MR imaging of neoplastic central nervous system lesions: review and recommendations for current practice

The effect of time-delayed contrast-enhanced scanning in determining the gross tumor target volume of large-volume brain metastases

BACKGROUND AND PURPOSE

To assess the variation of large-volume brain metastases (BMs) boundaries and shapes using enhanced magnetic resonance (MR) scanning with different delay times and to provide a basis for determining the gross tumor target volume (GTV) for radiotherapy of BMs.

MATERIALS AND METHODS

We prospectively enrolled 155 patients initially diagnosed with BMs (561 lesions > 1 cm). Contrast-enhanced (CE) T1-weighted imaging scans were performed 1, 3, 5, 10, 18, and 20 min after gadolinium-based contrast agent injection and GTVs were determined as GTV-1min, GTV-3min, GTV-5min, GTV-10min, GTV-18min, and GTV-20min, respectively, which were subsequently fused in different phases. Fusion of the six GTVs was defined as GTV-total, which was set as the reference GTV. The volume, shape, and signal intensity of the GTVs and brain white matter (BWM) were compared at different delay times.

RESULTS

GTV-3min, GTV-5min, GTV-10min, GTV-18min, and GTV-20min volumes increased by 2.2 %, 3.8 %, 6.5 %, 9.5 %, and 10.6 %, respectively (P < 0.05) compared with GTV-1min. Compared with GTV-total, GTV-1min, GTV-3min, GTV-5min, GTV-10min, GTV-18min, and GTV-20min volumes reduced by 25.4 %, 22.1 %, 18.7 %, 15.0 %, 11.2 %, and 10.3 %, respectively (P < 0.05). Compared with GTV-total, 29 (51.8 %) fused GTVs had a volume reduction rate < 5 %, 45 (80.4 %) had a Dice similarity coefficient > 0.95, and all contained GTV-10min, GTV-18min or GTV-20min. The signal intensity ratio between the GTV and BWM peaked at 5 min (0.351 ± 0.24).

CONCLUSION

Enhanced MR scans with different delay times show significant differences in the boundaries and shapes of large-volume BMs, and time-delayed multi-phase CE scanning should be used in GTV determination, with time phases ≥ 10 min being mandatory.

Advances in determining the gross tumor target volume for radiotherapy of brain metastases

Brain metastases (BMs) are the most prevalent intracranial malignant tumors in adults and are the leading cause of mortality attributed to malignant brain diseases. Radiotherapy (RT) plays a critical role in the treatment of BMs, with local RT techniques such as stereotactic radiosurgery (SRS)/stereotactic body radiotherapy (SBRT) showing remarkable therapeutic effectiveness. The precise determination of gross tumor target volume (GTV) is crucial for ensuring the effectiveness of SRS/SBRT. Multimodal imaging techniques such as CT, MRI, and PET are extensively used for the diagnosis of BMs and GTV determination. With the development of functional imaging and artificial intelligence (AI) technology, there are more innovative ways to determine GTV for BMs, which significantly improve the accuracy and efficiency of the determination. This article provides an overview of the progress in GTV determination for RT in BMs.

A Novel Multi-Model High Spatial Resolution Method for Analysis of DCE MRI Data: Insights from Vestibular Schwannoma Responses to Antiangiogenic Therapy in Type II Neurofibromatosis

This study aimed to develop and evaluate a new DCE-MRI processing technique that combines LEGATOS, a dual-temporal resolution DCE-MRI technique, with multi-kinetic models. This technique enables high spatial resolution interrogation of flow and permeability effects, which is currently challenging to achieve. Twelve patients with neurofibromatosis type II-related vestibular schwannoma (20 tumours) undergoing bevacizumab therapy were imaged at 1.5 T both before and at 90 days following treatment. Using the new technique, whole-brain, high spatial resolution images of the contrast transfer coefficient (Ktrans), vascular fraction (vp), extravascular extracellular fraction (ve), capillary plasma flow (Fp), and the capillary permeability-surface area product (PS) could be obtained, and their predictive value was examined. Of the five microvascular parameters derived using the new method, baseline PS exhibited the strongest correlation with the baseline tumour volume (p = 0.03). Baseline ve showed the strongest correlation with the change in tumour volume, particularly the percentage tumour volume change at 90 days after treatment (p < 0.001), and PS demonstrated a larger reduction at 90 days after treatment (p = 0.0001) when compared to Ktrans or Fp alone. Both the capillary permeability-surface area product (PS) and the extravascular extracellular fraction (ve) significantly differentiated the 'responder' and 'non-responder' tumour groups at 90 days (p < 0.05 and p < 0.001, respectively). These results highlight that this novel DCE-MRI analysis approach can be used to evaluate tumour microvascular changes during treatment and the need for future larger clinical studies investigating its role in predicting antiangiogenic therapy response.

An Effective Approach to Improve the Automatic Segmentation and Classification Accuracy of Brain Metastasis by Combining Multi-phase Delay Enhanced MR Images

The objective of this study is to analyse the diffusion rule of the contrast media in multi-phase delayed enhanced magnetic resonance (MR) T1 images using radiomics and to construct an automatic classification and segmentation model of brain metastases (BM) based on support vector machine (SVM) and Dpn-UNet. A total of 189 BM patients with 1047 metastases were enrolled. Contrast-enhanced MR images were obtained at 1, 3, 5, 10, 18, and 20 min following contrast medium injection. The tumour target volume was delineated, and the radiomics features were extracted and analysed. BM segmentation and classification models in the MR images with different enhancement phases were constructed using Dpn-UNet and SVM, and differences in the BM segmentation and classification models with different enhancement times were compared. (1) The signal intensity for BM decreased with time delay and peaked at 3 min. (2) Among the 144 optimal radiomics features, 22 showed strong correlation with time (highest R-value = 0.82), while 41 showed strong correlation with volume (highest R-value = 0.99). (3) The average dice similarity coefficients of both the training and test sets were the highest at 10 min for the automatic segmentation of BM, reaching 0.92 and 0.82, respectively. (4) The areas under the curve (AUCs) for the classification of BM pathology type applying single-phase MRI was the highest at 10 min, reaching 0.674. The AUC for the classification of BM by applying the six-phase image combination was the highest, reaching 0.9596, and improved by 42.3% compared with that by applying single-phase images at 10 min. The dynamic changes of contrast media diffusion in BM can be reflected by multi-phase delayed enhancement based on radiomics, which can more objectively reflect the pathological types and significantly improve the accuracy of BM segmentation and classification.

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

OBJECTIVE

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

PATIENTS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Predicting the grade of meningiomas by clinical-radiological features: A comparison of precontrast and postcontrast MRI

OBJECTIVES

Postcontrast magnetic resonance imaging (MRI) is important for the differentiation between low-grade (WHO I) and high-grade (WHO II/III) meningiomas. However, nephrogenic systemic fibrosis and cerebral gadolinium deposition are major concerns for postcontrast MRI. This study aimed to develop and validate an accessible risk-scoring model for this differential diagnosis using the clinical characteristics and radiological features of precontrast MRI.

