Predictive value of multimodality MRI using conventional, perfusion, and spectroscopy MR in anaplastic transformation of low-grade oligodendrogliomas

In vivo brain MR spectroscopy in gliomas: clinical and pre-clinical chances

Purpose

Gliomas, the most common primary brain tumours, have recently been re-classified incorporating molecular aspects with important clinical, prognostic, and predictive implications. Concurrently, the reprogramming of metabolism, altering intracellular and extracellular metabolites affecting gene expression, differentiation, and the tumour microenvironment, is increasingly being studied, and alterations in metabolic pathways are becoming hallmarks of cancer. Magnetic resonance spectroscopy (MRS) is a complementary, non-invasive technique capable of quantifying multiple metabolites. The aim of this review focuses on the methodology and analysis techniques in proton MRS (1H MRS), including a brief look at X-nuclei MRS, and on its perspectives for diagnostic and prognostic biomarkers in gliomas in both clinical practice and preclinical research.

Methods

PubMed literature research was performed cross-linking the following key words: glioma, MRS, brain, in-vivo, human, animal model, clinical, pre-clinical, techniques, sequences, 1H, X-nuclei, Artificial Intelligence (AI), hyperpolarization.

Results

We selected clinical works (n = 51), preclinical studies (n = 35) and AI MRS application papers (n = 15) published within the last two decades. The methodological papers (n = 62) were taken into account since the technique first description.

Conclusions

Given the development of treatments targeting specific cancer metabolic pathways, MRS could play a key role in allowing non-invasive assessment for patient diagnosis and stratification, predicting and monitoring treatment responses and prognosis. The characterization of gliomas through MRS will benefit of a wide synergy among scientists and clinicians of different specialties within the context of new translational competences. Head coils, MRI hardware and post-processing analysis progress, advances in research, experts’ consensus recommendations and specific professionalizing programs will make the technique increasingly trustworthy, responsive, accessible.

Surveillance imaging frequency in adult patients with lower-grade (WHO Grade 2 and 3) gliomas

With improved outcome following aggressive treatment in patients with grade 2 and 3 IDH-mutant (IDHmt), 1p/19q codeleted oligodendroglioma and IDHmt, non-codeleted astrocytoma, prolonged surveillance is desirable for early detection of tumor growth and malignant transformation. Current National Comprehensive Cancer Network (NCCN) guidelines provide imaging follow-up recommendations based on molecular classification of lower-grade gliomas, although individualized imaging guidelines based on treatments received and after tumor recurrence are not clearly specified. Other available guidelines have yet to incorporate the molecular biomarkers that inform the WHO classification of gliomas, and in some cases do not adequately consider current knowledge on IDHmt glioma growth rate and recurrence patterns. Moreover, these guidelines also do not provide specific recommendations for concerning clinical symptoms or radiographic findings warranting imaging studies out of prespecified intervals. Focusing on molecularly defined grade 2 and 3 IDHmt astrocytomas and oligodendrogliomas, we review current knowledge of tumor growth rates and time to tumor progression for each tumor type and propose a range of recommended MRI surveillance intervals for both the newly diagnosed and recurrent tumor setting. Additionally, we summarize situations in which imaging is advisable outside of these intervals.

Systematic review-Time to malignant transformation in low-grade gliomas: Predicting a catastrophic event with clinical, neuroimaging, and molecular markers

Background

Despite an initially indolent course, all WHO grade II, LGGs inevitably transform to malignant, WHO grades III and IV, without current curative options. Malignant transformation (MT) remains unpredictable with limited prognostic markers to steer timing of interventions. The aim of this study was to review and assign predictive value to specific clinical, molecular, and radiological markers impacting MT, thereby justifying timely therapeutic interventions.

Methods

Searches of MEDLINE, Embase, and Cochrane databases were conducted from inception to April 28, 2021 and outputs were analysed in accordance with PRISMA protocol.

Results

From an initial 5,032 articles, 33 articles were included, totalling 5672 patients. Forty-three prognostic factors were registered to significantly impact MT. These were categorised as 7 clinical; 14 neuroimaging; 8 biological/molecular; 3 volumetric; 5 topological; 3 histological; and 3 treatment-related. Following analysis, 10 factors were highlighted: the pre-operative prognosticators were 1. presentation with epileptic seizures; 2. VDE > 8 mm/y; 3. VDE > 4 mm/y; 4. rCBV > 1.75; 5. PTV ≥ 5 cm (65 ml); 6. PTV ≥ 100 ml; and 7. cortical involvement. The post-operative prognosticators were: (1) IDH-wt, (2) TP53 mutation, and (3) temozolomide monotherapy.

Conclusions

The management of LGGs remains controversial, as conservative and invasive treatment may be associated with MT and impaired quality of life, respectively. Our review indicates that MT can be predicted by specific metrics in VDE, PTV, and rCBV, alongside cortical involvement. Additionally, patients with IDH-wt tumours TP53 mutations, or receiving TMZ monotherapy are more likely to undergo MT. Our data may form the basis of a predictive scoring system.

Longitudinal structural and perfusion MRI enhanced by machine learning outperforms standalone modalities and radiological expertise in high-grade glioma surveillance

PURPOSE

Surveillance of patients with high-grade glioma (HGG) and identification of disease progression remain a major challenge in neurooncology. This study aimed to develop a support vector machine (SVM) classifier, employing combined longitudinal structural and perfusion MRI studies, to classify between stable disease, pseudoprogression and progressive disease (3-class problem).

METHODS

Study participants were separated into two groups: group I (total cohort: 64 patients) with a single DSC time point and group II (19 patients) with longitudinal DSC time points (2-3). We retrospectively analysed 269 structural MRI and 92 dynamic susceptibility contrast perfusion (DSC) MRI scans. The SVM classifier was trained using all available MRI studies for each group. Classification accuracy was assessed for different feature dataset and time point combinations and compared to radiologists' classifications.

RESULTS

SVM classification based on combined perfusion and structural features outperformed radiologists' classification across all groups. For the identification of progressive disease, use of combined features and longitudinal DSC time points improved classification performance (lowest error rate 1.6%). Optimal performance was observed in group II (multiple time points) with SVM sensitivity/specificity/accuracy of 100/91.67/94.7% (first time point analysis) and 85.71/100/94.7% (longitudinal analysis), compared to 60/78/68% and 70/90/84.2% for the respective radiologist classifications. In group I (single time point), the SVM classifier also outperformed radiologists' classifications with sensitivity/specificity/accuracy of 86.49/75.00/81.53% (SVM) compared to 75.7/68.9/73.84% (radiologists).

CONCLUSION

Our results indicate that utilisation of a machine learning (SVM) classifier based on analysis of longitudinal perfusion time points and combined structural and perfusion features significantly enhances classification outcome (p value= 0.0001).

Imaging growth as a predictor of grade of malignancy and aggressiveness of IDH-mutant and 1p/19q-codeleted oligodendrogliomas in adults

BACKGROUND

We quantified the spontaneous imaging growth rate of oligodendrogliomas. We assessed whether (i) it discriminates between World Health Organization (WHO) grade II and grade III oligodendrogliomas, and (ii) grade III oligodendrogliomas with neo-angiogenesis are associated with more fast growth rates (≥8 mm/y).

METHODS

This work employed a retrospective bicentric cohort study (2010-2016) of adult patients harboring a newly diagnosed supratentorial oligodendroglioma, isocitrate dehydrogenase (IDH) mutant and 1p/19q codeleted (WHO 2016 classification), with a minimum of 2 available MRIs before any treatment (minimum 6-week interval) to measure the spontaneous tumor growth rate.

