Optimal differentiation of high- and low-grade glioma and metastasis: a meta-analysis of perfusion, diffusion, and spectroscopy metrics

Metabolic habitat imaging with hemodynamic heterogeneity predicts individual progression-free survival in high-grade glioma

AIM

We design a feasibility study to obtain a set of metabolic-hemodynamic habitats for tackling tumor spatial metabolic patterns with hemodynamic information.

MATERIALS AND METHODS

Preoperative data from 69 high-grade gliomas (HGG) patients with subsequent histologic confirmation of HGG were prospectively collected (January 2016 to March 2020) after concurrent chemoradiotherapy (CCRT). Four vascular habitats were automatically segmented by multiparametric magnetic resonance imaging (MRI). The metabolic information, either at enhancing or edema tumor regions, was obtained by two neuroradiologists. The relative habitat volumes were used for weight estimation procedures for computing the coefficients of a linear regression model using weighted least squares (WLS) for metabolite semiquantifications (i.e. the Cho/NAA ratio and the Cho/Cr ratio) at vascular habitats. Multivariate Cox proportional hazard regression analyses are used to obtain the odds ratio (OR) and develop a nomogram using weighted estimators corresponding to each covariate derived from Cox regression coefficients.

RESULTS

There was a strongly correlation between perfusion indexes and the Cho/Cr ratio (rCBV, r=0.71) or Cho/NAA ratio (rCBV, r=0.66) at high-angiogenic enhancing tumor habitats (HAT) habitat. Compared isocitrate dehydrogenase (IDH) mutation to their wild type, the IDH wild type had significantly decreased Cho/Cr ratio (IDH mutation: Cho/Cr ratio = 2.44 ± 0.33, IDH wildtype: Cho/Cr ratio = 2.66 ± 0.36, p=0.02) and Cho/NAA ratio (IDH mutation: Cho/Cr ratio = 4.59 ± 0.61, IDH wildtype: Cho/Cr ratio = 4.99 ± 0.66, p=0.022) at the HAT. The C-index for the median progression-free survival (PFS) prediction was 0.769 for the Cho/NAA nomogram and 0.747 for the Cho/Cr nomogram through 1000 bootstrapping validation.

CONCLUSIONS

Our findings suggest that spatial metabolism combined with hemodynamic heterogeneity is associated with individual PFS to HGG patients post-CCRT.

7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading

INTRODUCTION

With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities. In this study, we evaluated the potential of 3D 7 T-MRSI for the preoperative noninvasive classification of glioma grade and isocitrate dehydrogenase (IDH) status. We demonstrated that IDH mutation and glioma grade are detectable by ultra-high field (UHF) MRI. This technique might potentially optimize the perioperative management of glioma patients.

METHODS

We prospectively included 36 patients with WHO 2021 grade 2-4 gliomas (20 IDH mutated, 16 IDH wildtype). Our 7 T 3D MRSI sequence provided high-resolution metabolic maps (e.g., choline, creatine, glutamine, and glycine) of these patients' brains. We employed multivariate random forest and support vector machine models to voxels within a tumor segmentation, for classification of glioma grade and IDH mutation status.

RESULTS

Random forest analysis yielded an area under the curve (AUC) of 0.86 for multivariate IDH classification based on metabolic ratios. We distinguished high- and low-grade tumors by total choline (tCho) / total N-acetyl-aspartate (tNAA) ratio difference, yielding an AUC of 0.99. Tumor categorization based on other measured metabolic ratios provided comparable accuracy.

CONCLUSIONS

We successfully classified IDH mutation status and high- versus low-grade gliomas preoperatively based on 7 T MRSI and clinical tumor segmentation. With this approach, we demonstrated imaging based tumor marker predictions at least as accurate as comparable studies, highlighting the potential application of MRSI for pre-operative tumor classifications.

Peak Resembling N-acetylaspartate (NAA) on Magnetic Resonance Spectroscopy of Brain Metastases

Background and Objectives: Differentiating between a high-grade glioma (HGG) and solitary cerebral metastasis presents a challenge when using standard magnetic resonance imaging (MRI) alone. Magnetic resonance spectroscopy (MRS), an advanced MRI technique, may assist in resolving this diagnostic dilemma. N-acetylaspartate (NAA), an amino acid found uniquely in the central nervous system and in high concentrations in neurons, typically suggests HGG over metastatic lesions in spectra from ring-enhancing lesions. This study investigates exceptions to this norm. Materials and Methods: We conducted an MRS study on 49 histologically confirmed and previously untreated patients with brain metastases, employing single-voxel (SVS) techniques with short and long echo times, as well as magnetic resonance spectroscopic imaging (MRSI). Results: In our cohort, 44 out of 49 (90%) patients demonstrated a typical MR spectroscopic profile consistent with secondary deposits: a Cho peak, very low or absent Cr, absence of NAA, and the presence of lipids. A peak at approximately 2 ppm, termed the "NAA-like peak", was present in spectra obtained with both short and long echo times. Among the MRS data from 49 individuals, we observed a peak at 2.0 ppm in five brain metastases from mucinous carcinoma of the breast, mucinous non-small-cell lung adenocarcinoma, two metastatic melanomas, and one metastatic non-small-cell lung cancer. Pathohistological verification of mucin in two of these five cases suggested this peak likely represents N-acetyl glycoproteins, indicative of mucin expression in cancer cells. Conclusions: The identification of a prominent peak at 2.0 ppm could be a valuable diagnostic marker for distinguishing single ring-enhancing lesions, potentially associated with mucin-expressing metastases, offering a new avenue for diagnostic specificity in challenging cases.

Multiparametric MRI and T2/FLAIR mismatch complements the World Health Organization 2021 classification for the diagnosis of IDH-mutant 1p/19q non-co-deleted/ATRX-mutant astrocytoma

AIM

To investigate whether T2-weighted imaging-fluid-attenuated inversion recovery (T2/FLAIR) mismatch, T2∗ dynamic susceptibility contrast (DSC) perfusion, and magnetic resonance spectroscopy (MRS) correlated with the histological diagnosis and grading of IDH (isocitrate dehydrogenase)-mutant, 1p/19q non-co-deleted/ATRX (alpha-thalassemia mental retardation X-linked)-mutant astrocytoma.

MATERIALS

Imaging of 101 IDH-mutant diffuse glioma cases of histological grades 2-3 (2019-2021) were analysed retrospectively by two neuroradiologists blinded to the molecular diagnosis. T2/FLAIR mismatch sign is used for radio-phenotyping, and pre-biopsy multiparametric MRI images were assessed for grading purposes. Cut-off values pre-determined for radiologically high-grade lesions were relative cerebral blood volume (rCBV) ≥2, choline/creatine ratio (Cho/Cr) ≥1.5 (30 ms echo time [TE]), Cho/Cr ≥1.8 (135 ms TE).

RESULTS

Sixteen of the 101 cases showed T2/FLAIR mismatch, all of which were histogenetically confirmed IDH-mutant 1p/19q non-co-deleted/ATRX mutant astrocytomas; 50% were grade 3 (8/16) and 50% grade 2 (8/16). None showed contrast enhancement. Nine of the 16 had adequate multiparametric MRI for analysis. Any positive value by combining rCBV ≥2 with Cho/Cr ≥1.5 (30 ms TE) or Cho/Cr ≥1.8 (135 ms TE) predicted grade 3 histology with sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%.

CONCLUSION

The T2/FLAIR mismatch sign detected diffuse astrocytomas with 100% specificity. When combined with high Cho/Cr and raised rCBV, this predicted histological grading with high accuracy. The future direction for imaging should explore a similar integrated layered approach of 2021 classification of central nervous system (CNS) tumours combining radio-phenotyping and grading from structural and multiparametric imaging.

Magnetic resonance-based imaging biopsy with signatures including topological Betti number features for prediction of primary brain metastatic sites

This study incorporated topology Betti number (BN) features into the prediction of primary sites of brain metastases and the construction of magnetic resonance-based imaging biopsy (MRB) models. The significant features of the MRB model were selected from those obtained from gray-scale and three-dimensional wavelet-filtered images, BN and inverted BN (iBN) maps, and clinical variables (age and gender). The primary sites were predicted as either lung cancer or other cancers using MRB models, which were built using seven machine learning methods with significant features chosen by three feature selection methods followed by a combination strategy. Our study dealt with a dataset with relatively smaller brain metastases, which included effective diameters greater than 2 mm, with metastases ranging from 2 to 9 mm accounting for 17% of the dataset. The MRB models were trained by T1-weighted contrast-enhanced images of 494 metastases chosen from 247 patients and applied to 115 metastases from 62 test patients. The most feasible model attained an area under the receiver operating characteristic curve (AUC) of 0.763 for the test patients when using a signature including features of BN and iBN maps, gray-scale and wavelet-filtered images, and clinical variables. The AUCs of the model were 0.744 for non-small cell lung cancer and 0.861 for small cell lung cancer. The results suggest that the BN signature boosted the performance of MRB for the identification of primary sites of brain metastases including small tumors.

Spectral Analysis Based on Hemodynamic Habitat Imaging Predicts Isocitrate Dehydrogenase Status and Prognosis in High-Grade Glioma

BACKGROUND

The intratumoral heterogeneity of high-grade gliomas (HGGs) is associated with isocitrate dehydrogenase (IDH) status and prognosis, which can be established by quantitative radioanalysis of spatial tumor habitats. Therefore, we designed a framework for tackling tumors based on spatial metabolism using the hemodynamic tissue signature (HTS), focusing on metabolic changes in tumor habitat to predict IDH status and assess prognosis in patients with HGG.

