Comparison of perfusion, diffusion, and MR spectroscopy between low-grade enhancing pilocytic astrocytomas and high-grade astrocytomas

Decoding the puzzle: A multidisciplinary systematic review of adult brainstem glioma

Adult brainstem gliomas (BSGs) are a group of rare central nervous system tumors with varying prognoses and controversial standard treatment strategies. To provide an overview of current trends, a systematic review using the PRISMA guidelines, Class of evidence (CE) and strength of recommendation (SR), was conducted. The review identified 27 studies. Surgery was found to have a positive impact on survival, particularly for focal lesions with CE II SR C. Stereotactic image-guided biopsy was recommended when resective surgery was not feasible with CE II and SR B. The role of systemic treatments remains unclear. Eight studies provided molecular biology data. This review gathers crucial literature on diagnosis and management of adult BSGs. It provides evidence-based guidance with updated recommendations for diagnosing and treating, taking into account recent molecular and genetic advancements. The importance of brain biopsy is emphasized to optimize treatment using emerging genetic-molecular findings and explore potential targeted therapies.

Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors

This study delineates the pivotal role of imaging within the field of neurology, emphasizing its significance in the diagnosis, prognostication, and evaluation of treatment responses for central nervous system (CNS) tumors. A comprehensive understanding of both the capabilities and limitations inherent in emerging imaging technologies is imperative for delivering a heightened level of personalized care to individuals with neuro-oncological conditions. Ongoing research in neuro-oncological imaging endeavors to rectify some limitations of radiological modalities, aiming to augment accuracy and efficacy in the management of brain tumors. This review is dedicated to the comparison and critical examination of the latest advancements in diverse imaging modalities employed in neuro-oncology. The objective is to investigate their respective impacts on diagnosis, cancer staging, prognosis, and post-treatment monitoring. By providing a comprehensive analysis of these modalities, this review aims to contribute to the collective knowledge in the field, fostering an informed approach to neuro-oncological care. In conclusion, the outlook for neuro-oncological imaging appears promising, and sustained exploration in this domain is anticipated to yield further breakthroughs, ultimately enhancing outcomes for individuals grappling with CNS tumors.

Differentiation of Pilocytic Astrocytoma from Glioblastoma using a Machine-Learning framework based upon quantitative T1 perfusion MRI

BACKGROUND AND PURPOSE

Differentiation of pilocytic astrocytoma (PA) from glioblastoma is difficult using conventional MRI parameters. The purpose of this study was to differentiate these two similar in appearance tumors using quantitative T₁ perfusion MRI parameters combined under a machine learning framework.

MATERIALS AND METHODS

This retrospective study included age/sex and location matched 26 PA and 33 glioblastoma patients with tumor histopathological characterization performed using WHO 2016 classification. Multi-parametric MRI data were acquired at 3 T scanner and included T₁ perfusion and DWI data along with conventional MRI images. Analysis of T₁ perfusion data using a leaky-tracer-kinetic-model, first-pass-model and piecewise-linear-model resulted in multiple quantitative parameters. ADC maps were also computed from DWI data. Tumors were segmented into sub-components such as enhancing and non-enhancing regions, edema and necrotic/cystic regions using T₁ perfusion parameters. Enhancing and non-enhancing regions were combined and used as an ROI. A support-vector-machine classifier was developed for the classification of PA versus glioblastoma using T₁ perfusion MRI parameters/features. The feature set was optimized using a random-forest based algorithm. Classification was also performed between the two tumor types using the ADC parameter.

RESULTS

T₁ perfusion parameter values were significantly different between the two groups. The combination of T₁ perfusion parameters classified tumors more accurately with a cross validated error of 9.80% against that of ADC's 17.65% error.

CONCLUSION

The approach of using quantitative T₁ perfusion parameters based upon a support-vector-machine classifier reliably differentiated PA from glioblastoma and performed better classification than ADC.

Glioblastoma masquerading as a cystic brain lesion: A case report and evidence-based review

INTRODUCTION AND IMPORTANCE

In adults, glioblastomas account for approximately 12-15 % of primary intracranial neoplasms. In current standard-of-care treatment, glioblastomas have a 5-year survival rate of ~7.5 % and a median survival of ~15 months. Glioblastoma exhibits a highly variable imaging appearance, but the thick and irregular ring enhancement surrounding a necrotic core with infiltrative growth is the most prevalent imaging pattern. Glioblastoma with a cystic component (also known as cystic glioblastoma) is a rare presentation that can be misleading and often mistaken for other cystic brain lesions.

CASE PRESENTATION

In this report, we present a case of a 43-year-old woman who presented to the emergency department with a 2-month history of progressive neurologic manifestations that was attributed to a right-sided cystic brain lesion detected on routine imaging studies, which was later characterized as a cystic glioblastoma based on specific imaging and molecular studies.

CLINICAL DISCUSSION

We highlight the importance of combining radiological and molecular modalities with clinical suspicion for a better characterization of cystic brain lesions and including glioblastoma in the list of potential diagnoses. Furthermore, we provide a comprehensive, evidence-based review of the entity of cystic glioblastoma and how the existence of the cystic component might affect the management and the overall prognosis.

CONCLUSION

Several characteristics make cystic glioblastoma unique. However, it is also capable of mimicking other benign cystic brain lesions, delaying definitive diagnosis and hence the most appropriate management plan.

Update for astrocytomas: medical and surgical management considerations

Astrocytomas include a wide range of tumors with unique mutations and varying grades of malignancy. These tumors all originate from the astrocyte, a star-shaped glial cell that plays a major role in supporting functions of the central nervous system (CNS), including blood-brain barrier (BBB) development and maintenance, water and ion regulation, influencing neuronal synaptogenesis, and stimulating the immunological response. In terms of epidemiology, glioblastoma (GB), the most common and malignant astrocytoma, generally occur with higher rates in Australia, Western Europe, and Canada, with the lowest rates in Southeast Asia. Additionally, significantly higher rates of GB are observed in males and non-Hispanic whites. It has been suggested that higher levels of testosterone observed in biological males may account for the increased rates of GB. Hereditary syndromes such as Cowden, Lynch, Turcot, Li-Fraumeni, and neurofibromatosis type 1 have been linked to increased rates of astrocytoma development. While there are a number of specific gene mutations that may influence malignancy or be targeted in astrocytoma treatment, O 6-methylguanine-DNA methyltransferase (MGMT) gene function is an important predictor of astrocytoma response to chemotherapeutic agent temozolomide (TMZ). TMZ for primary and bevacizumab in the setting of recurrent tumor formation are two of the main chemotherapeutic agents currently approved in the treatment of astrocytomas. While stereotactic radiosurgery (SRS) has debatable implications for increased survival in comparison to whole-brain radiotherapy (WBRT), SRS demonstrates increased precision with reduced radiation toxicity. When considering surgical resection of astrocytoma, the extent of resection (EoR) is taken into consideration. Subtotal resection (STR) spares the margins of the T1 enhanced magnetic resonance imaging (MRI) region, gross total resection (GTR) includes the margins, and supramaximal resection (SMR) extends beyond the margin of the T1 and into the T2 region. Surgical resection, radiation, and chemotherapy are integral components of astrocytoma treatment.

Common and uncommon neuroimaging manifestations of ataxia: an illustrated guide for the trainee radiologist. Part 2 - neoplastic, congenital, degenerative, and hereditary diseases

Abstract Ataxia is defined as a lack of coordination of voluntary movement, caused by a variety of factors. Ataxia can be classified by the age at onset and type (chronic or acute). The causative lesions involve the cerebellum and cerebellar connections. The correct, appropriate use of neuroimaging, particularly magnetic resonance imaging, can make the diagnosis relatively straightforward and facilitate implementation of the appropriate clinical management. The purpose of this pictorial essay is to describe the imaging findings of ataxia, based on cases obtained from the archives of a tertiary care hospital, with a review of the most important findings. We also discuss and review the imaging aspects of neoplastic diseases, malformations, degenerative diseases, and hereditary diseases related to ataxia.

