Imaging in neurooncology

Diagnostic validity and reliability of BT-RADS in the management of recurrent high-grade glioma

BACKGROUND AND PURPOSE

BT-RADS is a new framework system for reporting the treatment response of brain tumors. The aim of the study was to assess the diagnostic performance and reliability of the BT-RADS in predicting the recurrence of high-grade glioma (HGG).

MATERIALS AND METHODS

This prospective single-center study recruited 81 cases with previously operated and pathologically proven HGG. The patients underwent baseline and follow-up contrast-enhanced MRI (CE-MRI). Two neuro-radiologists with ten years-experience in neuroimaging independently analyzed and interpreted the MRI images and assigned a BT-RADS category for each case. To assess the diagnostic accuracy of the BT-RADS for detecting recurrent HGG, the reference standard was the histopathology for BT-RADS categories 3 and 4, while neurological clinical examination and clinical follow up were used as a reference for BT-RADS categories 1 and 2. The inter-reader agreement was assessed using the Cohen's Kappa test.

RESULTS

The study included 81 cases of HGG, of which 42 were recurrent and 39 were non-recurrent HGG cases based on the reference test. BT-RADS 3B was the best cutoff for predicting recurrent HGG with a sensitivity of 90.5 % to 92.9 %, specificity of 76.9 % to 84.6 %, and accuracy of 83.9 % to 88.9 %, based on both readers. The BT-RADS showed a substantial inter-reader agreement with a K of 0.710 (P = 0.001).

CONCLUSIONS

The BT-RADS is a valid and reliable framework for predicting recurrent HGG. Moreover, BT-RADS can help neuro-oncologists make clinical decisions that can potentially improve the patient's outcome.

Tailored magnetic resonance fingerprinting of post-operative pediatric brain tumor patients

PURPOSE

Brain and spinal cord tumors are the second most common cancer in children and account for one out of four cancers diagnosed. However, the long acquisition times associated with acquiring both data types prohibit using quantitative MR (qMR) in pediatric imaging protocols. This study aims to demonstrate the tailored magnetic resonance fingerprinting's (TMRF) ability to simultaneously provide quantitative maps (T1, T2) and multi-contrast qualitative images (T1 weighted, T1 FLAIR, T2 weighted) rapidly in pediatric brain tumor patients.

METHODS

In this work, we imaged five pediatric patients with brain tumors (resected/residual) using TMRF at 3 T. We compared the TMRF-derived T2 weighted images with those from the vendor-supplied sequence (as the gold standard, GS) for healthy and pathological tissue signal intensities. The relaxometric maps from TMRF were subjected to a region of interest (ROI) analysis to differentiate between healthy and pathological tissues. We performed the Wilcoxon rank sum test to check for significant differences between the two tissue types.

RESULTS

We found significant differences (p < 0.05) in both T1 and T2 ROI values between the two tissue types. A strong correlation was found between the TMRF-based T2 weighted and GS signal intensities for the healthy (correlation coefficient, r = 0.99) and pathological tissues (r = 0.88).

CONCLUSION

The TMRF implementation provides the two relaxometric maps and can potentially save ~2 min if it replaces the T2-weighted imaging in the current protocol.

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.

Intracranial Solitary Fibrous Tumor: A "New" Challenge for PET Radiopharmaceuticals

Solitary fibrous tumor (SFT) of the central nervous system, previously named and classified with the term hemangiopericytoma (HPC), is rare and accounts for less than 1% of all intracranial tumors. Despite its benign nature, it has a malignant behavior due to the high rate of recurrence and distant metastasis, occurring in up to 50% of cases. Surgical resection of the tumor is the treatment of choice. Radiotherapy represents the gold standard in the case of post-surgery residual disease, relapse, and distant metastases. In this context, imaging plays a crucial role in identifying the personalized therapeutic decision for each patient. Although the referring imaging approach in SFT is morphologic, an emerging role of positron emission tomography (PET) has been reported in the literature. However, there is still a debate on which radiotracers have the best accuracy for studying these uncommon tumors because of the histological or biological heterogeneity of SFT.

A Systematic Review of the Current Status and Quality of Radiomics for Glioma Differential Diagnosis

Simple Summary

Gliomas can be difficult to discern clinically and radiologically from other brain lesions (either neoplastic or non-neoplastic) since their clinical manifestations as well as preoperative imaging features often overlap and appear misleading. Radiomics could be extremely helpful for non-invasive glioma differential diagnosis (DDx). However, implementation in clinical practice is still distant and concerns have been raised regarding the methodological quality of radiomic studies. In this context, we aimed to summarize the current status and quality of radiomic studies concerning glioma DDx in a systematic review. In total, 42 studies were selected and examined in our work. Our study revealed that, despite promising and encouraging results, current studies on radiomics for glioma DDx still lack the quality required to allow its introduction into clinical practice. This work could provide new insights and help to reach a consensus on the use of the radiomic approach for glioma DDx.

Abstract

Radiomics is a promising tool that may increase the value of imaging in differential diagnosis (DDx) of glioma. However, implementation in clinical practice is still distant and concerns have been raised regarding the methodological quality of radiomic studies. Therefore, we aimed to systematically review the current status of radiomic studies concerning glioma DDx, also using the radiomics quality score (RQS) to assess the quality of the methodology used in each study. A systematic literature search was performed to identify original articles focused on the use of radiomics for glioma DDx from 2015. Methodological quality was assessed using the RQS tool. Spearman’s correlation (ρ) analysis was performed to explore whether RQS was correlated with journal metrics and the characteristics of the studies. Finally, 42 articles were selected for the systematic qualitative analysis. Selected articles were grouped and summarized in terms of those on DDx between glioma and primary central nervous system lymphoma, those aiming at differentiating glioma from brain metastases, and those based on DDx of glioma and other brain diseases. Median RQS was 8.71 out 36, with a mean RQS of all studies of 24.21%. Our study revealed that, despite promising and encouraging results, current studies on radiomics for glioma DDx still lack the quality required to allow its introduction into clinical practice. This work could provide new insights and help to reach a consensus on the use of the radiomic approach for glioma DDx.