METHODS

Preoperative data for 121 patients with HGG with subsequent histologic confirmation of HGG were prospectively collected (January 2016 to December 2020). The HTS was mapped from the image data, chemical shift imaging voxels were selected from the HTS habitat as the region of interest, and the metabolic ratio of the HTS was calculated using weighted least square method fitting. The metabolic rate of the tumor enhancement area was used as a control to analyze the efficacy of each HTS metabolic rate in predicting the IDH status and prognosis of HGG.

RESULTS

Total choline (Cho)/total creatine and Cho/N-acetyl-aspartate showed significant differences between IDH-wildtype and IDH-mutant in high- and low-angiogenic enhanced tumor sites (P < 0.05); Cho/total creatine was an independent risk factor for prognosis of HGG patients in high-angiogenic enhanced tumor habitats, with significant differences in survival time between groups (P < 0.05). The metabolic ratio in the tumor enhanced area could not predict IDH status or evaluate prognosis.

CONCLUSIONS

Spectral analysis based on hemodynamic habitat imaging can clearly distinguish IDH mutations and the prognosis assessment is more accurate, rendering it superior to traditional spectral analysis in tumor enhancement areas.

Glioma grading using multiparametric MRI: head-to-head comparison among dynamic susceptibility contrast, dynamic contrast-enhancement, diffusion-weighted images, and MR spectroscopy

PURPOSE

To assess the diagnostic accuracy of dynamic susceptibility contrast, dynamic contrast-enhancement, MR spectroscopy (MRS), and diffusion-weighted imaging for differentiating high-grade (HGGs) from low-grade gliomas (LGGs).

METHODS

Seventy-two patients (16 LGGs, 56 HGGs) with pathologically confirmed gliomas were retrospectively included. From three-dimensionally segmented tumor, histogram analyses of relative cerebral blood volume (rCBV), volume transfer constant (K^trans), and apparent diffusion coefficient (ADC) were performed. Choline-to-creatinine ratio (Cho/Cr) was calculated using MRS. Logistic regression analyses were performed to differentiate HGGs (grade ≥ 3) from LGGs (grade ≤ 2). Areas under the receiver operating characteristics curves (AUC) were plotted. Subgroup analysis was performed between IDH-wildtype glioblastomas and IDH-mutant astrocytomas. Pairwise Spearman's correlation coefficients (ρ) were computed.

RESULTS

HGGs had higher 95th percentile rCBV, K^trans and Cho/Cr (P < 0.01) than LGGs. AUC of 95th percentiles of rCBV and K^trans were 0.79 (95% CI, 0.67-0.91) and 0.74 (95% CI, 0.59-0.88), respectively. AUC of 5th percentile of ADC was 0.63 (95% CI, 0.48-0.79), and that of Cho/Cr was 0.67 (95% CI, 0.52-0.81). IDH-wildtype glioblastomas and IDH-mutant astrocytomas showed significantly different 95th percentile rCBV (P = 0.04) and K^trans (P < 0.01), with K^trans showing the highest AUC (0.73, 95% CI 0.57-0.89) in IDH status prediction. Moderate correlations were observed between 95th percentile rCBV and K^trans (ρ = 0.47), Cho/Cr (ρ = 0.40), and 5th percentile ADC (ρ = -0.36) (all P < 0.01).

CONCLUSIONS

The 95th percentile rCBV may be most helpful in discriminating HGGs from LGGs. The 95th percentile K^trans may aid predicting IDH status of diffuse gliomas.

Update on the current knowledge of lymphatic drainage system and its emerging roles in glioma management

The draining of brain interstitial fluid (ISF) to cerebrospinal fluid (CSF) and the subsequent draining of CSF to meningeal lymphatics is well-known. Nonetheless, its role in the development of glioma is a remarkable finding that has to be extensively understood. The glymphatic system (GS) collects CSF from the subarachnoid space and brain ISF through aquaporin-4 (AQP4) water channels. The glial limiting membrane and the perivascular astrocyte-end-feet membrane both have elevated levels of AQP4. CSF is thought to drain through the nerve sheaths of the olfactory and other cranial nerves as well as spinal meningeal lymphatics via dorsal or basal lymphatic vessels. Meningeal lymphatic vessels (MLVs) exist below the skull in the dorsal and basal regions. In this view, MLVs offer a pathway to drain macromolecules and traffic immunological cells from the CNS into cervical lymph nodes (CLNs), and thus can be used as a candidate curing strategy against glioma and other associated complications, such as neuro-inflammation. Taken together, the lymphatic drainage system could provide a route or approach for drug targeting of glioma and other neurological conditions. Nevertheless, its pathophysiological role in glioma remains elusive, which needs extensive research. The current review aims to explore the lymphatic drainage system, its role in glioma progression, and possible therapeutic techniques that target MLVs in the CNS.

Imaging-based stratification of adult gliomas prognosticates survival and correlates with the 2021 WHO classification

BACKGROUND

Because of the lack of global accessibility, delay, and cost-effectiveness of genetic testing, there is a clinical need for an imaging-based stratification of gliomas that can prognosticate survival and correlate with the 2021-WHO classification.

METHODS

In this retrospective study, adult primary glioma patients with pre-surgery/pre-treatment MRI brain images having T2, FLAIR, T1, T1 post-contrast, DWI sequences, and survival information were included in TCIA training-dataset (n = 275) and independent validation-dataset (n = 200). A flowchart for imaging-based stratification of adult gliomas(IBGS) was created in consensus by three authors to encompass all adult glioma types. Diagnostic features used were T2-FLAIR mismatch sign, central necrosis with peripheral enhancement, diffusion restriction, and continuous cortex sign. Roman numerals (I, II, and III) denote IBGS types. Two independent teams of three and two radiologists, blinded to genetic, histology, and survival information, manually read MRI into three types based on the flowchart. Overall survival-analysis was done using age-adjusted Cox-regression analysis, which provided both hazard-ratio (HR) and area-under-curve (AUC) for each stratification system(IBGS and 2021-WHO). The sensitivity and specificity of each IBSG type were analyzed with cross-table to identify the corresponding 2021-WHO genotype.

RESULTS

Imaging-based stratification was statistically significant in predicting survival in both datasets with good inter-observer agreement (age-adjusted Cox-regression, AUC > 0.5, k > 0.6, p < 0.001). IBGS type-I, type-II, and type-III gliomas had good specificity in identifying IDHmut 1p19q-codel oligodendroglioma (training - 97%, validation - 85%); IDHmut 1p19q non-codel astrocytoma (training - 80%, validation - 85.9%); and IDHwt glioblastoma (training - 76.5%, validation- 87.3%) respectively (p-value < 0.01).

CONCLUSIONS

Imaging-based stratification of adult diffuse gliomas predicted patient survival and correlated well with 2021-WHO glioma classification.

Comparison of the diagnostic value of liquid biopsy in leptomeningeal metastases: A systematic review and meta-analysis

Background

Brain metastases (BM) include brain parenchymal (BPM) and leptomeningeal metastases (LM), which are associated with a poor prognosis and high mortality rate. Early and accurate diagnosis and timely, effective treatment are crucial for improving the overall survival of LM patients. Cerebrospinal fluid (CSF) biopsy technology has attracted widespread attention for its diagnostic value in diverse cancers, including LM. We summarized studies to compare the potential diagnostic value of CSF liquid biopsy techniques in BM patients with meta-analysis.

Methods

The study protocol was prospectively registered in PROSPERO, registration number CRD42022373263. We obtained the literature on liquid biopsy for BM from 7 databases (PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, and Wanfang Data knowledge service platform). Then, a systematic review of those studies was performed according to PRISMA criteria.

Results

Nine publications have been obtained, and we found CSF liquid biopsy techniques to be more suitable for diagnosing LM. We analyzed the sensitivity, specificity, and area under the curve (AUC) of CSF liquid biopsy. The overall sensitivity, specificity, and AUC of CSF liquid biopsy in the diagnosis of LM were 0.65 (95% CI: 0.48 - 0.79), 0.70 (95% CI: 0.50 - 0.86), and 0.69, respectively. Then, we compared the diagnostic advantages of CSF liquid biopsy techniques and CSF cytology in LM. The results show that CSF liquid biopsy is superior to CSF cytology in LM diagnosis.

Conclusions

Our meta-analysis suggested that CSF liquid biopsy is more suitable for LM diagnosis and has higher accuracy than CSF cytology.

Revisiting the use of proton magnetic resonance spectroscopy in distinguishing between primary and secondary malignant tumors of the central nervous system

BACKGROUND AND PURPOSE

Conventional magnetic resonance images (MRI) has limitations in distinguishing primary from secondary brain tumors. Proton magnetic resonance spectroscopy (1H-MRS) allows evaluation of the concentration of metabolites in a brain lesion and, hence, better characterization of the tumor. Considering that an accurate diagnosis determines the choice of treatment, our purpose was to assess the usefulness of spectroscopy data for differentiating between primary and secondary brain neoplasms.