RESULTS

We included 108 patients (age 44.7 ± 14.1 y, 60 males). The tumor growth rate was higher in grade III oligodendrogliomas with neo-angiogenesis (n = 37, median 10.4 mm/y, mean 10.0 ± 6.9) than in grade III oligodendrogliomas with increased mitosis count only (cutoff ≥6 mitoses, n = 18, median 3.9 mm/y, mean 4.5 ± 3.2; P = 0.004), and higher than in grade II oligodendrogliomas (n = 53, median 2.3 mm/y, mean 2.8 ± 2.2; P < 0.001). There was increased prevalence of fast tumor growth rates in grade III oligodendrogliomas with neo-angiogenesis (54.1%) compared with grade III oligodendrogliomas with increased mitosis count only (11.1%; P < 0.001), and in grade II oligodendrogliomas (0.0%; P < 0.001). The tumor growth rate trends did not differ between centers (P = 0.121). Neo-angiogenesis (P < 0.001) and mitosis count at ≥9 (P = 0.013) were independently associated with tumor growth rates ≥8 mm/year. A tumor growth rate ≥8 mm/year was the only predictor independently associated with shorter progression-free survival (P = 0.041).

CONCLUSIONS

The spontaneous tumor growth rate recapitulates oligodendroglioma aggressiveness, permits identification of grade III oligodendrogliomas preoperatively when ≥8 mm/year, and questions the grading by mitosis count.

GliMR: Cross-Border Collaborations to Promote Advanced MRI Biomarkers for Glioma

Purpose

There is an annual incidence of 50,000 glioma cases in Europe. The optimal treatment strategy is highly personalised, depending on tumour type, grade, spatial localization, and the degree of tissue infiltration. In research settings, advanced magnetic resonance imaging (MRI) has shown great promise as a tool to inform personalised treatment decisions. However, the use of advanced MRI in clinical practice remains scarce due to the downstream effects of siloed glioma imaging research with limited representation of MRI specialists in established consortia; and the associated lack of available tools and expertise in clinical settings. These shortcomings delay the translation of scientific breakthroughs into novel treatment strategy. As a response we have developed the network “Glioma MR Imaging 2.0” (GliMR) which we present in this article.

Methods

GliMR aims to build a pan-European and multidisciplinary network of experts and accelerate the use of advanced MRI in glioma beyond the current “state-of-the-art” in glioma imaging. The Action Glioma MR Imaging 2.0 (GliMR) was granted funding by the European Cooperation in Science and Technology (COST) in June 2019.

Results

GliMR’s first grant period ran from September 2019 to April 2020, during which several meetings were held and projects were initiated, such as reviewing the current knowledge on advanced MRI; developing a General Data Protection Regulation (GDPR) compliant consent form; and setting up the website.

Conclusion

The Action overcomes the pre-existing limitations of glioma research and is funded until September 2023. New members will be accepted during its entire duration.

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

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

Advanced imaging in adult diffusely infiltrating low-grade gliomas

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

Radiology reporting of low-grade glioma growth underestimates tumor expansion

BACKGROUND

An important aspect in the management of patients with diffuse low-grade gliomas (LGGs) involves monitoring the lesions via serial magnetic resonance imaging (MRI). However, radiological interpretations of LGG interval scans are often qualitative and thus difficult to use clinically.

METHODS

To contextualize these assessments, we retrospectively compared radiological interpretations of LGG growth or stability to volume change measured by manual segmentation. Tumor diameter was also measured in one, two, and three dimensions to evaluate reported methods for assessment of glioma progression, including RECIST criteria, Macdonald/RANO criteria, and mean tumor diameter/ellipsoid method.

RESULTS

Tumors evaluated as stable by radiologists grew a median volume of 5.1 mL (11.1%) relative to the comparison scan, and those evaluated as having grown had a median volume increase of 13.3 mL (23.7%). Diameter-based measurements corresponded well but tended to overestimate gold standard segmented volumes. In addition, agreement with segmented volume measurements improved from 17.6 ± 8.0 to 4.5 ± 5.8 to 3.9 ± 3.6 mm for diameter and from 104.0 ± 96.6 to 25.3 ± 36.8 to 15.9 ± 21.3 mL for volume with radiological measurements in one, two, and three dimensions, respectively. Measurement overestimation increased with tumor size.

CONCLUSIONS

Given accumulating evidence that LGG volume and growth are prognostic factors, there is a need for objective lesion measurement. Current radiological reporting workflows fail to appreciate and communicate the true expansion of LGGs. While volumetric analysis remains the gold standard for assessment of growth, careful diametric measurements in three dimensions may be an acceptable alternative.

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.

Pre- and post-surgery MRSI predictive value in adult oligodendroglioma prognosis

PURPOSE

The aim of this study was to study the relationship between MRSI, before and after surgery, and patient survival. The accuracy of pre-operative MRSI in differentiating low- from high-grade oligodendrogliomas (ODGs) was also studied.

METHODS

Two hundred patients with ODG were retrospectively included in this study between 2000 and 2016. All patients underwent MRSI before any treatment or biopsy and/or after surgery for an intra-axial brain tumour. The R software was used for statistical data analysis. p < 0.05 was considered statistically significant. Kaplan-Meier curves were calculated for patients with low-grade ODG and high-grade ODG pre- and post-operatively, to study survival (overall survival, OS). The best threshold of each MRSI metabolite ratio was obtained using receiver operating characteristic curves (ROCs).

RESULTS

One hundred patients underwent pre-operative MRSI and 170 post-operative MRSI. N-acetylaspartate (NAA), lactate (Lac), choline (Cho) and creatine (Cr) were measured. Kapan-Meier curves showed that survival was poorer for a nCho/Cr > 3.02 in the pre-operative and nCho/Cr > 2.04, Lac/Cr > 0.743 and nCho/NAA > 3.63 in the post-operative period. Post-operative MRSI predicts survival better than pre-operative MRSI. nCho/Cr and Lac/Cr distinguished low- from high-grade ODG with a good positive predictive value.

CONCLUSION

MRSI is associated with survival. It is a non-invasive tool which completes histopathology and can predict patients' prognosis, thus improving patient management.

Tumor growth dynamics in serially-imaged low-grade glioma patients

BACKGROUND

Diffuse low-grade gliomas (LGGs) are infiltrative, slow-growing primary brain tumors that remain relatively asymptomatic for long periods of time before progressing into aggressive and fatal high-grade gliomas.

METHODS

We retrospectively identified LGG patients with numerous (≥ 8) serial magnetic resonance imaging (MRI) studies. Tumor volumes were measured by manual segmentation on serial imaging to study the natural history and growth of the lesion. Patient demographic information, tumor characteristics, and histological data were collected from electronic medical records and paper charts.

RESULTS

Out of 74 LGG patients, 10 patients (13.5%) were identified to meet the study criteria with number of MRIs acquired ranging from 8 to 18 (median, 11.5) over a median of 79.7 months (range 39.8-113.8 months). Tumor diameter increased at a median of 2.17 mm/year in a linear trajectory. Cox regression analysis revealed that initial tumor volume was an independent predictor of time to clinical intervention, and Mann-Whitney U test found that patients younger than 50 years old had significantly slower-growing tumors. Clinical intervention was more likely for tumors above a volume threshold of 73.6 mL.

CONCLUSION

We retrospectively analyzed the natural history of LGGs of patients managed at a single institution with numerous serial MRI scans. Comparisons of our cohort to the literature suggest that this is a subset of particularly slow-growing and low-risk tumors.

Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research

Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis. Given this heterogeneity, conventional processing workflows developed for research purposes are not optimal for clinical data. In this work, we describe an approach called Heterogeneous Optimization Framework (HOF) for developing image analysis pipelines that can handle the high degree of clinical data non-uniformity. HOF provides a set of guidelines for configuration, algorithm development, deployment, interpretation of results and quality control for such pipelines. At each step, we illustrate the HOF approach using the implementation of an automated pipeline for Multimodal Glioma Analysis (MGA) as an example. The MGA pipeline computes tissue diffusion characteristics of diffusion tensor imaging (DTI) acquisitions, hemodynamic characteristics using a perfusion model of susceptibility contrast (DSC) MRI, and spatial cross-modal co-registration of available anatomical, physiological and derived patient images. Developing MGA within HOF enabled the processing of neuro-oncology MR imaging studies to be fully automated. MGA has been successfully used to analyze over 160 clinical tumor studies to date within several research projects. Introduction of the MGA pipeline improved image processing throughput and, most importantly, effectively produced co-registered datasets that were suitable for advanced analysis despite high heterogeneity in acquisition protocols.

Imaging in low-grade glioma: a guide for neurologists

The management of low-grade glioma (LGG) is shifting as evidence has emergedthat refutes the previously commonplace imaging-based ‘watch and wait’ approach, in favour of early aggressive surgical resection. This coupled with the recent 2016 update to the World Health Organisation Classification of Tumours of the Central Nervous System is changing LGG imaging and management. Recently in Practical Neurology the contemporary management of low-grade glioma and the changes to this grading system were discussed in detail. 1 In this complementary article, we discuss the role of imaging in the diagnosis, surgical planning and post-treatment follow-up of LGG. We describe the principles of imaging these tumours and use several cases to highlight some difficult scenarios.

Insular gliomas: a surgical reappraisal based on a systematic review of the literature

INTRODUCTION

Insular gliomas are heterogeneous lesions whose management presents multiple challenges for their tendency to affect young patients in good neurological and cognitive conditions, their deep anatomic location and proximity with critical functional and vascular structures. The appropriate management of insular gliomas requires a multidisciplinary evidence-centred teamwork grounded on the best anatomic, neurophysiological and oncological knowledge. The present study provides a reappraisal of the management of insular gliomas based on a systematic review of the literature with the aim of guiding clinicians in the management of such tumors.

EVIDENCE ACQUISITION

A systematic review of the literature from the Medline, Embase and Cochrane Central databases was performed. From 2006 to 2016, all articles meeting specific inclusion criteria were included.

EVIDENCE SYNTHESIS

The present work summarizes the most relevant evidence about insular gliomas management. The anatomy and physiology of the insula, the new WHO 2016 classification and clinico-radiological presentation of insular gliomas are reviewed. Surgical pearls of insular gliomas resection as well as oncologic and functional outcomes after insular gliomas treatment are discussed.

CONCLUSIONS

Management of insular gliomas remains challenging despite improvement in surgical and oncological techniques. However, the literature review supports a growing evidence that recent developments in the multidisciplinary care account for constant improvements of survival and quality of life.

The Use of MR Perfusion Imaging in the Evaluation of Tumor Progression in Gliomas

Objective

Diagnosing tumor progression and pseudoprogression remains challenging for many clinicians. Accurate recognition of these findings remains paramount given necessity of prompt treatment. However, no consensus has been reached on the optimal technique to discriminate tumor progression. We sought to investigate the role of magnetic resonance perfusion (MRP) to evaluate tumor progression in glioma patients.

Methods

An institutional retrospective review of glioma patients undergoing MRP with concurrent clinical follow up visit was performed. MRP was evaluated in its ability to predict tumor progression, defined clinically or radiographically, at concurrent clinical visit and at follow up visit. The data was then analyzed based on glioma grade and subtype.

Resusts

A total of 337 scans and associated clinical visits were reviewed from 64 patients. Sensitivity, specificity, positive and negative predictive value were reported for each tumor subtype and grade. The sensitivity and specificity for high-grade glioma were 60.8% and 87.8% respectively, compared to low-grade glioma which were 85.7% and 89.0% respectively. The value of MRP to assess future tumor progression within 90 days was 46.9% (sensitivity) and 85.0% (specificity).

Conclusion

Based on our retrospective review, we concluded that adjunct imaging modalities such as MRP are necessary to help diagnose clinical disease progression. However, there is no clear role for stand-alone surveillance MRP imaging in glioma patients especially to predict future tumor progression. It is best used as an adjunctive measure in patients in whom progression is suspected either clinically or radiographically.

'Low grade glioma': an update for radiologists

With the recent publication of a new World Health Organization brain tumour classification that reflects increased understanding of glioma tumour genetics, there is a need for radiologists to understand the changes and their implications for patient management. There has also been an increasing trend for adopting earlier, more aggressive surgical approaches to low-grade glioma (LGG) treatment. We will summarize these changes, give some context to the increased role of tumour genetics and discuss the associated implications of their adoption for radiologists. We will discuss the earlier and more radical surgical resection of LGG and what it means for patients undergoing imaging.

Advanced MRI may complement histological diagnosis of lower grade gliomas and help in predicting survival

MRI grading of grade II and III gliomas may have an important impact on treatment decisions. Occasionally,both conventional MRI (cMRI) and histology fail to clearly establish the tumour grade. Three cMRI features(no necrosis; no relevant oedema; absent or faint contrast enhancement) previously validated in 196 patients with supratentorial gliomas directed our selection of 68 suspected low-grade gliomas (LGG) that were also investigated by advanced MRI (aMRI), including perfusion weighted imaging (PWI), diffusion weighted imaging(DWI) and spectroscopy. All the gliomas had histopathological diagnoses. Sensitivity and specificity of cMRI preoperative diagnosis were 78.5 and 38.5 %, respectively, and 85.7 and 53.8 % when a MRI was included, respectively. ROC analysis showed that cut-off values of 1.29 for maximum rCBV, 1.69 for minimum rADC, 2.1 for rCho/Cr ratio could differentiate between LGG and HGG with a sensitivity of 61.5, 53.8, and 53.8 % and a specificity of 54.7, 43 and 64.3 %, respectively. A significantly longer OS was observed in patients with a maximum rCBV<1.46 and minimum rADC>1.69 (80 vs 55 months, p = 0.01; 80 vs 51 months, p = 0.002, respectively). This result was also confirmed when cases were stratified according to pathology (LGG vs HGG). The ability of a MRI to differentiate between LGG and HGG and to predict survival improved as the number of a MRI techniques considered increased. In a selected population of suspected LGG,classification by cMRI underestimated the actual fraction of HGG. aMRI slightly increased the diagnostic accuracy compared to histopathology. However, DWI and PWI were prognostic markers independent of histological grade.

Early Detection of Malignant Transformation in Resected WHO II Low-Grade Glioma Using Diffusion Tensor-Derived Quantitative Measures

OBJECTIVE

Here, we retrospectively investigate the value of voxel-wisely plotted diffusion tensor-derived (DTI) axial, radial and mean diffusivity for the early detection of malignant transformation (MT) in WHO II glioma compared to contrast-enhanced images.

MATERIALS AND METHODS

Forty-seven patients underwent brain magnetic resonance imaging follow-up between 2006-2014 after gross-tumor resection of intra-axial WHO II glioma. Axial/Mean/Radial diffusivity maps (AD/MD/RD) were generated from DTI data. ADmin/MDmin/RDmin values were quantified within tumor regions-of-interest generated by two independent readers including tumor contrast-to-noise (CNR). Sensitivity/specificity and area-under-the-curve (AUC) were calculated using receiver-operating-characteristic analysis. Inter-reader agreement was assessed (Cohen's kappa).

