment of IDH Mutational Status in World Health Organization Grade II and III Astrocytomas Using DWI and DSC-PWI Combined with Conventional MR Imaging

BACKGROUND AND PURPOSE

Isocitrate dehydrogenase (IDH) has been shown to have both diagnostic and prognostic implications in gliomas. The purpose of this study was to examine whether DWI and DSC-PWI combined with conventional MR imaging could noninvasively predict IDH mutational status in World Health Organization grade II and III astrocytomas.

MATERIALS AND METHODS

We retrospectively reviewed DWI, DSC-PWI, and conventional MR imaging in 42 patients with World Health Organization grade II and III astrocytomas. Minimum ADC, relative ADC, and relative maximum CBV values were compared between IDH-mutant and wild-type tumors by using the Mann-Whitney U test. Receiver operating characteristic curve and logistic regression were used to assess their diagnostic performances.

RESULTS

Minimum ADC and relative ADC were significantly higher in IDH-mutated grade II and III astrocytomas than in IDH wild-type tumors (P < .05). Minimum ADC with the cutoff value of ≥1.01 × 10^-3 mm²/s could differentiate the mutational status with a sensitivity, specificity, positive predictive value, and negative predictive value of 76.9%, 82.6%, 91.2%, and 60.5%, respectively. The threshold value of <2.35 for relative maximum CBV in the prediction of IDH mutation provided a sensitivity, specificity, positive predictive value, and negative predictive value of 100.0%, 60.9%, 85.6%, and 100.0%, respectively. A combination of DWI, DSC-PWI, and conventional MR imaging for the identification of IDH mutations resulted in a sensitivity, specificity, positive predictive value, and negative predictive value of 92.3%, 91.3%, 96.1%, and 83.6%.

CONCLUSIONS

A combination of conventional MR imaging, DWI, and DSC-PWI techniques produces a high sensitivity, specificity, positive predictive value, and negative predictive value for predicting IDH mutations in grade II and III astrocytomas. The strategy of using advanced, semiquantitative MR imaging techniques may provide an important, noninvasive, surrogate marker that should be studied further in larger, prospective trials.

Genetically Defined Oligodendroglioma Is Characterized by Indistinct Tumor Borders at MRI

BACKGROUND AND PURPOSE

In 2016, the World Health Organization revised the brain tumor classification, making IDH mutation and 1p/19q codeletion the defining features of oligodendroglioma. To determine whether imaging characteristics previously associated with oligodendroglial tumors are still applicable, we evaluated the MR imaging features of genetically defined oligodendrogliomas.

MATERIALS AND METHODS

One hundred forty-eight adult patients with untreated World Health Organization grade II and III infiltrating gliomas with histologic oligodendroglial morphology, known 1p/19q status, and at least 1 preoperative MR imaging were retrospectively identified. The association of 1p/19q codeletion with tumor imaging characteristics and ADC values was evaluated.

RESULTS

Ninety of 148 (61%) patients had 1p/19q codeleted tumors, corresponding to genetically defined oligodendroglioma, and 58/148 (39%) did not show 1p/19q codeletion, corresponding to astrocytic tumors. Eighty-three of 90 (92%) genetically defined oligodendrogliomas had noncircumscribed borders, compared with 26/58 (45%) non-1p/19q codeleted tumors with at least partial histologic oligodendroglial morphology (P < .0001). Eighty-nine of 90 (99%) oligodendrogliomas were heterogeneous on T1- and/or T2-weighted imaging. In patients with available ADC values, a lower mean ADC value predicted 1p/19q codeletion (P = .0005).

CONCLUSIONS

Imaging characteristics of World Health Organization 2016 genetically defined oligodendrogliomas differ from the previously considered characteristics of morphologically defined oligodendrogliomas. We found that genetically defined oligodendrogliomas were commonly poorly circumscribed and were almost always heterogeneous in signal intensity.

Quantitative multi-modal MR imaging as a non-invasive prognostic tool for patients with recurrent low-grade glioma

Low-grade gliomas can vary widely in disease course and therefore patient outcome. While current characterization relies on both histological and molecular analysis of tissue resected during surgery, there remains high variability within glioma subtypes in terms of response to treatment and outcome. In this study we hypothesized that parameters obtained from magnetic resonance data would be associated with progression-free survival for patients with recurrent low-grade glioma. The values considered were derived from the analysis of anatomic imaging, diffusion weighted imaging, and ¹H magnetic resonance spectroscopic imaging data. Metrics obtained from diffusion and spectroscopic imaging presented strong prognostic capability within the entire population as well as when restricted to astrocytomas, but demonstrated more limited efficacy in the oligodendrogliomas. The results indicate that multi-parametric imaging data may be applied as a non-invasive means of assessing prognosis and may contribute to developing personalized treatment plans for patients with recurrent low-grade glioma.