METHODS

From January 2019 to October 2021, a total of 231 meningioma patients (development cohort n = 137, low grade/high grade, 85/52; external validation cohort n = 94, low-grade/high-grade, 60/34) were retrospectively included. Fourteen types of demographic and radiological characteristics were evaluated by logistic regression analyses in the development cohort. The selected characteristics were applied to develop two distinguishing models using nomograms, based on full MRI and precontrast MRI. Their distinguishing performances were validated and compared using the external validation cohort.

RESULTS

One demographic characteristic (male), three precontrast MRI features (intratumoral cystic changes, lobulated and irregular shape, and peritumoral edema), and one postcontrast MRI feature (absence of a dural tail sign) were independent predictive factors for high-grade meningiomas. The area under the receiver operating characteristic (ROC) curve (AUC) values of the two distinguishing models (precontrast-postcontrast nomogram vs. precontrast nomogram) in the development cohort were 0.919 and 0.898 and in the validation cohort were 0.922 and 0.878. DeLong's test showed no statistical difference between the AUC values of the two distinguishing models (p = 0.101).

CONCLUSIONS

An accessible risk-scoring model based on the demographic characteristics and radiological features of precontrast MRI is sufficient to distinguish between low-grade and high-grade meningiomas, with a performance equal to that of a full MRI, based on radiological features.

Contrast allergies for neurological imaging: When to proceed

Contrast-enhanced neuroimaging is often necessary for the diagnosis and care of patients with diseases of the central nervous system. Although contrast is generally well tolerated and allergy to contrast is rare, allergic reactions can be severe and life threatening. Therefore, physicians should take care to prevent severe contrast allergy. In this review, we will discuss contrast allergy as well as potential strategies to reduce the risk of severe reactions in patients who require neuroimaging techniques with contrast. First, we discuss the clinical presentation and pathogenesis of contrast allergy and the risk factors associated with reactions. We then review methods to reduce the risk of future contrast reactions through improved patient education and documentation strategies, use of alternate imaging modalities or contrast media, premedication, and desensitization.

The effect of time delay for magnetic resonance contrast-enhanced scan on imaging for small-volume brain metastases

PURPOSE

To study the effect of different enhancement timings of magnetic resonance (MR) on small-volume brain metastases (BM) visualisation and provide a basis for the contour of tumour targets.

METHOD

We prospectively enrolled 101 patients with BM who received radiotherapy. All patients underwent computed tomography (CT) and MR simulations. Contrast-enhanced MR scans at 1, 3, 5, 10, 18, and 20 min after injection of contrast medium were performed. The tumour target was determined on MR images at different enhancement times, and the differences of tumour target volume, maximum diameter, and MR signal intensity were compared.

RESULTS

(1) Of the 453 metastatic lesions, 24 (5.2 %) were not detected at 1 min and 8 (1.8 %) were not detected at 3 min; however, all metastases were detected after 5 min. The volume and maximum diameter of the 28 (6.2 %) metastases were stable at any time. (2) The average volume of metastatic lesions at 1, 3, 5, 10, 18, and 20 min was 0.09 cm³, 0.10 cm³, 0.12 cm³, 0.12 cm³, 0.13 cm³, and 0.13 cm³, respectively. Compared to 1 min, BM volume at other times increased by 13.1 %, 21.5 %, 31.6 %, 39.6 %, and 41.7 %, and the difference between the maximum and minimum volumes was statistically significant (p < 0.05). (3) The distribution of the maximum ratio of tumours to white matter mean signal intensity at different times were 39.6 %, 20 %, 14.6 %, 8.0 %, 10.4 %, and 10 %, respectively.

CONCLUSION

The visualisation of small-volume BM was significantly different at different enhancement times. Our results suggest that multi-timing enhancement scans for small-volume BM should be implemented and that scanning at >10 min is essential.

Preclinical Profile of Gadoquatrane: A Novel Tetrameric, Macrocyclic High Relaxivity Gadolinium-Based Contrast Agent

OBJECTIVES

The aim of this report was to characterize the key physicochemical, pharmacokinetic (PK), and magnetic resonance imaging (MRI) properties of gadoquatrane (BAY 1747846), a newly designed tetrameric, macrocyclic, extracellular gadolinium-based contrast agent (GBCA) with high relaxivity and stability.

MATERIALS AND METHODS

The r1-relaxivities of the tetrameric gadoquatrane at 1.41 and 3.0 T were determined in human plasma and the nuclear magnetic relaxation dispersion profiles in water and plasma. The complex stability was analyzed in human serum over 21 days at pH 7.4 at 37°C and was compared with the linear GBCA gadodiamide and the macrocyclic GBCA (mGBCA) gadobutrol. In addition, zinc transmetallation assay was performed to investigate the kinetic inertness. Protein binding and the blood-to-plasma ratio were determined in vitro using rat and human plasma. The PK profile was evaluated in rats (up to 7 days postinjection). Magnetic resonance imaging properties were investigated using a glioblastoma (GS9L) rat model.

RESULTS

The new chemical entity gadoquatrane is a macrocyclic tetrameric Gd complex with one inner sphere water molecule per Gd ( q = 1). Gadoquatrane showed high solubility in buffer (1.43 mol Gd/L, 10 mM Tris-HCl, pH 7.4), high hydrophilicity (logP -4.32 in 1-butanol/water), and negligible protein binding. The r1-relaxivity of gadoquatrane in human plasma per Gd of 11.8 mM -1 ·s -1 (corresponding to 47.2 mM -1 ·s -1 per molecule at 1.41 T at 37°C, pH 7.4) was more than 2-fold (8-fold per molecule) higher compared with established mGBCAs. Nuclear magnetic relaxation dispersion profiles confirmed the more than 2-fold higher r1-relaxivity in human plasma for the clinically relevant magnetic field strengths from 0.47 to 3.0 T. The complex stability of gadoquatrane at physiological conditions was very high. The observed Gd release after 21 days at 37°C in human serum was below the lower limit of quantification. Gadoquatrane showed no Gd 3+ release in the presence of zinc in the transmetallation assay. The PK profile (plasma elimination, biodistribution, recovery) was comparable to that of gadobutrol. In MRI, the quantitative evaluation of the tumor-to-brain contrast in the rat glioblastoma model showed significantly improved contrast enhancement using gadoquatrane compared with gadobutrol at the same Gd dose administered (0.1 mmol Gd/kg body weight). In comparison to gadoterate meglumine, similar contrast enhancement was reached with gadoquatrane with 75% less Gd dose. In terms of the molecule dose, this was reduced by 90% when compared with gadoterate meglumine. Because of its tetrameric structure and hence lower number of molecules per volume, all prepared formulations of gadoquatrane were iso-osmolar to blood.

CONCLUSIONS

The tetrameric gadoquatrane is a novel, highly effective mGBCA for use in MRI. Gadoquatrane provides favorable physicochemical properties (high relaxivity and stability, negligible protein binding) while showing essentially the same PK profile (fast extracellular distribution, fast elimination via the kidneys in an unchanged form) to established mGBCAs on the market. Overall, gadoquatrane is an excellent candidate for further clinical development.

From Dose Reduction to Contrast Maximization: Can Deep Learning Amplify the Impact of Contrast Media on Brain Magnetic Resonance Image Quality? A Reader Study

OBJECTIVES

The aim of this study was to evaluate a deep learning method designed to increase the contrast-to-noise ratio in contrast-enhanced gradient echo T1-weighted brain magnetic resonance imaging (MRI) acquisitions. The processed images are quantitatively evaluated in terms of lesion detection performance.