RESULTS

Eighteen patients demonstrated malignant transformation (MT) confirmed in 8/18 by histopathology and in 10/18 through imaging follow-up. Twelve of 18 patients (66.6%) with MT showed diffusion restriction timely coincidental with contrast-enhancement (CE). In the remaining six patients (33.3%), the diffusion restriction preceded the CE. The mean gain in detection time using DTI was (0.8±0.5 years, p = 0.028). Compared to MDmin and RDmin, ROC-analysis showed best diagnostic value for ADmin (sensitivity/specificity 94.94%/89.7%, AUC 0.96; p<0.0001) to detect MT. CNR was highest for AD (1.83±0.14), compared to MD (1.31±0.19; p<0.003) and RD (0.90±0.23; p<0.0001). Cohen's Kappa was 0.77 for ADmin, 0.71 for MDmin and 0.65 for RDmin (p<0.0001, respectively).

CONCLUSION

MT is detectable at the same time point or earlier compared to T1w-CE by diffusion restriction in diffusion-tensor-derived maps. AD demonstrated highest sensitivity/specificity/tumor-contrast compared to radial or mean diffusivity (= apparent diffusion coefficient) to detect MT.

Awake surgery for hemispheric low-grade gliomas: oncological, functional and methodological differences between pediatric and adult populations

INTRODUCTION

Brain mapping through a direct cortical and subcortical electrical stimulation during an awake craniotomy has gained an increasing popularity as a powerful tool to prevent neurological deficit while increasing extent of resection of hemispheric diffuse low-grade gliomas in adults. However, few case reports or very limited series of awake surgery in children are currently available in the literature.

METHODS

In this paper, we review the oncological and functional differences between pediatric and adult populations, and the methodological specificities that may limit the use of awake mapping in pediatric low-grade glioma surgery.

RESULTS

This could be explained by the fact that pediatric low-grade gliomas have a different epidemiology and biologic behavior in comparison to adults, with pilocytic astrocytomas (WHO grade I glioma) as the most frequent histotype, and with WHO grade II gliomas less prone to anaplastic transformation than their adult counterparts. In addition, aside from the issue of poor collaboration of younger children under 10 years of age, some anatomical and functional peculiarities of children developing brain (cortical and subcortical myelination, maturation of neural networks and of specialized cortical areas) can influence direct electrical stimulation methodology and sensitivity, limiting its use in children.

CONCLUSIONS

Therefore, even though awake procedure with cortical and axonal stimulation mapping can be adapted in a specific subgroup of children with a diffuse glioma from the age of 10 years, only few pediatric patients are nonetheless candidates for awake brain surgery.

The role of imaging in the management of adults with diffuse low grade glioma: A systematic review and evidence-based clinical practice guideline

QUESTION

What is the optimal imaging technique to be used in the diagnosis of a suspected low grade glioma, specifically: which anatomic imaging sequences are critical for most accurately identifying or diagnosing a low grade glioma (LGG) and do non-anatomic imaging methods and/or sequences add to the diagnostic specificity of suspected low grade gliomas?

TARGET POPULATION

These recommendations apply to adults with a newly diagnosed lesion with a suspected or histopathologically proven LGG.

RECOMMENDATION

LEVEL II

In patients with a suspected brain tumor, the minimum magnetic resonance imaging (MRI) exam should be an anatomic exam with both T2 weighted and pre- and post-gadolinium contrast enhanced T1 weighted imaging. CRITICAL IMAGING FOR THE IDENTIFICATION AND DIAGNOSIS OF LOW GRADE GLIOMA:

LEVEL II

In patients with a suspected brain tumor, anatomic imaging sequences should include T1 and T2 weighted and Fluid Attenuation Inversion Recovery (FLAIR) MR sequences and will include T1 weighted imaging after the administration of gadolinium based contrast. Computed tomography (CT) can provide additional information regarding calcification or hemorrhage, which may narrow the differential diagnosis. At a minimum, these anatomic sequences can help identify a lesion as well as its location, and potential for surgical intervention. IMPROVEMENT OF DIAGNOSTIC SPECIFICITY WITH THE ADDITION OF NON-ANATOMIC (PHYSIOLOGIC AND ADVANCED IMAGING) TO ANATOMIC IMAGING:

LEVEL II

Class II evidence from multiple studies and a significant number of Class III series support the addition of diffusion and perfusion weighted MR imaging in the assessment of suspected LGGs, for the purposes of discriminating the potential for tumor subtypes and identification of suspicion of higher grade diagnoses.

LEVEL III

Multiple series offer Class III evidence to support the potential for magnetic resonance spectroscopy (MRS) and nuclear medicine methods including positron emission tomography and single-photon emission computed tomography imaging to offer additional diagnostic specificity although these are less well defined and their roles in clinical practice are still being defined.

QUESTION

Which imaging sequences or parameters best predict the biological behavior or prognosis for patients with LGG?

TARGET POPULATION

These recommendations apply to adults with a newly diagnosed lesion with a suspected or histopathologically proven LGG.

RECOMMENDATION

Anatomic and advanced imaging methods and prognostic stratification

LEVEL III

Multiple series suggest a role for anatomic and advanced sequences to suggest prognostic stratification among low grade gliomas. Perfusion weighted imaging, particularly when obtained as a part of diagnostic evaluation (as recommended above) can play a role in consideration of prognosis. Other imaging sequences remain investigational in terms of their role in consideration of tumor prognosis as there is insufficient evidence to support more formal recommendations as to their use at this time.

QUESTION

What is the optimal imaging technique to be used in the follow-up of a suspected (or biopsy proven) LGG?

TARGET POPULATION

This recommendation applies to adults with a newly diagnosed low grade glioma.

RECOMMENDATIONS

LEVEL II

In patients with a diagnosis of LGG, anatomic imaging sequences should include T2/FLAIR MR sequences and T1 weighted imaging before and after the administration of gadolinium based contrast. Serial imaging should be performed to identify new areas of contrast enhancement or significant change in tumor size, which may signify transformation to a higher grade.

LEVEL III

Advanced imaging utility may depend on tumor subtype. Multicenter clinical trials with larger cohorts are needed. For astrocytic tumors, baseline and longitudinal elevations in tumor perfusion as assessed by dynamic susceptibility contrast perfusion MRI are associated with shorter time to tumor progression, but can be difficult to standardize in clinical practice. For oligodendrogliomas and mixed gliomas, MRS may be helpful for identification of progression.

Convex-Envelope Based Automated Quantitative Approach to Multi-Voxel 1H-MRS Applied to Brain Tumor Analysis

Background

Magnetic Resonance Spectroscopy (MRS) can measure in vivo brain tissue metabolism that exhibits unique biochemical characteristics in brain tumors. For clinical application, an efficient and versatile quantification method of MRS would be an important tool for medical research, particularly for exploring the scientific problem of tumor monitoring. The objective of our study is to propose an automated MRS quantitative approach and assess the feasibility of this approach for glioma grading, prognosis and boundary detection.

Methods

An automated quantitative approach based on a convex envelope (AQoCE) is proposed in this paper, including preprocessing, convex-envelope based baseline fitting, bias correction, sectional baseline removal, and peak detection, in a total of 5 steps. Some metabolic ratios acquired by this quantification are selected for statistical analysis. An independent sample t-test and the Kruskal-Wallis test are used for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and for detecting the tumor, peritumoral and contralateral areas, respectively. Seventy-eight cases of pre-operative brain gliomas with pathological reports are included in this study.