MRI-compatible electromagnetic servomotor for image-guided medical robotics

The soft-tissue imaging capabilities of magnetic resonance imaging (MRI) combined with high precision robotics has the potential to improve the precision and safety of a wide range of image-guided medical procedures. However, functional MRI-compatible robotics have not yet been realized in part because conventional electromagnetic servomotors can become dangerous projectiles near the strong magnetic field of an MRI scanner. Here we report an electromagnetic servomotor constructed from non-magnetic components, where high-torque and controlled rotary actuation is produced via interaction between electrical current in the servomotor armature and the magnetic field generated by the superconducting magnet of the MRI scanner itself. Using this servomotor design, we then build and test an MRI-compatible robot which can achieve the linear forces required to insert a large-diameter biopsy instrument in tissue during simultaneous MRI. Our electromagnetic servomotor can be safely operated (while imaging) in the patient area of a 3 Tesla clinical MRI scanner.

Radiographic markers of breast cancer brain metastases: relation to clinical characteristics and postoperative outcome

Objective

Occurrence of brain metastases BM is associated with poor prognosis in patients with breast cancer (BC). Magnetic resonance imaging (MRI) is the standard of care in the diagnosis of BM and determines further treatment strategy. The aim of the present study was to evaluate the association between the radiographic markers of BCBM on MRI with other patients’ characteristics and overall survival (OS).

Methods

We included 88 female patients who underwent BCBM surgery in our institution from 2008 to 2019. Data on demographic, clinical, and histopathological characteristics of the patients and postoperative survival were collected from the electronic health records. Radiographic features of BM were assessed upon the preoperative MRI. Univariable and multivariable analyses were performed.

Results

The median OS was 17 months. Of all evaluated radiographic markers of BCBM, only the presence of necrosis was independently associated with OS (14.5 vs 22.5 months, p = 0.027). In turn, intra-tumoral necrosis was more often in individuals with shorter time interval between BC and BM diagnosis (< 3 years, p = 0.035) and preoperative leukocytosis (p = 0.022). Moreover, dural affection of BM was more common in individuals with positive human epidermal growth factor receptor 2 status (p = 0.015) and supratentorial BM location (p = 0.024).

Conclusion

Intra-tumoral necrosis demonstrated significant association with OS after BM surgery in patients with BC. The radiographic pattern of BM on the preoperative MRI depends on certain tumor and clinical characteristics of patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00701-021-05026-4.

Construction and imaging of a neurovascular unit model

In 2001, the concept of the neurovascular unit was introduced at the Stroke Progress Review Group meeting. The neurovascular unit is an important element of the health and disease status of blood vessels and nerves in the central nervous system. Since then, the neurovascular unit has attracted increasing interest from research teams, who have contributed greatly to the prevention, treatment, and prognosis of stroke and neurodegenerative diseases. However, additional research is needed to establish an efficient, low-cost, and low-energy in vitro model of the neurovascular unit, as well as enable noninvasive observation of neurovascular units in vivo and in vitro. In this review, we first summarize the composition of neurovascular units, then investigate the efficacy of different types of stem cells and cell culture methods in the construction of neurovascular unit models, and finally assess the progress of imaging methods used to observe neurovascular units in recent years and their positive role in the monitoring and investigation of the mechanisms of a variety of central nervous system diseases.

Somatic mitochondrial DNA mutations in different grades of glioma

Aim: Mitochondrial DNA (mtDNA) alterations play an important role in the multistep processes of cancer development. Gliomas are among the most diagnosed brain cancer. The relationship between mtDNA alterations and different grades of gliomas are still elusive. This study aimed to elucidate the profile of somatic mtDNA mutations in different grades of gliomas and correlate it with clinical phenotype. Materials & methods: Forty histopathologically confirmed glioma tissue samples and their matched blood were collected and subjected for mtDNA sequencing. Results & conclusion: About 75% of the gliomas harbored at least one somatic mutation in the mtDNA gene, and 45% of these mutations were pathogenic. Mutations were scattered across the mtDNA genome, and the commonest nonsynonymous mutations were located at complex I and IV of the mitochondrial respiratory chain. These findings may have implication for future research to determine the mitochondrial energetics and its downstream metabolomics on gliomas.

Evaluating potential of multi-parametric MRI using co-registered histology: Application to a mouse model of glioblastoma

BACKGROUND

Conventional MRI fails to detect regions of glioblastoma cell infiltration beyond the contrast-enhanced T1 solid tumor region, with infiltrating tumor cells often migrating along host blood vessels.

PURPOSE

MRI is capable of generating a range of image contrasts which are commonly assessed individually by qualitative visual inspection. It has long been hypothesized that better diagnoses could be achieved by combining these multiple images, so called multi-parametric or multi-spectral MRI. However, the lack of clinical histology and the difficulties of co-registration, has meant this hypothesis has never been rigorously tested. Here we test this hypothesis, using a previously published multi-dimensional dataset consisting of registered MR images and histology.

STUDY TYPE

Animal Model.

SUBJECTS

Mice bearing orthotopic glioblastoma xenografts generated from a patient-derived glioblastoma cell line.

FIELD STRENGTH/SEQUENCES

7 Tesla, T₁/T₂ weighted, T₂ mapping, contrast enhance T_1, diffusion-weighted, diffusion tensor imaging.

ASSESSMENT

Immunohistochemistry sections were stained for Human Leukocyte Antigen (probing human-derived tumor cells). To achieve quantitative MRI-tissue comparison, multiple histological slices cut in the MRI plane were stacked to produce tumor cell density maps acting as 'ground truth'.

STATISTICAL TESTS

Sensitivity, specificity, accuracy and Dice similarity indices were calculated. ANOVA, t-test, Bonferroni correction and Pearson coefficients were used for statistical analysis.

RESULTS

Correlation coefficient analysis with co-registered 'ground truth' histology showed interactive regression maps had higher correlation coefficients and sensitivity values than T2W, ADC, FA, and T2map. Further, the interaction regression maps showed statistical improved detection of tumor volume.

DATA CONCLUSION

Voxel-by-voxel analysis provided quantitative evidence confirming the hypothesis that mpMRI can, potentially, better distinguish between the tumor region and normal tissue.

Clinical Applications of Magnetic Resonance Spectroscopy in Brain Tumors: From Diagnosis to Treatment

Magnetic resonance spectroscopy (MRS) is a valuable tool for imaging brain tumors, primarily as an adjunct to conventional imaging and clinical presentation. MRS is useful in initial diagnosis of brain tumors, helping differentiate tumors from possible mimics such as metastatic disease, lymphoma, demyelination, and infection, as well as in the subsequent follow-up of patients after resection and chemoradiation. Unfortunately, the spectroscopic appearance of many pathologies can overlap, and ultimately follow-up or biopsy may be required to make a definitive diagnosis. Future developments may continue to increase the value of MRS for initial diagnosis, treatment planning, and early detection of recurrence.