MATERIALS AND METHODS

We undertook a retrospective analysis of 61 MRI and 1H-MRS images of patients with histologically confirmed tumors (30 primary tumors and 31 metastatic tumors). The metabolite ratios of Cho/Cr and NAA/Cr at short TE were determined from spectroscopic curves, with a single voxel positioned in the enhancing tumor. Additional variables analyzed along with the metabolites, like as age and gender, allowed the construction of a logistic regression model to predict the tumor's nature. The statistical analysis was done using the R software (version 4.0.3 R Core Team, 2020).

RESULTS

The mean NAA/Cr and Cho/Cr ratios were higher in secondary tumors, with a good correlation between NAA/Cr and Cho/Cr (r = 0.61). The mean age of patients with primary tumors was lower than for secondary tumors (43.9 vs 55.9, respectively). Receiver operating characteristic analysis yielded a cut-off value of 0.4 for the NAA/Cr ratio with an accuracy of 73.8%, a sensitivity of 73.3% and a specificity of 74.2% in predicting metastatic tumors.

CONCLUSION

The model was reasonable in predicting the nature of the tumor and provides an additional tool for analyzing brain tumors.

Multiparametric Characterization of Intracranial Gliomas Using Dynamic [18F]FET-PET and Magnetic Resonance Spectroscopy

Both static and dynamic O-(2-[18F]fluoroethyl)-l-tyrosine-(FET)-PET and 1H magnetic resonance spectroscopy (MRS) are useful tools for grading and prognostication in gliomas. However, little is known about the potential of multimodal imaging comprising both procedures. We therefore acquired NAA/Cr and Cho/Cr ratios in multi-voxel MRS as well as FET-PET parameters in 67 glioma patients and determined multiparametric parameter combinations. Using receiver operating characteristics, differentiation between low-grade and high-grade glioma was possible by static FET-PET (area under the curve (AUC) 0.86, p = 0.001), time-to-peak (TTP; AUC 0.79, p = 0.049), and using the Cho/Cr ratio (AUC 0.72, p = 0.039), while the multimodal analysis led to improved discrimination with an AUC of 0.97 (p = 0.001). In order to distinguish glioblastoma from non-glioblastoma, MRS (NAA/Cr ratio, AUC 0.66, p = 0.031), and dynamic FET-PET (AUC 0.88, p = 0.001) were superior to static FET imaging. The multimodal analysis increased the accuracy with an AUC of 0.97 (p < 0.001). In the survival analysis, PET parameters, but not spectroscopy, were significantly correlated with overall survival (OS, static PET p = 0.014, TTP p = 0.012), still, the multiparametric analysis, including MRS, was also useful for the prediction of OS (p = 0.002). In conclusion, FET-PET and MRS provide complementary information to better characterize gliomas before therapy, which is particularly interesting with respect to the increasing use of hybrid PET/MRI for brain tumors.

Case report: immunotherapy successfully treated brain metastasis in intrahepatic cholangiocarcinoma and literature review

Brain metastasis from intrahepatic cholangiocarcinoma (iCCA) is extremely rare, and no standard therapeutic strategy has been established. Camrelizumab is a programmed cell death protein 1 (PD-1) inhibitor that has been widely studied in treating liver cancer. Combined immunotherapy and targeted therapy are a promising approach for treating advanced iCCA. Despite that immune checkpoint inhibitor (ICI)-based neoadjuvant therapy on iCCA has shown a significant response rate and resection rate, few reports have shown the therapeutic efficacy of immunotherapy in treating brain metastasis from iCCA. Although PD-1 inhibitors such as pembrolizumab, nivolumab, or camrelizumab are increasingly applied in clinic practice to treat multiple malignancies, to the best of our knowledge, we report the first case of an iCCA patient with brain metastasis successfully treated with a combined immunotherapy and targeted therapy. The patient is a 54-year-old man with metastatic iCCA in brain treated though camrelizumab plus lenvatinib therapy with a complete response (CR). By the time of writing, he has had a progression-free survival of 17.5 months and did not experience any severe side effects related to this therapy. Camrelizumab plus lenvatinib therapy showed favorable efficacy and manageable toxicity for this patient with advanced iCCA and could be of interest for more prospective randomized trials to further verify the potential clinical benefits.

MRT-Befundung hirneigener Tumoren

Hintergrund und Ziel

Eine strukturierte MRT-Befundung unter Verwendung konsensbasierter inhaltlicher Kategorien hat das Potenzial, die interdisziplinäre Kommunikation in der Neuroonkologie zu verbessern. Ziel dieser Studie war es daher, mittels einer bundesweiten Befragung von Mitgliedern medizinischer Fachgesellschaften mit neuroonkologischem Bezug die wesentlichen Befundungskategorien der Bildgebung hirneigener Tumoren aus klinischer Perspektive zu ermitteln.

Material und Methoden

Auf der Basis eines interdisziplinär entwickelten Katalogs von MRT-Befundungselementen wurde ein Online-Fragebogen erstellt. Im Anschluss wurden fachärztliche Mitglieder der Deutschen Gesellschaften für Neurochirurgie, Radioonkologie, Hämatologie und Medizinische Onkologie, Neurologie und Neuropathologie dazu eingeladen, die Items hinsichtlich ihrer klinischen Relevanz zu bewerten.

Ergebnisse

An der Umfrage nahmen insgesamt 171 Fachärzte aus dem Bundesgebiet teil (81 Neurochirurgen, 66 Strahlentherapeuten und 24 andere neuroonkologische Experten). Anzahl und anatomische Ausdehnung der Tumoren in einer kontrastmittelverstärkten T1- und 2‑D-T2-Sequenz (98,8 % vs. 97,1 %) sowie neu diagnostizierte Läsionen bei Folgeuntersuchungen (T1 + Kontrast 98,2 %; T2 94,7 %) wurden am häufigsten als essenziell betrachtet. Darüber hinaus beurteilten die Experten insbesondere die Beschreibung einer ependymalen und/oder leptomeningealen Tumordissemination (93,6 %) sowie Zeichen der Raumforderung inklusive Verschlusshydrozephalus und parenchymale Massenverschiebungen (jeweils > 75,0 %) als wesentlich. Eine standardmäßige Erwähnung von intratumoralen Verkalkungen, Hämorrhagien, Tumorgefäßarchitektur oder erweiterter Bildgebungsmethoden wie MR-Perfusion, Diffusion, Traktographie und Protonenspektroskopie bewertete lediglich eine Minderheit der Umfrageteilnehmer als praxisrelevant.

Schlussfolgerung

Ein zuweiserorientierter inhaltlicher Mindeststandard der magnetresonanztomographischen Hirntumordiagnostik sollte als klinisch relevante Kernelemente die exakte anatomische Ausbreitung der Raumforderung(en) inklusive ependymaler und meningealer Beteiligung sowie die einschlägigen Raumforderungszeichen enthalten.

Efficacy of MR diffusion kurtosis imaging for differentiating low-grade from high-grade glioma before surgery: A systematic review and meta-analysis

BACKGROUND

Accurate discrimination and diagnosis of low-grade glioma (LGG) and high-grade glioma (HGG) before surgery is clinically important because it affects the patient's outcome and guides the clinicians to select appropriate management. The aim of this study was to evaluate the diagnostic performance of diffusion kurtosis imaging (DKI) for differentiating LGG from HGG.

METHODS

A literature search of the PubMed, Web of Science, Cochrane Library and EMBASE databases was conducted up to December 15, 2020. Studies that evaluated the diagnostic performance of DKI for differentiating LGG from HGG were selected. Retrieved hits were evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Summary sensitivity and specificity were determined, and the data analysis was performed using Stata 14.0 and Review Manager 5.3.

RESULTS

Thirteen studies with 705 patients were included. The individual sensitivity and specificity of the 13 studies varied from 71% to 100% for sensitivity and 73-100% for specificity. The pooled sensitivity of DKI was 88% (95% confidence interval [CI], 83-91%), and the pooled specificity was 91% (95% CI, 86-95%). The area under the summary receiver operating characteristic curve was 0.93 (95% CI, 0.90-0.95). The pooled diagnostic odds ratio of DKI was 64.85 (95% CI 38.52-109.19). The levels of heterogeneity for sensitivity and specificity across the included studies were high (I² =66%) and mild (I² =47.04%), respectively. The multiple subgroup analyses were driven by DKI technique and study region.

CONCLUSIONS

DKI demonstrated a high diagnostic performance for differentiation of LGG from HGG.

The Use of 18F-FET-PET-MRI in Neuro-Oncology: The Best of Both Worlds—A Narrative Review

Gliomas are the most frequent primary tumors of the brain. They can be divided into grade II-IV astrocytomas and grade II-III oligodendrogliomas, based on their histomolecular profile. The prognosis and treatment is highly dependent on grade and well-identified prognostic and/or predictive molecular markers. Multi-parametric MRI, including diffusion weighted imaging, perfusion, and MR spectroscopy, showed increasing value in the non-invasive characterization of specific molecular subsets of gliomas. Radiolabeled amino-acid analogues, such as 18F-FET, have also been proven valuable in glioma imaging. These tracers not only contribute in the diagnostic process by detecting areas of dedifferentiation in diffuse gliomas, but this technique is also valuable in the follow-up of gliomas, as it can differentiate pseudo-progression from real tumor progression. Since multi-parametric MRI and 18F-FET PET are complementary imaging techniques, there may be a synergistic role for PET-MRI imaging in the neuro-oncological imaging of primary brain tumors. This could be of value for both primary staging, as well as during treatment and follow-up.