MATERIALS AND METHODS

A total of 250 multiparametric brain MRIs, acquired between November 2019 and March 2021 at Gustave Roussy Cancer Campus (Villejuif, France), were considered for inclusion in this retrospective monocentric study. Independent training (107 cases; age, 55 ± 14 years; 58 women) and test (79 cases; age, 59 ± 14 years; 41 women) samples were defined. Patients had glioma, brain metastasis, meningioma, or no enhancing lesion. Gradient echo and turbo spin echo with variable flip angles postcontrast T1 sequences were acquired in all cases. For the cases that formed the training sample, "low-dose" postcontrast gradient echo T1 images using 0.025 mmol/kg injections of contrast agent were also acquired. A deep neural network was trained to synthetically enhance the low-dose T1 acquisitions, taking standard-dose T1 MRI as reference. Once trained, the contrast enhancement network was used to process the test gradient echo T1 images. A read was then performed by 2 experienced neuroradiologists to evaluate the original and processed T1 MRI sequences in terms of contrast enhancement and lesion detection performance, taking the turbo spin echo sequences as reference.

RESULTS

The processed images were superior to the original gradient echo and reference turbo spin echo T1 sequences in terms of contrast-to-noise ratio (44.5 vs 9.1 and 16.8; P < 0.001), lesion-to-brain ratio (1.66 vs 1.31 and 1.44; P < 0.001), and contrast enhancement percentage (112.4% vs 85.6% and 92.2%; P < 0.001) for cases with enhancing lesions. The overall image quality of processed T1 was preferred by both readers (graded 3.4/4 on average vs 2.7/4; P < 0.001). Finally, the proposed processing improved the average sensitivity of gradient echo T1 MRI from 88% to 96% for lesions larger than 10 mm (P = 0.008), whereas no difference was found in terms of the false detection rate (0.02 per case in both cases; P > 0.99). The same effect was observed when considering all lesions larger than 5 mm: sensitivity increased from 70% to 85% (P < 0.001), whereas false detection rates remained similar (0.04 vs 0.06 per case; P = 0.48). With all lesions included regardless of their size, sensitivities were 59% and 75% for original and processed T1 images, respectively (P < 0.001), and the corresponding false detection rates were 0.05 and 0.14 per case, respectively (P = 0.06).

CONCLUSION

The proposed deep learning method successfully amplified the beneficial effects of contrast agent injection on gradient echo T1 image quality, contrast level, and lesion detection performance. In particular, the sensitivity of the MRI sequence was improved by up to 16%, whereas the false detection rate remained similar.

Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives

This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.

A Transfer Learning-Based Active Learning Framework for Brain Tumor Classification

Brain tumor is one of the leading causes of cancer-related death globally among children and adults. Precise classification of brain tumor grade (low-grade and high-grade glioma) at an early stage plays a key role in successful prognosis and treatment planning. With recent advances in deep learning, artificial intelligence-enabled brain tumor grading systems can assist radiologists in the interpretation of medical images within seconds. The performance of deep learning techniques is, however, highly depended on the size of the annotated dataset. It is extremely challenging to label a large quantity of medical images, given the complexity and volume of medical data. In this work, we propose a novel transfer learning-based active learning framework to reduce the annotation cost while maintaining stability and robustness of the model performance for brain tumor classification. In this retrospective research, we employed a 2D slice-based approach to train and fine-tune our model on the magnetic resonance imaging (MRI) training dataset of 203 patients and a validation dataset of 66 patients which was used as the baseline. With our proposed method, the model achieved area under receiver operating characteristic (ROC) curve (AUC) of 82.89% on a separate test dataset of 66 patients, which was 2.92% higher than the baseline AUC while saving at least 40% of labeling cost. In order to further examine the robustness of our method, we created a balanced dataset, which underwent the same procedure. The model achieved AUC of 82% compared with AUC of 78.48% for the baseline, which reassures the robustness and stability of our proposed transfer learning augmented with active learning framework while significantly reducing the size of training data.

The LEGATOS technique: A new tissue-validated dynamic contrast-enhanced MRI method for whole-brain, high-spatial resolution parametric mapping

PURPOSE

A DCE-MRI technique that can provide both high spatiotemporal resolution and whole-brain coverage for quantitative microvascular analysis is highly desirable but currently challenging to achieve. In this study, we sought to develop and validate a novel dual-temporal resolution (DTR) DCE-MRI-based methodology for deriving accurate, whole-brain high-spatial resolution microvascular parameters.

METHODS

Dual injection DTR DCE-MRI was performed and composite high-temporal and high-spatial resolution tissue gadolinium-based-contrast agent (GBCA) concentration curves were constructed. The high-temporal but low-spatial resolution first-pass GBCA concentration curves were then reconstructed pixel-by-pixel to higher spatial resolution using a process we call LEGATOS. The accuracy of kinetic parameters (K^trans , v_p , and v_e ) derived using LEGATOS was evaluated through simulations and in vivo studies in 17 patients with vestibular schwannoma (VS) and 13 patients with glioblastoma (GBM). Tissue from 15 tumors (VS) was examined with markers for microvessels (CD31) and cell density (hematoxylin and eosin [H&E]).

RESULTS

LEGATOS derived parameter maps offered superior spatial resolution and improved parameter accuracy compared to the use of high-temporal resolution data alone, provided superior discrimination of plasma volume and vascular leakage effects compared to other high-spatial resolution approaches, and correlated with tissue markers of vascularity (P ≤ 0.003) and cell density (P ≤ 0.006).

CONCLUSION

The LEGATOS method can be used to generate accurate, high-spatial resolution microvascular parameter estimates from DCE-MRI.

PET and SPECT Imaging of Brain Tumors

Neuroimaging plays a vital role in the diagnosis and post-treatment assessment of brain tumors, aiding in treatment optimization, prognostication, and patient management. New clinical treatments have resulted in increased complexity of imaging interpretation, thus integrating complementary information from multiple imaging modalities (computed tomography, magnetic resonance imaging, and nuclear medicine) contributes to a thorough and more accurate evaluation. In review, we discuss current strategies of brain tumor imaging, specifically detailing the role of nuclear medicine single-photon emission computed tomography and positron emission tomography with utilization of both common and uncommon radiotracers in tumor grading, diagnosis, and treatment response.

MR imaging by 3D T1-weighted black blood sequences may improve delineation of therapy-naive high-grade gliomas

Objectives

To investigate the value of contrast-enhanced (CE) turbo spin echo black blood (BB) sequences for imaging of therapy-naive high-grade gliomas (HGGs).

Methods

Consecutive patients with histopathologically confirmed World Health Organization (WHO) grade III or IV gliomas and no oncological treatment prior to index imaging (March 2019 to January 2020) were retrospectively included. Magnetic resonance imaging (MRI) at 3 Tesla comprised CE BB and CE turbo field echo (TFE) sequences. The lack/presence of tumor-related contrast enhancement and satellite lesions were evaluated by two readers. Sharper delineation of tumor boundaries (1, bad; 2, intermediate; 3, good delineation) and vaster expansion of HGGs into the adjacent brain parenchyma on CE BB imaging were the endpoints. Furthermore, contrast-to-noise ratios (CNRs) were calculated and compared between sequences.