Case report of primary dural lymphoma mimicking a cerebellar meningioma and brief review of literature

Primary dural lymphoma (PDL) is an extremely rare subtype of primary central nervous system lymphoma arising from the dura mater in absence of systemic disease. The most common histological type is the low-grade marginal zone lymphoma, whereas high-grade lymphomas are unusual. We present a case of primary diffuse large B-cell lymphoma, presenting as PDL in the posterior fossa, originating from the dura mater of the petrous bone covering the surface of the left cerebellum, a location not previously described. A 65-year-old woman presented with sudden onset of severe dizziness was admitted in otolaryngology department then transferred to neurosurgery ward. CT scan revealed a large lesion involving left cerebellum, subsequent MRI of the brain demonstrated an enhancing mass suggestive for petrous bone meningioma. The tumor was excised, and the histopathological examination unexpectedly revealed a diffuse large B-cell lymphoma. The patient received postoperative chemoradiotherapy. 20 months after surgery a good outcome was registered. Due to the rarity of primary dural lymphomas no standard treatment is available, however, gross total or subtotal resection followed by adjuvant therapy seems to be a good choice to manage the pathology.

Methods of Analysis: Functional MRI for Presurgical Planning

There are many technical and nontechnical steps involved in a successful clinical functional MRI (fMRI) scan. The output from scanning and analysis can only be as good as the input, so task instruction and rehearsal are the most important steps during an clinical fMRI procedure. Properly pre-processed data significantly affects statistical analysis, which has a great impact on image interpretation. Even though there is general agreement on how to process clinical fMRI data, such as algorithms for head motion detection and correction, the theory and practicalities associated with data processing remain complex and constantly evolving.

Robust Conditional Independence maps of single-voxel Magnetic Resonance Spectra to elucidate associations between brain tumours and metabolites

The aim of the paper is two-fold. First, we show that structure finding with the PC algorithm can be inherently unstable and requires further operational constraints in order to consistently obtain models that are faithful to the data. We propose a methodology to stabilise the structure finding process, minimising both false positive and false negative error rates. This is demonstrated with synthetic data. Second, to apply the proposed structure finding methodology to a data set comprising single-voxel Magnetic Resonance Spectra of normal brain and three classes of brain tumours, to elucidate the associations between brain tumour types and a range of observed metabolites that are known to be relevant for their characterisation. The data set is bootstrapped in order to maximise the robustness of feature selection for nominated target variables. Specifically, Conditional Independence maps (CI-maps) built from the data and their derived Bayesian networks have been used. A Directed Acyclic Graph (DAG) is built from CI-maps, being a major challenge the minimization of errors in the graph structure. This work presents empirical evidence on how to reduce false positive errors via the False Discovery Rate, and how to identify appropriate parameter settings to improve the False Negative Reduction. In addition, several node ordering policies are investigated that transform the graph into a DAG. The obtained results show that ordering nodes by strength of mutual information can recover a representative DAG in a reasonable time, although a more accurate graph can be recovered using a random order of samples at the expense of increasing the computation time.

Neurotheranostics as personalized medicines

The discipline of neurotheranostics was forged to improve diagnostic and therapeutic clinical outcomes for neurological disorders. Research was facilitated, in largest measure, by the creation of pharmacologically effective multimodal pharmaceutical formulations. Deployment of neurotheranostic agents could revolutionize staging and improve nervous system disease therapeutic outcomes. However, obstacles in formulation design, drug loading and payload delivery still remain. These will certainly be aided by multidisciplinary basic research and clinical teams with pharmacology, nanotechnology, neuroscience and pharmaceutic expertise. When successful the end results will provide "optimal" therapeutic delivery platforms. The current report reviews an extensive body of knowledge of the natural history, epidemiology, pathogenesis and therapeutics of neurologic disease with an eye on how, when and under what circumstances neurotheranostics will soon be used as personalized medicines for a broad range of neurodegenerative, neuroinflammatory and neuroinfectious diseases.

Computed tomography-guided navigated transcranial magnetic stimulation for preoperative brain motor mapping in brain lesion resection: A case report

Background:

Navigated transcranial magnetic stimulation (nTMS) is a well establish a noninvasive method for preoperative brain motor mapping. We commonly use magnetic resonance imaging (MRI) to supply the nTMS system. In some cases, MRI is not possible or available, and the use of computed tomography (CT) is necessary. We present the first report describing the association of CT and nTMS motor mapping for brain lesion resection.

Case Description:

CT imaging of a 59-year-old man suffering from acquired immune deficiency syndrome for 17 years, presenting with seizure and right hemiparesis, revealed a small single hypodense ring-enhancing lesion in the left central sulci suggesting cerebral toxoplasmosis. After 3 weeks of neurotoxoplasmosis treatment, due to four consecutive tonic-clonic seizures, a new CT scan was performed and showed no lesion changes. MRI was in maintenance at that time. Infectious diseases department suggested a brain lesion biopsy. Due to lesion’s location, we decided to perform a presurgical nTMS motor mapping. After a small craniotomy, we could precisely locate and safely totally remove the lesion. The pathology report revealed a high suspicious toxoplasmosis pattern. The patient was discharged after 2 days and continued toxoplasmosis treatment. After 6 months follow-up, he showed no signs of any procedure-related deficits or radiological recurrence.

Conclusion:

We report the feasibility and applicability of nTMS motor mapping using CT scan as an image source. It gives neurosurgeons another possibility to perform motor mapping for brain lesion removal, especially when MRI is not available or feasible.