Non-invasive assessment of heterogeneity of gliomas using diffusion and perfusion MRI: correlation with spatially co-registered PET

BACKGROUND

Heterogeneity of gliomas challenges the neuronavigated biopsy and oncological therapy. Diffusion and perfusion magnetic resonance imaging (MRI) can reveal the cellular and hemodynamic heterogeneity of tumors. Integrated positron emission tomography (PET)/MRI is expected to be a non-invasive imaging approach to characterizing glioma.

PURPOSE

To evaluate the value of apparent diffusion coefficient (ADC), cerebral blood volume (CBV), and spatially co-registered maximal standard uptake value (SUV_max) for tissue characterization and glioma grading.

MATERIAL AND METHODS

Thirty-seven consecutive patients with pathologically confirmed gliomas were retrospectively investigated. The relative minimum ADC (rADC_min), relative maximal ADC (rADC_max), relative maximal rCBV (rCBV_max), the relative minimum rCBV (rCBV_min), and the corresponding relative SUVmax (rSUV_max) were measured. The paired t-test was used to compare the quantitative parameters between different regions to clarify tumor heterogeneity. Imaging parameters between WHO grade IV and grade II/III gliomas were compared by t-test. The diagnostic efficiency of multiparametric PET/MRI was analyzed by receiver operating characteristic (ROC) curve.

RESULTS

The values of rSUV_max were significantly different between maximal diffusion/perfusion area and minimum diffusion/perfusion area (P < 0.001/P < 0.001) within tumor. The values of rADC_min (P < 0.001), rCBV_max (P = 0.002), and corresponding rSUV_max (P = 0.001/P < 0.001) could be used for grading gliomas. The areas under the ROC curves of rSUV_max defined by rADC_min and rCBV_max were 0.89 and 0.91, respectively.

CONCLUSION

Diffusion and perfusion MRI can detect glioma heterogeneity with excellent molecular imaging correlations. Regions with rCBV_max suggest tissues with the highest metabolism and malignancy for guiding glioma grading and tissue sampling.

Short TE downfield magnetic resonance spectroscopy in a mouse model of brain glioma

PURPOSE

Enhanced cell proliferation in tumors can be associated with altered metabolic profiles and dramatic microenvironmental changes. Downfield magnetic resonance spectroscopy (MRS) has received increasing attention due to its ability to report on labile resonances of molecules not easily detected in upfield ¹ H MRS. Image-selected-in-vivo-spectroscopy-relaxation enhanced MRS (iRE-MRS) was recently introduced for acquiring short echo-time (TE) spectra. Here, iRE-MRS was used to investigate in-vivo downfield spectra in glioma-bearing mice.

METHODS

Experiments were performed in vivo in an immunocompetent glioma mouse model at 9.4 T using a cryogenic coil. iRE-MRS spectra were acquired in N = 6 glioma-bearing mice (voxel size = 2.2³  mm³ ) and N = 6 control mice. Spectra were modeled by a sum of Lorentzian peaks simulating known downfield resonances, and differences between controls and tumors were quantified using relative peak areas.

RESULTS

Short TE tumor spectra exhibited large qualitative differences compared to control spectra. Most peaks appeared modulated, with strong attenuation of NAA (∼7.82, 7.86 ppm) and changes in relative peak areas between 6.75 and 8.49 ppm. Peak areas tended to be smaller for DF_6.83 , DF_7.60 , DF_8.18 and NAA; and larger for DF_7.95 and DF_8.24 . Differences were also detected in signals resonating above 8.5 ppm, assumed to arise from NAD+.

CONCLUSIONS

In-vivo downfield ¹ H iRE-MRS of mouse glioma revealed differences between controls and tumor bearing mice, including in metabolites which are not easily detectable in the more commonly investigated upfield spectrum. These findings motivate future downfield MRS investigations exploring pH and exchange contributions to these differences.

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.

CEST MRI provides amide/amine surrogate biomarkers for treatment-naïve glioma sub-typing

PURPOSE

Accurate glioma classification affects patient management and is challenging on non- or low-enhancing gliomas. This study investigated the clinical value of different chemical exchange saturation transfer (CEST) metrics for glioma classification and assessed the diagnostic effect of the presence of abundant fluid in glioma subpopulations.

METHODS

Forty-five treatment-naïve glioma patients with known isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status received CEST MRI (B_1rms = 2μT, T_sat = 3.5 s) at 3 T. Magnetization transfer ratio asymmetry and CEST metrics (amides: offset range 3-4 ppm, amines: 1.5-2.5 ppm, amide/amine ratio) were calculated with two models: 'asymmetry-based' (AB) and 'fluid-suppressed' (FS). The presence of T2/FLAIR mismatch was noted.

RESULTS

IDH-wild type had higher amide/amine ratio than IDH-mutant_1p/19q^codel (p < 0.022). Amide/amine ratio and amine levels differentiated IDH-wild type from IDH-mutant (p < 0.0045) and from IDH-mutant_1p/19q^ret (p < 0.021). IDH-mutant_1p/19q^ret had higher amides and amines than IDH-mutant_1p/19q^codel (p < 0.035). IDH-mutant_1p/19q^ret with AB/FS mismatch had higher amines than IDH-mutant_1p/19q^ret without AB/FS mismatch ( < 0.016). In IDH-mutant_1p/19q^ret, the presence of AB/FS mismatch was closely related to the presence of T2/FLAIR mismatch (p = 0.014).

CONCLUSIONS

CEST-derived biomarkers for amides, amines, and their ratio can help with histomolecular staging in gliomas without intense contrast enhancement. T2/FLAIR mismatch is reflected in the presence of AB/FS CEST mismatch. The AB/FS CEST mismatch identifies glioma subgroups that may have prognostic and clinical relevance.

Inorganic Nanomaterial for Biomedical Imaging of Brain Diseases

In the past few decades, brain diseases have taken a heavy toll on human health and social systems. Magnetic resonance imaging (MRI), photoacoustic imaging (PA), computed tomography (CT), and other imaging modes play important roles in disease prevention and treatment. However, the disadvantages of traditional imaging mode, such as long imaging time and large noise, limit the effective diagnosis of diseases, and reduce the precision treatment of diseases. The ever-growing applications of inorganic nanomaterials in biomedicine provide an exciting way to develop novel imaging systems. Moreover, these nanomaterials with special physicochemical characteristics can be modified by surface modification or combined with functional materials to improve targeting in different diseases of the brain to achieve accurate imaging of disease regions. This article reviews the potential applications of different types of inorganic nanomaterials in vivo imaging and in vitro detection of different brain disease models in recent years. In addition, the future trends, opportunities, and disadvantages of inorganic nanomaterials in the application of brain diseases are also discussed. Additionally, recommendations for improving the sensitivity and accuracy of inorganic nanomaterials in screening/diagnosis of brain diseases.

Radiomics and radiogenomics in gliomas: a contemporary update

The natural history and treatment landscape of primary brain tumours are complicated by the varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low-grade lesions), as well as the dilemmas with identification of radiation necrosis, tumour progression, and pseudoprogression on MRI. Radiomics and radiogenomics promise to offer precise diagnosis, predict prognosis, and assess tumour response to modern chemotherapy/immunotherapy and radiation therapy. This is achieved by a triumvirate of morphological, textural, and functional signatures, derived from a high-throughput extraction of quantitative voxel-level MR image metrics. However, the lack of standardisation of acquisition parameters and inconsistent methodology between working groups have made validations unreliable, hence multi-centre studies involving heterogenous study populations are warranted. We elucidate novel radiomic and radiogenomic workflow concepts and state-of-the-art descriptors in sub-visual MR image processing, with relevant literature on applications of such machine learning techniques in glioma management.

Advanced magnetic resonance spectroscopic neuroimaging: Experts' consensus recommendations

Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state-of-the-art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor-provided MRSI implementations, and identifies areas which need further technical development.

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.

Glutamate Is a Noninvasive Metabolic Biomarker of IDH1-Mutant Glioma Response to Temozolomide Treatment

Although lower grade gliomas are driven by mutations in the isocitrate dehydrogenase 1 (IDH1) gene and are less aggressive than primary glioblastoma, they nonetheless generally recur. IDH1-mutant patients are increasingly being treated with temozolomide, but early detection of response remains a challenge and there is a need for complementary imaging methods to assess response to therapy prior to tumor shrinkage. The goal of this study was to determine the value of magnetic resonance spectroscopy (MRS)-based metabolic changes for detection of response to temozolomide in both genetically engineered and patient-derived mutant IDH1 models. Using 1H MRS in combination with chemometrics identified several metabolic alterations in temozolomide-treated cells, including a significant increase in steady-state glutamate levels. This was confirmed in vivo, where the observed 1H MRS increase in glutamate/glutamine occurred prior to tumor shrinkage. Cells labeled with [1-13C]glucose and [3-13C]glutamine, the principal sources of cellular glutamate, showed that flux to glutamate both from glucose via the tricarboxylic acid cycle and from glutamine were increased following temozolomide treatment. In line with these results, hyperpolarized [5-13C]glutamate produced from [2-13C]pyruvate and hyperpolarized [1-13C]glutamate produced from [1-13C]α-ketoglutarate were significantly higher in temozolomide-treated cells compared with controls. Collectively, our findings identify 1H MRS-detectable elevation of glutamate and hyperpolarized 13C MRS-detectable glutamate production from either pyruvate or α-ketoglutarate as potential translatable metabolic biomarkers of response to temozolomide treatment in mutant IDH1 glioma. SIGNIFICANCE: These findings show that glutamate can be used as a noninvasive, imageable metabolic marker for early assessment of tumor response to temozolomide, with the potential to improve treatment strategies for mutant IDH1 patients.