Results

Fifty-four patients were included (mean age: 61.2 ± 15.9 years, 64% male). The vast majority of HGGs (51/54) showed contrast enhancement in both sequences, while two HGGs as well as one of six detected satellite lesions were depicted in CE BB imaging only. Tumor boundaries were significantly sharper (R1: 2.43 ± 0.71 vs. 2.73 ± 0.62, p < 0.001; R2: 2.44 ± 0.74 vs. 2.77 ± 0.60, p = 0.001), while the spread of HGGs into the adjacent parenchyma was larger when considering CE BB sequences according to both readers (larger spread in CE BB sequences: R1: 23 patients; R2: 20 patients). The CNR for CE BB sequences significantly exceeded that of CE TFE sequences (43.4 ± 27.1 vs. 32.5 ± 25.0, p = 0.0028).

Conclusions

Our findings suggest that BB imaging may considerably improve delineation of therapy-naive HGGs when compared with established TFE imaging. Thus, CE BB sequences might supplement MRI protocols for brain tumors.

Key Points

• This study investigated contrast-enhanced (CE) T1-weighted black blood (BB) sequences for improved MRI in patients with therapy-naive high-grade gliomas (HGGs).

• Compared with conventionally used turbo field echo (TFE) sequences, CE BB sequences depicted tumor boundaries and spread of HGGs into adjacent parenchyma considerably better, which also showed higher CNRs.

• Two enhancing tumor masses and one satellite lesion were exclusively identified in CE BB sequences, but remained undetected in conventionally used CE TFE sequences.

[Modern standards for magnetic resonance imaging of the brain tumors]

Neuroimaging is essential in survey of patients with brain tumors. An important objectives of neuroimaging are highly reliable non-invasive diagnosis, treatment planning and evaluation of treatment outcomes. Magnetic resonance imaging (MRI) is one of the modern neuroimaging methods. This technique ensures analysis of structural cerebral changes, vascular and metabolic characteristics of brain tumors. It is necessary to standardize imaging parameters and unify protocols and methods considering a widespread use of MRI for brain tumors. In our practice, we use our own experience, world literature data and evidence-based international guidelines on the diagnosis of various brain diseases. The purpose of this review is to study the modern principles of magnetic resonance imaging in adults with brain tumors in neurosurgical practice.

Applications for Transition-Metal Chemistry in Contrast-Enhanced Magnetic Resonance Imaging

Contrast-enhanced magnetic resonance imaging (MRI) is an indispensable tool for diagnostic medicine. However, safety concerns related to gadolinium in commercial MRI contrast agents have emerged in recent years. For patients suffering from severe renal impairment, there is an important unmet medical need to perform contrast-enhanced MRI without gadolinium. There are also concerns over the long-term effects of retained gadolinium within the general patient population. Demand for gadolinium-free MRI contrast agents is driving a new wave of inorganic chemistry innovation as researchers explore paramagnetic transition-metal complexes as potential alternatives. Furthermore, advances in personalized care making use of molecular-level information have motivated inorganic chemists to develop MRI contrast agents that can detect pathologic changes at the molecular level. Recent studies have highlighted how reaction-based modulation of transition-metal paramagnetism offers a highly effective mechanism to achieve MRI contrast enhancement that is specific to biochemical processes. This Viewpoint highlights how recent advances in transition-metal chemistry are leading the way for a new generation of MRI contrast agents.

PET/CT in pediatric oncology

The use of PET/CT in adult oncology has been consolidated by several and authoritative multicentric studies, metanalyses and systematic reviews. International guidelines help everyday nuclear medicine specialists, oncologists and radiologists in choosing the most suitable diagnostic path for each patient. Classifications based on traditional imaging and PET/CT findings define the most appropriate treatment and can predict the outcome for different types of malignancies. However, compared to adult patients the use of PET/CT in pediatric oncology is often burdened by lack of systematic and large multicentric studies and consequently accurate and precise guidelines. The cause of this shortage of large trials may be attributed to the rarity of these neoplasms and to the fear of long-term radiation effects on this peculiar category of patients. The aim of this article is to review the applications of PET/CT for imaging the most common pediatric neoplasms.

Recognition of Brain Metastases Using Gadolinium-Enhanced SWI MRI: Proof-of-Concept Study

Background and purpose: SWI MRI, a T2^*-dominant MRI sequence with T1 shine-through effect, uses intrinsic structural susceptibility to create enhancement among brain structures. We evaluated whether gadolinium-enhanced SWI (SWI-Gd) improves brain metastasis detection in combination with other MRI sequences.

Materials and methods: MRI images of 24 patients (46 studies) were prospectively acquired using a 1.5-T scanner. T1-weighted, unenhanced SWI (SWI-U) and SWI-Gd were evaluated blindly to clinical features by two board-certified radiologists.

Results: SWI-Gd revealed more significant metastatic lesions than either T1-Gd or SWI-U (p = 0.0004 for either comparator sequence). Moreover, SWI-Gd revealed more lesions only for those patients with ≤5 lesions on T1-Gd (n = 30 studies from 16 patients; p = 0.046). Performing SWI-Gd added <5 min of scanning time with no further additional risk.

Conclusions: Our findings suggest that, when added to T1-Gd and other common sequences, SWI-Gd may improve the diagnostic yield of brain metastases with only a few extra minutes of scanning time and no further risk than that of a regular gadolinium-enhanced MRI.

Determination of optimal virtual monochromatic energy level for target delineation of brain metastases in radiosurgery using dual-energy CT

OBJECTIVE

Determination of the optimal energy level of virtual monochromatic image (VMI) for brain metastases in contrast-enhanced dual-energy CT (DECT) for radiosurgery and assessment of the subjective and objective image quality of VMI at the optimal energy level.

METHODS

20 patients (total of 42 metastases) underwent contrast-enhanced DECT. Spectral image analysis of VMIs at energy levels ranging from 40 to 140 keV in 1 keV increments was performed to determine the optimal VMI (VMI_opt) as the one corresponding to the highest contrast-to-noise ratio (CNR) between brain parenchyma and the metastases. The objective and subjective values of VMI_opt were compared to those of the VMI with 120 kVp equivalent, defined as reference VMI (VMI_ref, 77 keV). The objective measurement parameters included mean HU value and SD of tumor and brain parenchyma, absolute lesion contrast (LC), and CNR. The subjective measurements included five-point scale assessment of "overall image quality" and "tumor delineation" by three radiation oncologists.

RESULTS

The VMI at 63 keV was defined as VMI_opt. The LC and CNR of VMI_opt were significantly (p < 0.01) higher than those of VMI_ref (LC: 37.4 HU vs 24.7 HU; CNR: 1.1 vs 0.8, respectively). Subjective analysis rated VMI_opt significantly (p < 0.01) superior to VMI_ref with respect to the overall image quality (3.2 vs 2.9, respectively) and tumor delineation (3.5 vs 2.9, respectively).

CONCLUSION

The VMI at 63 keV derived from contrast-enhanced DECT yielded the highest CNR and improved the objective and subjective image quality for radiosurgery, compared to VMI_ref.