Advanced magnetic resonance imaging findings of cerebellar hemangioblastomas: A report of three cases and a literature review

On conventional magnetic resonance imaging (MRI), hemangioblastomas typically appear as mural nodules with an adjacent surrounding cyst or a solid mass in the cerebellum. However, hemangioblastomas sometimes cannot be reliably distinguished using this imaging technique from other tumors, especially pilocytic astrocytomas and metastatic tumors, because of their similar imaging findings and locations. Herein, we report three cases of cerebellar hemangioblastomas and review their findings on conventional and advanced MRI, including diffusion-weighted imaging (DWI), dynamic susceptibility-weighted contrast-enhanced perfusion-weighted imaging (DSC-PWI), and magnetic resonance spectroscopy (MRS). Solid contrast-enhanced lesions of hemangioblastomas showed increased apparent diffusion coefficient values on DWI, increased relative cerebral blood volume ratio on DSC-PWI, and high lipid/lactate peak on MRS. Therefore, advanced MRI techniques can be helpful in understanding the pathological and metabolic changes of hemangioblastomas and may be useful for their characterization.

1H-MR spectroscopy in grading of cerebral glioma: A new view point, MRS image quality assessment

Background

Noninvasive preoperative prediction of histological grading is essential for clinical management of cerebral glioma.

Purpose

This study aimed to investigate the association between the image quality assessment of 1H magnetic resonance spectroscopy and accurate grading of glioma.

Materials and Methods

98 glioma patients confirmed by pathology were retrospectively recruited in this single-center study. All patients underwent 1H-MRS examination at 3.0T before surgery. According to WHO standards, all cases were divided into two groups: low-grade glioma (grade I and II, 48 cases) and high-grade glioma (grades III and IV, 50 cases). The metabolite ratios in both grades were calculated before and after image quality assessment. The area under the receiver operating characteristic (ROC) curve was used to evaluate the capacity of each ratio in glioma grading.

Results

The Cho/Cr, Cho/NAA and NAA/Cr metabolite ratios had certain differences in each glioma group before and after MRS image quality assessment. In the low-grade glioma group, there was a dramatic difference in the Cho/Cr ratio before and after image quality assessment (p = 0.011). After MRS image quality assessment, the accuracy of glioma grading was significantly improved. The Cho/Cr ratio with 83.3% sensitivity and 93.7% specificity is the best index of glioma grading, with the optimal cutoff value of the Cho/Cr ratio being 3.72.

Conclusion

The image quality of MRS does affect the metabolite ratios and the results of glioma grading. MRS image quality assessment can observably improve the accuracy rate of glioma grading. The Cho/Cr ratio has the best diagnostic performance in differentiating high-grade from low-grade glioma.

A fully automatic multiparametric radiomics model for differentiation of adult pilocytic astrocytomas from glioblastomas

OBJECTIVES

To develop a fully automatic radiomics model to differentiate adult pilocytic astrocytomas (PA) from high-grade gliomas (HGGs).

METHODS

This retrospective study included 302 adult patients with PA (n = 62) or HGG (n = 240). The patients were randomly divided into training (n = 211) and test (n = 91) sets. Clinical data were obtained, and radiomic features (n = 372) were extracted from multiparametric MRI with automatic tumour segmentation. After feature selection with F-score, a Light Gradient Boosting Machine classifier with subsampling was trained to develop three models: (1) clinical model, (2) radiomics model, and (3) combined clinical and radiomics model. Human performance was also assessed. The performance of the classifier was validated in the test set. SHapley Additive exPlanations (SHAP) was applied to explore the interpretability of the model.

RESULTS

A total of 15 radiomic features were selected. In the test set, the combined clinical and radiomics model (area under the curve [AUC], 0.93) showed a significantly higher performance than the clinical model (AUC, 0.79, p = 0.037) and had a similar performance to the radiomics model (AUC, 0.92, p = 0.828). The combined clinical and radiomics model also showed a significantly higher performance than humans (AUC, 0.76-0.81, p < 0.05). The model explanation by SHAP suggested that lower intratumoural heterogeneity from T2-weighted images was highly associated with PA diagnosis.

CONCLUSIONS

The fully automatic combined clinical and radiomics model may be helpful for differentiating adult PAs from HGGs.

KEY POINTS

• Differentiating adult PAs from HGGs is challenging because PAs may manifest a large spectrum of imaging presentations, often including aggressive imaging features. • The fully automatic combined clinical and radiomics model showed a significantly higher performance than the clinical model or humans. • The model explanation by SHAP suggested that second-order features from T2-weighted imaging were important in diagnosis and might reflect the underlying pathophysiology that PAs have lesser tissue heterogeneity than HGGs.

Pearls and Pitfalls of Imaging in Pediatric Brain Tumors

The central nervous system (CNS) tumors constitute the most common type of solid tumors in the pediatric population. The cerebral and cerebellar parenchyma are the most common site of pediatric CNS neoplasms. Imaging plays an important role in detection, characterization, staging and prognostication of brain tumors. The focus of the current article is pediatric brain tumor imaging with emphasis on pearls and pitfalls of conventional and advanced imaging in various pediatric brain tumor subtypes. The article also elucidates changes in brain tumor terms and entities as applicable to pediatric patients, updated as per World Health Organization (WHO) 2016 classification of primary CNS tumors. This classification introduced the genetic and/or molecular information of primary CNS neoplasms as part of comprehensive tumor pathology report in the routine clinical workflow. The concepts from 2016 classification have been further refined based on current research, by the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) group and published in the form of updates. The updates serve as guidelines in the time interval between WHO updates and expect to be broadly adopted in the subsequent WHO classification. The current review covers most pediatric brain tumors except pituitary tumors, meningeal origin tumors, nerve sheath tumors and CNS lymphoma/leukemia.

Dynamic susceptibility contrast and diffusion-weighted MRI in posterior fossa pilocytic astrocytoma and medulloblastoma

BACKGROUND AND PURPOSE

The utility of perfusion MRI in distinguishing between pilocytic astrocytoma (PA) and medulloblastoma (MB) is unclear. This study aimed to evaluate the diagnostic and prognostic performance of dynamic susceptibility contrast (DSC)-MRI parameters and apparent diffusion coefficient (ADC) values between PA and MB.

METHODS

Between January 2012 and August 2021, 49 (median, 7 years [range, 1-28 years]; 28 females) and 35 (median, 8 years [1-24 years]; 12 females) patients with pathologically confirmed PA and MB, respectively, were included. The normalized relative cerebral blood volume and flow (nrCBV and nrCBF) and mean and minimal normalized ADC (nADCmean and nADCmin) values were calculated using volume-of-interest analyses. Diagnostic performance and Pearson's correlation with progression-free survival were also evaluated.

RESULTS

The MB group showed a significantly higher nrCBV and nrCBF (nrCBV: 1.69 [0.93-4.23] vs. 0.95 [range, 0.37-2.28], p = .0032; nrCBF: 1.62 [0.93-3.16] vs. 1.07 [0.46-2.26], p = .0084) and significantly lower nADCmean and nADCmin (nADCmean: 0.97 [0.70-1.68] vs. 2.21 [1.44-2.80], p < .001; nADCmin: 0.50 [0.19-0.89] vs. 1.42 [0.89-2.20], p < .001) than the PA group. All parameters exhibited good diagnostic ability (accuracy >0.80) with nADCmin achieving the highest score (accuracy = 1). A moderate correlation was found between nADCmean and progression-free survival for MB (r = 0.44, p = .0084).

CONCLUSIONS

DSC-MRI parameters and ADC values were useful for distinguishing between PA and MB. A lower ADC indicated an unfavorable MB prognosis, but the DSC-MRI parameters did not correlate with progression-free survival in either group.

Intra-tumoral susceptibility signal: a post-processing technique for objective grading of astrocytoma with susceptibility-weighted imaging

BACKGROUND

Susceptibility-weighted imaging (SWI) is sensitive to the accumulation of paramagnetic substances, such as hemorrhage and increased venous vasculature, both being frequently found in high-grade tumors. The purpose of this retrospective study is to differentiate high-grade and low-grade astrocytoma by objectively measuring quantitative intra-tumoral susceptibility signals (qITSS) on SWI.