Efficiency of High and Standard b Value Diffusion-Weighted Magnetic Resonance Imaging in Grading of Gliomas

Background

Glioma is the most common fatal malignant tumor of the CNS. Early detection of glioma grades based on diffusion-weighted imaging (DWI) properties is considered one of the most recent noninvasive promising tools in the assessment of glioma grade and could be helpful in monitoring patient prognosis and response to therapy.

Aim

This study aimed to investigate the accuracy of DWI at both standard and high b values (b = 1000 s/mm² and b = 3000 s/mm²) to distinguish high-grade glioma (HGG) from low-grade glioma (LGG) in clinical practice based on histopathological results.

Materials and Methods

Twenty-three patients with glioma had DWI at l.5 T MR using two different b values (b = 1000 s/mm² and b = 3000 s/mm²) at Al-Shifa Medical Complex after obtaining ethical and administrative approvals, and data were collected from March 2019 to March 2020. Minimum, maximum, and mean of apparent diffusion coefficient (ADC) values were measured through drawing region of interest (ROI) on a solid part at ADC maps. Data were analyzed by using the MedCalc analysis program, version 19.0.4, receiver operating characteristic (ROC) curve analysis was done, and optimal cutoff values for grading gliomas were determined. Sensitivity and specificity were also calculated.

Results

The obtained results showed the ADC_mean, ADC_ratio, ADC_max, and ADC_min were performed to differentiate between LGG and HGG at both standard and high b values. Moreover, ADC values were inversely proportional to glioma grade, and these differences are more obvious at high b value. Minimum ADC values using standard b value were 1.13 ± 0.17 × 10⁻³ mm²/s, 0.89 ± 0.85 × 10⁻³ mm²/s, and 0.82 ± 0.17 × 10⁻³ mm²/s for grades II, III, and IV, respectively. Concerning high b value, ADC_min values were 0.76 ± 0.07 × 10⁻³ mm²/s, 0.61 ± 0.01 × 10⁻³ mm²/s, and 0.48 ± 0.07 × 10⁻³ mm²/s for grades II, III, and IV, respectively. ADC values were inversely correlated with results of glioma grades, and the correlation was stronger at ADC₃₀₀₀ (r = −0.722, P ≤ 0.001). The ADC₃₀₀₀ achieved the highest diagnostic accuracy with an area under the curve (AUC) of 0.618, 100% sensitivity, 85.7% specificity, and 85.7% accuracy for glioma grading at a cutoff point of ≤0.618 × 10⁻³ mm²/s. The high b value showed stronger agreement with histopathology compared with standard b value results (k = 0.89 and 0.79), respectively.

Conclusion

The ADC values decrease with an increase in tumor cellularity. Meanwhile, high b value provides better tissue contrast by reflecting more tissue diffusivity. Therefore, ADC-derived parameters at high b value are more useful in the grading of glioma than those obtained at standard b value. They might be a better surrogate imaging sequence in the preoperative evaluation of gliomas.

Main genetic differences in high-grade gliomas may present different MR imaging and MR spectroscopy correlates

OBJECTIVE

To assess whether the main genetic differences observed in high-grade gliomas (HGG) will present different MR imaging and MR spectroscopy correlates that could be used to better characterize lesions in the clinical setting.

METHODS

Seventy-nine patients with histologically confirmed HGG were recruited. Immunohistochemistry analyses for isocitrate dehydrogenase gene 1 (IDH1), alpha thalassemia mental retardation X-linked gene (ATRX), Ki-67, and p53 protein expression were performed. Tumour radiological features were examined on MR images. Metabolic profile and infiltrative pattern were assessed with MR spectroscopy. MR features were analysed to identify imaging-molecular associations. The Kaplan-Meier method and the Cox regression model were used to identify survival prognostic factors.

RESULTS

In total, 17.7% of the lesions were IDH1-mutated, 8.9% presented ATRX-mutated, 70.9% presented p53 unexpressed, and 22.8% had Ki-67 > 5%. IDH1 wild-type tumours had higher levels of mobile lipids (p = 0.001). The tumour-infiltrative pattern was higher in HGG with unexpressed p53 (p = 0.009). Mutated ATRX tumours presented higher levels of glutamate and glutamine (Glx) (p = 0.001). An association was observed between Glx tumour levels (p = 0.038) and Ki-67 expression (p = 0.008) with the infiltrative pattern. Survival analyses identified IDH1 status, age, and tumour choline levels as independent predictors of prognostic significance.

CONCLUSIONS

Our results suggest that IDH1-wt tumours are more necrotic than IDH1-mut. And that the presence of an infiltrative pattern in HGG is associated with loss of p53 expression, Ki-67 index, and Glx levels. Finally, tumour choline levels could be used as a predictive factor in survival in addition to the IDH1 status to provide a more accurate prediction of survival in HGG patients.

KEY POINTS

• IDH1-wt tumours present higher levels of mobile lipids than IDH1-mut. • Mutated ATRX tumours exhibit higher levels of glutamate and glutamine. • Loss of p53 expression, Ki-67 expression, and glutamate and glutamine levels may contribute to the presence of an infiltrative pattern in HGG.

Establishment of age group classification for risk stratification in glioma patients

Background

Age is associated with the prognosis of glioma patients, but there is no uniform standard of age-group classification to evaluate the prognosis of glioma patients. In this study, we aimed to establish an age group classification for risk stratification in glioma patients.

Methods

1502 patients diagnosed with gliomas at Nanfang Hospital between 2000 and 2018 were enrolled. The WHO grade of glioma was used as a dependent variable to evaluate the effect of age on risk stratification. The evaluation model was established by logistic regression, and the Akaike information criterion (AIC) value of the model was used to determine the optimal cutoff points for age-classification. The differences in gender, WHO grade, pathological subtype, tumor cell differentiation, tumor size, tumor location, and molecular markers between different age groups were analyzed. The molecular markers included GFAP, EMA, MGMT, P53, NeuN, Oligo2, EGFR, VEGF, IDH1, Ki-67, PR, CD3, H3K27M, TS, and 1p/19q status.

Results

The proportion of men with glioma was higher than that of women with glioma (58.3% vs 41.7%). Analysis of age showed that appropriate classifications of age group were 0–14 years old (pediatric group), 15–47 years old (youth group), 48–63 years old (middle-aged group), and ≥ 64 years old (elderly group).The proportions of glioblastoma and large tumor size (4–6 cm) increased with age (p = 0.000, p = 0.018, respectively). Analysis of the pathological molecular markers across the four age groups showed that the proportion of patients with larger than 10% area of Ki-67 expression or positive PR expression increased with age (p = 0.000, p = 0.017, respectively).

Conclusions

Appropriate classifications of the age group for risk stratification are 0–14 years old (pediatric group), 15–47 years old (young group), 48–63 years old (middle age group) and ≥ 64 years old (elderly group). This age group classification is effective in evaluating the risk of glioblastoma in glioma patients.

Multiparametric MRI: practical approach and pictorial review of a useful tool in the evaluation of brain tumours and tumour-like lesions

MRI has a vital role in the assessment of intracranial lesions. Conventional MRI has limited specificity and multiparametric MRI using diffusion-weighted imaging, perfusion-weighted imaging and magnetic resonance spectroscopy allows more accurate assessment of the tissue microenvironment. The purpose of this educational pictorial review is to demonstrate the role of multiparametric MRI for diagnosis, treatment planning and for assessing treatment response, as well as providing a practical approach for performing and interpreting multiparametric MRI in the clinical setting. A variety of cases are presented to demonstrate how multiparametric MRI can help differentiate neoplastic from non-neoplastic lesions compared to conventional MRI alone.

The diagnostic role of diffusional kurtosis imaging in glioma grading and differentiation of gliomas from other intra-axial brain tumours: a systematic review with critical appraisal and meta-analysis

Purpose

We aim to illustrate the diagnostic performance of diffusional kurtosis imaging (DKI) in the diagnosis of gliomas.

Methods

A review protocol was developed according to the (PRISMA-P) checklist, registered in the international prospective register of systematic reviews (PROSPERO) and published. A literature search in 4 databases was performed using the keywords ‘glioma’ and ‘diffusional kurtosis’. After applying a robust inclusion/exclusion criteria, included articles were independently evaluated according to the QUADAS-2 tool and data extraction was done. Reported sensitivities and specificities were used to construct 2 × 2 tables and paired forest plots using the Review Manager (RevMan®) software. A random-effect model was pursued using the hierarchical summary receiver operator characteristics.

Results

A total of 216 hits were retrieved. Considering duplicates and inclusion criteria, 23 articles were eligible for full-text reading. Ultimately, 19 studies were eligible for final inclusion. The quality assessment revealed 9 studies with low risk of bias in the 4 domains. Using a bivariate random-effect model for data synthesis, summary ROC curve showed a pooled area under the curve (AUC) of 0.92 and estimated sensitivity of 0.87 (95% CI 0.78–0.92) in high-/low-grade gliomas’ differentiation. A mean difference in mean kurtosis (MK) value between HGG and LGG of 0.22 (95% CI 0.25–0.19) was illustrated (p value = 0.0014) with moderate heterogeneity (I² = 73.8%).