ADVANCES IN KNOWLEDGE

This paper investigated for the first time the optimal energy level of VMI in DECT for brain metastases. The findings will lead to improvement in tumor visibility with optimal VMI and consequently supplement accuracy delineation of brain metastases.

Divide and Conquer: Stratifying Training Data by Tumor Grade Improves Deep Learning-Based Brain Tumor Segmentation

It is a general assumption in deep learning that more training data leads to better performance, and that models will learn to generalize well across heterogeneous input data as long as that variety is represented in the training set. Segmentation of brain tumors is a well-investigated topic in medical image computing, owing primarily to the availability of a large publicly-available dataset arising from the long-running yearly Multimodal Brain Tumor Segmentation (BraTS) challenge. Research efforts and publications addressing this dataset focus predominantly on technical improvements of model architectures and less on properties of the underlying data. Using the dataset and the method ranked third in the BraTS 2018 challenge, we performed experiments to examine the impact of tumor type on segmentation performance. We propose to stratify the training dataset into high-grade glioma (HGG) and low-grade glioma (LGG) subjects and train two separate models. Although we observed only minor gains in overall mean dice scores by this stratification, examining case-wise rankings of individual subjects revealed statistically significant improvements. Compared to a baseline model trained on both HGG and LGG cases, two separately trained models led to better performance in 64.9% of cases (p < 0.0001) for the tumor core. An analysis of subjects which did not profit from stratified training revealed that cases were missegmented which had poor image quality, or which presented clinically particularly challenging cases (e.g., underrepresented subtypes such as IDH1-mutant tumors), underlining the importance of such latent variables in the context of tumor segmentation. In summary, we found that segmentation models trained on the BraTS 2018 dataset, stratified according to tumor type, lead to a significant increase in segmentation performance. Furthermore, we demonstrated that this gain in segmentation performance is evident in the case-wise ranking of individual subjects but not in summary statistics. We conclude that it may be useful to consider the segmentation of brain tumors of different types or grades as separate tasks, rather than developing one tool to segment them all. Consequently, making this information available for the test data should be considered, potentially leading to a more clinically relevant BraTS competition.

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.

A Critical Appraisal of the Quality of Glioma Imaging Guidelines Using the AGREE II Tool: A EuroAIM Initiative

Background: Following the EuroAIM initiative to assess the quality of medical imaging guidelines by using the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument, we aimed to evaluate the quality of the current imaging guidelines in patients with gliomas.

Methods: A literature search was conducted to identify eligible imaging guidelines considered in the management of adult patients with gliomas. The selected guidelines were evaluated using the AGREE II instrument by four independent appraisers. The agreement among the four appraisers was estimated using the intraclass correlation coefficient (ICC) analysis.

Results: Seven guidelines were selected for the appraisal. Six out of the seven guidelines showed an average level of quality with only one showing a low quality. The highest scores were found in Domain 1 “Scope and purpose” (mean score = 81.2%) and Domain 4 “Clarity of presentation” (mean score = 77.6%). The remaining domains showed a low level of quality and, in particular, Domain 5 “Applicability” was the most critical with a mean score of 41.7%, mainly related to a minor attention to barriers and facilitators as well as costs and resources implications of applying the guidelines. The ICC analysis showed a very good agreement among the four appraisers with ICC values ranging from 0.907 to 0.993.

Conclusions: The available guidelines on glioma imaging emerged as of average quality according to the AGREE II tool analysis. Based on these results, further efforts should be made in order to involve different professional bodies and stakeholders and increase patient and public involvement in any future guideline drafting as well as to improve the applicability of these guidelines into the clinical practice.

A comparison of pseudo-continuous arterial spin labelling and dynamic susceptibility contrast MRI with and without contrast agent leakage correction in paediatric brain tumours

OBJECTIVE:

To investigate correlations between MRI perfusion metrics measured by dynamic susceptibility contrast and arterial spin labelling in paediatric brain tumours.

METHODS:

15 paediatric patients with brain tumours were scanned prospectively using pseudo-continuous arterial spin labelling (ASL) and dynamic susceptibility contrast (DSC-) MRI with a pre-bolus to minimise contrast agent leakage. Cerebral blood flow (CBF) maps were produced using ASL. Cerebral blood volume (CBV) maps with and without contrast agent leakage correction using the Boxerman technique and the leakage parameter, K₂, were produced from the DSC data. Correlations between the metrics produced were investigated.

RESULTS:

Histology resulted in the following diagnoses: pilocytic astrocytoma (n = 7), glioblastoma (n = 1), medulloblastoma (n = 1), rosette-forming glioneuronal tumour of fourth ventricle (n = 1), atypical choroid plexus papilloma (n = 1) and pilomyxoid astrocytoma (n = 1). Three patients had a non-invasive diagnosis of low-grade glioma. DSC CBV maps of T₁-enhancing tumours were difficult to interpret without the leakage correction. CBV values obtained with and without leakage correction were significantly different (p < 0.01). A significant positive correlation was observed between ASL CBF and DSC CBV (r = 0.516, p = 0.049) which became stronger when leakage correction was applied (r = 0.728, p = 0.002). K₂ values were variable across the group (mean = 0.35, range = -0.49 to 0.64).

CONCLUSION:

CBV values from DSC obtained with and without leakage correction were significantly different. Large increases in CBV were observed following leakage correction in highly T₁-enhancing tumours. DSC and ASL perfusion metrics were found to correlate significantly in a range of paediatric brain tumours. A stronger relationship between DSC and ASL was seen when leakage correction was applied to the DSC data. Leakage correction should be applied when analysing DSC data in enhancing paediatric brain tumours.

ADVANCES IN KNOWLEDGE:

We have shown that leakage correction should be applied when investigating enhancing paediatric brain tumours using DSC-MRI. A stronger correlation was found between CBF derived from ASL and CBV derived from DSC when a leakage correction was employed.

Imaging practice in low-grade gliomas among European specialized centers and proposal for a minimum core of imaging

OBJECTIVE

Imaging studies in diffuse low-grade gliomas (DLGG) vary across centers. In order to establish a minimal core of imaging necessary for further investigations and clinical trials in the field of DLGG, we aimed to establish the status quo within specialized European centers.

METHODS

An online survey composed of 46 items was sent out to members of the European Low-Grade Glioma Network, the European Association of Neurosurgical Societies, the German Society of Neurosurgery and the Austrian Society of Neurosurgery.

RESULTS

A total of 128 fully completed surveys were received and analyzed. Most centers (n = 96, 75%) were academic and half of the centers (n = 64, 50%) adhered to a dedicated treatment program for DLGG. There were national differences regarding the sequences enclosed in MRI imaging and use of PET, however most included T1 (without and with contrast, 100%), T2 (100%) and TIRM or FLAIR (20, 98%). DWI is performed by 80% of centers and 61% of centers regularly performed PWI.

CONCLUSION

A minimal core of imaging composed of T1 (w/wo contrast), T2, TIRM/FLAIR, PWI and DWI could be identified. All morphologic images should be obtained in a slice thickness of ≤ 3 mm. No common standard could be obtained regarding advanced MRI protocols and PET.

IMPORTANCE OF THE STUDY

We believe that our study makes a significant contribution to the literature because we were able to determine similarities in numerous aspects of LGG imaging. Using the proposed "minimal core of imaging" in clinical routine will facilitate future cooperative studies.