METHODS

Precontrast SWI and 3D contrast-enhanced T1WI of 65 patients with astrocytoma were collected at 1.5 Tesla. All tumors were histologically confirmed and classified into two groups: high grade (WHO grade III and IV, n=50) and low grade (WHO grade II, n=15). After manual delineation of the tumor on T1WI, normalized contrast (NC) was calculated voxel by voxel within the tumor by using the concept of contrast to noise ratio. Thresholding on NC was applied to detect qITSS, and the volumetric percentage of qITSS can be obtained for each tumor. Two-sample t-test was applied to examine significant difference of qITSS percentage between high-grade and low-grade astrocytoma for different NC thresholds, ranging from 4 to 20. Receiver operating characteristic analysis was performed to evaluate the performance of differentiation.

RESULTS

P value was less than 0.01 for a large range of NC thresholds [4-20], reflecting significant difference of qITSS percentage between high-grade and low-grade astrocytoma. The area under the receiver operating characteristic curve was larger than 0.9 at NC thresholds from 8 to 16 and peaks at 0.949 with a NC threshold of 14. It was shown that astrocytoma grading by qITSS percentage is successful for a wide range of NC threshold, demonstrating robustness on threshold selection.

CONCLUSIONS

Without relying on the selection of slice position and at the same time providing objective identification of hypointense signal in SWI, the qITSS percentage can be used to distinguish high-grade and low-grade astrocytoma reliably.

Clinical report of a brain magnetic resonance imaging finding in Noonan syndrome

Noonan syndrome (NS) is an autosomal dominant disease caused by aberrant up-regulated signaling through RAS GTPase. It is characterized by facial dysmorphisms, short stature, congenital heart defects, malformations of rib cage bones, bleeding problems, learning difficulties, or mild intellectual disability. Additional intracranial findings in NS patients include tumors, midline anomalies, and malformations of cortical development. In this report, we present the case of a young female patient, with a known diagnosis of Noonan syndrome that in complete well being developed two brain lesions, in the right nucleus pallidus and in the left cerebellar hemisphere respectively, whose location and signal on MRI looked similar to neurofibromatosis type 1 unidentified bright objects (UBOs), and whose spectroscopic characteristics excluded neoplasms.

Differentiation between supratentorial pilocytic astrocytoma and extraventricular ependymoma using multiparametric MRI

BACKGROUND

The differentiation of supratentorial pilocytic astrocytomas (STPAs) and supratentorial extraventricular ependymomas (STEEs) is clinically pivotal because of distinct therapeutic management and prognosis, which is sometimes challenging to both neuroradiologists and pathologists.

PURPOSE

To explore and compare the conventional and advanced magnetic resonance imaging (MRI) features between STPA and STEE.

MATERIAL AND METHODS

A total of 23 patients with STPAs and 23 patients with STEEs were reviewed in this study. All patients performed conventional MRI, susceptibility-weighted imaging (SWI), and diffusion-weighted imaging (DWI), and 34 patients (17 with STPAs and 17 with STEEs) examined dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) in addition. Clinical data, conventional MRI features, minimum relative apparent diffusion coefficient ratio (rADC_min), and maximum relative cerebral blood volume ratio (rCBV_max) were compared between the two groups and subgroups. The optimal cutoff values of rADC_min and rCBV_max with sensitivity and specificity were calculated.

RESULTS

STPA manifested similar to STEE as a solid-cystic mass but more frequently presented with a marked enhancing deep nodule (P = 0.02), no peritumoral edema (P = 0.036), higher rADC_min value (2.0 ± 0.5 vs. 0.9 ± 0.2; P < 0.001), and lower rCBV_max value (2.1 ± 0.4 vs. 14.4 ± 5.5; P < 0.001). The cutoff value of >1.39 for rADC_min and ≤ 2.81 for rCBV_max produced a high sensitivity of 95.65% and 100.0%, respectively, and all produced a specificity of 100.0% in differentiating STPAs from STEEs.

CONCLUSION

Multiparametric MRI techniques including conventional MRI, DWI, and DSC-PWI contribute to the differential diagnosis of STPA and STEE.

A diagnostic tree for differentiation of adult pilocytic astrocytomas from high-grade gliomas

BACKGROUND

To develop a diagnostic tree analysis (DTA) model based on demographical information and conventional MRI for differential diagnosis of adult pilocytic astrocytomas (PAs) and high-grade gliomas (HGGs; World Health Organization grade III-IV).

METHODS

A total of 357 adult patients with pathologically confirmed PA (n = 65) and HGGs (n = 292) who underwent conventional MRI were included. The patients were randomly divided into training (n = 250) and validation (n = 107) datasets to assess the diagnostic performance of the DTA model. The DTA model was created using a classification and regression tree algorithm on the basis of demographical and MRI findings.

RESULTS

In the DTA model, tumor location (on cerebellum, brainstem, hypothalamus, optic nerve, or ventricle), cystic mass with mural nodule appearance, presence of infiltrative growth, and major axis (cutoff value, 2.9 cm) were significant predictors for differential diagnosis of adult PAs and HGGs. The AUC, accuracy, sensitivity, and specificity were 0.94 (95% confidence interval 0.86-1.00), 96.2%, 89.5%, and 97.7%, respectively, in the test set. The accuracy of the DTA model was significantly higher than the no-information rate in the test (96.2 % vs 85.0%, P < 0.001) set.

CONCLUSION

The DTA model based on MRI findings may be useful for differential diagnosis of adult PA and HGGs.

Radiohistogenomics of pediatric low-grade neuroepithelial tumors

PURPOSE

In addition to histology, genetic alteration is now required to classify many central nervous system (CNS) tumors according to the most recent World Health Organization CNS tumor classification scheme. Although that is still not the case for classifying pediatric low-grade neuroepithelial tumors (PLGNTs), genetic and molecular features are increasingly being used for making treatment decisions. This approach has become a standard clinical practice in many specialized pediatric cancer centers and will likely be more widely practiced in the near future. This paradigm shift in the management of PLGNTs necessitates better understanding of how genetic alterations influence histology and imaging characteristics of individual PLGNT phenotypes.

METHODS

The complex association of genetic alterations with histology, clinical, and imaging of each phenotype of the extremely heterogeneous PLGNT family has been addressed in a holistic approach in this up-to-date review article. A new imaging stratification scheme has been proposed based on tumor morphology, location, histology, and genetics. Imaging characteristics of each PLGNT entity are also depicted in light of histology and genetics.

CONCLUSION

This article reviews the association of specific genetic alteration with location, histology, imaging, and prognosis of a specific tumor of the PLGNT family and how that information can be used for better imaging of these tumors.

Combined application of MRS and DWI can effectively predict cell proliferation and assess the grade of glioma: A prospective study

In order to assess combined application of MRS and DWI for prediction cell proliferation and grade diagnosis of glioma, We prospectively collected the Cho/Cr, Cho/NAA, Cr/NAA of MRS and tumor parenchyma ADC (ADC_T), contralateral mirror brain tissue ADC (ADC_H), rADC (rADC = ADC_T/ADC_H). According to postoperative pathology, the patients were divided into two groups: LGG group and HGG group, compared differences of age, gender, Ki67, MRS, DWI between two groups. Next, we analyzed the correlation between MRS, DWI and Ki67. On this basis, the sensitivity and specificity of MRS, DWI and MRS combined with DWI (MRS + DWI) in diagnosis of glioma grade were evaluated. The differences of Ki67, Cho/Cr, Cho/NAA, Cr/NAA, ADC_T, rADC between LGG group and HGG group were statistically significant (p = 0.000, 0.000, 0.000, 0.008, 0.000, and 0.000 respectively). From ROC curve, area under the curve (AUC), sensitivity and specificity of Cho/Cr, Cho/NAA, Cr/NAA, ADC_T, rADC, PRE (MRS + DWI) were (0.901, 86.7%, 85.7%), (0.876, 80.0%, 82.1%), (0.704, 63.3%, 71.4%), (0.862, 82.1%, 83.3%), (0.820, 75.0%, 76.7%), (0.920, 86.7%, 89.3%), respectively. Fisher's linear discriminant functions results suggest: Y₁ = -20.447 + 3.46•X₁ + 17.141•X₂ (LGG), Y₂ = -19.415 + 4.828•X₁ + 14.543•X₂ (HGG). Our study suggested that MRS and DWI can effectively predict cell proliferation preoperative. MRS combined with DWI can further improve sensitivity and specificity in assessing the grade of glioma.