Results

Cho/NAA, Cho/Cr and Lip-Lac/Cr (LL/Cr) calculated by AQoCE in the tumor area differ significantly between LGG and HGG, with p≤0.005. Using logistic regression combining Cho/NAA, Cho/Cr and LL/Cr to generate a ROC curve, AQoCE achieves a sensitivity of 92.9%, a specificity of 72.2%, and an area under ROC curve (AUC) of 0.860. Moreover, both Cho/NAA and Cho/Cr in the AQoCE approach show a significant difference (p≤0.019) between tumoral, peritumoral, and contralateral areas. The comparison between the results of AQoCE and Siemens MRS processing software are also discussed in this paper.

Conclusions

The AQoCE approach is an automated method of residual water removal and metabolite quantification. It can be applied to multi-voxel ¹H-MRS for evaluating brain glioma grading and demonstrating characteristics of brain glioma metabolism. It can also detect infiltration in the peritumoral area. Under the limited clinical data used, AQoCE is significantly more versatile and efficient compared to the reference approach of Siemens.

Outcomes in Reoperated Low-Grade Gliomas

BACKGROUND:

Low-grade gliomas (LGGs) comprise a diverse set of intrinsic brain tumors that correlate strongly with survival. Data on the effect of reoperation are sparse.

OBJECTIVE:

To evaluate the effect of reoperation on patients with LGG.

METHODS:

Fifty-two consecutive patients with reoperated LGGs treated at the University of Washington between 1986 and 2004 were identified and evaluated in a retrospective analysis.

RESULTS:

The average overall survival (OS) for this cohort was 12.95 ± 0.96 years. The overall 10-year survival rate was 57%. The absence of any residual tumor at either the first or second operation was associated with significantly increased OS. Negative prognostic variables for OS included the use of upfront radiation and pathology at recurrence. The average overall progression-free survival to the first recurrence (PFS1) was 6.23 ± 0.51 years. Positive prognostic factors for improved PFS1 included the use of upfront radiation therapy. Variables not associated with differences in PFS1 included the use of upfront chemotherapy, enhancement, pathology, extent of resection, the presence of residual tumor, and Karnofsky Performance Scale score &lt;80. The average overall progression-free survival to the second recurrence was 2.73 ± 0.39 years. Pathology at recurrence was associated with significant differences in progression-free survival to the second recurrence, as was extent of resection at time of first recurrence, and Karnofsky Performance Scale score &lt;80.

CONCLUSION:

This is among the largest studies to assess variables associated with outcome in patients with reoperated LGG. Reresection appears to provide significant benefit, and extent of resection remains the strongest predictor of OS.

Prediction of anaplastic transformation in low-grade oligodendrogliomas based on magnetic resonance spectroscopy and 1p/19q codeletion status

The aim of this study was to assess whether combining multimodal magnetic resonance imaging (MRI) with the determination of the 1p/19q codeletion status could improve the ability to predict anaplastic transformation in low-grade oligodendrogliomas. Twenty patients with grade II oligodendrogliomas were followed-up using multimodal MR [proton MR spectroscopy (MRS), perfusion, and conventional MR imaging]. All patients diagnoses were histologically proven, and 1p/19q codeletion status was analyzed for all patients. Median follow-up was 30.5 ± 11.4 months. Anaplastic transformation was observed in six patients. The only MRI feature that was associated with anaplastic transformation was an elevation of the choline/creatine ratio >2.4 which was observed in 4 out of 6 patients with anaplastic transformation versus 1 out of 14 patients without anaplastic transformation. In patients without 1p/19q codeletion, an elevation of the choline/creatine ratio >2.4 was associated with the occurrence of anaplastic transformation in all cases (4 out of 4 patients), with a mean time of 12 months. In contrast, in patients with a 1p/19q codeletion, no anaplastic transformation was observed in the patient who had an elevation of >2.4 of the choline/creatine ratio and two patients demonstrated an anaplastic transformation without any elevation of this ratio.Prospective validation in a larger series is needed, yet the present study suggests that combining data from in vivo proton MRS and genetic analysis could be a promising strategy to predict time to anaplastic transformation at the individual level in patients with low-grade oligodendrogliomas and may help deciding when chemotherapy and/or radiotherapy should be initiated in these tumors.

Microfoci of malignant progression in diffuse low-grade gliomas: towards the creation of an intermediate grade in glioma classification?

Low-grade gliomas (GII) inescapably progress to high-grade gliomas (GIII). The duration of this transition is highly variable between patients and reliable predictive markers do not exist. We noticed in a subset of cases of GII, obtained by awake neurosurgery, the presence of microfoci with high cellular density, high vascular density, or minimal endothelial proliferation, which we called GII+. Our aim was to investigate whether these foci display immunohistochemical and molecular characteristics similar to GIII and whether their presence is correlated to poor prognosis. We analyzed cell proliferation, hypoxia, vascularization, and alterations of tumorigenic pathways by immunohistochemistry (Ki-67, CD31, HIF-1-alpha, EGFR, P-AKT, P53, MDM2) and fluorescence in situ hybridization (EGFR, MDM2, PDGFRA) in the hypercellular foci of 16 GII+ cases. We compared overall survival between GII, GII+, and GIII. Ki-67, and CD31 expression was higher in the foci than in the tumor background in all cases. Aberrant expression of protein markers and genomic aberrations were also observed in some foci, distinct from the tumor background. Survival was shorter in GII+ than in GII cases. Our results suggest that these foci are the early histological hallmark of anaplastic transformation, which is supported by molecular aberrations. Our study is the first to demonstrate intratumoral morphological, immunohistochemical, and molecular heterogeneity in resection specimens of GII, the presence of which is correlated to shorter survival. Our findings question the discriminative capacity of the current glioma classification and provide arguments in favor of the creation of a grade intermediate between GII and GIII, to optimize the treatment strategy of GII.

Evaluation of the diagnostic performance of magnetic resonance spectroscopy in brain tumors: a systematic review and meta-analysis

Object

The aim of this study was to determine the suitability of magnetic resonance spectroscopy (MRS) for screening brain tumors, based on a systematic review and meta-analysis of published data on the diagnostic performance of MRS.

Methods

The PubMed and PHMC databases were systematically searched for relevant studies up to December 2013. The sensitivities and specificities of MRS in individual studies were calculated and the pooled diagnostic accuracies, with 95% confidence intervals (CI), were assessed under a fixed-effects model.

Results

Twenty-four studies were included, comprising a total of 1013 participants. Overall, no heterogeneity of diagnostic effects was observed between studies. The pooled sensitivity and specificity of MRS were 80.05% (95% CI = 75.97%–83.59%) and 78.46% (95% CI: 73.40%–82.78%), respectively. The area under the summary receiver operating characteristic curve was 0.78. Stratified meta analysis showed higher sensitivity and specificity in child than adult. CSI had higher sensitivity and SV had higher specificity. Higher sensitivity and specificity were obtained in short TE value.

Conclusion

Although the qualities of the studies included in the meta-analysis were moderate, current evidence suggests that MRS may be a valuable adjunct to magnetic resonance imaging for diagnosing brain tumors, but requires selection of suitable technique and TE value.

DCE and DSC MR perfusion imaging in the differentiation of recurrent tumour from treatment-related changes in patients with glioma

AIM

To retrospectively compare the utility of perfusion magnetic resonance imaging (MRI) in distinguishing treatment-related changes from recurrent disease in glioma patients.

MATERIALS AND METHODS

Thirty-one patients with histologically diagnosed gliomas and increased enhancement after or during concurrent (chemo-) radiation therapy were enrolled. They underwent dynamic contrast-enhanced (DCE) permeability MRI followed by dynamic susceptibility contrast (DSC) perfusion MRI. The vascular transfer constant (rK(trans)) and initial areas under the concentration curve (riAUC) were obtained from DCE MRI, and cerebral blood volume (rCBV) was obtained from DSC MRI. Patients were classified as having treatment-related changes or recurrent tumours based on clinicoradiological results or pathological results from surgery.