Diagnostic performance of apparent diffusion coefficient parameters for glioma grading

This study was to evaluate the diagnostic performance of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) parameters derived from diffusion tensor imaging in the differentiation between grade II and III gliomas. The records of 60 patients (30 women, 30 men; mean age, 45.4 years) suspected of having gliomas who underwent an ADC image-guided stereotactic biopsy were retrospectively reviewed. The values of FA and ADC were measured, and the sensitivity, specificity, accuracy and area under the curve (AUC) of those parameters were calculated based on the receiver operating characteristic curve analysis. A predictive diagnostic equation was also constructed and evaluated. Significant differences in minimum ADC values were found in the quantitative analysis between the grade III and II glioma groups. The sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), accuracy and AUC for identifying grade III and II gliomas at the optimum cut-off value of 0.895 × 10^-3 mm²/s of minimum ADC were 81.0, 89.1, 77.3, 91.1, 86.6 and 0.87, respectively. The predictive diagnostic equation was superior to the single minimum ADC indicator with a sensitivity of 90.5%, a specificity of 84.8%, a PPV of 73.1%, an NPV of 95.1%, and an accuracy of 86.6%, respectively. The study provides evidence that minimum ADC values have a superior diagnostic performance in differentiating grade III and II gliomas, and the predictive diagnostic equation may be helpful in the differentiation.

Overview of neuroradiology

Neuroradiology with computed tomography (CT) and magnetic resonance imaging (MRI) is essential for the initial evaluation of patients with a clinical suspicion of brain and spine disorders. Morphologic imaging is required to obtain a probable diagnosis to support the treatment decisions in pre- and perinatal disorders, vascular diseases, traumatic injuries, metabolic disorders, epilepsy, infection/inflammation, neurodegenerative disorders, degenerative spinal disease, and tumors of the central nervous system. Different postprocessing tools are increasingly used for three-dimensional visualization and quantification of lesions. Additional information is provided by angiographic methods and physiologic CT and MRI techniques, such as diffusion MRI, perfusion CT/MRI, MR spectroscopy, functional MRI, tractography, and nuclear medicine imaging methods. Positron emission tomography (PET) is now integrated with CT (PET/CT), and PET/MR scanners have recently also been introduced. These hybrid techniques facilitate the co-registration of lesions with different modalities, and give new possibilites for functional imaging. Repeated imaging is increasingly performed for treatment monitoring. The improved imaging techniques together with the neuropathologic diagnosis after biopsy or surgery allow more personalized treatment of the patient. Neuroradiology also includes endovascular treatment of aneurysms and arteriovenous malformations as well as thrombectomy in acute stroke. This catheter-based treatment has replaced invasive neurosurgery in many cases.

Gadobutrol in India-A Comprehensive Review of Safety and Efficacy

Gadobutrol is a gadolinium (Gd)-based contrast agent for magnetic resonance imaging (MRI). In India, gadobutrol is approved for MRI of the central nervous system (CNS), liver, kidneys, breast and for MR angiography for patients 2 years and older. The standard dose for all age groups is 0.1 mmol/kg body weight. The safety profile has been demonstrated in 42 clinical phase 2 to 4 studies (>6800 patients), 7 observational studies, and by assessing pharmacovigilance data of 29 million applications. Furthermore, studies in children, adults, and elderly and in patients with impaired liver or kidney function did not show any increased adverse event rate. Diagnostic efficacy was demonstrated in numerous studies and various indications, such as diseases of the CNS, peripheral and supra-aortic vessels, kidneys, liver, and breast.

MR-guided radiation therapy: transformative technology and its role in the central nervous system

This review article describes advancement of magnetic resonance imaging technologies in radiation therapy planning, guidance, and adaptation of brain tumors. The potential for MR-guided radiation therapy to improve outcomes and the challenges in its adoption are discussed.

Preradiotherapy MR Imaging: A Prospective Pilot Study of the Usefulness of Performing an MR Examination Shortly before Radiation Therapy in Patients with Glioblastoma

BACKGROUND AND PURPOSE

Current protocols in patients with glioblastoma include performing an MR examination shortly after surgery and then 2-6 weeks after ending concomitant chemoradiotherapy. The assessment of this first postradiotherapy examination is challenging because the pseudoprogression phenomenon may appear. The aim of this study was to explore if performing an MR examination shortly before radiation therapy (preradiotherapy MR imaging) could improve the radiologic assessment of patients with glioblastoma.

MATERIALS AND METHODS

A preradiotherapy MR imaging examination was prospectively performed before the start of radiation therapy in 28 consecutive patients with glioblastoma who had undergone surgical resection. Tumor response to chemoradiotherapy was assessed twice: with the early postoperative MR examination as baseline and with the preradiotherapy MR imaging examination as baseline. In addition, tumor growth in the preradiotherapy MR imaging examination was evaluated, and its correlation with patient survival was assessed with Kaplan-Meier analysis and Cox regression.

RESULTS

Tumor progression after radiation therapy was found in 16 patients, corresponding to pseudoprogression in 7 of them (44%). Four assessments of pseudoprogression switched to partial response or stable disease when preradiotherapy MR imaging was the baseline examination, and the ratio of pseudoprogression was reduced to 25% (3 of 12). Significant differences in survival were found when patients were stratified according to the pattern of tumor growth on preradiotherapy MR imaging (median overall survival "no-growth," 837 days; "focal-growth," 582 days; "global-growth," 344 days; P = .001).

CONCLUSIONS

Performing a preradiotherapy MR imaging examination may improve the clinical management of patients with glioblastoma by reducing the ratio of pseudoprogression assessments and providing prognostic information.

Additive value of 320-section low-dose dynamic volume CT in relation to 3-T MRI for the preoperative evaluation of brain tumors

PURPOSE

To assess whether 320-section low-dose dynamic volume computed tomography (320-LDVCT) with adaptive iterative dose reduction (AIDR) adds value to 3-T MRI for the preoperative evaluation of brain tumors.

METHODS

The study population was comprised of 16 consecutive patients with brain tumors who, in addition to preoperative 3-T MRI, underwent 320-LDVCT with AIDR. Two radiologists independently evaluated the CT and MRI studies; one measured the relative cerebral blood volume (rCBV) in the tumor and contralateral brain on CT and MR perfusion maps. Interobserver agreement was assessed by κ statistics.

RESULTS

In 3 of 16 patients (19 %), 320-LDVCT added diagnostic value to 3-T MRI studies with respect to the visualization of feeders (κ = 0.77), and in 12 (75 %) it helped the delineation of venous structures (κ = 0.71) and the relationship between the tumor and adjacent vessels (κ = 0.85). The average standardized rCBV value was 12.2 ± 2.40 (range 0.7-36.6) on MR and 8.80 ± 2.77 (range 0.8-38.0) on CT perfusion studies; the correlation between these values was very strong (r = 0.92, p < 0.0001). According to the neurosurgeons, 320-LDVCT added helpful information for surgery in 4 patients (25 %).

CONCLUSION

The 320-LDVCT can add value to 3-T MRI for the tumor feeders and relationship between the tumor and adjacent vessels.