The Disruption of Geniculocalcarine Tract in Occipital Neoplasm: A Diffusion Tensor Imaging Study

Aim. Investigate the disruption of geniculocalcarine tract (GCT) in different occipital neoplasm by diffusion tensor imaging (DTI). Methods. Thirty-two subjects (44.1 ± 3.6 years) who had single occipital neoplasm (9 gliomas, 6 meningiomas, and 17 metastatic tumors) with ipsilateral GCT involved and thirty healthy subjects (39.2 ± 3.3 years) underwent conventional sequences scanning and diffusion tensor imaging by a 1.5T MR scanner. The diffusion-sensitive gradient direction is 13. Compare the fractional anisotropy (FA) and mean diffusivity (MD) values of healthy GCT with the corresponding values of GCT in peritumoral edema area. Perform diffusion tensor tractography (DTT) on GCT by the line propagation technique in all subjects. Results. The FA values of GCT in peritumoral edema area decreased (P = 0.001) while the MD values increased (P = 0.002) when compared with healthy subjects. There was no difference in the FA values across tumor types (P = 0.114) while the MD values of GCT in the metastatic tumor group were higher than the other groups (P = 0.001). GCTs were infiltrated in all the 9 gliomas cases, with displacement in 2 cases and disruption in 7 cases. GCTs were displaced in 6 meningiomas cases. GCTs were displaced in all the 7 metastatic cases, with disruption in 7 cases. Conclusions. DTI represents valid markers for evaluating GCT's disruption in occipital neoplasm. The disruption of GCT varies according to the properties of neoplasm.

Intra-axial brain tumors

There is a wide variety of intra-axial primary and secondary brain neoplasms. Many of them have characteristic imaging features while other tumors can present in a similar fashion. There are peculiar posttreatment imaging phenomena that can present as intra-axial mass-like lesions (such as pseudoprogression or radiation necrosis), further complicating the diagnosis and clinical follow-up of patients with intracerebral tumors. The purpose of this chapter is to present a general overview of the most common intra-axial brain tumors and peculiar posttreatment changes that are very important in the diagnosis and clinical follow-up of patients with brain tumors.

Genetics and imaging of oligodendroglial tumors

Oligodendroglial tumors are chemosensitive with a favorable prognosis compared with other histological subtypes. The genetic hallmark of co-deletion of 1p and 19q determines both treatment response and prognosis. While this test now forms part of routine histopathology diagnosis in many laboratories, alternative noninvasive imaging biomarkers of tumor genotype remain an attractive proposition. This review will focus on imaging biomarkers of molecular genetics in oligodendroglial tumors.

Unraveling the multiscale structural organization and connectivity of the human brain: the role of diffusion MRI

The structural architecture and the anatomical connectivity of the human brain show different organizational principles at distinct spatial scales. Histological staining and light microscopy techniques have been widely used in classical neuroanatomical studies to unravel brain organization. Using such techniques is a laborious task performed on 2-dimensional histological sections by skilled anatomists possibly aided by semi-automated algorithms. With the recent advent of modern magnetic resonance imaging (MRI) contrast mechanisms, cortical layers and columns can now be reliably identified and their structural properties quantified post-mortem. These developments are allowing the investigation of neuroanatomical features of the brain at a spatial resolution that could be interfaced with that of histology. Diffusion MRI and tractography techniques, in particular, have been used to probe the architecture of both white and gray matter in three dimensions. Combined with mathematical network analysis, these techniques are increasingly influential in the investigation of the macro-, meso-, and microscopic organization of brain connectivity and anatomy, both in vivo and ex vivo. Diffusion MRI-based techniques in combination with histology approaches can therefore support the endeavor of creating multimodal atlases that take into account the different spatial scales or levels on which the brain is organized. The aim of this review is to illustrate and discuss the structural architecture and the anatomical connectivity of the human brain at different spatial scales and how recently developed diffusion MRI techniques can help investigate these.