FET PET in the evaluation of indeterminate brain lesions on MRI: Differentiating glioma from other non-neoplastic causes - A pilot study

We aimed to determine the utility of FET PET in the management of indeterminate CNS lesions found on MRI. We performed a retrospective analysis of patients with FET PET at a single tertiary institution from 2011 to 2015. FET PET images were processed using usual methods and measurements taken including SUVmax, TBRmax, and analysis of dynamic series where available (Kipeak, Vdpeak, as well as tumor:background ratio for these variables). Correlation studies were performed using ANOVA between cohorts of high-grade histology, low-grade histology, and benign histology/stable on observation. Thirty-five patients were included, of whom 34 were suitable for analysis with median follow-up of 5 months. The positive predictive value of FET PET in this cohort was 83.3%. FET SUVmax differentiated between patients with high-grade (mean SUV 3.38, 95% CI 2.21-4.55), low-grade (1.88, 95% CI 1.33-2.43) and benign/observation (1.42, 95% CI 1.13-1.71) cohorts (p = 0.0003). Similarly, tumour to brain ratio was significant (p < 0.0001). Kipeak distinguished between high grade and observation cohorts (p = 0.036), as did KiTBR (p = 0.025). Vd peak was not significantly different in these two cohorts (p = 0.057) but Vd TBR was (p = 0.041). In conclusion, FET PET demonstrated a high positive predictive value for glioma in patients with indeterminate brain lesions on MRI. The combination of negative FET and negative FDG PET scans may predict an indolent clinical course. Confirmatory trials are needed to establish the potential value of FET PET in guiding surgical management in this cohort.

Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI

Objectives

Magnetic resonance imaging (MRI) is the method of choice for imaging meningiomas. Volumetric assessment of meningiomas is highly relevant for therapy planning and monitoring. We used a multiparametric deep-learning model (DLM) on routine MRI data including images from diverse referring institutions to investigate DLM performance in automated detection and segmentation of meningiomas in comparison to manual segmentations.

Methods

We included 56 of 136 consecutive preoperative MRI datasets [T1/T2-weighted, T1-weighted contrast-enhanced (T1CE), FLAIR] of meningiomas that were treated surgically at the University Hospital Cologne and graded histologically as tumour grade I (n = 38) or grade II (n = 18). The DLM was trained on an independent dataset of 249 glioma cases and segmented different tumour classes as defined in the brain tumour image segmentation benchmark (BRATS benchmark). The DLM was based on the DeepMedic architecture. Results were compared to manual segmentations by two radiologists in a consensus reading in FLAIR and T1CE.

Results

The DLM detected meningiomas in 55 of 56 cases. Further, automated segmentations correlated strongly with manual segmentations: average Dice coefficients were 0.81 ± 0.10 (range, 0.46-0.93) for the total tumour volume (union of tumour volume in FLAIR and T1CE) and 0.78 ± 0.19 (range, 0.27-0.95) for contrast-enhancing tumour volume in T1CE.

Conclusions

The DLM yielded accurate automated detection and segmentation of meningioma tissue despite diverse scanner data and thereby may improve and facilitate therapy planning as well as monitoring of this highly frequent tumour entity.

Key Points

• Deep learning allows for accurate meningioma detection and segmentation

• Deep learning helps clinicians to assess patients with meningiomas

• Meningioma monitoring and treatment planning can be improved

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5595-8) contains supplementary material, which is available to authorized users.

Multimodal Imaging of Patients With Gliomas Confirms 11C-MET PET as a Complementary Marker to MRI for Noninvasive Tumor Grading and Intraindividual Follow-Up After Therapy

The value of combined L-( methyl-[¹¹C]) methionine positron-emitting tomography (MET-PET) and magnetic resonance imaging (MRI) with regard to tumor extent, entity prediction, and therapy effects in clinical routine in patients with suspicion of a brain tumor was investigated. In n = 65 patients with histologically verified brain lesions n = 70 MET-PET and MRI (T1-weighted gadolinium-enhanced [T1w-Gd] and fluid-attenuated inversion recovery or T2-weighted [FLAIR/T2w]) examinations were performed. The computer software "visualization and analysis framework volume rendering engine (Voreen)" was used for analysis of extent and intersection of tumor compartments. Binary logistic regression models were developed to differentiate between World Health Organization (WHO) tumor types/grades. Tumor sizes as defined by thresholding based on tumor-to-background ratios were significantly different as determined by MET-PET (21.6 ± 36.8 cm³), T1w-Gd-MRI (3.9 ± 7.8 cm³), and FLAIR/T2-MRI (64.8 ± 60.4 cm³; P < .001). The MET-PET visualized tumor activity where MRI parameters were negative: PET positive tumor volume without Gd enhancement was 19.8 ± 35.0 cm³ and without changes in FLAIR/T2 10.3 ± 25.7 cm³. FLAIR/T2-MRI visualized greatest tumor extent with differences to MET-PET being greater in posttherapy (64.6 ± 62.7 cm³) than in newly diagnosed patients (20.5 ± 52.6 cm³). The binary logistic regression model differentiated between WHO tumor types (fibrillary astrocytoma II n = 10 from other gliomas n = 16) with an accuracy of 80.8% in patients at primary diagnosis. Combined PET and MRI improve the evaluation of tumor activity, extent, type/grade prediction, and therapy-induced changes in patients with glioma and serve information highly relevant for diagnosis and management.

Nanomaterial applications for neurological diseases and central nervous system injury

The effectiveness of noninvasive treatment for neurological disease is generally limited by the poor entry of therapeutic agents into the central nervous system (CNS). Most CNS drugs cannot permeate into the brain parenchyma because of the blood-brain barrier thus, overcoming this problem has become one of the most significant challenges in the development of neurological therapeutics. Nanotechnology has emerged as an innovative alternative for treating neurological diseases. In fact, rapid advances in nanotechnology have provided promising solutions to this challenge. This review highlights the applications of nanomaterials in the developing neurological field and discusses the evidence for their efficacies.

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.

Endoscopic detection of cancer with lensless radioluminescence imaging and machine vision

Complete removal of residual tumor tissue during surgical resection improves patient outcomes. However, it is often difficult for surgeons to delineate the tumor beyond its visible boundary. This has led to the development of intraoperative detectors that can image radiotracers accumulated within tumors, thus facilitating the removal of residual tumor tissue during surgical procedures. We introduce a beta imaging system that converts the beta radiation from the radiotracer into photons close to the decay origin through a CdWO₄ scintillator and does not use any optical elements. The signal is relayed onto an EMCCD chip through a wound imaging fiber. The sensitivity of the device allows imaging of activity down to 100 nCi and the system has a resolution of at least 500 μm with a field of view of 4.80 × 6.51 mm. Advances in handheld beta cameras have focused on hardware improvements, but we apply machine vision to the recorded images to extract more information. We automatically classify sample regions in human renal cancer tissue ex-vivo into tumor or benign tissue based on image features. Machine vision boosts the ability of our system to distinguish tumor from healthy tissue by a factor of 9 ± 3 and can be applied to other beta imaging probes.