The Evaluation of Radiomic Models in Distinguishing Pilocytic Astrocytoma From Cystic Oligodendroglioma With Multiparametric MRI

PURPOSE

To assess whether a machine-learning model based on texture features extracted from multiparametric magnetic resonance imaging could yield an accurate diagnosis in differentiating pilocytic astrocytoma from cystic oligodendrogliomas.

MATERIALS AND METHODS

The preoperative images from multisequences were used for tumor segmentation. Radiomic features were extracted and selected for machine-learning models. Semantic features and selected radiomic features from training data set were built, and the performance of each model was evaluated by receiver operating characteristic curve and accuracy from isolated testing data set.

RESULTS

In terms of different sequences, the best classifier was built by radiomic features extracted from enhanced T1WI-based classifier. The best model in our study turned out to be the gradient boosted trees classifier with an area under curve value of 0.99.

CONCLUSION

Our study showed that gradient boosted trees based on texture features extracted from enhanced T1WI could become an additional tool for improving diagnostic accuracy to differentiate pilocytic astrocytoma from cystic oligodendroglioma.

The diagnostic value of quantitative analysis of ASL, DSC-MRI and DKI in the grading of cerebral gliomas: a meta-analysis

OBJECTIVE

To perform quantitative analysis on the efficacy of using relative cerebral blood flow (rCBF) in arterial spin labeling (ASL), relative cerebral blood volume (rCBV) in dynamic magnetic sensitivity contrast-enhanced magnetic resonance imaging (DSC-MRI), and mean kurtosis (MK) in diffusion kurtosis imaging (DKI) to grade cerebral gliomas.

METHODS

Literature regarding ASL, DSC-MRI, or DKI in cerebral gliomas grading in both English and Chinese were searched from PubMed, Embase, Web of Science, CBM, China National Knowledge Infrastructure (CNKI), and Wanfang Database as of 2019. A meta-analysis was performed to evaluate the efficacy of ASL, DSC-MRI, and DKI in the grading of cerebral gliomas.

RESULT

A total of 54 articles (11 in Chinese and 43 in English) were included. Three quantitative parameters in the grading of cerebral gliomas, rCBF in ASL, rCBV in DSC-MRI, and MK in DKI had the pooled sensitivity of 0.88 [95% CI (0.83,0.92)], 0.92 [95% CI (0.83,0.96)], 0.88 [95% CI (0.82,0.92)], and the pooled specificity of 0.91 [95% CI (0.84,0.94)], 0.81 [95% CI (0.73,0.88)], 0.86 [95% CI (0.78,0.91)] respectively. The pooled area under the curve (AUC) were 0.95 [95% CI (0.93,0.97)], 0.91 [95% CI (0.89,0.94)], 0.93 [95% CI (0.91,0.95)] respectively.

CONCLUSION

Quantitative parameters rCBF, rCBV and MK have high diagnostic accuracy for preoperative grading of cerebral gliomas.

The effect of semi-quantitative T1-perfusion parameters for the differentiation between pediatric medulloblastoma and ependymoma

Background

The differentiation between medulloblastomas and ependymomas plays an important role in treatment planning and prognosis for children. This study aims to investigate the role of T1-perfusion parameters during the differentiation between medulloblastomas and ependymomas in children. The institutional review board approved this prospective study. The brain magnetic resonance imaging (MRI) protocol, including axial T1-perfusion, was assessed in 26 patients, divided into a medulloblastoma group (group 1, n = 22) and an ependymoma group (group 2, n = 4). The quantified region of interest (ROI) values for tumors and the tumor to parenchyma ratios were collected and compared between the two groups. Receiver operating characteristic (ROC) curve analysis and the Youden index were utilized to identify the best cut-off, sensitivity, specificity, and area under the curve (AUC) values for the independent T1-perfusion parameters.

Results

The relative enhancement, maximum enhancement, maximum relative enhancement, time to peak, and AUC values for medulloblastomas were significantly higher than those for ependymomas (p < 0.05). Furthermore, the maximum enhancement and maximum relative enhancement for medulloblastoma to parenchyma ratios were also significantly higher than those for ependymomas. A cut-off maximum enhancement value of 100.25 was identified as sufficient to discriminate between medulloblastoma and ependymoma and resulted in a sensitivity of 90.9%, a specificity of 100%, and an AUC of 94.3%.

Conclusion

A cut-off maximum enhancement value of 100.25 derived from T1-perfusion was able to discriminate between medulloblastoma and ependymoma, with high sensitivity, specificity, and accuracy values.

Comparing amide proton transfer imaging with dynamic susceptibility contrast-enhanced perfusion in predicting histological grades of gliomas: a meta-analysis

Background

As a subtype of chemical exchange saturation transfer imaging without contrast agent administration, amide proton transfer (APT) imaging has demonstrated the potential for differentiating the histologic grades of gliomas. Dynamic susceptibility contrast-enhanced perfusion, a perfusion-weighted imaging technique, is a well-established technique in grading gliomas.

Purpose

To compare the ability of amide proton transfer and dynamic susceptibility contrast-enhanced imaging for predicting the grades of gliomas.

Material and Methods

A comprehensive literature search was performed independently by two observers to identify articles about the diagnostic performance of amide proton transfer and dynamic susceptibility contrast-enhanced perfusion in predicting the grade of gliomas. Summary estimates of diagnostic accuracy were obtained by using a random-effects model.

Results

Of 179 studies identified, 23 studies were included the analysis. Eight studies evaluated amide proton transfer and 16 studies evaluated dynamic susceptibility contrast-enhanced perfusion with the parameter rCBV. The pooled sensitivities and specificities of each study’s best performing parameter were 88% (95% confidence interval [CI] 74–95) and 89% (95% CI 78–95) for amide proton transfer, and 95% (95% CI 87–98), 88% (95% CI 81–93) for perfusion-weighted imaging–dynamic susceptibility contrast-enhanced perfusion, respectively. The pooled sensitivities and specificities for grading gliomas using the two most commonly evaluated parameters, were 92% (95% CI 80–97) and 90% (95% CI 75–96) for APTmax, and 97% (95% CI 91–99) and 87% (95% CI 80–92) for rCBVmax, respectively.

Conclusion

Considering the similar performance of APT and dynamic susceptibility contrast-enhanced (DSC) in predicting glioma grade, the former method appears preferable since it needs no contrast agent.

Accuracy of apparent diffusion coefficient values and magnetic resonance imaging in differentiating suprasellar germinomas from chiasmatic/hypothalamic gliomas

OBJECTIVE

The aim of this study was to differentiate suprasellar germinomas from chiasmatic/hypothalamic gliomas (CHGs) using apparent diffusion coefficient (ADC) values and magnetic resonance imaging (MRI) characteristics.

MATERIALS AND METHODS

A cross-sectional study was conducted on 11 patients with suprasellar germinomas and 11 patients with CHGs who underwent pretreatment MRI. The ADC values (minimum and average ADC values) of the tumors were measured and the MRI characteristics were evaluated.

RESULTS

The average and minimum ADC values of suprasellar germinomas were significantly lower than those of CHGs (p = 0.016 and 0.004 respectively). The selection of 941.15 × 10^-6 mm²/s as a cutoff value of the minimum ADC value was used to differentiate suprasellar germinomas and CHGs; the best results were obtained with area under the curve of 0.889, sensitivity of 87.5%, specificity of 77.8% and accuracy of 82.4%. MRI characteristics suggested the diagnosis of suprasellar germinomas were T2W hypointensity and involvement of pituitary gland and/or stalk. MRI characteristics suggested the diagnosis of CHGs was higher degree of contrast enhancement and presence of macrocysts.

CONCLUSION

ADC values have a role in differentiating suprasellar germinomas and CHGs, especially when imaging findings on conventional MRI are inconclusive. Furthermore, some MRI features are in favor of differentiation between these tumor entities including tumor location, cyst pattern, T2W hypointensity, degree of contrast enhancement, stalk and pituitary gland involvement.