Apparent diffusion coefficient in glioblastoma with PNET-like components, a GBM variant

Glioblastoma (GBM) with primitive neuroectodermal tumor (PNET)-like (GBM-PNET) components is a rare variant of GBM. Recent studies describe PNET-like clinical behavior in these patients-with significantly increased propensity for CSF dissemination and a benefit of "PNET-like" chemotherapy. The imaging appearance of GBM-PNET is not well-described and given areas of marked cellularity in the PNET components one might expect significantly reduced diffusion on MRI. The purpose of this study is to quantitatively evaluate the diffusion characteristics in GBM-PNET and compare them with conventional GBMs. Nine patients with surgical specimens yielding GBM-PNET were identified from the UCSF Pathology files. MR images of these patients were reviewed retrospectively. DWI (diffusion-weighted imaging) sequences were analyzed with multiple regions of interests placed within the tumor, and ADC (apparent diffusion coefficient) values were measured. Results were compared to previously published ADC values in pathology-proven conventional GBM cases from our institution. Reduced ADC was seen in GBM-PNET (mean 581 × 10(-6) mm(2)/s, range 338-817) compared to previously published mean of 1,030 × 10(-6) mm(2)/s in the enhancing components of conventional GBMs. We report substantially reduced ADC values in GBM-PNETs compared to conventional GBMs. If demonstrated in a larger sample, when areas of marked reduced diffusion are seen in a suspected GBM, MRI may appropriately direct tissue sampling and can advocate a thorough search for PNET-like components on histopathology. These patients may have a higher chance of developing CSF dissemination and may benefit from "PNET-like" platinum-based chemotherapy.

Lower apparent diffusion coefficients indicate distinct prognosis in low-grade and high-grade glioma

Tumor grade and molecular variants influence the survival of patients with glioma. The apparent diffusion coefficient (ADC) map is a non-invasive tool for evaluating the outcomes and response to therapy in glioma. In this study, we investigated the correlation between the tumor grade and prognostic biomarkers with the ADC in glioma patients. Eighty-two patients with supratentorial glioma were identified via analysis of surgical specimens and neuroradiological data. Using the World Health Organization grade, histological subtype, and molecular variants (1p/19q codeletion, isocitrate dehydrogenase 1/2 mutation, Ki-67 index, O6-methylguanine DNA methyltransferase, P53, and vascular endothelial growth factor immunoactivity) as prognostic biomarkers, we performed receiver operating characteristic analysis and multiple linear regression to assess the association between the magnetic resonance diffusion parameter and mean ADC and the prognostic factors of glioma pathology. Univariate analysis and multiple linear regression revealed inverse correlations between the ADC values and the tumor grade, oligodendrocytoma histology, and 1p/19q codeletion. A threshold mean ADC value could predict the 1p/19q chromosomal status in WHO II gliomas with 72 % sensitivity and 88 % specificity (area under the curve 0.82, 95 % confidence interval 0.68-0.97) and could distinguish low-grade glioma with low-risk factors from the high-risk group (P < 0.01). The mean ADC value could be used as a non-invasive tool to evaluate the prognosis of supratentorial glioma patients. A threshold mean ADC value could be used to predict the 1p/19q codeletion and to identify low-risk low-grade gliomas (LGGs). Lower ADC values are indicative of a favorable prognosis in LGGs.

Can diffusion tensor imaging noninvasively detect IDH1 gene mutations in astrogliomas? A retrospective study of 112 cases

BACKGROUND AND PURPOSE

IDH1 mutational status probably plays an important role in the predictive response for patients with astroglioma. This study explores whether DTI metrics are able to noninvasively detect IDH1 status in astrogliomas.

MATERIALS AND METHODS

The DTI data of 112 patients with pathologically proven astroglioma (including 25, 12, and 10 cases with IDH1 mutation and 11, 11, and 43 cases without mutation in grades II, III, and IV, respectively) were retrospectively reviewed. The maximal fractional anisotropy, minimal ADC, ratio of maximal fractional anisotropy, and ratio of minimal ADC in the tumor body were measured. In the same World Health Organization grading, the imaging parameters of patients with and without IDH1 R132H mutation were compared by means of optimal metrics for detecting mutations. Receiver operating characteristic curve analysis was performed.

RESULTS

The maximal fractional anisotropy and ratio of maximal fractional anisotropy values had statistical significance between patients with IDH1 R132H mutation and those without mutation in astrogliomas of grades II and III. The areas under the curve for maximal fractional anisotropy and ratio of maximal fractional anisotropy were both 0.92 in grade II and 0.80 and 0.82 in grade III. The minimal ADC value and ratio of minimal ADC value also demonstrated statistical significance between patients with mutation and those without mutation in all astroglioma grades. The areas under the curve for minimal ADC were 0.94 (II), 0.76 (III), and 0.66 (IV), and the areas under the curve for ratio of minimal ADC were 0.93 (II), 0.83 (III), and 0.70 (IV).