A systematic pipeline for the objective comparison of whole-brain spectroscopic MRI with histology in biopsy specimens from grade III glioma

The diagnosis, prognosis, and management of patients with gliomas are largely dictated by the pathological analysis of tissue biopsied from a selected region within the lesion. However, the heterogeneous and infiltrative nature of gliomas make it difficult to identify the optimal region for biopsy with conventional magnetic resonance imaging (MRI). This is particularly true for low-grade gliomas, which are often nonenhancing tumors. To improve the management of patients with such tumors, neuro-oncology requires an imaging modality that can specifically identify a tumor's most anaplastic/aggressive region(s) for biopsy targeting. The addition of metabolic mapping using spectroscopic MRI (sMRI) to supplement conventional MRI could improve biopsy targeting and, ultimately, diagnostic accuracy. Here, we describe a pipeline for the integration of state-of-the-art, high-resolution, whole-brain 3-dimensional sMRI maps into a stereotactic neuronavigation system for guiding biopsies in gliomas with nonenhancing components. We also outline a machine-learning method for automated histological analysis that generates normalized, quantitative metrics describing tumor infiltration in immunohistochemically stained tissue specimens. As a proof of concept, we describe the combination of these 2 techniques in a small cohort of patients with grade 3 glioma. With this work, we aim to present a systematic pipeline to stimulate histopathological image validation of advanced MRI techniques, such as sMRI.

A comparison study of (11)C-methionine and (18)F-fluorodeoxyglucose positron emission tomography-computed tomography scans in evaluation of patients with recurrent brain tumors

Introduction:

¹¹C-methonine ([¹¹C]-MET) positron emission tomography-computed tomography (PET-CT) is a well-established technique for evaluation of tumor for diagnosis and treatment planning in neurooncology. [¹¹C]-MET reflects amino acid transport and has been shown to be more sensitive than magnetic resonance imaging (MRI) in stereotactic biopsy planning. This study compared fluorodeoxyglucose (FDG) PET-CT and MET PET-CT in the detection of various brain tumors.

Materials and Methods:

Sixty-four subjects of brain tumor treated by surgery, chemotherapy, and/or radiotherapy were subjected to [¹⁸F]-FDG, [¹¹C]-MET, and MRI scan. The lesion was analyzed semiquantitatively using tumor to normal contralateral ratio. The diagnosis was confirmed by surgery, stereotactic biopsy, clinical follow-up, MRI, or CT scans.

Results:

Tumor recurrence was found in 5 out of 22 patients on [F-18] FDG scan while [¹¹C]-MET was able to detect recurrence in 18 out of 22 patients in low-grade gliomas. Two of these patients were false positive for the presence of recurrence of tumor and later found to be harboring necrosis. Among oligodendroglioma, medulloblastoma and high-grade glioma out of 42 patients 39 were found to be concordant MET and FDG scans. On semiquantitative analysis, mean T/NT ratio was found to be 2.96 ± 0.94 for lesions positive for recurrence of tumors and 1.18 ± 0.74 for lesions negative for recurrence of tumor on [¹¹C]-MET scan. While the ratio for FDG scan on semiquantitative analysis was found to be 2.05 ± 1.04 for lesions positive for recurrence of tumors and 0.52 ± 0.15 for lesions negative for recurrence of tumors.

Conclusion:

The study highlight that [¹¹C]-MET is superior to [¹⁸F]-FDG PET scans to detect recurrence in low-grade glioma. A cut-off value of target to nontarget value of 1.47 is a useful parameter to distinguish benign from malignant lesion on an [¹¹C]-MET Scan. Both [¹⁸F]-FDG and [¹¹C]-MET scans were found to be useful in high-grade astrocytoma, oligodendroglioma, and medulloblastoma.

Primary diffuse large B-cell lymphoma of the dura with skull and scalp involvement: A case report and brief review of the literature

Primary dural lymphoma (PDL) refers to a lymphoma with epidural or subdural involvement and is a rare subtype of primary central nervous system lymphoma. Diffuse large B-cell lymphoma (DLBCL) presenting as PDL is extremely rare. The present study reports a case of PDL with skull and scalp involvement in a 56-year-old man. Magnetic resonance imaging (MRI) revealed that the tumor was located under the right parietal inner plate and was attached to the dura mater. Following contrast-enhanced MRI, markedly enhanced tumor signals were observed, and mild homogeneous enhancement was observed in the diploë and soft tissues under the scalp, near the parietal bone. Under general anesthesia, the patient underwent craniotomy and tumor resection. The postoperative pathological diagnosis was DLBCL. Tumors were additionally identified inside the skull and subcutaneous tissues. The patient was administered chemotherapy postoperatively, and the prognosis subsequent to the 4-year follow-up was favorable. Primary malignant lymphoma should be considered in the differential diagnosis of scalp masses and meningeal lesions. Early diagnosis and individualized treatment is closely associated with a favorable outcome.

(18)F-Fluoroethyl-l-Thyrosine Positron Emission Tomography to Delineate Tumor Residuals After Glioblastoma Resection: A Comparison with Standard Postoperative Magnetic Resonance Imaging

OBJECTIVE

Complete resection of contrast-enhancing tumor is an important prognostic factor in glioblastoma therapy. The current clinical standard for control of resection is magnetic resonance imaging (MRI). (18)F-Fluoroethyl-l-thyrosine (FET) is a positron emission tomography (PET) radiopharmaceutical applicable for widespread use because of its long half-life radionuclide. We assessed the sensitivity of postoperative MRI versus FET-PET to detect residual tumor and the impact of the time interval between resection and FET-PET.

METHODS

MRI and FET-PET were performed preoperatively and postoperatively in 62 patients undergoing 63 operations. FET-PET was performed in 43 cases within 72 hours after resection and in 20 cases >72 hours after resection. Detection and measurement of volume of residual tumors were compared. Correlations between residual tumor detection and timing of PET after resection and recurrence were examined.

RESULTS

Complete resection was confirmed by both imaging modalities in 44% of cases, and residual tumor was detected consistently in 37% of cases. FET-PET detected residual tumor in 14% of cases in which MRI showed no residual tumor. MRI showed residual tumors in 5% of cases that were not identified by PET. Average PET-based residual tumor volume was higher than MRI-based volume (3.99 cm(3) vs. 1.59 cm(3)). Detection of and difference in volume of residual tumor were not correlated with timing of PET after resection or recurrence status.