Accuracy of ADC derived from DWI for differentiating high-grade from low-grade gliomas: Systematic review and meta-analysis

OBJECTIVE

Quantitative apparent diffusion coefficient (ADC) values of diffusion weighted imaging (DWI) could be applied to grade gliomas. This meta-analysis was conducted to assess the accuracy of ADC analysis in differentiating high-grade (HGGs) from low-grade gliomas (LGGs).

METHODS

PubMed, Cochrane library, Science Direct, and Embase were searched to identify suitable studies up to September 1, 2018. The quality of studies was evaluated by the quality assessment of diagnostic accuracy studies (QUADAS 2). We estimated the pooled sensitivity, specificity, positive and negative likelihood ratios (LR), diagnostic accuracy ratio (DOR) with 95% confidence intervals (CI), and determined the accuracy of the data by using the summary receiver operating characteristic (SROC) and calculating the area under the curve (AUC) to identity the accuracy of ADC analysis in grading gliomas.

RESULTS

Eighteen studies including 1172 patients were included and analyzed. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC with 95% CIs of DWI with b values of 1000 s/mm for separating HGGs from LGGs were 0.81 (95% CI 0.75-0.86), 0.87 (95% CI 0.81-0.91), 6.1 (95% CI 4.2-8.9), 0.22 (95% CI 0.17-0.29), 28 (95% CI 17-45), and 0.91 (95% CI 0.88-0.93), respectively. DWI with b values of 3000 s/mm showed slightly higher accuracy than that of 1000 (sensitivity 0.80, specificity 0.90 and AUC 0.92). Meta-regression analyses showed that field strengths and b values had significant impacts on diagnostic efficacy. Deeks testing confirmed no significant publication bias in all studies.

CONCLUSIONS

This meta-analysis suggested that ADC analysis of DWI have high accuracy in differentiating HGGs from LGGs. Standardized methodology is warranted to guide the use of this technique for clinical decision-making.

The combined role of MR spectroscopy and perfusion imaging in preoperative differentiation between high- and low-grade gliomas

Background

Brain tumors are an important health problem. The preoperative classification of gliomas by non-invasive techniques is a significant problem. Relative cerebral blood volume and spectroscopy have the ability to sample the entire lesion non-invasively. The present study aims to evaluate the combined role of dynamic susceptibility perfusion and spectroscopy in the classification of primary brain tumors. The combination of both provides overall diagnostic accuracy (100%). Relative cerebral blood volume in peritumoral region plays an important additional role in this regard.

Results

On the basis of histopathology, among 50 patients with brain tumors, high-grade gliomas accounted for 58%, while low-grade gliomas accounted for 42%. The relative cerebral blood volume in the tumor had the best sensitivity, specificity, and accuracy of 96.8%, 95.3%, and 96, respectively. The use of relative cerebral blood volume and choline/N-acetyl Aspartate increased diagnostic accuracy by 100%.

Conclusion

The combination of magnetic resonance spectroscopy and perfusion can increase sensitivity and positive predictive value to define the degree of glioma.

Perfusion, Diffusion, Or Brain Tumor Barrier Integrity: Which Represents The Glioma Features Best?

Purpose

This study aims to incorporate informative histogram indicator analyses and advanced multimodal MRI parameters to differentiate low-grade gliomas (LGGs) from high-grade gliomas (HGGs) and to explore the features associated with patients’ survival.

Patients and methods

A total of 120 patients with pathologically confirmed LGGs or HGGs receiving conventional and advanced MRI such as three-dimensional arterial spin labeling (3D-ASL), intravoxel incoherent motion-diffusion weighted imaging (IVIM-DWI), and dynamic contrast-enhanced MRI (DCE-MRI) were included. The mean and histogram indicators from advanced MRI were calculated from the entire tumor. The efficacies of a single indicator or multiple parameters were tested in distinguishing HGGs from LGGs and predicting patients’ survival. Receiver operating characteristic (ROC) curve and multivariable stepwise logistic regression were used to evaluate the diagnostic efficacies. Leave-one-out cross-validation was further used to validate the accuracy of the parameter sets in glioma grading. Log-rank test using the Kaplan–Meier curve was utilized to predict patients’ survival.

Results

Overall, parameters from DCE-MRI performed better than those from 3D-ASL or IVIM-DWI in both glioma grading and survival prediction. The histogram metrics of V_e were demonstrated to have higher accuracies (the accuracies for Extended Tofts_V_e^mean and Extended Tofts_V_e^median were 68.33% and 71.67%, respectively, while those for the Incremental_V_e^mean and Incremental_V_e^75th were 68.33% and 72.50%, respectively) in grading LGGs from HGGs. The combination of Tofts_V_e histogram metrics was the one with the highest accuracy (81.67%) and area under ROC curve (AUC = 0.840). On the other hand, Patlak_K_trans^95th (AUC = 0.9265) and Extended Tofts_V_e^95th (AUC = 0.9154) performed better than their corresponding means (Patlak_K_trans^mean: AUC = 0.9118 and Extended Tofts_V_e^mean: AUC = 0.9044) in predicting patients’ overall survival (OS) at 18-month follow-up.

Conclusion

DCE-MRI-derived histogram features from the entire tumor were promising metrics for glioma grading and OS prediction. Combining single modal histogram features improved glioma grading.

Trial registration

NCT 02622620.

Pediatric Brain Tumor Genetics: What Radiologists Need to Know

Brain tumors are the most common solid tumors in the pediatric population. Pediatric neuro-oncology has changed tremendously during the past decade owing to ongoing genomic advances. The diagnosis, prognosis, and treatment of pediatric brain tumors are now highly reliant on the genetic profile and histopathologic features of the tumor rather than the histopathologic features alone, which previously were the reference standard. The clinical information expected to be gleaned from radiologic interpretations also has evolved. Imaging is now expected to not only lead to a relevant short differential diagnosis but in certain instances also aid in predicting the specific tumor and subtype and possibly the prognosis. These processes fall under the umbrella of radiogenomics. Therefore, to continue to actively participate in patient care and/or radiogenomic research, it is important that radiologists have a basic understanding of the molecular mechanisms of common pediatric central nervous system tumors. The genetic features of pediatric low-grade gliomas, high-grade gliomas, medulloblastomas, and ependymomas are reviewed; differences between pediatric and adult gliomas are highlighted; and the critical oncogenic pathways of each tumor group are described. The role of the mitogen-activated protein kinase pathway in pediatric low-grade gliomas and of histone mutations as epigenetic regulators in pediatric high-grade gliomas is emphasized. In addition, the oncogenic drivers responsible for medulloblastoma, the classification of ependymomas, and the associated imaging correlations and clinical implications are discussed. ^©RSNA, 2018.

MR imaging features of spinal pilocytic astrocytoma

Background

The purpose of this retrospective review is to determine the MR imaging features of pilocytic astrocytoma (PA) in the spinal cord to help neuroradiologists preoperatively differentiate PA from other intramedullary tumors.

Methods

Neuro-oncology database review revealed 13 consecutive patients with a pathological spinal PA diagnosis and availability of preoperative MR imaging. Three patients had preoperative diffusion-weighted MR imaging. Demographics and conventional and diffusion MR imaging records were retrospectively evaluated.

Results

Among 13 cases of spinal PA, six PAs were located in the cervical region, 4 in the cervical-thoracic region, and 3 in the thoracic region. The average length of vertebral segments involved for the tumors were 4.7 ± 4.6 segments. Six tumors had associated syringomyelia. Eight PAs were located eccentrically in the spinal cord, and eleven had well-defined margins. Eight tumors (61.5%) were intermixed cystic and solid. All were contrast-enhanced, and 53.8% of all PAs showed focal nodule enhancement of the solid components. Two PAs showed intratumoral hemorrhages, and only one demonstrated cap sign. The ADC values (n = 3) of the tumors were 1.40 ± 0.28 × 10^− 3 mm²/s (min–max: 1.17–1.71 × 10^− 3 mm²/s).

Conclusions

PA should be considered in the differential diagnosis of intramedullary tumors that occur in the cervical and thoracic regions. Eccentric growth pattern, well-defined margin, intermixed cystic and solid appearance, focal nodular enhancement of solid components and syringomyelia are relatively frequent features. Relatively high ADC values compared with normal-appearing spinal cord parenchyma are common in spinal PA.