Conclusion

DKI shows good diagnostic accuracy in the differentiation of high- and low-grade gliomas further supporting its potential role in clinical practice. Further exploration of DKI in differentiating IDH status and in characterising non-glioma CNS tumours is however needed.

Electronic supplementary material

The online version of this article (10.1007/s00234-020-02425-9) contains supplementary material, which is available to authorized users.

Correction to: Advanced imaging in adult diffusely infiltrating low-grade gliomas

The original article [1] contains errors in Table 1 in rows ktrans and Ve; the correct version of Table 1 can be viewed in this Correction article.

Discrimination between Glioblastoma and Solitary Brain Metastasis: Comparison of Inflow-Based Vascular-Space-Occupancy and Dynamic Susceptibility Contrast MR Imaging

BACKGROUND AND PURPOSE

Accurate differentiation between glioblastoma and solitary brain metastasis is of vital importance clinically. This study aimed to investigate the potential value of the inflow-based vascular-space-occupancy MR imaging technique, which has no need for an exogenous contrast agent, in differentiating glioblastoma and solitary brain metastasis and to compare it with DSC MR imaging.

MATERIALS AND METHODS

Twenty patients with glioblastoma and 22 patients with solitary brain metastasis underwent inflow-based vascular-space-occupancy and DSC MR imaging with a 3T clinical scanner. Two neuroradiologists independently measured the maximum inflow-based vascular-space-occupancy-derived arteriolar CBV and DSC-derived CBV values in intratumoral regions and peritumoral T2-hyperintense regions, which were normalized to the contralateral white matter (relative arteriolar CBV and relative CBV, inflow-based vascular-space-occupancy relative arteriolar CBV, and DSC-relative CBV). The intraclass correlation coefficient, Student t test, or Mann-Whitney U test and receiver operating characteristic analysis were performed.

RESULTS

All parameters of both regions had good or excellent interobserver reliability (0.74∼0.89). In peritumoral T2-hyperintese regions, DSC-relative CBV (P < .001), inflow-based vascular-space-occupancy arteriolar CBV (P = .001), and relative arteriolar CBV (P = .005) were significantly higher in glioblastoma than in solitary brain metastasis, with areas under the curve of 0.94, 0.83, and 0.72 for discrimination, respectively. In the intratumoral region, both inflow-based vascular-space-occupancy arteriolar CBV and relative arteriolar CBV were significantly higher in glioblastoma than in solitary brain metastasis (both P < .001), with areas under the curve of 0.91 and 0.90, respectively. Intratumoral DSC-relative CBV showed no significant difference (P = .616) between the 2 groups.

CONCLUSIONS

Inflow-based vascular-space-occupancy has the potential to discriminate glioblastoma from solitary brain metastasis, especially in the intratumoral region.

Prediction of IDH Status Through MRI Features and Enlightened Reflection on the Delineation of Target Volume in Low-Grade Gliomas

Isocitrate dehydrogenase mutational status defines distinct biologic behavior and clinical outcomes in low-grade gliomas. We sought to determine magnetic resonance imaging characteristics associated with isocitrate dehydrogenase mutational status to evaluate the predictive roles of magnetic resonance imaging features in isocitrate dehydrogenase mutational status and therefore their potential impact on the determination of clinical target volume in radiotherapy. Forty-eight isocitrate dehydrogenase-mutant and 28 isocitrate dehydrogenase–wild-type low-grade gliomas were studied. Isocitrate dehydrogenase mutation was related to more frequency of cortical involvement compared to isocitrate dehydrogenase–wild-type group (34/46 vs 6/24, P = .0001). Peritumoral edema was less frequent in isocitrate dehydrogenase–mutant tumors (32.6% vs 58.3% for isocitrate dehydrogenase–wild-type tumors, P = .0381). Isocitrate dehydrogenase–wild-type tumors were more likely to have a nondefinable border, while isocitrate dehydrogenase–mutant tumors had well-defined borders (66.7% vs 39.1%, P = .0287). Only 8 (17.4%) of 46 of the isocitrate dehydrogenase–mutant tumors demonstrated marked enhancement, while this was 66.7% in isocitrate–wild-type tumors (P < .0001). Choline–creatinine ratio for isocitrate dehydrogenase–wild-type tumors was significantly higher than that for isocitrate dehydrogenase–mutant tumors. In conclusion, frontal location, well-defined border, cortical involvement, less peritumoral edema, lack of enhancement, and low choline–creatinine ratio were predictive for the definition of isocitrate dehydrogenase–mutant low-grade gliomas. Magnetic resonance imaging can provide an advantage in the detection of isocitrate dehydrogenase status indirectly and indicate the need to explore new design for treatment planning in gliomas. Choline–creatinine ratio in magnetic resonance spectroscopy could be a potential more reasonable reference for the new design of delineation of target volume in low-grade gliomas.

Metastases to the central nervous system: Molecular basis and clinical considerations

BACKGROUND

Metastatic tumors are the most common malignancies of the central nervous system (CNS) in adults. CNS metastases are associated with unfavorable prognosis, high morbidity and mortality. Lung cancer is the most common source of brain metastases, followed by breast cancer and melanoma. Rising incidence is primarily due to improvements in systemic control of primary malignancies, prolonged survival and advances in cancer detection.

PURPOSE

To provide an overview of the metastatic cascade and the role of angiogenesis, neuroinflammation, metabolic adaptations, and clinical details about brain metastases from different primary tumors.

METHODS

A review of the literature on brain metastases was conducted, focusing on the pathophysiology and clinical aspects of the disease. PubMed was used to search for relevant articles published from January 1975 through December 2019 using the keywords brain metabolism, brain metastasis, metastatic cascade, molecular mechanisms, incidence, risk factors, and prognosis. 146 articles met the criteria and were included in this review.

DISCUSSION

Some primary tumors have a higher tendency to metastasize to the CNS. Establishing a suitable metastatic microenvironment is important in maintaining tumor cell growth and survival. Magnetic resonance imaging (MRI) is a widely used tool for diagnosis and treatment monitoring. Available treatments include surgery, radiotherapy, stereotactic radiosurgery, chemotherapy, immunotherapy, and systemic targeted therapies.

CONCLUSIONS

Prevention of metastases to the CNS remains a difficult challenge. Advances in screening of high-risk patients and future development of novel treatments may improve patient outcomes.

Advanced imaging in adult diffusely infiltrating low-grade gliomas

The adult diffusely infiltrating low-grade gliomas (LGGs) are typically IDH mutant and slow-growing gliomas having moderately increased cellularity generally without mitosis, necrosis, and microvascular proliferation. Supra-total resection of LGG significantly increases the overall survival by delaying malignant transformation compared with a simple debulking so accurate MR diagnosis is crucial for treatment planning. Data from meta-analysis support the addition of diffusion and perfusion-weighted MR imaging and MR spectroscopy in the diagnosis of suspected LGG. Typically, LGG has lower cellularity (ADCmin), angiogenesis (rCBVmax), capillary permeability (Ktrans), and mitotic activity (Cho/Cr ratio) compared to high-grade glioma. The identification of 2-hydroxyglutarate by MR spectroscopy can reflect the IDH status of the tumor. The initial low ADCmin, high rCBVmax, and Ktrans values are consistent with the poor prognosis. The gradual increase in intratumoral Cho/Cr ratio and rCBVmax values are well correlated with tumor progression. Besides MR-based technical artifacts, which are minimized by the voxel-based assessment of data obtained by histogram analysis, the problems derived from the diversity and the analysis of imaging data should be solved by using artificial intelligence techniques. The quantitative multiparametric MR imaging of LGG can either improve the diagnostic accuracy of their differential diagnosis or assess their prognosis.

The anatomy and metabolome of the lymphatic system in the brain in health and disease

Recent studies have demonstrated that the brain is equipped with a lymphatic drainage system that is actively involved in parenchymal waste clearance, brain homeostasis and immune regulation. However, the exact anatomic drainage routes of brain lymph fluid (BLF) remain elusive, hampering the physiological study and clinical application of this system. In this study, we systematically dissected the anatomy of the BLF pathways in a rat model. Moreover, we developed a protocol to collect BLF from the afferent lymphatic vessels of deep cervical lymph nodes (dcLNs) and cerebrospinal fluid (CSF) from the fourth ventricle. Nuclear magnetic resonance spectroscopy showed that BLF contains more metabolites than CSF, suggesting that BLF might be a more sensitive indicator of brain dynamics under physiological and pathological conditions. Finally, we identified several metabolites as potential diagnostic biomarkers for glioma, Parkinson's disease and CNS infectious diseases. Together, these data may provide insight into the physiology of the lymphatic system in the brain and into the clinical diagnosis of CNS disorders.

TSPO PET, tumour grading and molecular genetics in histologically verified glioma: a correlative 18F-GE-180 PET study

BACKGROUND

The 18-kDa translocator protein (TSPO) is overexpressed in brain tumours and represents an interesting target for glioma imaging. ¹⁸F-GE-180, a novel TSPO ligand, has shown improved binding affinity and a high target-to-background contrast in patients with glioblastoma. However, the association of uptake characteristics on TSPO PET using ¹⁸F-GE-180 with the histological WHO grade and molecular genetic features so far remains unknown and was evaluated in the current study.