CONCLUSIONS

Postoperative FET-PET revealed residual tumor with higher sensitivity than MRI and showed larger tumor volumes. In this series, performing PET >72 hours after resection did not influence the results of PET. We recommend FET-PET as a helpful adjunct in addition to MRI for postoperative assessment of residual tumor.

Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI

PURPOSE

In quantitative PET/MR imaging, attenuation correction (AC) of PET data is markedly challenged by the need of deriving accurate attenuation maps from MR images. A number of strategies have been developed for MRI-guided attenuation correction with different degrees of success. In this work, we compare the quantitative performance of three generic AC methods, including standard 3-class MR segmentation-based, advanced atlas-registration-based and emission-based approaches in the context of brain time-of-flight (TOF) PET/MRI.

MATERIALS AND METHODS

Fourteen patients referred for diagnostic MRI and (18)F-FDG PET/CT brain scans were included in this comparative study. For each study, PET images were reconstructed using four different attenuation maps derived from CT-based AC (CTAC) serving as reference, standard 3-class MR-segmentation, atlas-registration and emission-based AC methods. To generate 3-class attenuation maps, T1-weighted MRI images were segmented into background air, fat and soft-tissue classes followed by assignment of constant linear attenuation coefficients of 0, 0.0864 and 0.0975 cm(-1) to each class, respectively. A robust atlas-registration based AC method was developed for pseudo-CT generation using local weighted fusion of atlases based on their morphological similarity to target MR images. Our recently proposed MRI-guided maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm was employed to estimate the attenuation map from TOF emission data. The performance of the different AC algorithms in terms of prediction of bones and quantification of PET tracer uptake was objectively evaluated with respect to reference CTAC maps and CTAC-PET images.

RESULTS

Qualitative evaluation showed that the MLAA-AC method could sparsely estimate bones and accurately differentiate them from air cavities. It was found that the atlas-AC method can accurately predict bones with variable errors in defining air cavities. Quantitative assessment of bone extraction accuracy based on Dice similarity coefficient (DSC) showed that MLAA-AC and atlas-AC resulted in DSC mean values of 0.79 and 0.92, respectively, in all patients. The MLAA-AC and atlas-AC methods predicted mean linear attenuation coefficients of 0.107 and 0.134 cm(-1), respectively, for the skull compared to reference CTAC mean value of 0.138cm(-1). The evaluation of the relative change in tracer uptake within 32 distinct regions of the brain with respect to CTAC PET images showed that the 3-class MRAC, MLAA-AC and atlas-AC methods resulted in quantification errors of -16.2 ± 3.6%, -13.3 ± 3.3% and 1.0 ± 3.4%, respectively. Linear regression and Bland-Altman concordance plots showed that both 3-class MRAC and MLAA-AC methods result in a significant systematic bias in PET tracer uptake, while the atlas-AC method results in a negligible bias.

CONCLUSION

The standard 3-class MRAC method significantly underestimated cerebral PET tracer uptake. While current state-of-the-art MLAA-AC methods look promising, they were unable to noticeably reduce quantification errors in the context of brain imaging. Conversely, the proposed atlas-AC method provided the most accurate attenuation maps, and thus the lowest quantification bias.

Prognostic value of combined visualization of MR diffusion and perfusion maps in glioblastoma

We analyzed whether the combined visualization of decreased apparent diffusion coefficient (ADC) values and increased cerebral blood volume (CBV) in perfusion imaging can identify prognosis-related growth patterns in patients with newly diagnosed glioblastoma. Sixty-five consecutive patients were examined with diffusion and dynamic susceptibility-weighted contrast-enhanced perfusion weighted MRI. ADC and CBV maps were co-registered on the T1-w image and a region of interest (ROI) was manually delineated encompassing the enhancing lesion. Within this ROI pixels with ADC values <the 30th percentile (ADCmin), pixels with CBV values >the 70th percentile (CBVmax) and the intersection of pixels with ADCmin and CBVmax were automatically calculated and visualized. Initially, all tumors with a mean intersection greater than the upper quartile of the normally distributed mean intersection of all patients were subsumed to the first growth pattern termed big intersection (BI). Subsequently, the remaining tumors' growth patterns were categorized depending on the qualitative representation of ADCmin, CBVmax and their intersection. Log-rank test exposed a significantly longer overall survival of BI (n = 16) compared to non-BI group (n = 49) (p = 0.0057). Thirty-one, four and 14 patients of the non-BI group were classified as predominant ADC-, CBV- and mixed growth group, respectively. In a multivariate Cox regression model, the BI-, CBV- and mixed groups had significantly lower adjusted hazard ratios (p-value, α(Bonferroni) < 0.006) when compared to the reference group ADC: 0.29 (0.0027), 0.11 (0.038) and 0.33 (0.0059). Our study provides evidence that the combination of diffusion and perfusion imaging allows visualization of different glioblastoma growth patterns that are associated with prognosis. A possible biological hypothesis for this finding could be the interpretation of the ADCmin fraction as the invasion-front of tumor cells while the CBVmax fraction might represent the vascular rich tumor border that is "trailing behind" the invasion-front in the ADC group.

Early [18F]FET-PET in Gliomas after Surgical Resection: Comparison with MRI and Histopathology

Background

The precise definition of the post-operative resection status in high-grade gliomas (HGG) is crucial for further management. We aimed to assess the feasibility of assessment of the resection status with early post-operative positron emission tomography (PET) using [¹⁸F]O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine ([¹⁸F]FET).

Methods

25 patients with the suspicion of primary HGG were enrolled. All patients underwent pre-operative [¹⁸F]FET-PET and magnetic resonance imaging (MRI). Intra-operatively, resection status was assessed using 5-aminolevulinic acid (5-ALA). Imaging was repeated within 72h after neurosurgery. Post-operative [¹⁸F]FET-PET was compared with MRI, intra-operative assessment and clinical follow-up.

Results

[¹⁸F]FET-PET, MRI and intra-operative assessment consistently revealed complete resection in 12/25 (48%) patients and incomplete resection in 6/25 cases (24%). In 7 patients, PET revealed discordant findings. One patient was re-resected. 3/7 experienced tumor recurrence, 3/7 died shortly after brain surgery.