Time-delayed contrast-enhanced MRI improves detection of brain metastases: a prospective validation of diagnostic yield

The radiological detection of brain metastases (BMs) is essential for optimizing a patient's treatment. This statement is even more valid when stereotactic radiosurgery, a noninvasive image guided treatment that can target BM as small as 1-2 mm, is delivered as part of that care. The timing of image acquisition after contrast administration can influence the diagnostic sensitivity of contrast enhanced magnetic resonance imaging (MRI) for BM. Investigate the effect of time delayed acquisition after administration of intravenous Gadavist® (Gadobutrol 1 mmol/ml) on the detection of BM. This is a prospective IRB approved study of 50 patients with BM who underwent post-contrast MRI sequences after injection of 0.1 mmol/kg Gadavist® as part of clinical care (time-t0), followed by axial T1 sequences after a 10 min (time-t1) and 20 min delay (time-t2). MRI studies were blindly compared by three neuroradiologists. Single measure intraclass correlation coefficients were very high (0.914, 0.904 and 0.905 for time-t0, time-t1 and time-t2 respectively), corresponding to a reliable inter-observer correlation. The delayed MRI at time-t2 delayed sequences showed a significant and consistently higher diagnostic sensitivity for BM by every participating neuroradiologist and for the entire cohort (p = 0.016, 0.035 and 0.034 respectively). A disproportionately high representation of BM detected on the delayed studies was located within posterior circulation territories (compared to predictions based on tissue volume and blood-flow volumes). Considering the safe and potentially high yield nature of delayed MRI sequences, it should supplement the standard MRI sequences in all patients in need of precise delineation of their intracranial disease.

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

AIM

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

PATIENTS AND METHODS

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

RESULTS

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

CONCLUSION

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

High-grade glioma management and response assessment-recent advances and current challenges

The management of high-grade gliomas (hggs) is complex and ever-evolving. The standard of care for the treatment of hggs consists of surgery, chemotherapy, and radiotherapy. However, treatment options are influenced by multiple factors such as patient age and performance status, extent of tumour resection, biomarker profile, and tumour histology and grade. Follow-up cranial magnetic resonance imaging (mri) to differentiate treatment response from treatment effect can be challenging and affects clinical decision-making. An assortment of advanced radiologic techniques-including perfusion imaging with dynamic susceptibility contrast mri, dynamic contrast-enhanced mri, diffusion-weighted imaging, proton spectroscopy, mri subtraction imaging, and amino acid radiotracer imaging-can now incorporate novel physiologic data, providing new methods to help characterize tumour progression, pseudoprogression, and pseudoresponse. In the present review, we provide an overview of current treatment options for hgg and summarize recent advances and challenges in imaging technology.

Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review

Angiogenesis plays a fundamental role in cancer growth and the formation of metastasis. Novel cancer therapies aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature are currently being developed and clinically tested. The need for earlier and improved cancer diagnosis, and for early evaluation and monitoring of therapeutic response to angiogenic treatment, have led to the development of several imaging methods for in vivo noninvasive assessment of angiogenesis. The combination of dynamic contrast-enhanced imaging with mathematical modeling of the contrast agent kinetics enables quantitative assessment of the structural and functional changes in the microvasculature that are associated with tumor angiogenesis. In this paper, we review quantitative imaging of angiogenesis with dynamic contrast-enhanced magnetic resonance imaging, computed tomography, and ultrasound.

Diagnosis and New Treatment Modalities for Glioblastoma: Do They Improve Patient Survival?

Central nervous system (CNS) malignances include tumors of the brain and spinal cord. Taking into account the cell type where they originate from, there are almost 120 different types of CNS tumors. Benign tumors are not aggressive and normally do not invade other organs; however, they require surgical removal before they alter the surrounding brain functions. Primary malignant brain tumors commonly include astrocytomas, oligodendrogliomas, and ependimomas, where astrocytomas represent around 76%. The World Health Organization (WHO) has defined four histological grades of astrocytomas that range from the less aggressive tumors (grade I) to highly malignant tumors (grade IV). These grade IV tumors, also called glioblastoma (GBM), are the most aggressive of the primary malignant brain tumors. Patients with GBM have a median survival of 12 to 15 months. Current treatment for GBM includes surgery, radiotherapy and chemotherapy. Although there have been some advances in diagnosis and treatment, there is still no optimal treatment available for GBMs. In this review, we will discuss the approaches for GBM diagnosis and treatment, with a special emphasis to post-treatment imaging, and whether novel targeted therapies have impacted the survival of GBM patients. In addition, we will discuss clinical trials and the future of GBM diagnosis and treatment.

Advanced neuroimaging in the clinic: critical appraisal of the evidence base

The shortage of high-quality systematic reviews in the field of radiology limits evidence-based integration of imaging methods into clinical practice and may perpetuate misconceptions regarding the efficacy and appropriateness of imaging techniques for specific applications. Diffusion tensor imaging for patients with mild traumatic brain injury (DTI-mTBI) and dynamic susceptibility contrast MRI for patients with glioma (DSC-glioma) are applications of quantitative neuroimaging, which similarly detect manifestations of disease where conventional neuroimaging techniques cannot. We performed a critical appraisal of reviews, based on the current evidence-based medicine methodology, addressing the ability of DTI-mTBI and DSC-glioma to (a) detect brain abnormalities and/or (b) predict clinical outcomes. 23 reviews of DTI-mTBI and 26 reviews of DSC-glioma met criteria for inclusion. All reviews addressed detection of brain abnormalities, whereas 12 DTI-mTBI reviews and 22 DSC-glioma reviews addressed prediction of a clinical outcome. All reviews were assessed using a critical appraisal worksheet consisting of 19 yes/no questions. Reviews were graded according to the total number of positive responses and the 2011 Oxford Centre for evidence-based medicine levels of evidence criteria. Reviews addressing DTI-mTBI detection had moderate quality, while those addressing DSC-glioma were of low quality. Reviews addressing prediction of outcomes for both applications were of low quality. Five DTI-mTBI reviews, but only one review of DSC-glioma met criteria for classification as a meta-analysis/systematic/quantitative review.

25 Years of Contrast-Enhanced MRI: Developments, Current Challenges and Future Perspectives

In 1988, the first contrast agent specifically designed for magnetic resonance imaging (MRI), gadopentetate dimeglumine (Magnevist(®)), became available for clinical use. Since then, a plethora of studies have investigated the potential of MRI contrast agents for diagnostic imaging across the body, including the central nervous system, heart and circulation, breast, lungs, the gastrointestinal, genitourinary, musculoskeletal and lymphatic systems, and even the skin. Today, after 25 years of contrast-enhanced (CE-) MRI in clinical practice, the utility of this diagnostic imaging modality has expanded beyond initial expectations to become an essential tool for disease diagnosis and management worldwide. CE-MRI continues to evolve, with new techniques, advanced technologies, and novel contrast agents bringing exciting opportunities for more sensitive, targeted imaging and improved patient management, along with associated clinical challenges. This review aims to provide an overview on the history of MRI and contrast media development, to highlight certain key advances in the clinical development of CE-MRI, to outline current technical trends and clinical challenges, and to suggest some important future perspectives.

FUNDING

Bayer HealthCare.