The role of diffusion and perfusion magnetic resonance imaging in differentiation of haemangioblastomas and pilocytic astrocytomas

Purpose

Haemangioblastomas (HABLs) and pilocytic astrocytomas (PAs) are brain tumours presenting similar appearance and location in conventional magnetic resonance (MR) imaging. The purpose of our study was to determine whether a detailed analysis of diffusion (DWI) and perfusion (PWI) characteristics can be useful in preoperative differentiation of these tumours.

Material and methods

The study group consisted of biopsy proven six HABLs and six PAs, which underwent preoperative standard MR examinations including PWI and DWI. In PWI relative cerebral blood volume (rCBV) and the shape of perfusion curves (parameters of peak height - rPH and percentage of signal recovery - rPSR) were analysed. All perfusion parameters were measured for the entire tumour core (mean rCBV, mean rPH, mean rPSR) and in regions with maximal values (max rCBV, max rPH, max rPSR). In DWI parameters of apparent diffusion coefficient (ADC) from the entire tumour core (mean ADC) and in regions with minimal values (min ADC) were evaluated.

Results

Compared to PAs, HABLs presented significantly higher rCBV and rPH values and lower mean rPSR value. PAs showed significantly lower rCBV and rPH values and higher mean rPSR value. Mean rCBV showed no overlap in the values between HABLs and PAs, and thus it provided the highest accuracy in differentiating between them. Max rPSR, mean ADC, and min ADC did not show any significant differences.

Conclusions

High rCBV values and deep perfusion curves with only partial return to the baseline are characteristic features of HABLs differentiating them from PAs, which show lower rCBV values and perfusion curves overshooting the baseline. Diffusion parameters are not useful in differentiation of these tumours.

Arterial Spin-Labeling in Children with Brain Tumor: A Meta-Analysis

BACKGROUND

The value of arterial spin-labeling in a pediatric population has not been assessed in a meta-analysis.

PURPOSE

Our aim was to assess the diagnostic accuracy of arterial spin-labeling-derived cerebral blood flow to discriminate low- and high-grade tumors.

DATA SOURCES

MEDLINE, EMBASE, the Web of Science Core Collection, and the Cochrane Library were used.

STUDY SELECTION

Pediatric patients with arterial spin-labeling MR imaging with verified neuropathologic diagnoses were included.

DATA ANALYSIS

Relative CBF and absolute CBF and tumor grade were extracted, including sequence-specific information. Mean differences in CBF between low- and high-grade tumors were calculated. Study quality was assessed.

DATA SYNTHESIS

Data were aggregated using the bivariate summary receiver operating characteristic curve model. Heterogeneity was explored with meta-regression and subgroup analyses. The study protocol was published at PROSPERO (CRD42017075055). Eight studies encompassing 286 pediatric patients were included. The mean differences in absolute CBF were 29.62 mL/min/100 g (95% CI, 10.43-48.82 mL/min/100 g), I2 = 74, P = .002, and 1.34 mL/min/100 g (95% CI, 0.95-1.74 mL/min/100 g), P < .001, I2 = 38 for relative CBF. Pooled sensitivity for relative CBF ranged from 0.75 to 0.90, and specificity, from 0.77 to 0.92 with an area under curve = 0.92. Meta-regression showed no moderating effect of sequence parameters TE, TR, acquisition time, or ROI method.

LIMITATIONS

Included tumor types, analysis method, and original data varied among included studies.

CONCLUSIONS

Arterial spin-labeling-derived CBF measures showed high diagnostic accuracy for discriminating low- and high-grade tumors in pediatric patients with brain tumors. The relative CBF showed less variation among studies than the absolute CBF.

Diagnostic accuracy of diffusion weighted imaging for differentiation of supratentorial pilocytic astrocytoma and pleomorphic xanthoastrocytoma

Purpose

Supratentorial pilocytic astrocytoma (PA) may mimic pleomorphic xanthoastrocytoma (PXA) on conventional MR imaging, and a differentiation is clinically important because of distinct recurrence rate and anaplastic transformation rate. The purpose of this study was to investigate the diagnostic potential of diffusion-weighted imaging (DWI) in differentiating supratentorial PA from PXA.

Methods

We retrospectively reviewed DWI and conventional MR imaging of 16 patients with supratentorial PA and 8 patients with PXA. Variables of mean ADC values (ADC_mean) and minimum ADC values (ADC_min) were calculated from the ROIs containing the contrast-enhancing lesion on DWI. ADC_mean values and ADC_min values were compared among all supratentorial PA and PXA as well as between the subgroup of lobar PA and PXA by using an unpaired Student’s t test. The optimum threshold, sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC) were determined.

Results

Both ADC_mean values (1542 ± 186 vs 1084 ± 201 × 10⁻⁶ mm²/s; P < 0.001) and ADC_min values (1355 ± 183 vs 988 ± 180 × 10⁻⁶ mm²/s; P < 0.001) were significantly higher in supratentorial PA compared with PXA. The ADC_mean values and ADC_min values were also significantly higher in lobar PA than those in PXA. The ADC_mean values were useful for differentiating supratentorial PA from PXA, with a threshold value of > 1189.8 × 10⁻⁶ mm²/s (sensitivity, 93.8%; specificity, 100%). The optimal threshold values of > 1189.8 × 10⁻⁶ mm²/s for ADC_mean values provide sensitivity and specificity of 85.7 and 100%, respectively, for discriminating lobar PA from PXA. The optimum threshold value for ADC_min was > 1063.5 × 10⁻⁶ mm²/s.

Conclusion

DWI is helpful in characterization and differentiation of supratentorial PA from PXA.

Electronic supplementary material

The online version of this article (10.1007/s00234-018-2036-y) contains supplementary material, which is available to authorized users.

Diagnostic Values of DCE-MRI and DSC-MRI for Differentiation Between High-grade and Low-grade Gliomas: A Comprehensive Meta-analysis

RATIONALE AND OBJECTIVES

This study aimed to collect the studies on the role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI) in differentiating the grades of gliomas, and evaluate the diagnostic performances of relevant quantitative parameters in glioma grading.

MATERIALS AND METHODS

We systematically searched studies on the diagnosis of gliomas with DCE-MRI or DSC-MRI in Medline, PubMed, China National Knowledge Infrastructure database, Cochrane Library, and Embase published between January 2005 and December 2016. Standardized mean differences and 95% confidence intervals were calculated for volume transfer coefficient (K^trans), volume fraction of extravascular extracellular space (V_e), rate constant of backflux (K_ep), relative cerebral blood volume (rCBV), and relative cerebral blood flow (rCBF) using Review Manager 5.2 software. Sensitivity, specificity, area under the curve (AUC), and Begg test were calculated by Stata 12.0.

RESULTS

Twenty-two studies with available outcome data were included in the analysis. The standardized mean difference of K^trans values between high-grade glioma and low-grade glioma were 1.18 (0.91, 1.45); V_e values were 1.43 (1.06, 1.80); K_ep values were 0.65 (-0.05, 1.36); rCBV values were 1.44 (1.08, 1.81); and rCBF values were 1.17 (0.68, 1.67), respectively. The results were all significant statistically (P < .05) except K_ep values (P = .07), and high-grade glioma had higher K^trans, V_e, rCBV, and rCBF values than low-grade glioma. AUC values of K^trans, V_e, rCBV, and rCBF were 0.90, 0.88, 0.93, and 0.73, respectively; rCBV had the largest AUC among the four parameters (P < .05).

CONCLUSION

Both DCE-MRI and DSC-MRI are reliable techniques in differentiating the grades of gliomas, and rCBV was found to be the most sensitive one.

Usefulness of perfusion- and diffusion-weighted imaging to differentiate between pilocytic astrocytomas and high-grade gliomas: a multicenter study in Japan

PURPOSE

Imaging findings of pilocytic astrocytoma (PA) vary widely, sometimes resembling those of high-grade glioma (HGG). This study aimed to identify the imaging parameters that can be used to differentiate PA from HGG.