RESULTS

Nineteen patients were diagnosed as having recurrences and 12 patients as having treatment-related changes. The rK(trans), riAUC, and rCBV values in the recurrent group were significantly higher than the values in the group with treatment-related changes (p < 0.05). For all 31 patients, there was no significant difference between DSC MRI and DCE MRI for the differentiating power between recurrence and treatment-related changes (p = 0.7227). However, when including only the 24 patients with concordant values of rK(trans) and riAUC, DCE MRI showed a significant AUC value of 0.786 in the receiver operating characteristic (ROC) curve analysis (p = 0.003), whereas DSC MRI did not (AUC = 0.643, p = 0.229).

CONCLUSION

MRI perfusion images appear to show promise in distinguishing treatment-related changes from recurrent tumours. When both rK(trans) and riAUC show concordant values, DCE MRI seems to be more powerful than DSC MRI in the differentiation of recurrence from treatment-related changes.

Metabolic mapping of gliomas using hybrid MR-PET imaging: feasibility of the method and spatial distribution of metabolic changes

BACKGROUND AND PURPOSE

The most powerful adjunct to histopathology for the grading of gliomas seems to be the metabolic imaging using positron emission tomography and magnetic resonance spectroscopy (MRS). The purposes of this study were to examine the feasibility of simultaneous acquisition of both techniques for purposes of tumor grading in a newly launched hybrid magnetic resonance positron emission tomography (MR-PET) and to examine the spatial distributions of metabolic changes in gliomas.

MATERIALS AND METHODS

Twenty-eight consecutive patients with gliomas underwent simultaneous methionine (Met) MR-PET imaging for detection of the most malignant tumor part before surgical sampling. After coregistration and fusion of MR-PET and MRS data, tumor to normal brain (T/N) Met uptake ratios and the corresponding metabolites peaks (choline [Cho], creatine [Cr], and N-acetylaspartate [NAA]) in MRS were recorded. The patients were divided into 4 types on the basis of the relation between the Met uptake area and the increased metabolite ratios: type I, the increased Met uptake area had at least 50% overlap or was completely within the area of increased Cho/NAA ratio; type II, the increased Met uptake site had less than 50% overlap of increased Cho/NAA ratio site; type III, the increased Met uptake region had no spatial relationship with the "hot" lesions in the MRS maps; and type IV, there was no pathologically increased Met uptake. The surgical sampling was performed in the tumor part with the highest Met uptake and, in the absence of increased Met accumulation, in the site with the highest Cho/NAA ratio. All surgical samples were referred to the neuropathology division for histological grading.

RESULTS

A total of 16 low-grade gliomas (World Health Organization grade II) and 12 high-grade gliomas (World Health Organization grade III) were included. Three lesions (10%) of type I were identified. Four lesions (14%) were classified as type II and 6 lesions (21%) were classified as type 3, where the increased Met uptake region had no spatial relationship with the hot lesions in the MRS maps. In 15 of the 28 patients (54%), there was no increased Met accumulation (type 4 lesions). Maps of Cho/NAA and Cr/NAA showed a close spatial relationship in most of the patients. Median T/N Met uptake ratio in the pooled surgically sampled tumor sites was 1.6 (range, 1-3), and median Cho/NAA and Cho/Cr ratios were 2.1 (range, 0.9-5.8) and 1.5 (range, 0.5-8.3), respectively. Spearman rank correlations of the metabolic markers in the low-grade gliomas showed significant correlations between Met uptake and Cr/NAA ratio (ρ = 0.59; P = 0.015) as well as between Cho/NAA and Cr/NAA ratios (ρ = 0.79; P = 0.0002). The normalized tumor creatine was significantly higher in anaplastic tumors compared with the low-grade gliomas (P = 0.001). A tendency for a significant positive correlation was found between normalized tumor creatine and Met uptake in the anaplastic tumors.

CONCLUSIONS

Metabolic mapping before histological sampling is feasible using simultaneous MR-PET imaging. High T/N Met uptake ratio reflecting high expression of amino-acid membrane transporters, which is indicative of proliferating tumor cell populations, does not always spatially correlate with neuronal cell loss and cell membrane proliferation (Cho/NAA) seen in MRS. Increased Cr/NAA is associated with increased methionine uptake in low-grade gliomas, whereas normalized creatine in tumor tends to correlate with methionine accumulation, which indicates a possible coupling of these metabolic indices in anaplastic tumors. Thus, spatial distribution differences in gliomas should be taken into account when planning surgical sampling.

Spontaneous and therapeutic prognostic factors in adult hemispheric World Health Organization Grade II gliomas: a series of 1097 cases

Object

The spontaneous prognostic factors and optimal therapeutic strategy for WHO Grade II gliomas (GIIGs) have yet to be unanimously defined. Specifically, the role of resection is still debated, most notably because the actual amount of resection has seldom been assessed.

Methods

Cases of GIIGs treated before December 2007 were extracted from a multicenter database retrospectively collected since January 1985 and prospectively collected since 1996. Inclusion criteria were a patient age ≥ 18 years at diagnosis, histological diagnosis of WHO GIIG, and MRI evaluation of tumor volume at diagnosis and after initial surgery. One thousand ninety-seven lesions were included in the analysis. The mean follow-up was 7.4 years since radiological diagnosis. Factors significant in a univariate analysis (with a p value ≤ 0.1) were included in the multivariate Cox proportional hazard regression model analysis.

Results

At the time of radiological diagnosis, independent spontaneous factors of a poor prognosis were an age ≥ 55 years, an impaired functional status, a tumor location in a nonfrontal area, and, most of all, a larger tumor size. When the study starting point was set at the time of first treatment, independent favorable prognostic factors were limited to a smaller tumor size, an epileptic symptomatology, and a greater extent of resection.

Conclusions

This large series with its volumetric assessment refines the prognostic value of previously stressed clinical and radiological parameters and highlights the importance of tumor size and location. The results support additional arguments in favor of the predominant role of resection, in accordance with recently reported experiences.

Utility of multiparametric 3-T MRI for glioma characterization

INTRODUCTION

Accurate grading of cerebral glioma using conventional structural imaging techniques remains challenging due to the relatively poor sensitivity and specificity of these methods. The purpose of this study was to evaluate the relative sensitivity and specificity of structural magnetic resonance imaging and MR measurements of perfusion, diffusion, and whole-brain spectroscopic parameters for glioma grading.

METHODS

Fifty-six patients with radiologically suspected untreated glioma were studied with T1- and T2-weighted MR imaging, dynamic contrast-enhanced MR imaging, diffusion tensor imaging, and volumetric whole-brain MR spectroscopic imaging. Receiver-operating characteristic analysis was performed using the relative cerebral blood volume (rCBV), apparent diffusion coefficient, fractional anisotropy, and multiple spectroscopic parameters to determine optimum thresholds for tumor grading and to obtain the sensitivity, specificity, and positive and negative predictive values for identifying high-grade gliomas. Logistic regression was performed to analyze all the parameters together.

RESULTS

The rCBV individually classified glioma as low and high grade with a sensitivity and specificity of 100 and 88 %, respectively, based on a threshold value of 3.34. On combining all parameters under consideration, the classification was achieved with 2 % error and sensitivity and specificity of 100 and 96 %, respectively.

CONCLUSION

Individually, CBV measurement provides the greatest diagnostic performance for predicting glioma grade; however, the most accurate classification can be achieved by combining all of the imaging parameters.