Conclusion

Early assessment of the resection status in HGG with [¹⁸F]FET-PET seems to be feasible.

Accuracy of percentage of signal intensity recovery and relative cerebral blood volume derived from dynamic susceptibility-weighted, contrast-enhanced MRI in the preoperative diagnosis of cerebral tumours

Conventional magnetic resonance imaging (MRI) is the technique of choice for diagnosis of cerebral tumours, and has become an increasingly powerful tool for their evaluation; however, the diagnosis of common contrast-enhancing lesions can be challenging, as it is sometimes impossible to differentiate them using conventional imaging. Histopathological analysis of biopsy specimens is the gold standard for diagnosis; however, there are significant risks associated with the invasive procedure and definitive diagnosis is not always achieved. Early accurate diagnosis is important, as management differs accordingly. Advanced MRI techniques have increasing utility for aiding diagnosis in a variety of clinical scenarios. Dynamic susceptibility-weighted contrast-enhanced (DSC) MRI is a perfusion imaging technique and a potentially important tool for the characterisation of cerebral tumours. The percentage of signal intensity recovery (PSR) and relative cerebral blood volume (rCBV) derived from DSC MRI provide information about tumour capillary permeability and neoangiogenesis, which can be used to characterise tumour type and grade, and distinguish tumour recurrence from treatment-related effects. Therefore, PSR and rCBV potentially represent a non-invasive means of diagnosis; however, the clinical utility of these parameters has yet to be established. We present a review of the literature to date.

T 2- and T*2-weighted MRI of rat glioma using polysorbate-coated magnetic nanocrystals as a blood-pool contrast agent

In this study, T₂- and T*2-weighted imaging potential of polysorbate-coated magnetic nanocrystals (P-MNCs) was investigated as a blood-pool contrast agent using a 9L-rat glioma model after intravenous injection via 3.0T MRI.

Applications of positron emission tomography in neuro-oncology: a clinical approach

The field of neuro-oncology is concerned with some of the most challenging and difficult to treat conditions in medicine. Despite modern therapies patients diagnosed with primary brain tumours often have a poor prognosis. Imaging can play an important role in evaluating the disease status of such patients. In addition to the structural information derived from MRI and CT scans, positron emission tomography (PET) provides important quantitative metabolic assessment of brain tumours. This review describes the use of PET with radiolabelled glucose and amino acid analogues to aid in the diagnosis of tumours, differentiate between recurrent tumour and radiation necrosis and guide biopsy or treatment. [(18)F]Fluorodeoxyglucose (FDG) is the tracer that has been used most widely because it has a 2 h half life and can be transported to imaging centres remote from the cyclotron and radiochemistry facilities which synthesise the tracers. The high uptake of FDG in normal grey matter however limits its use in some low grade tumours which may not be visualised. [(11)C] methionine (MET) is an amino acid tracer with low accumulation in normal brain which can detect low grade gliomas, but its short 20 min half life has limited its use to imaging sites with their own cyclotron. The emergence of new fluorinated amino acid tracers like [(18)F]Fluoroethyl-l-tyrosine (FET) will likely increase the availability and utility of PET for patients with primary brain tumours. PET can, further, characterise brain tumours by investigating other metabolic processes such as DNA synthesis or thymidine kinase activity, phospholipid membrane biosynthesis, hypoxia, receptor binding and oxygen metabolism and blood flow, which will be important in the future assessment of targeted therapy.

Intracranial primary dural diffuse large B-cell lymphoma successfully treated with chemotherapy

Diffuse large B-cell lymphoma (DLBCL) presented as a primary dural lesion is an extremely rare entity, which may be misdiagnosed as meningioma. Patients with symptomatic meningioma are usually treated with tumor resection. The five previously described cases of intracranial dural DLBCL were treated with surgery followed by chemotherapy and/or radiotherapy, with a favorable outcome, but with potential sequels. We reported the first case of DLBCL, presented as a primary dural lesion, successfully treated with chemotherapy only in a 52-year-old woman presented in October 2011 with rapidly progressive headaches, nausea and vomiting. Magnetic resonance imaging of the brain and head computed tomography showed a lesion en plaque in the right parieto-occipital region, tracking the dura matter, and osteolytic lesions. The patient underwent an open tumor biopsy, and the diagnosis of DLBCL was established. The patient received dexamethasone, cisplatin and cytarabine (DHAP) followed by methotrexate plus cytarabine, and obtained a durable complete response. Thus, intracranial dural DLBCL must be considered in differential diagnosis of meningeal lesions, particularly when a rapid progression of symptoms and osteolytic lesions are present, because an early diagnosis and rapid initiation of treatment, even though with chemotherapy, is associated with favorable outcome.

Malignant gliomas: strategies to increase the effectiveness of targeted molecular treatment

Recently, there has been increasing interest in the use of targeted molecular agents for the treatment of malignant gliomas. These agents are generally well tolerated but have demonstrated only modest activity. In this article, the current status of targeted molecular agents for malignant gliomas will be reviewed and strategies to improve their effectiveness will be discussed.

Effect of imaging time in the magnetic resonance detection of intracerebral metastases using single dose gadobutrol

OBJECTIVE

To compare the effect of imaging time delay on the MR detection of intracerebral metastases using single dose gadobutrol.

MATERIALS AND METHODS

Twenty-one patients with intracerebral metastases underwent contrast-enhanced MR with three-dimensional T1-weighted sequence at 1 minute, 5 minutes and 10 minutes after a single dose injection of gadobutrol. One hundred index metastatic lesions (1 to 30 mm; median, 7 mm) were chosen for the analysis. For the qualitative analysis, lesion conspicuity were assessed on a 1 (worst) to 5 (best) scale of the index lesions by an expert reader. For the quantitative analysis, signal intensity (SI) of enhancing lesions and normal parenchyma was measured to determine the contrast rate (CR, %) ([postcontrast SI lesion - postcontrast SI white matter] × 100 / postcontrast SI white matter) and the enhancement rate (ER, %) ([postcontrast SI lesion - baseline SI gray matter] × 100 / baseline SI gray matter). Statistical comparisons were made between three different time delays.

RESULTS

Lesion conspicuity did not differ significantly among the three time delays (p = 0.097). Although the SI, CR and ER of lesions did not reveal any significant difference between 1 minute and 5 minutes delayed images, both the 1 minute and 5 minutes delayed images showed significantly higher CRs of lesions compared with the 10 minutes delayed images (p = 0.004 and p = 0.001, respectively).