METHODS

Altogether, 60 patients with PAs and 138 patients with HGGs were included in the study. Tumor properties and the presence of hydrocephalus, peritumoral edema, and dissemination were evaluated. We also measured the maximum relative cerebral blood flow (rCBF_max) and volume (rCBV_max) and determined the minimum apparent diffusion coefficient (ADC_min) in the tumor's solid components. The relative T1 (rT1), T2 (rT2), and contrast-enhanced T1 (rCE-T1) intensity values were evaluated. Parameters were compared between PAs and HGGs using the Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis was also used to evaluate these imaging parameters. A value of P < .05 was considered to indicate significance.

RESULTS

Intratumoral hemorrhage and calcification were observed in 10.0% and 21.7% of PAs, respectively. The rCBF_max and rCBV_max values were significantly lower in PAs (0.50 ± 0.35, 1.82 ± 1.21) than those in HGGs (2.98 ± 1.80, 9.54 ± 6.88) (P < .0001, P = .0002, respectively). The ADC_min values were significantly higher in PAs (1.36 ± 0.56 × 10^-3 mm²/s) than those in HGGs (0.86 ± 0.37 × 10^-3 mm²/s) (P < .0001). ROC analysis showed that the best diagnostic performance was achieved with rCBF_max.

CONCLUSION

The rCBF_max, rCBV_max, and ADC_min can differentiate PAs from HGGs.

Application of a Simplified Method for Estimating Perfusion Derived from Diffusion-Weighted MR Imaging in Glioma Grading

Purpose: To evaluate the feasibility of a simplified method based on diffusion-weighted imaging (DWI) acquired with three b-values to measure tissue perfusion linked to microcirculation, to validate it against from perfusion-related parameters derived from intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging, and to investigate its utility to differentiate low- from high-grade gliomas. Materials and Methods: The prospective study was approved by the local institutional review board and written informed consent was obtained from all patients. From May 2016 and May 2017, 50 patients confirmed with glioma were assessed with multi-b-value DWI and DCE MR imaging at 3.0 T. Besides conventional apparent diffusion coefficient (ADC_0,1000) map, perfusion-related parametric maps for IVIM-derived perfusion fraction (f) and pseudodiffusion coefficient (D*), DCE MR imaging-derived pharmacokinetic metrics, including K^trans, v_e and v_p, as well as a metric named simplified perfusion fraction (SPF), were generated. Correlation between perfusion-related parameters was analyzed by using the Spearman rank correlation. All imaging parameters were compared between the low-grade (n = 19) and high-grade (n = 31) groups by using the Mann-Whitney U test. The diagnostic performance for tumor grading was evaluated with receiver operating characteristic (ROC) analysis. Results: SPF showed strong correlation with IVIM-derived f and D* (ρ = 0.732 and 0.716, respectively; both P < 0.001). Compared with f, SPF was more correlated with DCE MR imaging-derived K^trans (ρ = 0.607; P < 0.001) and v_p (ρ = 0.397; P = 0.004). Among all parameters, SPF achieved the highest accuracy for differentiating low- from high-grade gliomas, with an area under the ROC curve value of 0.942, which was significantly higher than that of ADC_0,1000 (P = 0.004). By using SPF as a discriminative index, the diagnostic sensitivity and specificity were 87.1% and 94.7%, respectively, at the optimal cut-off value of 19.26%. Conclusion: The simplified method to measure tissue perfusion based on DWI by using three b-values may be helpful to differentiate low- from high-grade gliomas. SPF may serve as a valuable alternative to measure tumor perfusion in gliomas in a noninvasive, convenient and efficient way.

Addition of Amide Proton Transfer Imaging to FDG-PET/CT Improves Diagnostic Accuracy in Glioma Grading: A Preliminary Study Using the Continuous Net Reclassification Analysis

BACKGROUND AND PURPOSE

Amide proton transfer imaging has been successfully applied to brain tumors, however, the relationships between amide proton transfer and other quantitative imaging values have yet to be investigated. The aim was to examine the additive value of amide proton transfer imaging alongside [¹⁸F] FDG-PET and DWI for preoperative grading of gliomas.

MATERIALS AND METHODS

Forty-nine patients with newly diagnosed gliomas were included in this retrospective study. All patients had undergone MR imaging, including DWI and amide proton transfer imaging on 3T scanners, and [¹⁸F] FDG-PET. Logistic regression analyses were conducted to examine the relationship between each imaging parameter and the presence of high-grade (grade III and/or IV) glioma. These parameters included the tumor-to-normal ratio of FDG uptake, minimum ADC, mean amide proton transfer value, and their combinations. In each model, the overall discriminative power for the detection of high-grade glioma was assessed with receiver operating characteristic curve analysis. Additive information from minimum ADC and mean amide proton transfer was also evaluated by continuous net reclassification improvement. P < .05 was considered significant.

RESULTS

Tumor-to-normal ratio, minimum ADC, and mean amide proton transfer demonstrated comparable diagnostic accuracy in differentiating high-grade from low-grade gliomas. When mean amide proton transfer was combined with the tumor-to-normal ratio, the continuous net reclassification improvement was 0.64 (95% CI, 0.036-1.24; P = .04) for diagnosing high-grade glioma and 0.95 (95% CI, 0.39-1.52; P = .001) for diagnosing glioblastoma. When minimum ADC was combined with the tumor-to-normal ratio, the continuous net reclassification improvement was 0.43 (95% CI, -0.17-1.04; P = .16) for diagnosing high-grade glioma, and 1.36 (95% CI, 0.79-1.92; P < .001) for diagnosing glioblastoma.

CONCLUSIONS

Addition of amide proton transfer imaging to FDG-PET/CT may improve the ability to differentiate high-grade from low-grade gliomas.

Pilomyxoid astrocytoma of the corpus callosum presenting with primary haemorrhage in an adolescent

A 17-year-old male patient with history of intraventricular haemorrhage in 2007 underwent a brain MRI scan in 2013 owing to headache. Brain MRI scan showed an expansive lesion adjacent to the left lateral ventricle infiltrating the anterior portion of the corpus callosum. After surgery, pathology confirmed a pilomyxoid astrocytoma (PMA), an aggressive subtype of astrocytoma that occurs predominantly in the hypothalamic-chiasmatic region. On imaging, PMA presents as a tumour isointense on T₁, hyperintense on T₂ that enhanced heterogeneously with contrast. The T₂ signal is higher than pilocytic astrocytoma, which indicates the presence of myxoid matrix. These findings on MRI scan have a direct correlation with a specific pathological finding—monomorphic proliferation of piloid cells in a mucopolysaccharide-rich matrix. These characteristics associated with the absence of Rosenthal fibres or eosinophilic granules indicated the diagnosis of PMA. To our knowledge, this is the first case report of PMA affecting the corpus callosum in an adolescent.

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

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Adult anaplastic pilocytic astrocytoma - a diagnostic challenge? A case series and literature review

INTRODUCTION

Anaplastic pilocytic astrocytoma (APA) is an exceptionally rare type of high-grade glioma in adults. Establishing histopathological diagnosis is challenging and its clinical and radiological appearance insidious. By this case series and first literature review we investigated the various clinical, neuroradiological, and histopathological features of APA in adults.

METHODS

An in hospital screening of the database from the Institute of Pathology was conducted to identify cases of APA. Further, we performed a literature review in PubMed using the keywords "anaplastic/malignant/atypical AND pilocytic astrocytoma" and "anaplastic astrocytoma/glioblastoma AND Rosenthal fibers" and summarized the current knowledge about APA in adults.

RESULTS

Over the last decade we were able to identify 3 adult patients with APA in our hospital. According to the pertinent literature, the prognosis of APA in adults (documented survival of up to 10 years) appears to be better than in other high-grade gliomas. Few cases were associated with neurofibromatosis type 1, which seems to predispose for development of APA. Although molecular genetics is still of limited value for differentiation of APA from other high-grade glioma, advanced neuroimaging techniques such as magnetic resonance perfusion imaging and spectroscopy allow improved differential work-up. In particular, APA in adults has the ability to mimic various neurological diseases such as tumefactive demyelinating lesions, low-, or high-grade gliomas.