The importance of measuring the velocity of diameter expansion on MRI in upfront management of suspected WHO grade II glioma - case report

A right insular lesion was incidentally discovered in a 48-year-old male. Morphological and metabolic radiological characteristics on magnetic resonance imaging (MRI) were in favor of a World Health Organization (WHO) grade II glioma. Despite being advised that surgery was appropriate, the patient elected for conservative management. A second MRI was performed 5 months after, and interpreted as unchanged. A third MRI 4 months later demonstrated a significant increase in tumor size and enhancement in a new distant tumor focus. The patient was referred to our center and underwent surgical resection. Histopathology revealed a grade III astrocytoma. A retrospective quantitative measurement of the radiological growth between the two first MRIs yielded a growth rate of 12 mm/year. This value, highly suggestive of a malignant glioma, should have triggered surgery at the time of the second MRI. We conclude that, whenever surgical treatment of a suspected WHO grade II gliomas is postponed, assessing tumor kinetics quantitatively is important to identify patients whose tumor is indeed a WHO grade III glioma. The tumor should be indeed followed by serial MRIs with quantitative measurement of tumor growth, not just "eyeball" qualitative examination. Immediate treatment is indicated in patients with radiological tumor expansion of greater than 8mm/year.

From patient-specific mathematical neuro-oncology to precision medicine

Gliomas are notoriously aggressive, malignant brain tumors that have variable response to treatment. These patients often have poor prognosis, informed primarily by histopathology. Mathematical neuro-oncology (MNO) is a young and burgeoning field that leverages mathematical models to predict and quantify response to therapies. These mathematical models can form the basis of modern “precision medicine” approaches to tailor therapy in a patient-specific manner. Patient-specific models (PSMs) can be used to overcome imaging limitations, improve prognostic predictions, stratify patients, and assess treatment response in silico. The information gleaned from such models can aid in the construction and efficacy of clinical trials and treatment protocols, accelerating the pace of clinical research in the war on cancer. This review focuses on the growing translation of PSM to clinical neuro-oncology. It will also provide a forward-looking view on a new era of patient-specific MNO.

Velocity of tumor spontaneous expansion predicts long-term outcomes for diffuse low-grade gliomas

BACKGROUND

Supratentorial diffuse low-grade gliomas present a slow macroscopic tumor growth that can be quantified through the measurement of their velocity of diametric expansion. We assessed whether spontaneous velocity of diametric expansion can predict long-term outcomes as a categorical variable and as a continuous predictor.

METHODS

A total of 407 adult patients with newly diagnosed supratentorial diffuse low-grade gliomas in adults were studied.

RESULTS

The mean spontaneous velocity of diametric expansion before first-line treatment was 5.8 ± 6.3 mm/year. During the follow-up (mean, 86.5 ± 59.4 months), 209 patients presented a malignant transformation, and 87 died. The malignant progression-free survival and the overall survival were significantly longer in cases of slow velocity of diametric expansion (median, 103 and 249 months, respectively) than in cases of fast velocity of diametric expansion (median, 35 and 91 months, respectively; P < .001). In multivariate analyses, spontaneous velocity of diametric expansion as a categorical variable (<4, ≥4 and <8, ≥8 and <12, ≥12 mm/year) was an independent prognostic factor for malignant progression-free survival (P < .001; hazard ratio, 3.87; 95% confidence interval [CI], 2.67-5.52) and for overall survival (P < .001; hazard ratio, 4.62; 95% CI, 2.58-7.97). Velocity of diametric expansion was also an independent prognostic factor for overall survival as a continuous predictor, showing a linear relationship between overall survival and spontaneous velocity of diametric expansion (hazard ratio, 1.09 per one unit increase; 95% CI, 1.06-1.12; P < .001).

CONCLUSIONS

Independent of the molecular status, the spontaneous velocity of diametric expansion allows the identification of rapidly growing diffuse low-grade gliomas (at higher risk of worsened evolution) during the pretherapeutic period and without delaying treatment.

Quantitative morphological magnetic resonance imaging follow-up of low-grade glioma: a plea for systematic measurement of growth rates

Supratentorial hemispheric diffuse low-grade gliomas (LGGs), i.e., World Health Organization grade II gliomas, are a heterogeneous group of tumors. During their natural course, LGGs tend to progress to a higher grade of malignancy, leading to neurological disability and ultimately to death. In this review, we will show, that during their low-grade period, these tumors exhibit systematically a spontaneous and continuous radiological growth, whatever their histological subtypes. The radiological tumor growth is easily quantified by measuring the evolution of the equivalent tumor diameter (calculated from the tumor volume), obtaining the velocity of diametric expansion (VDE). The spontaneous VDE of LGGs varies markedly with an average VDE of about 4 mm/year. It depends on intrinsic factors (1p19q codeletion status, P53 overexpression status) and can be modified by extrinsic factors (pregnancy). The spontaneous VDE carries a strong prognostic significance regarding progression-free and overall survivals. As a consequence, VDE should be integrated along with the other "static" parameters (multimodal imaging, histological and molecular analyses) in the initial investigations. In addition, the assessment of VDE obtained before, during, and after a particular oncological treatment helps in analyzing their effects on LGGs on an individual basis, helping to guide the decision making.

Improving the time-machine: estimating date of birth of grade II gliomas

OBJECTIVES

Here we present a model aiming to provide an estimate of time from tumour genesis, for grade II gliomas. The model is based on a differential equation describing the diffusion-proliferation process. We have applied our model to situations where tumour diameter was shown to increase linearly with time, with characteristic diametric velocity.

MATERIALS AND METHODS

We have performed numerical simulations to analyse data, on patients with grade II gliomas and to extract information concerning time of tumour biological onset, as well as radiology and distribution of model parameters.

RESULTS AND CONCLUSIONS

We show that the estimate of tumour onset obtained from extrapolation using a constant velocity assumption, always underestimates biological tumour age, and that the correction one should add to this estimate is given roughly by 20/v (year), where v is the diametric velocity of expansion of the tumour (expressed in mm/year). Within the assumptions of the model, we have identified two types of tumour: the first corresponds to very slowly growing tumours that appear during adolescence, and the second type corresponds to slowly growing tumours that appear later, during early adulthood. That all these tumours become detectable around a mean patient age of 30 years could be interesting for formulation of strategies for early detection of tumours.

Heterogeneity in malignant gliomas: a magnetic resonance analysis of spatial distribution of metabolite changes and regional blood volume

First-pass contrast-enhanced dynamic perfusion imaging provides information about the regional cerebral blood volume (rCBV), an increase of which indicates neovascularization. MR spectroscopic imaging informs about metabolite changes in brain tumors, with elevated choline (Cho) values revealing cell proliferation and density, and the glial metabolite creatine (Cr) representing high-energy storage. This study investigates metabolite changes within the tumor voxel of maximal rCBV value (rCBVmax). Anatomically coregistered parameter maps of rCBV, Cho and Cr were evaluated in 36 patients with primary or recurrent WHO grade III or IV gliomas. Apart from Cho and Cr values within the voxel of rCBVmax (Choperf, Crperf), the maximal Cho and Cr values of the tumor tissue were recorded (Chomax, Crmax). The correlation between these parameters was analyzed with Spearman’s rho test while a binomial test was performed to check whether Chomax = Choperf and Crmax = Crperf. We found that, in 29 of the 36 patients, neither Cho nor Cr had their maxima in the voxel of rCBVmax (Choperf, Crperf < Chomax, Crmax, P < 0.001). However, Choperf was highly correlated with Chomax (r = 0.76, P < 0.001) and Crperf with Crmax (r = 0.47, P < 0.001). Further Choperf correlated with Crperf (r = 0.55, P < 0.001). Neither of the spectroscopic parameters (Chomax, Crmax, Choperf, Crperf,) correlated with rCBVmax. In conclusion, in WHO grade III and IV gliomas the voxel with maximal rCBV often differs from the voxel with the maximal Cho and Cr, indicating the spatial divergence between neovascularization and tumor cell proliferation, cell density and glial processes. However, tCho and tCr changes within the area of neovascularization are positively correlated with the maximal increase within the tumor tissue. These results demonstrate aspects of regional tumor heterogeneity as characterized by different MR modalities that, apart from histopathological grading might be crucial for neurosurgical biopsy as well as for antiangiogenetic and future molecular therapies.