CONCLUSION

With single dose gadobutrol, imaging time delay did not have an effect on lesion conspicuity. Both 1-minute and 5-minute-delayed imaging after gadobutrol injection appears to be effective for the detection of intracerebral metastases.

Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) in the tumors of central nervous system (CNS)

Malignant neoplasms of the central nervous system (CNS) account for about 1.3 % of all tumors and 2.2 % of all cancer-related deaths. CNS tumors consist of heterogeneous group of neoplasms, including different variants of primary brain tumors and metastatic neoplasms. Advanced imaging techniques improved the neuroradiological diagnostic accuracy, although these methods are not specific enough for differentiation of CNS tumors, thus new approaches of patients' diagnosis are critically needed. The best solution for the diagnosis of patients with CNS tumors could be easily available biomarkers, which could be useful for the management of CNS neoplasms. Biomarkers should facilitate the diagnosis, monitor of treatment response and assess the prognosis of patients' survival. Currently, except for rare germ cell tumors, there is a lack of knowledge on biochemical markers for CNS neoplasms. Therefore, in this paper we summarized and referred a number of comprehensive reviews concerning the role of matrix metalloproteinases (MMPs) and their tissue inhibitors in tumor progression, including CNS neoplasms as well as described the general biochemistry of MMPs and their tissue inhibitors. Moreover, we presented the wide variety of previous findings, where authors suggested the significance of selected MMPs and their tissue inhibitors as potential biomarkers of human tumors, including CNS tumors. However, future investigations are needed to be performed before some of these enzymes could finally be used as biomarkers of specific types of CNS neoplasms.

Specific chemotaxis of magnetically labeled mesenchymal stem cells: implications for MRI of glioma

PURPOSE

Glioblastoma multiforme (GBM) is a lethal disease marked by infiltration of cancerous cells into the surrounding normal brain. The dire outcome of GBM patients stems in part from the limitations of current neuroimaging methods. Notably, early cancer detection methodologies are lacking, without the ability to identify aggressive, metastatic tumor cells. We propose a novel approach for tumor detection using magnetic resonance imaging (MRI) based on imaging specific tumor tropism of mesenchymal stem cells (MSCs) labeled with micron-sized iron oxide particles (MPIOs).

PROCEDURES

MPIO labeled and unlabeled MSCs were compared for viability, multi-lineage differentiation, and migration, where both chemotactic and chemokinetic movement were assessed in the presence of serum-free medium, serum-containing medium, and glioma-conditioned medium. MRI was performed on agarose samples, consisting of MPIO-labeled single MSCs, to confirm the capability to detect single cells.

RESULTS

We determined that MPIO-labeled MSCs exhibit specific and significant chemotactic migration towards glioma-conditioned medium in vitro. Confocal fluorescence microscopy confirmed that MPIOs are internalized and do not impact important cell processes of MSCs. Lastly, MPIO-labeled MSCs appear as single distinct, dark spots on T(2)*-weighted MRI, supporting the robustness of this contrast agent for cell tracking.

CONCLUSIONS

This is the first study to show that MPIO-labeled MSCs exhibit specific tropism toward tumor-secreted factors in vitro. The potential for detecting single MPIO-labeled MSCs provides rationale for in vivo extension of this methodology to visualize GBM in animal models.

[(18)F]FET-PET Imaging for Treatment and Response Monitoring of Radiation Therapy in Malignant Glioma Patients - A Review

In the treatment of patients suffering from malignant glioma, it is a paramount importance to deliver a high radiation dose to the tumor on the one hand and to spare organs at risk at one the other in order to achieve a sufficient tumor control and to avoid severe side effects. New radiation therapy techniques have emerged like intensity modulated radiotherapy and image guided radiotherapy that help facilitate this aim. In addition, there are advanced imaging techniques like Positron emission tomography (PET) and PET/CT which can help localize the tumor with higher sensitivity, and thus contribute to therapy planning, tumor control, and follow-up. During follow-up care, it is crucial to differentiate between recurrence and treatment-associated, unspecific lesions, like radiation necrosis. Here, too, PET/CT can facilitate in differentiating tumor relapse from unspecific changes. This review article will discuss therapy response criteria according to the current imaging methods like Magnet resonance imaging, CT, and PET/CT. It will focus on the significance of PET in the clinical management for treatment and follow-up.

Analysis of the growth dynamics of angiogenesis-dependent and -independent experimental glioblastomas by multimodal small-animal PET and MRI

The hypothesis of this study was that distinct experimental glioblastoma phenotypes resembling human disease can be noninvasively distinguished at various disease stages by imaging in vivo.

METHODS

Cultured spheroids from 2 human glioblastomas were implanted into the brains of nude rats. Glioblastoma growth dynamics were followed by PET using (18)F-FDG, (11)C-methyl-l-methionine ((11)C-MET), and 3'-deoxy-3'-(18)F-fluorothymidine ((18)F-FLT) and by MRI at 3-6 wk after implantation. For image validation, parameters were coregistered with immunohistochemical analysis.

RESULTS

Two tumor phenotypes (angiogenic and infiltrative) were obtained. The angiogenic phenotype showed high uptake of (11)C-MET and (18)F-FLT and relatively low uptake of (18)F-FDG. (11)C-MET was an early indicator of vessel remodeling and tumor proliferation. (18)F-FLT uptake correlated to positive Ki67 staining at 6 wk. T1- and T2-weighted MR images displayed clear tumor delineation with strong gadolinium enhancement at 6 wk. The infiltrative phenotype did not accumulate (11)C-MET and (18)F-FLT and impaired the (18)F-FDG uptake. In contrast, the Ki67 index showed a high proliferation rate. The extent of the infiltrative tumors could be observed by MRI but with low contrast.

CONCLUSION

For angiogenic glioblastomas, noninvasive assessment of tumor activity corresponds well to immunohistochemical markers, and (11)C-MET was more sensitive than (18)F-FLT at detecting early tumor development. In contrast, infiltrative glioblastoma growth in the absence of blood-brain barrier breakdown is difficult to noninvasively follow by existing imaging techniques, and a negative (18)F-FLT PET result does not exclude the presence of proliferating glioma tissue. The angiogenic model may serve as an advanced system to study imaging-guided antiangiogenic and antiproliferative therapies.