METHODS

Fifty-eight patients with histologically validated glioma at initial diagnosis or recurrence were included. All patients underwent ¹⁸F-GE-180 PET, and the maximal and mean tumour-to-background ratios (TBR_max, TBR_mean) as well as the PET volume were assessed. On MRI, presence/absence of contrast enhancement was evaluated. Imaging characteristics were correlated with neuropathological parameters (i.e. WHO grade, isocitrate dehydrogenase (IDH) mutation, O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation and telomerase reverse transcriptase (TERT) promoter mutation).

RESULTS

Six of 58 patients presented with WHO grade II, 16/58 grade III and 36/58 grade IV gliomas. An (IDH) mutation was found in 19/58 cases, and 39/58 were classified as IDH-wild type. High ¹⁸F-GE-180-uptake was observed in all but 4 cases (being WHO grade II glioma, IDH-mutant). A high association of ¹⁸F-GE-180-uptake and WHO grades was seen: WHO grade IV gliomas showed the highest uptake intensity compared with grades III and II gliomas (median TBR_max 5.15 (2.59-8.95) vs. 3.63 (1.85-7.64) vs. 1.63 (1.50-3.43), p < 0.001); this association with WHO grades persisted within the IDH-wild-type and IDH-mutant subgroup analyses (p < 0.05). Uptake intensity was also associated with the IDH mutational status with a trend towards higher ¹⁸F-GE-180-uptake in IDH-wild-type gliomas in the overall group (median TBR_max 4.67 (1.56-8.95) vs. 3.60 (1.50-7.64), p = 0.083); however, within each WHO grade, no differences were found (e.g. median TBR_max in WHO grade III glioma 4.05 (1.85-5.39) vs. 3.36 (2.32-7.64), p = 1.000). No association was found between uptake intensity and MGMT or TERT (p > 0.05 each).

CONCLUSION

Uptake characteristics on ¹⁸F-GE-180 PET are highly associated with the histological WHO grades, with the highest ¹⁸F-GE-180 uptake in WHO grade IV glioblastomas and a PET-positive rate of 100% among the investigated high-grade gliomas. Conversely, all TSPO-negative cases were WHO grade II gliomas. The observed association of ¹⁸F-GE-180 uptake and the IDH mutational status seems to be related to the high inter-correlation of the IDH mutational status and the WHO grades.

Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging-a comprehensive overview

Gadolinium-based contrast agents (GBCAs) increase lesion detection and improve disease characterization for many cerebral pathologies investigated with MRI. These agents, introduced in the late 1980s, are in wide use today. However, some non-ionic linear GBCAs have been associated with the development of nephrogenic systemic fibrosis in patients with kidney failure. Gadolinium deposition has also been found in deep brain structures, although it is of unclear clinical relevance. Hence, new guidelines from the International Society for Magnetic Resonance in Medicine advocate cautious use of GBCA in clinical and research practice. Some linear GBCAs were restricted from use by the European Medicines Agency (EMA) in 2017.

This review focuses on non-contrast-enhanced MRI techniques that can serve as alternatives for the use of GBCAs. Clinical studies on the diagnostic performance of non-contrast-enhanced as well as contrast-enhanced MRI methods, both well established and newly proposed, were included. Advantages and disadvantages together with the diagnostic performance of each method are detailed. Non-contrast-enhanced MRIs discussed in this review are arterial spin labeling (ASL), time of flight (TOF), phase contrast (PC), diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS), susceptibility weighted imaging (SWI), and amide proton transfer (APT) imaging.

Ten common diseases were identified for which studies reported comparisons of non-contrast-enhanced and contrast-enhanced MRI. These specific diseases include primary brain tumors, metastases, abscess, multiple sclerosis, and vascular conditions such as aneurysm, arteriovenous malformation, arteriovenous fistula, intracranial carotid artery occlusive disease, hemorrhagic, and ischemic stroke.

In general, non-contrast-enhanced techniques showed comparable diagnostic performance to contrast-enhanced MRI for specific diagnostic questions. However, some diagnoses still require contrast-enhanced imaging for a complete examination.

PI3K/mTOR inhibition of IDH1 mutant glioma leads to reduced 2HG production that is associated with increased survival

70-90% of low-grade gliomas and secondary glioblastomas are characterized by mutations in isocitrate dehydrogenase 1 (IDHmut). IDHmut produces the oncometabolite 2-hydroxyglutarate (2HG), which drives tumorigenesis in these tumors. The phosphoinositide-3-kinase (PI3K)/mammalian target of rapamycin (mTOR) pathway represents an attractive therapeutic target for IDHmut gliomas, but noninvasive indicators of drug target modulation are lacking. The goal of this study was therefore to identify magnetic resonance spectroscopy (MRS)-detectable metabolic biomarkers associated with IDHmut glioma response to the dual PI3K/(mTOR) inhibitor XL765. ¹H-MRS of two cell lines genetically modified to express IDHmut showed that XL765 induced a significant reduction in several intracellular metabolites including 2HG. Importantly, examination of an orthotopic IDHmut tumor model showed that enhanced animal survival following XL765 treatment was associated with a significant in vivo ¹H-MRS detectable reduction in 2HG but not with significant inhibition in tumor growth. Further validation is required, but our results indicate that 2HG could serve as a potential noninvasive MRS-detectable metabolic biomarker of IDHmut glioma response to PI3K/mTOR inhibition.

Amide proton transfer imaging of glioblastoma, neuroblastoma, and breast cancer cells on a 11.7 T magnetic resonance imaging system

PURPOSE

The purpose of this study was (i) to determine the optimal magnetization transfer (MT) pulse parameter for amide proton transfer (APT) chemical exchange saturation transfer (CEST) imaging on an ultra-high-field magnetic resonance imaging (MRI) system and (ii) to use APT CEST imaging to noninvasively assess brain orthotopic and ectopic tumor cells transplanted into the mouse brain.

METHODS

To evaluate APT without the influence of other metabolites, we prepared egg white phantoms. Next, we used 7-11-week-old nude female mice and the following cell lines to establish tumors after injection into the left striatum of mice: C6 (rat glioma, n = 8) as primary tumors and Neuro-2A (mouse neuroblastoma, n = 11) and MDA-MB231 (human breast cancer, n = 8) as metastatic tumors. All MRI experiments were performed on an 11.7 T vertical-bore scanner. CEST imaging was performed at 1 week after injection of Neuro-2A cells and at 2 weeks after injection of C6 and MDA-MB231 cells. The MT pulse amplitude was set at 2.2 μT or 4.4 μT. We calculated and compared the magnetization transfer ratio (MTR) and difference of MTR asymmetry between normal tissue and tumor (ΔMTR asymmetry) on APT CEST images between mouse models of brain tumors. Then, we performed hematoxylin and eosin (HE) staining and Ki-67 immunohistochemical staining to compare the APT CEST effect on tumor tissues and the pathological findings.

RESULTS

Phantom study of the amide proton phantom containing chicken egg white, z-spectra obtained at a pulse length of 500 ms showed smaller peaks, whereas those obtained at a pulse length of 2000 ms showed slightly higher peaks. The APT CEST effect on tumor tissues was clearer at a pulse amplitude of 2.2 μT than at 4.4 μT. For all mouse models of brain tumors, ΔMTR asymmetry was higher at 2.2 μT than at 4.4 μT. ΔMTR asymmetry was significantly higher for the Neuro-2A model than for the MDA-MB231 model. HE staining revealed light bleeding in Neuro-2A tumors. Immunohistochemical staining revealed that the density of Ki-67-positive cells was higher in Neuro-2A tumors than in C6 or MDA-MB231 tumors.

CONCLUSION

The MTR was higher at 4.4 μT than at 2.2 μT for each concentration of egg white at a pulse length of 500 ms or 2000 ms. High-resolution APT CEST imaging on an ultra-high-field MRI system was able to provide tumor information such as proliferative potential and intratumoral bleeding, noninvasively.

Comparison of L-Methyl-11C-Methionine PET With Magnetic Resonance Spectroscopy in Detecting Newly Diagnosed Glioma

AIMS

Amino acid PET and magnetic resonance spectroscopy (MRS) are at the forefront of noninvasive imaging techniques used for detection and subtyping of glioma-suspicious lesions. In this pilot study, we compare L-methyl-C-methionine PET and MRS for their ability to predict glioma subtypes.

METHODS

Nineteen patients with histologically, confirmed newly diagnosed glioma underwent preoperative L-methyl-C-methionine PET and MRS in 1 diagnostic session. According to the molecular portfolio and histopathologic diagnosis, patients were subdivided in isocitrate dehydrogenase (IDH) wild-type glioblastoma, IDH wild-type grade II/III glioma, IDH-mutant grade II/III glioma without 1p/19q codeletion, and with 1p/19q codeletion subgroups. Maximum tumor-to-brain ratio (TBRmax), creatine, choline, and N-acetyl aspartate peaks were correlated with postoperative histopathologic tumor diagnoses.

RESULTS

Maximum tumor-to-brain ratio was highest in glioblastoma patients (4.18) followed by patients with IDH wild-type grade II and III glioma (3.41). The latter TBRmax values were higher compared with those in patients with IDH-mutant grade II/III glioma without 1p/19q codeletion (1.95) and in patients with IDH-mutant 1p/19q codeleted grade II and III glioma (2.79). Magnetic resonance spectroscopy marker distribution showed no clear trend. Receiver operating characteristic analysis revealed TBRmax to be the best performing parameter in identifying IDH status (area under the curve, 0.67) and all spectroscopy markers combined in identifying glioma subgroups (area under the curve, 0.68), respectively.