Radiation-induced brain injury: retrospective analysis of twelve pathologically proven cases

Purpose

This study was designed to determine the influencing factors and clinical course of pathologically proven cases of radiation-induced brain injury (RIBI).

Materials and Methods

The pathologic records of twelve patients were reviewed; these patients underwent surgery following radiotherapy due to disease progression found by follow-up imaging. However, they were finally diagnosed with RIBI. All patients had been treated with 3-dimensional conventional fractionated radiotherapy and/or radiosurgery for primary or metastatic brain tumors with or without chemotherapy. The histological distribution was as follows: two falx meningioma, six glioblastoma multiform (GBM), two anaplastic oligodendroglioma, one low grade oligodendroglioma, and one small cell lung cancer with brain metastasis.

Results

Radiation necrosis was noted in eight patients and the remaining four were diagnosed with radiation change. Gender (p = 0.061) and biologically equivalent dose (BED)₃ (p = 0.084) were the only marginally influencing factors of radiation necrosis. Median time to RIBI was 7.3 months (range, 0.5 to 61 months). Three prolonged survivors with GBM were observed. In the subgroup analysis of high grade gliomas, RIBI that developed <6 months after radiotherapy was associated with inferior overall survival rates compared to cases of RIBI that occurred ≥6 months (p = 0.085).

Conclusion

Our study demonstrated that RIBI could occur in early periods after conventional fractionated brain radiotherapy within normal tolerable dose ranges. Studies with a larger number of patients are required to identify the strong influencing factors for RIBI development.

Mean intensity curve on dynamic contrast-enhanced susceptibility-weighted perfusion MR imaging--review of a new parameter to differentiate intracranial tumors

Dynamic susceptibility contrast (DSC) perfusion imaging has been in clinical use for various indications, including characterization and grading of intracranial neoplasms. However, several technical factors can lead to pitfalls in image interpretation. This review discusses the extraction of T1 and T2* information from mean curve analysis of DSC perfusion imaging of various brain tumors, which provides further insights into tumor biology and, thus, may be useful in the differential diagnosis of such tumors. Indeed, by looking at the mean time-signal intensity curve from the tumor bed in addition to the rCBV maps, it is possible to obtain further inferences of capillary density and lesion leakiness. When dynamic contrast enhanced (DCE) T1 perfusion is not available, DSC perfusion with mean curve analysis appears to be a valid alternative for characterizing various brain neoplasms in a routine clinical setting.

Effects of PBN and OKN007 in rodent glioma models assessed by 1H MR spectroscopy

Gliomas, the most common primary brain tumors in adults, have a poor outcome. PBN (α-phenyl-tert-butylnitrone) and OKN007 (2,4-disulfophenyl-PBN) are nitrones that have demonstrated beneficial effects in many aging diseases. In this study, we evaluated the anti-tumor effects of PBN and OKN007 in several rodent glioma models (C6, RG2, and GL261) by assessing metabolite alterations with magnetic resonance spectroscopy (MRS). PBN or OKN007 was administered in drinking water before or after tumor formation. MR imaging and single-voxel point-resolved spectroscopy were done to assess tumor morphology and metabolites, after therapy. Major metabolite ratios (choline, N-acetylaspartate, and lipid (methylene or methyl), all compared to creatine), as well as quantification of individual metabolite concentrations, were assessed. Nitrones induced tumor metabolism changes that resulted in restoring major metabolite ratios close to their normal levels, in the glioma regression phase. Nitrone treatment decreased the lipid (methylene)-to-creatine ratio, as well as the estimated concentration of lipid (methylene) significantly. Alterations in lipids can be a useful marker for the evaluation of the efficacy associated with treatment and were found in this study to be related to the reduction of necrosis, but not apoptosis. OKN007 was more effective than PBN when administered after tumor formation in the C6 glioma model. In conclusion, (1)H MRS and conventional MRI are useful methods to assess and follow the response of varied glioma models to anti-tumor treatments.

Predicting the outcome of grade II glioma treated with temozolomide using proton magnetic resonance spectroscopy

Background:

This study was designed to evaluate proton magnetic resonance spectroscopy (¹H-MRS) for monitoring the WHO grade II glioma (low-grade glioma (LGG)) treated with temozolomide (TMZ).

Methods:

This prospective study included adult patients with progressive LGG that was confirmed by magnetic resonance imaging (MRI). Temozolomide was administered at every 28 days. Response to TMZ was evaluated by monthly MRI examinations that included MRI with volumetric calculations and ¹H-MRS for assessing Cho/Cr and Cho/NAA ratios. Univariate, multivariate and receiver-operating characteristic statistical analyses were performed on the results.

Results:

A total of 21 LGGs from 31 patients were included in the study, and followed for at least n=14 months during treatment. A total of 18 (86%) patients experienced a decrease in tumour volume with a greater decrease of metabolic ratios. Subsequently, five (28%) of these tumours resumed growth despite the continuation of TMZ administration with an earlier increase of metabolic ratios of 2 months. Three (14%) patients did not show any volume or metabolic change. The evolutions of the metabolic ratios, mean(Cho/Cr)_n and mean(Cho/NAA)_n, were significantly correlated over time (Spearman ρ=+0.95) and followed a logarithmic regression (P>0.001). The evolutions over time of metabolic ratios, mean(Cho/Cr)_n and mean(Cho/NAA)_n, were significantly correlated with the evolution of the mean relative decrease of tumour volume, mean(ΔV_n/V_o), according to a linear regression (P<0.001) in the ‘response/no relapse’ patient group, and with the evolution of the mean tumour volume (meanV_n), according to an exponential regression (P<0.001) in the ‘response/relapse’ patient group. The mean relative decrease of metabolic ratio, mean(Δ(Cho/Cr)_n/(Cho/Cr)_o), at n=3 months was predictive of tumour response over the 14 months of follow-up. The mean relative change between metabolic ratios, mean((Cho/NAA)_n−(Cho/Cr)_n)/(Cho/NAA)_n, at n=4 months was predictive of tumour relapse with a significant cutoff of 0.046, a sensitivity of 60% and a specificity of 100% (P=0.004).

Conclusions:

The ¹H-MRS profile changes more widely and rapidly than tumour volume during the response and relapse phases, and represents an early predictive factor of outcome over 14 months of follow-up. Thus, ¹H-MRS may be a promising, non-invasive tool for predicting and monitoring the clinical response to TMZ.

Management of low-grade glioma

The optimal management of patients with low-grade glioma (LGG) is controversial. The controversy largely stems from the lack of well-designed clinical trials with adequate follow-up to account for the relatively long progression-free survival and overall survival of patients with LGG. Nonetheless, the literature increasingly suggests that expectant management is no longer optimal. Rather, there is mounting evidence supporting active management including consideration of surgical resection, radiotherapy, chemotherapy, molecular and histopathologic characterization, and use of modern imaging techniques for monitoring and prognostication. In particular, there is growing evidence favoring extensive surgical resection and increasing interest in the role of chemotherapy (especially temozolomide) in the management of these tumors. In this review, we critically analyze emerging trends in the literature with respect to management of LGG, with particular emphasis on reports published during the past year.