CONCLUSIONS

Fractional anisotropy and ADC from DTI can noninvasively detect IDH1 R132H mutation in astrogliomas.

Detection rate, location, and size of pulmonary nodules in trimodality PET/CT-MR: comparison of low-dose CT and Dixon-based MR imaging

OBJECTIVE

The objective of this study was to prospectively compare the detection rate, the location, and the size of pulmonary nodules in low-dose computed tomography (CT) and in magnetic resonance (MR) imaging with a 3-dimensional (3D) dual-echo gradient-echo (GRE) pulse sequence using a trimodality positron emission tomography (PET)/CT-MR setup.

METHODS

Forty consecutive patients (25 men and 15 women; mean [SD] age 64 [12] years) referred for staging of malignancy were prospectively included in this single-center, Institutional Review Board-approved study. Imaging using trimodality PET/CT-MR setup (full ring, time-of-flight PET/CT and 3-T whole-body MR imager) comprised PET, low-dose CT for anatomic referencing/attenuation correction of PET, and MR imaging with 3D dual-echo GRE pulse sequence, allowing the reconstruction of water-only (WO) and in-phase (IP) images. Two blinded and independent readers assessed all images randomly for the presence, the location, and the size of pulmonary nodules. Detection rates, defined as the proportion of screened participants with at least 1 pulmonary nodule, were compared between low-dose CT and MR imaging including both WO and IP images.

RESULTS

Inter-reader agreements were high regarding the location (k = 0.93-0.98) and the size of pulmonary nodules (intraclass correlation analysis = 0.94-0.98) in CT and in MR imaging. Computed tomographic scans revealed 66 pulmonary nodules in 34 of the 40 patients (85%), whereas WO and IP images showed 56 and 58 pulmonary nodules in 33 of the 40 patients (83%), respectively. The detection rates of CT and MR imaging were similar (P's >; 0.05) regarding all nodules, 18F-Fluordesoxyglucose-positive pulmonary nodules, and 18F-Fluordesoxyglucose-negative pulmonary nodules. The size of pulmonary nodules was significantly smaller on WO (P <; 0.05; mean difference, 3 mm; 95% confidence interval, - 13 to 18 mm) and IP images (P <; 0.001; mean difference, 4 mm; 95% confidence interval, -5 to 12 mm) compared with in CT.

CONCLUSIONS

Our study indicates that a 3D Dixon-based, dual-echo GRE pulse sequence might be suitable for lung imaging in clinical whole-body PET/MR examinations. Although the detection rates were lower, there was no statistically significant difference on a patient-based evaluation concerning detection rates of pulmonary nodules compared with low-dose CT. Assessment of nodule location can be performed equally well with MR imaging.

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.

Regional variation in histopathologic features of tumor specimens from treatment-naive glioblastoma correlates with anatomic and physiologic MR Imaging

Histopathologic evaluation of glioblastoma multiforme (GBM) at initial diagnosis is typically performed on tissue obtained from regions of contrast enhancement (CE) as depicted on gadolinium-enhanced, T1-weighted images. The non-enhancing (NE) portion of the lesion, which contains both reactive edema and infiltrative tumor, is only partially removed due to concerns about damaging functioning brain. The purpose of this study was to evaluate histopathologic and physiologic MRI features of image-guided tissue specimens from CE and NE regions to investigate correlations between imaging and histopathologic parameters. One hundred nineteen tissue specimens (93 CE and 26 NE regions) were acquired from 51 patients with newly diagnosed GBM by utilizing stereotactic image-guided sampling. Variables of anatomic, diffusion-weighted imaging (DWI), and dynamic susceptibility-weighted, contrast-enhanced perfusion imaging (DSC) from each tissue sample location were obtained and compared with histopathologic features such as tumor score, cell density, proliferation, architectural disruption, hypoxia, and microvascular hyperplasia. Tissue samples from CE regions had increased tumor score, cellular density, proliferation, and architectural disruption compared with NE regions. DSC variables such as relative cerebral blood volume, peak height, and recovery factor were significantly higher, and the percentage of signal intensity recovery was significantly lower in the CE compared with the NE regions. DWI variables were correlated with histopathologic features of GBM within NE regions. Image-guided tissue acquisition and assessment of residual tumor from treatment-naive GBM should be guided by DSC in CE regions and by DWI in NE regions.