Increased diffusion in the normal appearing white matter of brain tumor patients: is this just tumor infiltration?

Altered diffusion in the normal appearing white matter (NAWM) of glioma patients has been explained by tumor infiltration. The goal of the present study was to test this explanation indirectly by examining whether these alterations were also present in the contralateral NAWM of non-infiltrative tumors like meningiomas; and to search for other possible reasons for this abnormality. Twenty-seven patients with histologically verified glioma (grade II-IV), 22 meningioma patients and two groups of age- and sex-matched healthy controls underwent diffusion weighted imaging (DWI) on a 3T MR. All patients were examined before treatment. Apparent diffusion coefficient (ADC) values were calculated in the entire NAWM of the hemisphere contralateral to the tumor. ADC values of the NAWM were compared between groups with Mann-Whitney U-test and multiple linear regression. The relations of ADC in NAWM to glioma grade and to tumor volume were also investigated. ADC values of the contralateral NAWM were significantly higher in both glioma and meningioma patients compared to controls (P = 0.0006 and 0.0099, respectively). ADC value was higher in the NAWM of high grade gliomas than in low grade gliomas (P = 0.0181) and in healthy control subjects (P = 0.0003). ADC did not depend on tumor volume in any of the patient groups. Elevated ADC in the NAWM of both glioma and meningioma patients might indicate that the effect of infiltrating tumor cells is not the only reason for the alteration as it has been previously suggested. Although the role of mass effect was not proved, other mechanisms might also contribute to ADC elevation.

Conventional and advanced (DTI/SWI) neuroimaging findings in pediatric oligodendroglioma

PURPOSE

Oligodendroglioma are rare pediatric brain tumors. The literature about neuroimaging findings is scant. A correct presurgical diagnosis is important to plan the therapeutic approach. Here, we evaluated the conventional and advanced neuroimaging features in our cohort of pediatric oligodendrogliomas and discuss our findings in the context of the current literature.

METHODS

Clinical histories were reviewed for tumor grading, neurologic manifestation, treatment, and clinical status at the last follow-up. Neuroimaging studies were retrospectively evaluated for tumor morphology and characteristics on conventional and advanced magnetic resonance imaging (MRI).

RESULTS

Five children with oligodendroglioma were included in this study. Four children were diagnosed with a low-grade oligodendroglioma. The location of the tumors included the frontal and temporal lobe in two cases each and the fronto-parietal lobe in one. In all oligodendrogliomas, tumor margins appeared sharp. In the high-grade oligodendroglioma, a cystic and partially hemorrhagic component was seen. In all children, the tumor showed a T1-hypointense and T2-hyperintense signal. The signal intensity on fluid attenuation inversion recovery (FLAIR) images was hyperintense in four and mixed hypo-hyperintense in one child. The anaplastic oligodendroglioma showed postcontrast enhancement and decreased diffusion while the low-grade oligodendrogliomas showed increased diffusion. One low-grade oligodendroglioma showed calcifications on susceptibility weighted imaging.

CONCLUSION

Conventional MRI findings of pediatric oligodendrogliomas are nonspecific. Advanced MRI sequences may differentiate (1) low-grade and high-grade pediatric oligodendrogliomas and (2) pediatric oligodendrogliomas and other brain tumors.

Survival prediction in high-grade gliomas using CT perfusion imaging

Patients with high-grade gliomas usually have heterogeneous response to surgery and chemoirradiation. The objectives of this study were (1) to evaluate serial changes in tumor volume and perfusion imaging parameters and (2) to determine the value of these data in predicting overall survival (OS). Twenty-nine patients with World Health Organization grades III and IV gliomas underwent magnetic resonance (MR) and computed tomography (CT) perfusion examinations before surgery, and 1, 3, 6, 9, and 12 months after radiotherapy. Serial measurements of tumor volumes and perfusion parameters were evaluated by receiver operating characteristic analysis, Cox proportional hazards regression, and Kaplan-Meier survival analysis to determine their values in predicting OS. Higher trends in blood flow (BF), blood volume (BV), and permeability-surface area product in the contrast-enhancing lesions (CEL) and the non-enhancing lesions (NEL) were found in patients with OS < 18 months compared to those with OS ≥ 18 months, and these values were significant at selected time points (P < 0.05). Only CT perfusion parameters yielded sensitivities and specificities of ≥ 70% in predicting 18 and 24 months OS. Pre-surgery BF in the NEL and BV in the CEL and NEL 3 months after radiotherapy had sensitivities and specificities >80% in predicting 24 months OS in patients with grade IV gliomas. Our study indicated that CT perfusion parameters were predictive of survival and could be useful in assessing early response and in selecting adjuvant treatment to prolong survival if verified in a larger cohort of patients.

Exploring the biomechanical properties of brain malignancies and their pathologic determinants in vivo with magnetic resonance elastography

Malignant tumors are typically associated with altered rigidity relative to normal host tissue. Magnetic resonance elastography (MRE) enables the noninvasive quantitation of the mechanical properties of deep-seated tissue following application of an external vibrational mechanical stress to that tissue. In this preclinical study, we used MRE to quantify (kPa) the elasticity modulus Gd and viscosity modulus Gl of three intracranially implanted glioma and breast metastatic tumor models. In all these brain tumors, we found a notable softness characterized by lower elasticity and viscosity than normal brain parenchyma, enabling their detection on Gd and Gl parametric maps. The most circumscribed tumor (U-87 MG glioma) was the stiffest, whereas the most infiltrative tumor (MDA-MB-231 metastatic breast carcinoma) was the softest. Tumor cell density and microvessel density correlated significantly and positively with elasticity and viscosity, whereas there was no association with the extent of collagen deposition or myelin fiber entrapment. In conclusion, although malignant tumors tend to exhibit increased rigidity, intracranial tumors presented as remarkably softer than normal brain parenchyma. Our findings reinforce the case for MRE use in diagnosing and staging brain malignancies, based on the association of different tumor phenotypes with different mechanical properties.

Comparison of amino acid positron emission tomographic radiotracers for molecular imaging of primary and metastatic brain tumors

Positron emission tomography (PET) is an imaging technology that can detect and characterize tumors based on their molecular and biochemical properties, such as altered glucose, nucleoside, or amino acid metabolism. PET plays a significant role in the diagnosis, prognostication, and treatment of various cancers, including brain tumors. In this article, we compare uptake mechanisms and the clinical performance of the amino acid PET radiotracers (l-[methyl-11C]methionine [MET], 18F-fluoroethyl-tyrosine [FET], 18F-fluoro-l-dihydroxy-phenylalanine [FDOPA], and 11C-alpha-methyl-l-tryptophan [AMT]) most commonly used for brain tumor imaging. First, we discuss and compare the mechanisms of tumoral transport and accumulation, the basis of differential performance of these radioligands in clinical studies. Then we summarize studies that provided direct comparisons among these amino acid tracers and to clinically used 2-deoxy-2[18F]fluoro-d-glucose [FDG] PET imaging. We also discuss how tracer kinetic analysis can enhance the clinical information obtained from amino acid PET images. We discuss both similarities and differences in potential clinical value for each radioligand. This comparative review can guide which radiotracer to favor in future clinical trials aimed at defining the role of these molecular imaging modalities in the clinical management of brain tumor patients.