CONCLUSIONS

L-Methyl-C-methionine PET and MRS bear limited potential in glioma subgrouping. L-Methyl-C-methionine PET appears to be superior in differentiating IDH status, whereas MRS is more helpful in glioma subgrouping.

Differentiation of Glioblastoma and Solitary Brain Metastasis by Gradient of Relative Cerebral Blood Volume in the Peritumoral Brain Zone Derived from Dynamic Susceptibility Contrast Perfusion Magnetic Resonance Imaging

OBJECTIVE

The purpose of our study was to evaluate the efficacy of the relative cerebral blood volume (rCBV) gradient in the peritumoral brain zone (PBZ)-the difference in the rCBV values from the area closest to the enhancing lesion to the area closest to the healthy white matter-in differentiating glioblastoma (GB) from solitary brain metastasis (MET).

METHODS

A 3.0-T magnetic resonance imaging (MRI) machine was used to perform dynamic susceptibility contrast perfusion MRI (DSC-MRI) on 43 patients with a solitary brain tumor (24 GB, 19 MET). The rCBV ratios were acquired by DSC-MRI data in 3 regions of the PBZ (near the enhancing tumor, G1; intermediate distance from the enhancing tumor, G2; far from the enhancing tumor, G3). The maximum rCBV ratios in the PBZ (rCBVp) and the enhancing tumor were also calculated, respectively. The perfusion parameters were evaluated using the nonparametric Mann-Whitney test. The sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve were identified.

RESULTS

The rCBVp ratios and rCBV gradient in the PBZ were significantly higher in GB compared with MET (P < 0.05 for both rCBVp ratios and rCBV gradient). The threshold values of 0.50 or greater for rCBVp ratios provide sensitivity and specificity of 57.69% and 79.17%, respectively, for differentiation of GB from MET. Compared with rCBVp ratios, rCBV gradient had higher sensitivity (94.44%) and specificity (91.67%) using the threshold value of greater than 0.06.

CONCLUSIONS

The parameter of rCBV gradient derived from DSC-MRI in the PBZ seems to be the most efficient parameter to differentiate GB from METs.

Brain metastases

An estimated 20% of all patients with cancer will develop brain metastases, with the majority of brain metastases occurring in those with lung, breast and colorectal cancers, melanoma or renal cell carcinoma. Brain metastases are thought to occur via seeding of circulating tumour cells into the brain microvasculature; within this unique microenvironment, tumour growth is promoted and the penetration of systemic medical therapies is limited. Development of brain metastases remains a substantial contributor to overall cancer mortality in patients with advanced-stage cancer because prognosis remains poor despite multimodal treatments and advances in systemic therapies, which include a combination of surgery, radiotherapy, chemotherapy, immunotherapy and targeted therapies. Thus, interest abounds in understanding the mechanisms that drive brain metastases so that they can be targeted with preventive therapeutic strategies and in understanding the molecular characteristics of brain metastases relative to the primary tumour so that they can inform targeted therapy selection. Increased molecular understanding of the disease will also drive continued development of novel immunotherapies and targeted therapies that have higher bioavailability beyond the blood-tumour barrier and drive advances in radiotherapies and minimally invasive surgical techniques. As these discoveries and innovations move from the realm of basic science to preclinical and clinical applications, future outcomes for patients with brain metastases are almost certain to improve.

Diffuse Low-Grade Glioma - Changing Concepts in Diagnosis and Management: A Review

Though diffuse low-grade gliomas (dLGGs) represent only 15% of gliomas, they have been receiving increasing attention in the past decade. Significant advances in knowledge of the natural history and clinical diversity have been documented, and an improved pathological classification of gliomas that integrates histological features with molecular markers has been issued by the WHO. Advances in the radiological assessment of dLGG, particularly new magnetic resonance imaging scanning sequences, allow improved diagnostic and prognostic information. The management paradigms are evolving from “wait and watch” of the past to more active interventional therapy to obviate the risk of malignant transformation. New surgical technologies allow more aggressive surgical resections with a reduction of morbidity. Many reports suggest the association of gross total resection with longer overall survival and progression-free survival in addition to better seizure control. The literature also shows the use of chemotherapeutics and radiation therapy as important adjuncts to surgery. The goals of management have has been increasing survival with increasing stress on quality of life. Our review highlights the recent advances in the molecular diagnosis and management of dLGG with trends toward multidisciplinary and multimodality management of dLGG with an aim to surgically resect the primary disease, followed by chemoradiation in cases of progressive or recurrent disease.

Multivoxel 1H-MR Spectroscopy Biometrics for Preoprerative Differentiation Between Brain Tumors

We investigated multivoxel proton magnetic resonance spectroscopy (¹H-MRS) biometrics for preoperative differentiation and prognosis of patients with brain metastases (MET), low-grade glioma (LGG) and high-grade glioma (HGG). In total, 33 patients (HGG, 14; LGG, 9; and 10 MET) were included. ¹H-MRS imaging (MRSI) data were assessed and neurochemical profiles for metabolites N-acetyl aspartate (NAA) + NAAG(NAA), Cr + PCr(total creatine, tCr), Glu + Gln(Glx), lactate (Lac), myo-inositol(Ins), GPC + PCho(total choline, tCho), and total lipids, and macromolecule (tMM) signals were estimated. Metabolites were reported as absolute concentrations or ratios to tCho or tCr levels. Voxels of interest in an MRSI matrix were labeled according to tissue. Logistic regression, receiver operating characteristic, and Kaplan-Meier survival analysis was performed. Across HGG, LGG, and MET, average Ins/tCho was shown to be prognostic for overall survival (OS): low values (≤1.29) in affected hemisphere predicting worse OS than high values (>1.29), (log rank < 0.007). Lip/tCho and Ins/tCho combined showed 100% sensitivity and specificity for both HGG/LGG (P < .001) and LGG/MET (P < .001) measured in nonenhancing/contrast-enhancing lesional tissue. Combining tCr/tCho in perilesional edema with tCho/tCr and NAA/tCho from ipsilateral normal- appearing tissue yielded 100% sensitivity and 81.8% specificity (P < .002) for HGG/MET. Best single biomarker: Ins/tCho for HGG/LGG and total lipid/tCho for LGG/MET showed 100% sensitivity and 75% and 100% specificity, respectively. HGG/MET; NAA/tCho showed 75% sensitivity and 84.6% specificity. Multivoxel 1H-MRSI provides prognostic information for OS for HGG/LGG/MET and a multibiometric approach for differentiation may equal or outperform single biometrics.

Evaluation of the INTERPRET decision-support system: can it improve the diagnostic value of magnetic resonance spectroscopy of the brain?

Purpose

We evaluated in a clinical setting the INTERPRET decision-support system (DSS), a software generated to aid in MRS analysis to achieve a specific diagnosis for brain lesions.

Methods

The material consisted of 100 examinations of focal intracranial lesions with confirmed diagnoses. MRS was obtained at 1.5 T using TE 20–30 ms. Data were processed with the LCModel for conventional analysis. The INTERPRET DSS 3.1. was used to obtain specific diagnoses. MRI and MRS were reviewed by one interpreter. DSS analysis was made by another interpreter, in 80 cases by two interpreters. The diagnoses were compared with the definitive diagnoses. For comparisons between DSS, conventional MRS analysis, and MRI, the diagnoses were categorised: high-grade tumour, low-grade tumour, non-neoplastic lesion.

Results

Interobserver agreement in choosing the diagnosis from the INTERPRET database was 75%. The diagnosis was correct in 38/100 cases, incorrect in 57 cases. No good match was found in 5/100 cases. The diagnostic category was correct with DSS/conventional MRS/MRI in 67/58/52 cases, indeterminate in 5/8/20 cases, incorrect in 28/34/28 cases. Results with DSS were not significantly better than with conventional MRS analysis. All definitive diagnoses did not exist in the INTERPRET database. In the 61 adult patients with the diagnosis included in the database, DSS/conventional MRS/MRI yielded a correct diagnosis category in 48/32/29 cases (DSS vs conventional MRS: p = 0.002, DSS vs MRI: p = 0.0004).

Conclusion

Use of the INTERPRET DSS did not improve MRS categorisation of the lesions in the unselected clinical cases. In adult patients with lesions existing in the INTERPRET database, DSS improved the results, which indicates the potential of this software with an extended database.

Electronic supplementary material

The online version of this article (10.1007/s00234-018-2129-7) contains supplementary material, which is available to authorized users.

Exogenous Amino Acid-Loaded Nanovehicles: Stepping across Endogenous Magnetic Resonance Spectroscopy

Magnetic resonance spectroscopy (MRS) allows the assessment of metabolic contents and biochemical information in vivo. It provides essential compositional information in the diagnosis and monitoring of central nervous system (CNS) diseases, especially brain tumors. Conventional MRS is usually confined to endogenous metabolites that may lack specificity for certain disease such as differentiating glioma from other tumor and non-tumorous lesions. Therefore, exogenous MRS contrast agents (CAs) that may improve the sensitivity and specificity of MRS are highly desirable for its clinical use. In this work, a novel MRS CA, β-alanine loaded hollow mesoporous silica nanospheres, with a high biosafety profile and characteristic MRS spectrum was synthesized and investigated. This new CA is further tested to realize the accurate functional MRS diagnosis of brain glioma with high sensitivity. The general approach of synthesizing disease specific CA for MRS may lead to a new era of molecular imaging.