CONCLUSIONS

Although currently not explicitly recognized as a distinct clinico-pathologic entity it seems that adult APA behaves differently from conventional high-grade glioma and should be included in differential diagnostics to enable adequate patient care. However, further studies are needed to better understand this extremely rare disease.

Potential Utility of Visually AcceSAble Rembrandt Images Assessment in Brain Astrocytoma Grading

OBJECTIVE

The aim of this study was to evaluate the predictive value of multivariate factors of Visually AcceSAble Rembrandt Images (VASARI) in brain astrocytoma grading.

METHODS

Presurgical magnetic resonance images of 126 patients with brain astrocytomas (World Health Organization grade 2, n = 38; grade 3, n = 36; grade 4, n = 52) were rated by 2 neuroradiologists for tumor size, location, and tumor morphology by using a standardized imaging feature set VASARI.

RESULTS

Significant differences were noted in 12 factors of VASARI including enhancement quality, enhancing proportion, noncontrast enhancing tumor proportion, necrosis proportion, edema proportion, hemorrhage, thickness of enhancing margin, definition of the enhancing margin, pial and ependymal invasion, enhanced tumor crossing midline, and satellites between brain astrocytoma grades (grades 1-IV, P < 0.05). On multivariate regression analysis, enhancement quality was an independent diagnostic factor for high-grade brain astrocytoma, whereas edema proportion was an independent diagnostic factor in differentiating grade 2 and grade 3. Noncontrast enhancing tumor proportion was a predictive factor in the diagnosis of grade 4 astrocytoma. Receiver operating characteristic analysis illustrates edema proportion score higher than 2 with sensitivity of 86.1% in differentiating grade 2 and grade 3 astrocytoma. Noncontrast enhancing tumor proportion scores 4 or lower has high sensitivity (92.3%) but moderate specificity (50.0%) in differentiating grade 3 and grade 4 astrocytoma.

CONCLUSIONS

Our data illustrate that magnetic resonance features of VASARI especially enhancement quality, edema proportion, and noncontrast enhancing tumor proportion provided precise and detailed information of astrocytoma grading and suggested that prediction of astrocytoma grading is based on VASARI as an adjunct to biopsy.

Contrast Leakage Patterns from Dynamic Susceptibility Contrast Perfusion MRI in the Grading of Primary Pediatric Brain Tumors

BACKGROUND AND PURPOSE

The pattern of contrast leakage from DSC tissue signal intensity time curves have shown utility in distinguishing adult brain neoplasms, but has limited description in the literature for pediatric brain tumors. The purpose of this study is to evaluate the utility of grading pediatric brain tumors with this technique.

MATERIALS AND METHODS

A retrospective review of tissue signal-intensity time curves from 63 pediatric brain tumors with preoperative DSC perfusion MR imaging was performed independently by 2 neuroradiologists. Tissue signal-intensity time curves were generated from ROIs placed in the highest perceived tumor relative CBV. The postbolus portion of the curve was independently classified as returning to baseline, continuing above baseline (T1-dominant contrast leakage), or failing to return to baseline (T2*-dominant contrast leakage). Interobserver agreement of curve classification was evaluated by using the Cohen κ. A consensus classification of curve type was obtained in discrepant cases, and the consensus classification was compared with tumor histology and World Health Organization grade.

RESULTS

Tissue signal-intensity time curve classification concordance was 0.69 (95% CI, 0.54-0.84) overall and 0.79 (95% CI, 0.59-0.91) for a T1-dominant contrast leakage pattern. Twenty-five of 25 tumors with consensus T1-dominant contrast leakage were low-grade (positive predictive value, 1.0; 95% CI, 0.83-1.00). By comparison, tumors with consensus T2*-dominant contrast leakage or return to baseline were predominantly high-grade (10/15 and 15/23, respectively) with a high negative predictive value (1.0; 95% CI, 0.83-1.0). For pilomyxoid or pilocytic astrocytomas, a T1-dominant leak demonstrated high sensitivity (0.91; 95% CI, 0.70-0.98) and specificity (0.90, 95% CI, 0.75-0.97).

CONCLUSIONS

There was good interobserver agreement in the classification of DSC perfusion tissue signal-intensity time curves for pediatric brain tumors, particularly for T1-dominant leakage. Among patients with pediatric brain tumors, a T1-dominant leakage pattern is highly specific for a low-grade tumor and demonstrates high sensitivity and specificity for pilocytic or pilomyxoid astrocytomas.

Pediatric thalamic tumors in the MRI era: a Canadian perspective

BACKGROUND

Thalamic gliomas are rare. The natural history is unpredictable, and the optimal management of these tumors in children is poorly defined. The aim was to identify outcomes, prognostic factors, and response to various modalities of treatment in a relatively large population of pediatric thalamic tumors from many centers within a fairly homogeneous health care system.

METHODS

We performed a Canadian multicenter retrospective review of pediatric thalamic tumors presenting during the MRI era (1989-2012). Radiology and pathology were reviewed by central independent reviewers. Paraffin shavings for RNA extraction were taken and tested for fusion events involving KIAA1549:BRAF. Tumors were classified as unilateral or bithalamic based on their origin on imaging. Univariate and multivariate analyses on factors influencing survival were performed.

RESULTS

Seventy-two thalamic tumors were identified from 11 institutions. Females represented 53% of the study population, and the mean age at presentation was 8.9 years. Sixty-two tumors were unilateral and 10 bithalamic. Unilateral tumors had a greater propensity to grow inferiorly towards the brainstem. These tumors were predominantly low grade in comparison to bithalamic tumors which were high-grade astrocytomas. The 5-year overall survival was 61 ± 13% for unithalamic tumors compared to 37 ± 32% for bithalamic tumors (p = 0.097). Multivariate analysis indicated tumor grade as the only significant prognostic factor for unithalamic tumors. Six unilateral tumors, all low grade, were BRAF fusion positive.

CONCLUSION

Unilateral and bilateral thalamic tumors behave differently. Surgical resection is an appropriate treatment option in unilateral tumors, most of which are low grade, but outcome is not related to extent of resection (EOR). Bilateral thalamic tumors have a poorer prognosis, but the occasional patient does remarkably well. The efficacy of chemotherapy and radiotherapy has not been clearly demonstrated. Novel therapeutic approaches are required to improve the prognosis for malignant unilateral thalamic tumors and bilateral thalamic tumors.

Differentiation of hemangioblastomas from pilocytic astrocytomas using 3-T magnetic resonance perfusion-weighted imaging and MR spectroscopy

INTRODUCTION

Hemangioblastomas and pilocytic astrocytomas (PAs) present similar imaging features on conventional MR imaging, making differential diagnosis a challenge. The purpose of this study was to evaluate the usefulness of dynamic susceptibility-weighted contrast-enhanced perfusion-weighted imaging (DSC-PWI) and proton MR spectroscopic imaging in the differentiation of hemangioblastomas and PAs.

METHODS

A 3.0-T MR imaging unit was used to perform DSC-PWI and conventional MR imaging on 14 patients with hemangioblastomas and 22 patients with PAs. Four patients with hemangioblastomas and 10 PA patients also underwent proton MR spectroscopy. Parameters of relative peak height (rPH) and relative percentage of signal intensity recovery (rPSR) were acquired by DSC-PWI and variables of N-acetylaspasrtate (NAA)/creatine (Cr), choline (Cho)/Cr, and lactate-lipid (Lac-Lip)/Cr by MR spectroscopy. The sensitivity, specificity, and the area under the receiver operating characteristic curve of all analyzed parameters at respective cutoff values were determined.

RESULTS

Higher rPH but lower rPSR values were detected in hemangioblastomas compared to PAs. The NAA/Cr ratio was significantly lower in hemangioblastomas compared with PAs. The threshold values ≥3.2 for rPH provide sensitivity, specificity, positive predictive values, and negative predictive values of 85.7, 95.5, 92.3, and 91.3%, respectively, for differentiating hemangioblastomas from PAs. The optimal threshold values were ≤0.9 for rPSR and ≤1.5 for NAA/Cr ratios in tumor.

CONCLUSION

Significantly higher rPH and lower NAA/Cr were seen in patients with hemangioblastomas when compared with PA patients, suggesting that DSC-PWI and proton MR spectroscopy are helpful in the characterization and differentiation of these two types of tumors.